From 0f2c13a226e547220275e88eb6bd09a36b4026e9 Mon Sep 17 00:00:00 2001 From: Piotr Kubala Date: Sat, 7 Jun 2025 17:07:23 +0200 Subject: [PATCH 1/7] parallel v1 --- .../Loftus_and_Wordsworth_2021/figure_2.ipynb | 4262 +---------------- uv.lock | 46 +- 2 files changed, 195 insertions(+), 4113 deletions(-) diff --git a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb index c48d4892c3..5b6e665b9c 100644 --- a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb +++ b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb @@ -2,13 +2,20 @@ "cells": [ { "cell_type": "code", - "execution_count": 25, + "execution_count": 38, "id": "d8f644e9", "metadata": {}, "outputs": [], "source": [ + "import copy\n", + "\n", "import PySDM.products as PySDM_products\n", "import numpy as np\n", + "from numba import njit, prange\n", + "\n", + "from tqdm import tqdm\n", + "from tqdm_joblib import tqdm_joblib\n", + "\n", "from PySDM import Builder\n", "from PySDM import Formulae\n", "from PySDM_examples.Lowe_et_al_2019.constants_def import LOWE_CONSTS\n", @@ -22,7 +29,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 39, "id": "2fb6b5aa", "metadata": {}, "outputs": [], @@ -37,7 +44,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 40, "id": "92a3a574", "metadata": {}, "outputs": [], @@ -54,7 +61,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 41, "id": "41f0ed6d", "metadata": {}, "outputs": [ @@ -64,7 +71,7 @@ "300.0" ] }, - "execution_count": 28, + "execution_count": 41, "metadata": {}, "output_type": "execute_result" } @@ -76,4121 +83,107 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 42, "id": "3249b65e", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due 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warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - 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"/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.9634134833789\n", - "\t\t p\n", - "\t\t 1012822.9500843065\n", - "\t\t RH\n", - "\t\t 0.9765862871248907\n", - "\t\t a\n", - "\t\t -30.95918841010328\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.578296789640031\n", - "\t\t fb\n", - "\t\t -6168699570125.941\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.9634207104974\n", - "\t\t p\n", - "\t\t 1012823.0355222607\n", - "\t\t RH\n", - "\t\t 0.9765859543352727\n", - "\t\t a\n", - "\t\t -30.95918841010328\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.5783049178971956\n", - "\t\t fb\n", - "\t\t -6168700281630.32\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.96342793761573\n", - "\t\t p\n", - "\t\t 1012823.1209602171\n", - "\t\t RH\n", - "\t\t 0.9765856215457984\n", - "\t\t a\n", - "\t\t -30.95918841010328\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.5783130461532092\n", - "\t\t fb\n", - "\t\t -6168700993134.571\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.9507209513936\n", - "\t\t p\n", - "\t\t 1012676.3824214343\n", - "\t\t RH\n", - "\t\t 0.9620369993030186\n", - "\t\t a\n", - "\t\t -29.81642202197012\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8666415026044445\n", - "\t\t fb\n", - "\t\t -12373299220677.494\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.90662277570584\n", - "\t\t p\n", - "\t\t 1012158.79325844\n", - "\t\t RH\n", - "\t\t 0.9488745587023921\n", - "\t\t a\n", - "\t\t -29.845959483572216\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.5932155847342155\n", - "\t\t fb\n", - "\t\t -6184810344976.083\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.9066333010911\n", - "\t\t p\n", - "\t\t 1012158.917629983\n", - "\t\t RH\n", - "\t\t 0.9488740875640582\n", - "\t\t a\n", - "\t\t -29.845959483572216\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.593221138936329\n", - "\t\t fb\n", - "\t\t -6184811380402.374\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.90664382647594\n", - "\t\t p\n", - "\t\t 1012159.0420015308\n", - "\t\t RH\n", - "\t\t 0.9488736164260189\n", - "\t\t a\n", - "\t\t -29.845959483572216\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.5932266931373219\n", - "\t\t fb\n", - "\t\t -6184812415828.394\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.93820260636215\n", - "\t\t p\n", - "\t\t 1012535.7005486615\n", - "\t\t RH\n", - "\t\t 0.9323193298702869\n", - "\t\t a\n", - "\t\t -28.488153087711776\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6349078434077443\n", - "\t\t fb\n", - "\t\t -12411922510608.846\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.8177218723501\n", - "\t\t p\n", - "\t\t 1011116.2068822231\n", - "\t\t RH\n", - "\t\t 0.9224053590916934\n", - "\t\t a\n", - "\t\t -28.86221864419622\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.9313547337171976\n", - "\t\t fb\n", - "\t\t -12389068535747.512\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.9943736831119\n", - "\t\t p\n", - "\t\t 1013207.5322592934\n", - "\t\t RH\n", - "\t\t 0.8996476830823505\n", - "\t\t a\n", - "\t\t -28.30139780596837\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8315066664607937\n", - "\t\t fb\n", - "\t\t -12441925103929.836\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.95428420335634\n", - "\t\t p\n", - "\t\t 1012737.6130844497\n", - "\t\t RH\n", - "\t\t 0.8862182861954118\n", - "\t\t a\n", - "\t\t -28.924739899377165\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.7133459113657017\n", - "\t\t fb\n", - "\t\t -6216235315697.642\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.94573279103884\n", - "\t\t p\n", - "\t\t 1012640.7213250437\n", - "\t\t RH\n", - "\t\t 0.8714381890397797\n", - "\t\t a\n", - "\t\t -27.74375633713891\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.733942374500773\n", - "\t\t fb\n", - "\t\t -12457266327821.965\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.97248126580394\n", - "\t\t p\n", - "\t\t 1012961.2616366227\n", - "\t\t RH\n", - "\t\t 0.8552212862638529\n", - "\t\t a\n", - "\t\t -27.07506960810236\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.5298846067986657\n", - "\t\t fb\n", - "\t\t -12482630173385.459\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.61308346437954\n", - "\t\t p\n", - "\t\t 1008722.881951865\n", - "\t\t RH\n", - "\t\t 0.8544814073629403\n", - "\t\t a\n", - "\t\t -28.985844710864058\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.9431953287465719\n", - "\t\t fb\n", - "\t\t -6191747867651.295\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.6131020964191\n", - "\t\t p\n", - "\t\t 1008723.1015820028\n", - "\t\t RH\n", - "\t\t 0.8544806544604215\n", - "\t\t a\n", - "\t\t -28.985844710864058\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.9432005537054442\n", - "\t\t fb\n", - "\t\t -6191749700880.462\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.67504551555817\n", - "\t\t p\n", - "\t\t 1009458.0559705176\n", - "\t\t RH\n", - "\t\t 0.8366496131787623\n", - "\t\t a\n", - "\t\t -27.2919314232323\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6865617532343624\n", - "\t\t fb\n", - "\t\t -12434693879454.594\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.78113628679904\n", - "\t\t p\n", - "\t\t 1010714.5777850668\n", - "\t\t RH\n", - "\t\t 0.8172109612077316\n", - "\t\t a\n", - "\t\t -27.243427595841084\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.7454617422883495\n", - "\t\t fb\n", - "\t\t -12464588720288.66\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.93639568798415\n", - "\t\t p\n", - "\t\t 1012553.4130444452\n", - "\t\t RH\n", - "\t\t 0.7961007213258735\n", - "\t\t a\n", - "\t\t -27.45735064584614\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.9618273611364095\n", - "\t\t fb\n", - "\t\t -12499738720389.633\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.55856038469784\n", - "\t\t p\n", - "\t\t 1008099.5501643746\n", - "\t\t RH\n", - "\t\t 0.7950199449271899\n", - "\t\t a\n", - "\t\t -27.266316298646004\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8450500056239783\n", - "\t\t fb\n", - "\t\t -12435588165975.783\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.76436003945315\n", - "\t\t p\n", - "\t\t 1010531.700768368\n", - "\t\t RH\n", - "\t\t 0.7720553130841131\n", - "\t\t a\n", - "\t\t -26.991953293184714\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.7862195513879606\n", - "\t\t fb\n", - "\t\t -12489560841021.805\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.3762280119534\n", - "\t\t p\n", - "\t\t 1005963.3610371638\n", - "\t\t RH\n", - "\t\t 0.7708117070502777\n", - "\t\t a\n", - "\t\t -27.76000864318786\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6533457271261173\n", - "\t\t fb\n", - "\t\t -6198771660676.603\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.3762495295871\n", - "\t\t p\n", - "\t\t 1005963.614188258\n", - "\t\t RH\n", - "\t\t 0.7708109211164261\n", - "\t\t a\n", - "\t\t -27.76000864318786\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6533482503285692\n", - "\t\t fb\n", - "\t\t -6198773776708.654\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.3762710472189\n", - "\t\t p\n", - "\t\t 1005963.8673393718\n", - "\t\t RH\n", - "\t\t 0.7708101351835809\n", - "\t\t a\n", - "\t\t -27.76000864318786\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6533507735300453\n", - "\t\t fb\n", - "\t\t -6198775892739.596\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.6386503663267\n", - "\t\t p\n", - "\t\t 1009059.633989164\n", - "\t\t RH\n", - "\t\t 0.7459376545882029\n", - "\t\t a\n", - "\t\t -28.049697612923204\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.883905407482185\n", - "\t\t fb\n", - "\t\t -6232807549026.076\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.96843012835257\n", - "\t\t p\n", - "\t\t 1012959.05658442\n", - "\t\t RH\n", - "\t\t 0.7192913688709481\n", - "\t\t a\n", - "\t\t -27.79787376067437\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8304781613488469\n", - "\t\t fb\n", - "\t\t -6264034630967.177\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.9684526690836\n", - "\t\t p\n", - "\t\t 1012959.3230890674\n", - "\t\t RH\n", - "\t\t 0.7192906044223643\n", - "\t\t a\n", - "\t\t -27.79787376067437\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8304807946281323\n", - "\t\t fb\n", - "\t\t -6264036817252.785\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.9684752098124\n", - "\t\t p\n", - "\t\t 1012959.5895937356\n", - "\t\t RH\n", - "\t\t 0.7192898399748074\n", - "\t\t a\n", - "\t\t -27.79787376067437\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8304834279063279\n", - "\t\t fb\n", - "\t\t -6264039003537.17\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.5647883078875\n", - "\t\t p\n", - "\t\t 1008200.6176316094\n", - "\t\t RH\n", - "\t\t 0.7177226772693551\n", - "\t\t a\n", - "\t\t -26.685765015429112\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.7917025483244458\n", - "\t\t fb\n", - "\t\t -12495504889727.533\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.96388245266064\n", - "\t\t p\n", - "\t\t 1012917.3203774029\n", - "\t\t RH\n", - "\t\t 0.6891957908215012\n", - "\t\t a\n", - "\t\t -26.03057471454337\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.5692294892959228\n", - "\t\t fb\n", - "\t\t -12614584749311.312\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.5487660825412\n", - "\t\t p\n", - "\t\t 1008024.1933415018\n", - "\t\t RH\n", - "\t\t 0.6874180599561547\n", - "\t\t a\n", - "\t\t -26.50013640516871\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.7750814690527159\n", - "\t\t fb\n", - "\t\t -12517666561596.486\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.1263073775298\n", - "\t\t p\n", - "\t\t 1003061.9568294361\n", - "\t\t RH\n", - "\t\t 0.685585751321056\n", - "\t\t a\n", - "\t\t -27.374182570649307\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6903408826343748\n", - "\t\t fb\n", - "\t\t -6203646073041.76\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.12633602323774\n", - "\t\t p\n", - "\t\t 1003062.2931498039\n", - "\t\t RH\n", - "\t\t 0.6855848187531304\n", - "\t\t a\n", - "\t\t -27.374182570649307\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6903433318476198\n", - "\t\t fb\n", - "\t\t -6203648891736.9795\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.59719805859504\n", - "\t\t p\n", - "\t\t 1008608.134868544\n", - "\t\t RH\n", - "\t\t 0.6550663572221505\n", - "\t\t a\n", - "\t\t -26.707368570811177\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.982852877883842\n", - "\t\t fb\n", - "\t\t -12539185333289.902\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.1621264200539\n", - "\t\t p\n", - "\t\t 1003496.1233044433\n", - "\t\t RH\n", - "\t\t 0.6530010760114098\n", - "\t\t a\n", - "\t\t -27.086585109608947\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6299263318547909\n", - "\t\t fb\n", - "\t\t -6219531963837.108\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.1621600706134\n", - "\t\t p\n", - "\t\t 1003496.5185089135\n", - "\t\t RH\n", - "\t\t 0.6530000328922426\n", - "\t\t a\n", - "\t\t -27.086585109608947\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6299286558387365\n", - "\t\t fb\n", - "\t\t -6219535268606.5\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.71850671589897\n", - "\t\t p\n", - "\t\t 1010052.8396879905\n", - "\t\t RH\n", - "\t\t 0.6207177830246923\n", - "\t\t a\n", - "\t\t -27.40899182734051\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8620717093032405\n", - "\t\t fb\n", - "\t\t -6268407723961.931\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.718532644886\n", - "\t\t p\n", - "\t\t 1010053.1456281864\n", - "\t\t RH\n", - "\t\t 0.6207170225767731\n", - "\t\t a\n", - "\t\t -27.40899182734051\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8620738852557082\n", - "\t\t fb\n", - "\t\t -6268410236524.556\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.7185585738702\n", - "\t\t p\n", - "\t\t 1010053.4515684105\n", - "\t\t RH\n", - "\t\t 0.6207162621300264\n", - "\t\t a\n", - "\t\t -27.40899182734051\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8620760612071947\n", - "\t\t fb\n", - "\t\t -6268412749085.575\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.2702097258826\n", - "\t\t p\n", - "\t\t 1004780.5862983869\n", - "\t\t RH\n", - "\t\t 0.6184014577006727\n", - "\t\t a\n", - "\t\t -27.494233628209678\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.9096879930408022\n", - "\t\t fb\n", - "\t\t -6227398634951.213\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.2702353319097\n", - "\t\t p\n", - "\t\t 1004780.887301095\n", - "\t\t RH\n", - "\t\t 0.6184007066930584\n", - "\t\t a\n", - "\t\t -27.494233628209678\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.9096902551531747\n", - "\t\t fb\n", - "\t\t -6227401136482.012\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.2702609379339\n", - "\t\t p\n", - "\t\t 1004781.1883038302\n", - "\t\t RH\n", - "\t\t 0.6183999556865956\n", - "\t\t a\n", - "\t\t -27.494233628209678\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.9096925172645424\n", - "\t\t fb\n", - "\t\t -6227403638011.231\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.9229274444732\n", - "\t\t p\n", - "\t\t 1012482.0202629202\n", - "\t\t RH\n", - "\t\t 0.5844473315459593\n", - "\t\t a\n", - "\t\t -27.1838014885193\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8177626204242621\n", - "\t\t fb\n", - "\t\t -6307463212086.996\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.9229657042697\n", - "\t\t p\n", - "\t\t 1012482.4724735708\n", - "\t\t RH\n", - "\t\t 0.5844462768441333\n", - "\t\t a\n", - "\t\t -27.1838014885193\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8177653192936476\n", - "\t\t fb\n", - "\t\t -6307466903857.707\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.46069317040946\n", - "\t\t p\n", - "\t\t 1007037.0902348979\n", - "\t\t RH\n", - "\t\t 0.5818656131131787\n", - "\t\t a\n", - "\t\t -26.525770556213537\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.5266312994781783\n", - "\t\t fb\n", - "\t\t -6277104428651.627\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.46074004330904\n", - "\t\t p\n", - "\t\t 1007037.642119093\n", - "\t\t RH\n", - "\t\t 0.581864321662108\n", - "\t\t a\n", - "\t\t -26.525770556213537\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.5266334236334191\n", - "\t\t fb\n", - "\t\t -6277108996003.316\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 298.98908194337633\n", - "\t\t p\n", - "\t\t 1001503.3881659433\n", - "\t\t RH\n", - "\t\t 0.579192226038954\n", - "\t\t a\n", - "\t\t -26.067474651387215\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.7753490491425593\n", - "\t\t fb\n", - "\t\t -12499129757004.676\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.7452115348817\n", - "\t\t p\n", - "\t\t 1010407.7384859911\n", - "\t\t RH\n", - "\t\t 0.5435233639760522\n", - "\t\t a\n", - "\t\t -26.728020255579516\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6601975995114632\n", - "\t\t fb\n", - "\t\t -6297310107423.109\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.7452444341992\n", - "\t\t p\n", - "\t\t 1010408.1267720256\n", - "\t\t RH\n", - "\t\t 0.5435225192866958\n", - "\t\t a\n", - "\t\t -26.728020255579516\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6601992559348544\n", - "\t\t fb\n", - "\t\t -6297313281927.258\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.74527733351226\n", - "\t\t p\n", - "\t\t 1010408.5150581059\n", - "\t\t RH\n", - "\t\t 0.5435216745989843\n", - "\t\t a\n", - "\t\t -26.728020255579516\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6602009123573385\n", - "\t\t fb\n", - "\t\t -6297316456428.848\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.2583142123211\n", - "\t\t p\n", - "\t\t 1004681.6893377787\n", - "\t\t RH\n", - "\t\t 0.540556675445887\n", - "\t\t a\n", - "\t\t -26.064909127313054\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8502251142462253\n", - "\t\t fb\n", - "\t\t -12573190804047.61\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 298.76081905752415\n", - "\t\t p\n", - "\t\t 998855.0908611602\n", - "\t\t RH\n", - "\t\t 0.5374783054397425\n", - "\t\t a\n", - "\t\t -27.03939476437234\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8063893469040323\n", - "\t\t fb\n", - "\t\t -6203483915430.949\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 298.76084784256267\n", - "\t\t p\n", - "\t\t 998855.4278116744\n", - "\t\t RH\n", - "\t\t 0.5374775685070795\n", - "\t\t a\n", - "\t\t -27.03939476437234\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8063911083575289\n", - "\t\t fb\n", - "\t\t -6203486742038.943\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 298.7608766275977\n", - "\t\t p\n", - "\t\t 998855.7647622237\n", - "\t\t RH\n", - "\t\t 0.5374768315756829\n", - "\t\t a\n", - "\t\t -27.03939476437234\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8063928698102046\n", - "\t\t fb\n", - "\t\t -6203489568644.957\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.6345822748919\n", - "\t\t p\n", - "\t\t 1009130.0847110075\n", - "\t\t RH\n", - "\t\t 0.5002840005025697\n", - "\t\t a\n", - "\t\t -25.613832705415277\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6916978879199097\n", - "\t\t fb\n", - "\t\t -12695442955964.844\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 298.59374199220275\n", - "\t\t p\n", - "\t\t 996929.8672275824\n", - "\t\t RH\n", - "\t\t 0.4933511605950075\n", - "\t\t a\n", - "\t\t -26.01209163852019\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8936181772524167\n", - "\t\t fb\n", - "\t\t -12480048956456.535\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.59846761895216\n", - "\t\t p\n", - "\t\t 1008734.9601573372\n", - "\t\t RH\n", - "\t\t 0.45497077906450356\n", - "\t\t a\n", - "\t\t -26.55718263514624\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.703820807499301\n", - "\t\t fb\n", - "\t\t -6325862706578.566\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.5985221206016\n", - "\t\t p\n", - "\t\t 1008735.6026492111\n", - "\t\t RH\n", - "\t\t 0.45496960626990074\n", - "\t\t a\n", - "\t\t -26.55718263514624\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.7038230928980492\n", - "\t\t fb\n", - "\t\t -6325867969616.5\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.05302540297635\n", - "\t\t p\n", - "\t\t 1002330.6290007515\n", - "\t\t RH\n", - "\t\t 0.4510955224244599\n", - "\t\t a\n", - "\t\t -26.489724792419523\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6720403871552741\n", - "\t\t fb\n", - "\t\t -6293487292384.741\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 298.4936049040689\n", - "\t\t p\n", - "\t\t 995792.5298544584\n", - "\t\t RH\n", - "\t\t 0.447056467755106\n", - "\t\t a\n", - "\t\t -25.50725569678658\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.69729784035404\n", - "\t\t fb\n", - "\t\t -12520697401323.71\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.6386875398746\n", - "\t\t p\n", - "\t\t 1009243.7380141908\n", - "\t\t RH\n", - "\t\t 0.4080244137828001\n", - "\t\t a\n", - "\t\t -25.808855904570255\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.9335990751525294\n", - "\t\t fb\n", - "\t\t -12741811261076.008\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.0580149333527\n", - "\t\t p\n", - "\t\t 1002424.9751234822\n", - "\t\t RH\n", - "\t\t 0.40362039001371713\n", - "\t\t a\n", - "\t\t -26.400507021227444\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6888223537049074\n", - "\t\t fb\n", - "\t\t -6311273200677.684\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 298.4612365810754\n", - "\t\t p\n", - "\t\t 995451.6040362052\n", - "\t\t RH\n", - "\t\t 0.3990133803764959\n", - "\t\t a\n", - "\t\t -26.583978364305075\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.7744024442858238\n", - "\t\t fb\n", - "\t\t -6252081968152.138\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.75729651343744\n", - "\t\t p\n", - "\t\t 1010682.5201739138\n", - "\t\t RH\n", - "\t\t 0.3599180550573331\n", - "\t\t a\n", - "\t\t -25.40815038618358\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.7768808771103395\n", - "\t\t fb\n", - "\t\t -12822045052161.95\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.13591979919784\n", - "\t\t p\n", - "\t\t 1003380.430799292\n", - "\t\t RH\n", - "\t\t 0.35493481307386104\n", - "\t\t a\n", - "\t\t -26.56059175918776\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.828029446606078\n", - "\t\t fb\n", - "\t\t -6311999304582.672\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.1359802303137\n", - "\t\t p\n", - "\t\t 1003381.1405048287\n", - "\t\t RH\n", - "\t\t 0.35493379464028496\n", - "\t\t a\n", - "\t\t -26.56059175918776\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8280317718010065\n", - "\t\t fb\n", - "\t\t -6312005162704.229\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 298.49550007237843\n", - "\t\t p\n", - "\t\t 995894.279243401\n", - "\t\t RH\n", - "\t\t 0.34970454256139255\n", - "\t\t a\n", - "\t\t -24.946083209684975\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.5673066614242958\n", - "\t\t fb\n", - "\t\t -12633997501643.025\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.95733252026787\n", - "\t\t p\n", - "\t\t 1013091.2848584556\n", - "\t\t RH\n", - "\t\t 0.31113939257485534\n", - "\t\t a\n", - "\t\t -24.928018045147482\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6122417853631499\n", - "\t\t fb\n", - "\t\t -12939045993046.453\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.2883945619583\n", - "\t\t p\n", - "\t\t 1005219.5661128054\n", - "\t\t RH\n", - "\t\t 0.3055196097854639\n", - "\t\t a\n", - "\t\t -25.962943185374478\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6020543149237779\n", - "\t\t fb\n", - "\t\t -6355154960367.686\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.2884671009792\n", - "\t\t p\n", - "\t\t 1005220.419140811\n", - "\t\t RH\n", - "\t\t 0.3055185588520758\n", - "\t\t a\n", - "\t\t -25.962943185374478\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6020561107407586\n", - "\t\t fb\n", - "\t\t -6355161967995.529\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 298.59683125577067\n", - "\t\t p\n", - "\t\t 997127.9169250539\n", - "\t\t RH\n", - "\t\t 0.2995937000525491\n", - "\t\t a\n", - "\t\t -26.10623029362231\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6560340730579426\n", - "\t\t fb\n", - "\t\t -6266092974909.267\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 298.59688438804767\n", - "\t\t p\n", - "\t\t 997128.5381438957\n", - "\t\t RH\n", - "\t\t 0.29959294078821314\n", - "\t\t a\n", - "\t\t -26.10623029362231\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6560355031956475\n", - "\t\t fb\n", - "\t\t -6266098154336.182\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 298.5969375203124\n", - "\t\t p\n", - "\t\t 997129.1593628546\n", - "\t\t RH\n", - "\t\t 0.29959218152629075\n", - "\t\t a\n", - "\t\t -26.10623029362231\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.6560369333322771\n", - "\t\t fb\n", - "\t\t -6266103333756.395\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 297.8811713226632\n", - "\t\t p\n", - "\t\t 988803.7391899653\n", - "\t\t RH\n", - "\t\t 0.29332510901658\n", - "\t\t a\n", - "\t\t -26.509685757794315\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.8577808690303017\n", - "\t\t fb\n", - "\t\t -6231300078266.314\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/4046310924.py:23: RuntimeWarning: The iteration is not making good progress, as measured by the \n", - " improvement from the last ten iterations.\n", - " tdews = (fsolve(f, [150,300]))\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "/Users/emmaware/PySDM/PySDM/backends/numba.py:48: UserWarning: Disabling Numba threading due to ARM64 CPU (atomics do not work yet)\n", - " warnings.warn(\n", - "failed to find interval\n", - "\tfile: /Users/emmaware/PySDM/PySDM/backends/impl_numba/methods/condensation_methods.py\n", - "\tcontext:\n", - "\t\t T\n", - "\t\t 299.51504213715594\n", - "\t\t p\n", - "\t\t 1007943.1840128525\n", - "\t\t RH\n", - "\t\t 0.2558983502422977\n", - "\t\t a\n", - "\t\t -25.174929273112294\n", - "\t\t b\n", - "\t\t -65.34255573852614\n", - "\t\t fa\n", - "\t\t -0.7717154280335414\n", - "\t\t fb\n", - "\t\t -12862931725688.932\n" - ] - } - ], + "outputs": [], + "source": [ + "# radius_array = np.logspace(-4.5, -2.5, 50) * si.m\n", + "# RH_array = np.linspace(0.25, .99, 50)\n", + "# output_matrix = np.full((len(RH_array), len(radius_array)), np.nan)\n", + "# const = formulae.constants\n", + "\n", + "# def mix(dry,vap,ratio):\n", + "# return (dry + ratio * vap)/(1 + ratio)\n", + "\n", + "# def compute_plot():\n", + "# RH_reversed = RH_array[::-1]\n", + "# size_reversed = len(RH_reversed)\n", + "\n", + "# for i in range(size_reversed):\n", + "# RH = RH_reversed[i]\n", + "\n", + "# new_Earth.RH_zref = RH\n", + "\n", + "# pvs = formulae.saturation_vapour_pressure.pvs_water(new_Earth.T_STP)\n", + "# initial_water_vapour_mixing_ratio = const.eps / (new_Earth.p_STP / new_Earth.RH_zref / pvs - 1\n", + "# )\n", + "\n", + "# Rair = mix(const.Rd,const.Rv,initial_water_vapour_mixing_ratio)\n", + "# c_p = mix(const.c_pd,const.c_pv,initial_water_vapour_mixing_ratio)\n", + "\n", + "# def f(x):\n", + "# return initial_water_vapour_mixing_ratio/(initial_water_vapour_mixing_ratio+ const.eps)*new_Earth.p_STP*(x/new_Earth.T_STP)**(c_p/Rair\n", + "# ) - formulae.saturation_vapour_pressure.pvs_water(x)\n", + " \n", + "# tdews = (fsolve(f, [150,300]))\n", + "# Tcloud = np.max(tdews)\n", + "# Zcloud = (new_Earth.T_STP-Tcloud)*c_p/new_Earth.g_std\n", + "# thstd = formulae.trivia.th_std(new_Earth.p_STP, new_Earth.T_STP)\n", + "\n", + "# pcloud = formulae.hydrostatics.p_of_z_assuming_const_th_and_initial_water_vapour_mixing_ratio(new_Earth.p_STP, \n", + "# thstd, initial_water_vapour_mixing_ratio, Zcloud)\n", + "\n", + "\n", + "# np.testing.assert_approx_equal(\n", + "# actual=pcloud*(initial_water_vapour_mixing_ratio/(initial_water_vapour_mixing_ratio + const.eps))/\n", + "# formulae.saturation_vapour_pressure.pvs_water(Tcloud),\n", + "# desired=1,\n", + "# significant=4\n", + "# )\n", + "\n", + "# for j,r in enumerate(radius_array[::-1]):\n", + "# settings = Settings(\n", + "# planet=new_Earth,\n", + "# r_wet= r,\n", + "# mass_of_dry_air= 1e5*si.kg,\n", + "# coord= \"WaterMassLogarithm\",\n", + "# initial_water_vapour_mixing_ratio= initial_water_vapour_mixing_ratio,\n", + "# pcloud= pcloud,\n", + "# Zcloud= Zcloud,\n", + "# Tcloud= Tcloud,\n", + "# formulae=formulae,\n", + "# )\n", + "# simulation = Simulation(settings)\n", + "# try:\n", + "# output = simulation.run()\n", + "# if output['z'][-1] > 0:\n", + "# output_matrix[i, j] = np.nan\n", + "# break\n", + "# else:\n", + "# output_matrix[i, j] = 1 - (output['r'][-1] /(r*1e6))\n", + "# except Exception as e:\n", + "# break" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "d3a8f4b9", + "metadata": {}, + "outputs": [], "source": [ + "from concurrent.futures import ProcessPoolExecutor, as_completed\n", + "\n", "radius_array = np.logspace(-4.5, -2.5, 50) * si.m\n", "RH_array = np.linspace(0.25, .99, 50)\n", "output_matrix = np.full((len(RH_array), len(radius_array)), np.nan)\n", "const = formulae.constants\n", "\n", + "@njit(parallel=True)\n", "def mix(dry,vap,ratio):\n", " return (dry + ratio * vap)/(1 + ratio)\n", "\n", - "for i,RH in enumerate(RH_array[::-1]):\n", + "def compute_one_RH(RH):\n", + " \"\"\"\n", + " Compute one row of the output_matrix for a given RH.\n", + " Returns a 1D numpy array of length len(radius_array).\n", + " \"\"\"\n", " new_Earth.RH_zref = RH\n", "\n", " pvs = formulae.saturation_vapour_pressure.pvs_water(new_Earth.T_STP)\n", " initial_water_vapour_mixing_ratio = const.eps / (new_Earth.p_STP / new_Earth.RH_zref / pvs - 1\n", - " )\n", + " )\n", "\n", " Rair = mix(const.Rd,const.Rv,initial_water_vapour_mixing_ratio)\n", " c_p = mix(const.c_pd,const.c_pv,initial_water_vapour_mixing_ratio)\n", @@ -4210,13 +203,13 @@ "\n", " np.testing.assert_approx_equal(\n", " actual=pcloud*(initial_water_vapour_mixing_ratio/(initial_water_vapour_mixing_ratio + const.eps))/\n", - " formulae.saturation_vapour_pressure.pvs_water(Tcloud),\n", + " formulae.saturation_vapour_pressure.pvs_water(Tcloud),\n", " desired=1,\n", " significant=4\n", " )\n", "\n", " for j,r in enumerate(radius_array[::-1]):\n", - " settings = Settings( \n", + " settings = Settings(\n", " planet=new_Earth,\n", " r_wet= r,\n", " mass_of_dry_air= 1e5*si.kg,\n", @@ -4226,7 +219,7 @@ " Zcloud= Zcloud,\n", " Tcloud= Tcloud,\n", " formulae=formulae,\n", - " )\n", + " )\n", " simulation = Simulation(settings)\n", " try:\n", " output = simulation.run()\n", @@ -4241,7 +234,52 @@ }, { "cell_type": "code", - "execution_count": 120, + "execution_count": null, + "id": "4352de81", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "\n", + "\u001b[A\u001b[A" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "b689421b8135426ba682b30cb58374ee", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/50 [00:00= '3.10'" }, +] +wheels = [ + { url = 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+3525,7 @@ tests = [ { name = "matplotlib", version = "3.9.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version == '3.9.*'" }, { name = "matplotlib", version = "3.10.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10'" }, { name = "open-atmos-jupyter-utils" }, + { name = "pypartmc" }, { name = "pyrcel" }, { name = "pysdm-examples" }, { name = "pytest" }, @@ -3501,6 +3544,7 @@ requires-dist = [ { name = "open-atmos-jupyter-utils", marker = "extra == 'tests'", specifier = ">=1.2.0" }, { name = "pint" }, { name = "pyevtk" }, + { name = "pypartmc", marker = "extra == 'tests'" }, { name = "pyrcel", marker = "extra == 'tests'" }, { name = "pysdm-examples", marker = "extra == 'tests'" }, { name = "pytest", marker = "extra == 'tests'" }, From c23abda2df28f1cb1ad108c741d7786f747bb370 Mon Sep 17 00:00:00 2001 From: Piotr Kubala Date: Sat, 7 Jun 2025 17:09:49 +0200 Subject: [PATCH 2/7] thread count fix --- .../Loftus_and_Wordsworth_2021/figure_2.ipynb | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb index 5b6e665b9c..2e85f0c1d6 100644 --- a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb +++ b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb @@ -2,12 +2,12 @@ "cells": [ { "cell_type": "code", - "execution_count": 38, + "execution_count": null, "id": "d8f644e9", "metadata": {}, "outputs": [], "source": [ - "import copy\n", + "import os\n", "\n", "import PySDM.products as PySDM_products\n", "import numpy as np\n", @@ -272,7 +272,7 @@ "source": [ "from joblib import Parallel, delayed\n", "with tqdm_joblib(tqdm(desc=\"RH‐sweep\", total=len(RH_array))) as progress:\n", - " all_rows = Parallel(n_jobs=12)(\n", + " all_rows = Parallel(n_jobs=os.cpu_count())(\n", " delayed(compute_one_RH)(RH) for RH in RH_array\n", " )" ] From cd3772397defb750537343ef6372a0c19288a9fa Mon Sep 17 00:00:00 2001 From: Piotr Kubala Date: Sat, 7 Jun 2025 17:41:25 +0200 Subject: [PATCH 3/7] parallel --- .../Loftus_and_Wordsworth_2021/figure_2.ipynb | 35 ++++++++++++------- 1 file changed, 23 insertions(+), 12 deletions(-) diff --git a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb index 2e85f0c1d6..356d655305 100644 --- a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb +++ b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb @@ -11,7 +11,7 @@ "\n", "import PySDM.products as PySDM_products\n", "import numpy as np\n", - "from numba import njit, prange\n", + "from numba import njit, jit\n", "\n", "from tqdm import tqdm\n", "from tqdm_joblib import tqdm_joblib\n", @@ -158,7 +158,7 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": null, "id": "d3a8f4b9", "metadata": {}, "outputs": [], @@ -174,7 +174,7 @@ "def mix(dry,vap,ratio):\n", " return (dry + ratio * vap)/(1 + ratio)\n", "\n", - "def compute_one_RH(RH):\n", + "def compute_one_RH(i, RH):\n", " \"\"\"\n", " Compute one row of the output_matrix for a given RH.\n", " Returns a 1D numpy array of length len(radius_array).\n", @@ -228,7 +228,7 @@ " break\n", " else:\n", " output_matrix[i, j] = 1 - (output['r'][-1] /(r*1e6))\n", - " except Exception as e:\n", + " except Exception as _:\n", " break" ] }, @@ -273,13 +273,13 @@ "from joblib import Parallel, delayed\n", "with tqdm_joblib(tqdm(desc=\"RH‐sweep\", total=len(RH_array))) as progress:\n", " all_rows = Parallel(n_jobs=os.cpu_count())(\n", - " delayed(compute_one_RH)(RH) for RH in RH_array\n", + " delayed(compute_one_RH)(i, RH) for i, RH in enumerate(RH_array[::-1])\n", " )" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 49, "id": "8e6027d8", "metadata": {}, "outputs": [ @@ -287,17 +287,17 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/3000932436.py:7: UserWarning: The following kwargs were not used by contour: 'aspect', 'interpolation'\n", + "C:\\Users\\piotr\\AppData\\Local\\Temp\\ipykernel_7832\\3000932436.py:7: UserWarning: The following kwargs were not used by contour: 'aspect', 'interpolation'\n", " h = ax[1].contourf(\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/3000932436.py:24: UserWarning: The following kwargs were not used by contour: 'label'\n", + "C:\\Users\\piotr\\AppData\\Local\\Temp\\ipykernel_7832\\3000932436.py:24: UserWarning: The following kwargs were not used by contour: 'label'\n", " ax[1].contour(radius_array,RH_array[::-1],output_matrix[:,::-1], levels=contour_levels, colors=\"red\", linewidths=1.5,label=\"10% mass evaporated\")\n", - "/var/folders/yz/7pzr048d36q2lbzgc7xyqqf80000gn/T/ipykernel_54096/3000932436.py:25: UserWarning: No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", + "C:\\Users\\piotr\\AppData\\Local\\Temp\\ipykernel_7832\\3000932436.py:25: UserWarning: No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", " ax[1].legend()\n" ] }, { "data": { - "image/png": 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", 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", 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" ] @@ -337,13 +337,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 50, "id": "369fa24a", "metadata": {}, "outputs": [ + { + "ename": "NameError", + "evalue": "name 'output' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mNameError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[50]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m 1\u001b[39m fig,axs = plt.subplots(\u001b[32m1\u001b[39m, \u001b[32m3\u001b[39m, figsize=(\u001b[32m10\u001b[39m, \u001b[32m8\u001b[39m),sharey=\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m axs[\u001b[32m0\u001b[39m].plot(\u001b[43moutput\u001b[49m[\u001b[33m\"\u001b[39m\u001b[33mr\u001b[39m\u001b[33m\"\u001b[39m], output[\u001b[33m\"\u001b[39m\u001b[33mz\u001b[39m\u001b[33m\"\u001b[39m], label=\u001b[33m\"\u001b[39m\u001b[33mRadius\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m 3\u001b[39m axs[\u001b[32m0\u001b[39m].set_ylabel(\u001b[33m\"\u001b[39m\u001b[33mHeight (m)\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m 4\u001b[39m axs[\u001b[32m0\u001b[39m].set_xlabel(\u001b[33m\"\u001b[39m\u001b[33mRadius (um)\u001b[39m\u001b[33m\"\u001b[39m)\n", + "\u001b[31mNameError\u001b[39m: name 'output' is not defined" + ] + }, { "data": { - "image/png": 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", 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" ] From 35200656c45aad392b38baf42ebffdabb3ec1918 Mon Sep 17 00:00:00 2001 From: Piotr Kubala Date: Sat, 7 Jun 2025 18:19:00 +0200 Subject: [PATCH 4/7] small parallel fixes --- .../Loftus_and_Wordsworth_2021/figure_2.ipynb | 65 +++++++++++-------- .../Loftus_and_Wordsworth_2021/simulation.py | 2 +- 2 files changed, 40 insertions(+), 27 deletions(-) diff --git a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb index 356d655305..4c9fd50608 100644 --- a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb +++ b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb @@ -2,10 +2,19 @@ "cells": [ { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "d8f644e9", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\piotr\\Desktop\\PySDM\\.venv\\Lib\\site-packages\\tqdm_joblib\\__init__.py:4: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n", + " from tqdm.autonotebook import tqdm\n" + ] + } + ], "source": [ "import os\n", "\n", @@ -15,6 +24,7 @@ "\n", "from tqdm import tqdm\n", "from tqdm_joblib import tqdm_joblib\n", + "from joblib import Parallel, delayed\n", "\n", "from PySDM import Builder\n", "from PySDM import Formulae\n", @@ -29,7 +39,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 2, "id": "2fb6b5aa", "metadata": {}, "outputs": [], @@ -44,7 +54,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 3, "id": "92a3a574", "metadata": {}, "outputs": [], @@ -61,7 +71,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 4, "id": "41f0ed6d", "metadata": {}, "outputs": [ @@ -71,7 +81,7 @@ "300.0" ] }, - "execution_count": 41, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -83,7 +93,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 5, "id": "3249b65e", "metadata": {}, "outputs": [], @@ -163,18 +173,16 @@ "metadata": {}, "outputs": [], "source": [ - "from concurrent.futures import ProcessPoolExecutor, as_completed\n", - "\n", "radius_array = np.logspace(-4.5, -2.5, 50) * si.m\n", "RH_array = np.linspace(0.25, .99, 50)\n", "output_matrix = np.full((len(RH_array), len(radius_array)), np.nan)\n", "const = formulae.constants\n", "\n", - "@njit(parallel=True)\n", + "@njit()\n", "def mix(dry,vap,ratio):\n", " return (dry + ratio * vap)/(1 + ratio)\n", "\n", - "def compute_one_RH(i, RH):\n", + "def compute_one_RH(output_matrix, i, RH):\n", " \"\"\"\n", " Compute one row of the output_matrix for a given RH.\n", " Returns a 1D numpy array of length len(radius_array).\n", @@ -227,6 +235,7 @@ " output_matrix[i, j] = np.nan\n", " break\n", " else:\n", + " print(f\"ADDED! i={i}, j={j}, RH={RH}, r={r}\")\n", " output_matrix[i, j] = 1 - (output['r'][-1] /(r*1e6))\n", " except Exception as _:\n", " break" @@ -234,7 +243,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "id": "4352de81", "metadata": {}, "outputs": [ @@ -242,15 +251,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "\n", - "\n", - "\u001b[A\u001b[A" + "RH‐sweep: 0%| | 0/50 [00:00 \u001b[39m\u001b[32m2\u001b[39m all_rows = \u001b[43mParallel\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mos\u001b[49m\u001b[43m.\u001b[49m\u001b[43mcpu_count\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 3\u001b[39m \u001b[43m \u001b[49m\u001b[43mdelayed\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcompute_one_RH\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43moutput_matrix\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mi\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mRH\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mi\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mRH\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43menumerate\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mRH_array\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[43m:\u001b[49m\u001b[43m-\u001b[49m\u001b[32;43m1\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 4\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\piotr\\Desktop\\PySDM\\.venv\\Lib\\site-packages\\joblib\\parallel.py:2072\u001b[39m, in \u001b[36mParallel.__call__\u001b[39m\u001b[34m(self, iterable)\u001b[39m\n\u001b[32m 2066\u001b[39m \u001b[38;5;66;03m# The first item from the output is blank, but it makes the interpreter\u001b[39;00m\n\u001b[32m 2067\u001b[39m \u001b[38;5;66;03m# progress until it enters the Try/Except block of the generator and\u001b[39;00m\n\u001b[32m 2068\u001b[39m \u001b[38;5;66;03m# reaches the first `yield` statement. This starts the asynchronous\u001b[39;00m\n\u001b[32m 2069\u001b[39m \u001b[38;5;66;03m# dispatch of the tasks to the workers.\u001b[39;00m\n\u001b[32m 2070\u001b[39m \u001b[38;5;28mnext\u001b[39m(output)\n\u001b[32m-> \u001b[39m\u001b[32m2072\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m output \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.return_generator \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43moutput\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\piotr\\Desktop\\PySDM\\.venv\\Lib\\site-packages\\joblib\\parallel.py:1682\u001b[39m, in \u001b[36mParallel._get_outputs\u001b[39m\u001b[34m(self, iterator, pre_dispatch)\u001b[39m\n\u001b[32m 1679\u001b[39m \u001b[38;5;28;01myield\u001b[39;00m\n\u001b[32m 1681\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m._backend.retrieval_context():\n\u001b[32m-> \u001b[39m\u001b[32m1682\u001b[39m \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m._retrieve()\n\u001b[32m 1684\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mGeneratorExit\u001b[39;00m:\n\u001b[32m 1685\u001b[39m \u001b[38;5;66;03m# The generator has been garbage collected before being fully\u001b[39;00m\n\u001b[32m 1686\u001b[39m \u001b[38;5;66;03m# consumed. This aborts the remaining tasks if possible and warn\u001b[39;00m\n\u001b[32m 1687\u001b[39m \u001b[38;5;66;03m# the user if necessary.\u001b[39;00m\n\u001b[32m 1688\u001b[39m \u001b[38;5;28mself\u001b[39m._exception = \u001b[38;5;28;01mTrue\u001b[39;00m\n", + "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\piotr\\Desktop\\PySDM\\.venv\\Lib\\site-packages\\joblib\\parallel.py:1800\u001b[39m, in \u001b[36mParallel._retrieve\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m 1789\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.return_ordered:\n\u001b[32m 1790\u001b[39m \u001b[38;5;66;03m# Case ordered: wait for completion (or error) of the next job\u001b[39;00m\n\u001b[32m 1791\u001b[39m \u001b[38;5;66;03m# that have been dispatched and not retrieved yet. If no job\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 1795\u001b[39m \u001b[38;5;66;03m# control only have to be done on the amount of time the next\u001b[39;00m\n\u001b[32m 1796\u001b[39m \u001b[38;5;66;03m# dispatched job is pending.\u001b[39;00m\n\u001b[32m 1797\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m (nb_jobs == \u001b[32m0\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[32m 1798\u001b[39m \u001b[38;5;28mself\u001b[39m._jobs[\u001b[32m0\u001b[39m].get_status(timeout=\u001b[38;5;28mself\u001b[39m.timeout) == TASK_PENDING\n\u001b[32m 1799\u001b[39m ):\n\u001b[32m-> \u001b[39m\u001b[32m1800\u001b[39m \u001b[43mtime\u001b[49m\u001b[43m.\u001b[49m\u001b[43msleep\u001b[49m\u001b[43m(\u001b[49m\u001b[32;43m0.01\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m 1801\u001b[39m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[32m 1803\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m nb_jobs == \u001b[32m0\u001b[39m:\n\u001b[32m 1804\u001b[39m \u001b[38;5;66;03m# Case unordered: jobs are added to the list of jobs to\u001b[39;00m\n\u001b[32m 1805\u001b[39m \u001b[38;5;66;03m# retrieve `self._jobs` only once completed or in error, which\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 1811\u001b[39m \u001b[38;5;66;03m# timeouts before any other dispatched job has completed and\u001b[39;00m\n\u001b[32m 1812\u001b[39m \u001b[38;5;66;03m# been added to `self._jobs` to be retrieved.\u001b[39;00m\n", + "\u001b[31mKeyboardInterrupt\u001b[39m: " ] } ], "source": [ - "from joblib import Parallel, delayed\n", "with tqdm_joblib(tqdm(desc=\"RH‐sweep\", total=len(RH_array))) as progress:\n", " all_rows = Parallel(n_jobs=os.cpu_count())(\n", - " delayed(compute_one_RH)(i, RH) for i, RH in enumerate(RH_array[::-1])\n", + " delayed(compute_one_RH)(output_matrix, i, RH) for i, RH in enumerate(RH_array[::-1])\n", " )" ] }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 27, "id": "8e6027d8", "metadata": {}, "outputs": [ @@ -287,11 +300,11 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\piotr\\AppData\\Local\\Temp\\ipykernel_7832\\3000932436.py:7: UserWarning: The following kwargs were not used by contour: 'aspect', 'interpolation'\n", + "C:\\Users\\piotr\\AppData\\Local\\Temp\\ipykernel_15956\\3000932436.py:7: UserWarning: The following kwargs were not used by contour: 'aspect', 'interpolation'\n", " h = ax[1].contourf(\n", - "C:\\Users\\piotr\\AppData\\Local\\Temp\\ipykernel_7832\\3000932436.py:24: UserWarning: The following kwargs were not used by contour: 'label'\n", + "C:\\Users\\piotr\\AppData\\Local\\Temp\\ipykernel_15956\\3000932436.py:24: UserWarning: The following kwargs were not used by contour: 'label'\n", " ax[1].contour(radius_array,RH_array[::-1],output_matrix[:,::-1], levels=contour_levels, colors=\"red\", linewidths=1.5,label=\"10% mass evaporated\")\n", - "C:\\Users\\piotr\\AppData\\Local\\Temp\\ipykernel_7832\\3000932436.py:25: UserWarning: No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", + "C:\\Users\\piotr\\AppData\\Local\\Temp\\ipykernel_15956\\3000932436.py:25: UserWarning: No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", " ax[1].legend()\n" ] }, diff --git a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/simulation.py b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/simulation.py index 4c7d516519..22ac08fa52 100644 --- a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/simulation.py +++ b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/simulation.py @@ -15,7 +15,6 @@ # Some of this is probably not needed, not sure what yet class Simulation: def __init__(self, settings, backend=CPU): - builder = Builder( backend=backend( formulae=settings.formulae, @@ -75,6 +74,7 @@ def save(self, output): output["S"].append(self.particulator.products["RH"].get()[cell_id] / 100 - 1) output["t"].append(self.particulator.products["t"].get()) + def run(self): output = { "r": [], From 338f86fd4f84c51da459ee1c3f5312429f66d9ee Mon Sep 17 00:00:00 2001 From: lursz Date: Sat, 7 Jun 2025 19:02:40 +0200 Subject: [PATCH 5/7] working multithread solution --- .../Loftus_and_Wordsworth_2021/figure_2.ipynb | 203 ++++-------------- 1 file changed, 37 insertions(+), 166 deletions(-) diff --git a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb index 4c9fd50608..c695386821 100644 --- a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb +++ b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb @@ -5,16 +5,7 @@ "execution_count": 1, "id": "d8f644e9", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\Users\\piotr\\Desktop\\PySDM\\.venv\\Lib\\site-packages\\tqdm_joblib\\__init__.py:4: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n", - " from tqdm.autonotebook import tqdm\n" - ] - } - ], + "outputs": [], "source": [ "import os\n", "\n", @@ -22,8 +13,6 @@ "import numpy as np\n", "from numba import njit, jit\n", "\n", - "from tqdm import tqdm\n", - "from tqdm_joblib import tqdm_joblib\n", "from joblib import Parallel, delayed\n", "\n", "from PySDM import Builder\n", @@ -44,9 +33,6 @@ "metadata": {}, "outputs": [], "source": [ - "from PySDM.physics import terminal_velocity\n", - "from PySDM.physics import drop_growth\n", - "from PySDM.physics import ventilation\n", "from PySDM.physics.particle_shape_and_density.oblate_spheroid import OblateSpheroid\n", "from PySDM.physics import si\n", "from scipy.optimize import fsolve\n" @@ -54,18 +40,18 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "92a3a574", "metadata": {}, "outputs": [], "source": [ "formulae= Formulae(\n", - " # terminal_velocity=\"LofusEtAl2021\", #eqn 8\n", - " # drop_growth=\"RogersAndYau1996\", #eqn 10\n", - " # particle_shape_and_density=\"OblateSpheroid\",\n", - " ventilation=\"PruppacherAndRasmussen1979\", #drag force/ gravitation eqns\n", - " saturation_vapour_pressure=\"AugustRocheMagnus\",\n", - " diffusion_coordinate=\"WaterMassLogarithm\",\n", + " # terminal_velocity = \"LofusEtAl2021\", #eqn 8\n", + " # drop_growth = \"RogersAndYau1996\", #eqn 10\n", + " # particle_shape_and_density = \"OblateSpheroid\",\n", + " ventilation = \"PruppacherAndRasmussen1979\", #drag force/ gravitation eqns\n", + " saturation_vapour_pressure = \"AugustRocheMagnus\",\n", + " diffusion_coordinate = \"WaterMassLogarithm\",\n", ")\n" ] }, @@ -93,82 +79,7 @@ }, { "cell_type": "code", - "execution_count": 5, - "id": "3249b65e", - "metadata": {}, - "outputs": [], - "source": [ - "# radius_array = np.logspace(-4.5, -2.5, 50) * si.m\n", - "# RH_array = np.linspace(0.25, .99, 50)\n", - "# output_matrix = np.full((len(RH_array), len(radius_array)), np.nan)\n", - "# const = formulae.constants\n", - "\n", - "# def mix(dry,vap,ratio):\n", - "# return (dry + ratio * vap)/(1 + ratio)\n", - "\n", - "# def compute_plot():\n", - "# RH_reversed = RH_array[::-1]\n", - "# size_reversed = len(RH_reversed)\n", - "\n", - "# for i in range(size_reversed):\n", - "# RH = RH_reversed[i]\n", - "\n", - "# new_Earth.RH_zref = RH\n", - "\n", - "# pvs = formulae.saturation_vapour_pressure.pvs_water(new_Earth.T_STP)\n", - "# initial_water_vapour_mixing_ratio = const.eps / (new_Earth.p_STP / new_Earth.RH_zref / pvs - 1\n", - "# )\n", - "\n", - "# Rair = mix(const.Rd,const.Rv,initial_water_vapour_mixing_ratio)\n", - "# c_p = mix(const.c_pd,const.c_pv,initial_water_vapour_mixing_ratio)\n", - "\n", - "# def f(x):\n", - "# return initial_water_vapour_mixing_ratio/(initial_water_vapour_mixing_ratio+ const.eps)*new_Earth.p_STP*(x/new_Earth.T_STP)**(c_p/Rair\n", - "# ) - formulae.saturation_vapour_pressure.pvs_water(x)\n", - " \n", - "# tdews = (fsolve(f, [150,300]))\n", - "# Tcloud = np.max(tdews)\n", - "# Zcloud = (new_Earth.T_STP-Tcloud)*c_p/new_Earth.g_std\n", - "# thstd = formulae.trivia.th_std(new_Earth.p_STP, new_Earth.T_STP)\n", - "\n", - "# pcloud = formulae.hydrostatics.p_of_z_assuming_const_th_and_initial_water_vapour_mixing_ratio(new_Earth.p_STP, \n", - "# thstd, initial_water_vapour_mixing_ratio, Zcloud)\n", - "\n", - "\n", - "# np.testing.assert_approx_equal(\n", - "# actual=pcloud*(initial_water_vapour_mixing_ratio/(initial_water_vapour_mixing_ratio + const.eps))/\n", - "# formulae.saturation_vapour_pressure.pvs_water(Tcloud),\n", - "# desired=1,\n", - "# significant=4\n", - "# )\n", - "\n", - "# for j,r in enumerate(radius_array[::-1]):\n", - "# settings = Settings(\n", - "# planet=new_Earth,\n", - "# r_wet= r,\n", - "# mass_of_dry_air= 1e5*si.kg,\n", - "# coord= \"WaterMassLogarithm\",\n", - "# initial_water_vapour_mixing_ratio= initial_water_vapour_mixing_ratio,\n", - "# pcloud= pcloud,\n", - "# Zcloud= Zcloud,\n", - "# Tcloud= Tcloud,\n", - "# formulae=formulae,\n", - "# )\n", - "# simulation = Simulation(settings)\n", - "# try:\n", - "# output = simulation.run()\n", - "# if output['z'][-1] > 0:\n", - "# output_matrix[i, j] = np.nan\n", - "# break\n", - "# else:\n", - "# output_matrix[i, j] = 1 - (output['r'][-1] /(r*1e6))\n", - "# except Exception as e:\n", - "# break" - ] - }, - { - "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "d3a8f4b9", "metadata": {}, "outputs": [], @@ -182,7 +93,7 @@ "def mix(dry,vap,ratio):\n", " return (dry + ratio * vap)/(1 + ratio)\n", "\n", - "def compute_one_RH(output_matrix, i, RH):\n", + "def compute_one_RH(i, RH):\n", " \"\"\"\n", " Compute one row of the output_matrix for a given RH.\n", " Returns a 1D numpy array of length len(radius_array).\n", @@ -216,6 +127,8 @@ " significant=4\n", " )\n", "\n", + " output = None\n", + " row_data = np.full(len(radius_array), np.nan)\n", " for j,r in enumerate(radius_array[::-1]):\n", " settings = Settings(\n", " planet=new_Earth,\n", @@ -232,67 +145,36 @@ " try:\n", " output = simulation.run()\n", " if output['z'][-1] > 0:\n", - " output_matrix[i, j] = np.nan\n", + " row_data[j] = np.nan\n", " break\n", " else:\n", - " print(f\"ADDED! i={i}, j={j}, RH={RH}, r={r}\")\n", - " output_matrix[i, j] = 1 - (output['r'][-1] /(r*1e6))\n", + " row_data[j] = 1 - (output['r'][-1] /(r*1e6))\n", " except Exception as _:\n", - " break" + " break\n", + "\n", + " return i, row_data, output" ] }, { "cell_type": "code", - "execution_count": 28, + "execution_count": null, "id": "4352de81", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "RH‐sweep: 0%| | 0/50 [00:00 \u001b[39m\u001b[32m2\u001b[39m all_rows = \u001b[43mParallel\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mos\u001b[49m\u001b[43m.\u001b[49m\u001b[43mcpu_count\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 3\u001b[39m \u001b[43m \u001b[49m\u001b[43mdelayed\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcompute_one_RH\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43moutput_matrix\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mi\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mRH\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mi\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mRH\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43menumerate\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mRH_array\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[43m:\u001b[49m\u001b[43m-\u001b[49m\u001b[32;43m1\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 4\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\piotr\\Desktop\\PySDM\\.venv\\Lib\\site-packages\\joblib\\parallel.py:2072\u001b[39m, in \u001b[36mParallel.__call__\u001b[39m\u001b[34m(self, iterable)\u001b[39m\n\u001b[32m 2066\u001b[39m \u001b[38;5;66;03m# The first item from the output is blank, but it makes the interpreter\u001b[39;00m\n\u001b[32m 2067\u001b[39m \u001b[38;5;66;03m# progress until it enters the Try/Except block of the generator and\u001b[39;00m\n\u001b[32m 2068\u001b[39m \u001b[38;5;66;03m# reaches the first `yield` statement. This starts the asynchronous\u001b[39;00m\n\u001b[32m 2069\u001b[39m \u001b[38;5;66;03m# dispatch of the tasks to the workers.\u001b[39;00m\n\u001b[32m 2070\u001b[39m \u001b[38;5;28mnext\u001b[39m(output)\n\u001b[32m-> \u001b[39m\u001b[32m2072\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m output \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.return_generator \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43moutput\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\piotr\\Desktop\\PySDM\\.venv\\Lib\\site-packages\\joblib\\parallel.py:1682\u001b[39m, in \u001b[36mParallel._get_outputs\u001b[39m\u001b[34m(self, iterator, pre_dispatch)\u001b[39m\n\u001b[32m 1679\u001b[39m \u001b[38;5;28;01myield\u001b[39;00m\n\u001b[32m 1681\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m._backend.retrieval_context():\n\u001b[32m-> \u001b[39m\u001b[32m1682\u001b[39m \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m._retrieve()\n\u001b[32m 1684\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mGeneratorExit\u001b[39;00m:\n\u001b[32m 1685\u001b[39m \u001b[38;5;66;03m# The generator has been garbage collected before being fully\u001b[39;00m\n\u001b[32m 1686\u001b[39m \u001b[38;5;66;03m# consumed. This aborts the remaining tasks if possible and warn\u001b[39;00m\n\u001b[32m 1687\u001b[39m \u001b[38;5;66;03m# the user if necessary.\u001b[39;00m\n\u001b[32m 1688\u001b[39m \u001b[38;5;28mself\u001b[39m._exception = \u001b[38;5;28;01mTrue\u001b[39;00m\n", - "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\piotr\\Desktop\\PySDM\\.venv\\Lib\\site-packages\\joblib\\parallel.py:1800\u001b[39m, in \u001b[36mParallel._retrieve\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m 1789\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.return_ordered:\n\u001b[32m 1790\u001b[39m \u001b[38;5;66;03m# Case ordered: wait for completion (or error) of the next job\u001b[39;00m\n\u001b[32m 1791\u001b[39m \u001b[38;5;66;03m# that have been dispatched and not retrieved yet. If no job\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 1795\u001b[39m \u001b[38;5;66;03m# control only have to be done on the amount of time the next\u001b[39;00m\n\u001b[32m 1796\u001b[39m \u001b[38;5;66;03m# dispatched job is pending.\u001b[39;00m\n\u001b[32m 1797\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m (nb_jobs == \u001b[32m0\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[32m 1798\u001b[39m \u001b[38;5;28mself\u001b[39m._jobs[\u001b[32m0\u001b[39m].get_status(timeout=\u001b[38;5;28mself\u001b[39m.timeout) == TASK_PENDING\n\u001b[32m 1799\u001b[39m ):\n\u001b[32m-> \u001b[39m\u001b[32m1800\u001b[39m \u001b[43mtime\u001b[49m\u001b[43m.\u001b[49m\u001b[43msleep\u001b[49m\u001b[43m(\u001b[49m\u001b[32;43m0.01\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m 1801\u001b[39m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[32m 1803\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m nb_jobs == \u001b[32m0\u001b[39m:\n\u001b[32m 1804\u001b[39m \u001b[38;5;66;03m# Case unordered: jobs are added to the list of jobs to\u001b[39;00m\n\u001b[32m 1805\u001b[39m \u001b[38;5;66;03m# retrieve `self._jobs` only once completed or in error, which\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 1811\u001b[39m \u001b[38;5;66;03m# timeouts before any other dispatched job has completed and\u001b[39;00m\n\u001b[32m 1812\u001b[39m \u001b[38;5;66;03m# been added to `self._jobs` to be retrieved.\u001b[39;00m\n", - "\u001b[31mKeyboardInterrupt\u001b[39m: " - ] - } - ], + "outputs": [], "source": [ - "with tqdm_joblib(tqdm(desc=\"RH‐sweep\", total=len(RH_array))) as progress:\n", - " all_rows = Parallel(n_jobs=os.cpu_count())(\n", - " delayed(compute_one_RH)(output_matrix, i, RH) for i, RH in enumerate(RH_array[::-1])\n", - " )" + "all_rows = Parallel(n_jobs=os.cpu_count())(\n", + " delayed(compute_one_RH)(i, RH) for i, RH in enumerate(RH_array[::-1])\n", + ")\n", + "\n", + "last_output = None\n", + "for i, row_data, output in all_rows:\n", + " output_matrix[i] = row_data\n", + " last_output = output" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 8, "id": "8e6027d8", "metadata": {}, "outputs": [ @@ -300,17 +182,17 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\piotr\\AppData\\Local\\Temp\\ipykernel_15956\\3000932436.py:7: UserWarning: The following kwargs were not used by contour: 'aspect', 'interpolation'\n", + "/var/folders/8p/ctsxm4l530g0pklqbwhg1fg00000gn/T/ipykernel_3283/3000932436.py:7: UserWarning: The following kwargs were not used by contour: 'aspect', 'interpolation'\n", " h = ax[1].contourf(\n", - "C:\\Users\\piotr\\AppData\\Local\\Temp\\ipykernel_15956\\3000932436.py:24: UserWarning: The following kwargs were not used by contour: 'label'\n", + "/var/folders/8p/ctsxm4l530g0pklqbwhg1fg00000gn/T/ipykernel_3283/3000932436.py:24: UserWarning: The following kwargs were not used by contour: 'label'\n", " ax[1].contour(radius_array,RH_array[::-1],output_matrix[:,::-1], levels=contour_levels, colors=\"red\", linewidths=1.5,label=\"10% mass evaporated\")\n", - "C:\\Users\\piotr\\AppData\\Local\\Temp\\ipykernel_15956\\3000932436.py:25: UserWarning: No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", + "/var/folders/8p/ctsxm4l530g0pklqbwhg1fg00000gn/T/ipykernel_3283/3000932436.py:25: UserWarning: No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", " ax[1].legend()\n" ] }, { "data": { - "image/png": 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", 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", 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" ] @@ -350,24 +232,13 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 9, "id": "369fa24a", "metadata": {}, "outputs": [ - { - "ename": "NameError", - "evalue": "name 'output' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mNameError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[50]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m 1\u001b[39m fig,axs = plt.subplots(\u001b[32m1\u001b[39m, \u001b[32m3\u001b[39m, figsize=(\u001b[32m10\u001b[39m, \u001b[32m8\u001b[39m),sharey=\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m axs[\u001b[32m0\u001b[39m].plot(\u001b[43moutput\u001b[49m[\u001b[33m\"\u001b[39m\u001b[33mr\u001b[39m\u001b[33m\"\u001b[39m], output[\u001b[33m\"\u001b[39m\u001b[33mz\u001b[39m\u001b[33m\"\u001b[39m], label=\u001b[33m\"\u001b[39m\u001b[33mRadius\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m 3\u001b[39m axs[\u001b[32m0\u001b[39m].set_ylabel(\u001b[33m\"\u001b[39m\u001b[33mHeight (m)\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m 4\u001b[39m axs[\u001b[32m0\u001b[39m].set_xlabel(\u001b[33m\"\u001b[39m\u001b[33mRadius (um)\u001b[39m\u001b[33m\"\u001b[39m)\n", - "\u001b[31mNameError\u001b[39m: name 'output' is not defined" - ] - }, { "data": { - "image/png": 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", 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", 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" ] @@ -378,15 +249,15 @@ ], "source": [ "fig,axs = plt.subplots(1, 3, figsize=(10, 8),sharey=True)\n", - "axs[0].plot(output[\"r\"], output[\"z\"], label=\"Radius\")\n", + "axs[0].plot(last_output[\"r\"], last_output[\"z\"], label=\"Radius\")\n", "axs[0].set_ylabel(\"Height (m)\")\n", "axs[0].set_xlabel(\"Radius (um)\")\n", "axs[0].legend()\n", - "axs[1].plot(output[\"S\"], output[\"z\"], label=\"Supersaturation\")\n", + "axs[1].plot(last_output[\"S\"], last_output[\"z\"], label=\"Supersaturation\")\n", "axs[1].set_xlabel(\"Supersaturation\")\n", "axs[1].set_ylabel(\"Height (m)\")\n", "axs[1].legend()\n", - "axs[2].plot(output[\"t\"], output[\"z\"], label=\"Height\")\n", + "axs[2].plot(last_output[\"t\"], last_output[\"z\"], label=\"Height\")\n", "axs[2].set_ylabel(\"Height (m)\")\n", "axs[2].set_xlabel(\"Time (s)\")\n", "axs[2].legend()\n", From b9141b22c0c5d6b3c1f48221139c8a09a18c9b6d Mon Sep 17 00:00:00 2001 From: lursz Date: Sat, 7 Jun 2025 19:32:36 +0200 Subject: [PATCH 6/7] Multi-thread + vector plots --- .../Loftus_and_Wordsworth_2021/figure_2.ipynb | 14577 +++++++++++++++- 1 file changed, 14508 insertions(+), 69 deletions(-) diff --git a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb index c695386821..20c4d7495d 100644 --- a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb +++ b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/figure_2.ipynb @@ -2,62 +2,57 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, + "id": "1e8d983b", + "metadata": {}, + "outputs": [], + "source": [ + "# !pip install joblib" + ] + }, + { + "cell_type": "code", + "execution_count": 10, "id": "d8f644e9", "metadata": {}, "outputs": [], "source": [ "import os\n", - "\n", - "import PySDM.products as PySDM_products\n", + "import matplotlib.pyplot as plt\n", "import numpy as np\n", - "from numba import njit, jit\n", - "\n", + "from numba import njit\n", + "from open_atmos_jupyter_utils import show_plot\n", "from joblib import Parallel, delayed\n", - "\n", - "from PySDM import Builder\n", "from PySDM import Formulae\n", "from PySDM_examples.Lowe_et_al_2019.constants_def import LOWE_CONSTS\n", - "\n", "from PySDM_examples.Loftus_and_Wordsworth_2021 import Settings\n", - "from PySDM_examples.Loftus_and_Wordsworth_2021.planet import Planet,EarthLike, Earth, EarlyMars, Jupiter, Saturn, K2_18B\n", - "from PySDM_examples.Loftus_and_Wordsworth_2021.parcel import AlienParcel\n", + "from PySDM_examples.Loftus_and_Wordsworth_2021.planet import (Planet, EarthLike, Earth, EarlyMars, Jupiter, Saturn, K2_18B)\n", "from PySDM_examples.Loftus_and_Wordsworth_2021 import Simulation\n", - "import matplotlib.pyplot as plt" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "2fb6b5aa", - "metadata": {}, - "outputs": [], - "source": [ "from PySDM.physics.particle_shape_and_density.oblate_spheroid import OblateSpheroid\n", "from PySDM.physics import si\n", - "from scipy.optimize import fsolve\n" + "from scipy.optimize import fsolve" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "92a3a574", "metadata": {}, "outputs": [], "source": [ - "formulae= Formulae(\n", + "formulae = Formulae(\n", " # terminal_velocity = \"LofusEtAl2021\", #eqn 8\n", " # drop_growth = \"RogersAndYau1996\", #eqn 10\n", " # particle_shape_and_density = \"OblateSpheroid\",\n", - " ventilation = \"PruppacherAndRasmussen1979\", #drag force/ gravitation eqns\n", - " saturation_vapour_pressure = \"AugustRocheMagnus\",\n", - " diffusion_coordinate = \"WaterMassLogarithm\",\n", - ")\n" + " ventilation=\"PruppacherAndRasmussen1979\", # drag force/ gravitation eqns\n", + " saturation_vapour_pressure=\"AugustRocheMagnus\",\n", + " diffusion_coordinate=\"WaterMassLogarithm\",\n", + ")" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 12, "id": "41f0ed6d", "metadata": {}, "outputs": [ @@ -67,7 +62,7 @@ "300.0" ] }, - "execution_count": 4, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -79,19 +74,21 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 13, "id": "d3a8f4b9", "metadata": {}, "outputs": [], "source": [ "radius_array = np.logspace(-4.5, -2.5, 50) * si.m\n", - "RH_array = np.linspace(0.25, .99, 50)\n", + "RH_array = np.linspace(0.25, 0.99, 50)\n", "output_matrix = np.full((len(RH_array), len(radius_array)), np.nan)\n", "const = formulae.constants\n", "\n", + "\n", "@njit()\n", - "def mix(dry,vap,ratio):\n", - " return (dry + ratio * vap)/(1 + ratio)\n", + "def mix(dry, vap, ratio):\n", + " return (dry + ratio * vap) / (1 + ratio)\n", + "\n", "\n", "def compute_one_RH(i, RH):\n", " \"\"\"\n", @@ -101,54 +98,64 @@ " new_Earth.RH_zref = RH\n", "\n", " pvs = formulae.saturation_vapour_pressure.pvs_water(new_Earth.T_STP)\n", - " initial_water_vapour_mixing_ratio = const.eps / (new_Earth.p_STP / new_Earth.RH_zref / pvs - 1\n", + " initial_water_vapour_mixing_ratio = const.eps / (\n", + " new_Earth.p_STP / new_Earth.RH_zref / pvs - 1\n", " )\n", "\n", - " Rair = mix(const.Rd,const.Rv,initial_water_vapour_mixing_ratio)\n", - " c_p = mix(const.c_pd,const.c_pv,initial_water_vapour_mixing_ratio)\n", + " Rair = mix(const.Rd, const.Rv, initial_water_vapour_mixing_ratio)\n", + " c_p = mix(const.c_pd, const.c_pv, initial_water_vapour_mixing_ratio)\n", "\n", " def f(x):\n", - " return initial_water_vapour_mixing_ratio/(initial_water_vapour_mixing_ratio+ const.eps)*new_Earth.p_STP*(x/new_Earth.T_STP)**(c_p/Rair\n", - " ) - formulae.saturation_vapour_pressure.pvs_water(x)\n", - " \n", - " tdews = (fsolve(f, [150,300]))\n", + " return initial_water_vapour_mixing_ratio / (\n", + " initial_water_vapour_mixing_ratio + const.eps\n", + " ) * new_Earth.p_STP * (x / new_Earth.T_STP) ** (\n", + " c_p / Rair\n", + " ) - formulae.saturation_vapour_pressure.pvs_water(\n", + " x\n", + " )\n", + "\n", + " tdews = fsolve(f, [150, 300])\n", " Tcloud = np.max(tdews)\n", - " Zcloud = (new_Earth.T_STP-Tcloud)*c_p/new_Earth.g_std\n", + " Zcloud = (new_Earth.T_STP - Tcloud) * c_p / new_Earth.g_std\n", " thstd = formulae.trivia.th_std(new_Earth.p_STP, new_Earth.T_STP)\n", "\n", - " pcloud = formulae.hydrostatics.p_of_z_assuming_const_th_and_initial_water_vapour_mixing_ratio(new_Earth.p_STP, \n", - " thstd, initial_water_vapour_mixing_ratio, Zcloud)\n", - "\n", + " pcloud = formulae.hydrostatics.p_of_z_assuming_const_th_and_initial_water_vapour_mixing_ratio(\n", + " new_Earth.p_STP, thstd, initial_water_vapour_mixing_ratio, Zcloud\n", + " )\n", "\n", " np.testing.assert_approx_equal(\n", - " actual=pcloud*(initial_water_vapour_mixing_ratio/(initial_water_vapour_mixing_ratio + const.eps))/\n", - " formulae.saturation_vapour_pressure.pvs_water(Tcloud),\n", - " desired=1,\n", - " significant=4\n", + " actual=pcloud\n", + " * (\n", + " initial_water_vapour_mixing_ratio\n", + " / (initial_water_vapour_mixing_ratio + const.eps)\n", " )\n", + " / formulae.saturation_vapour_pressure.pvs_water(Tcloud),\n", + " desired=1,\n", + " significant=4,\n", + " )\n", "\n", " output = None\n", " row_data = np.full(len(radius_array), np.nan)\n", - " for j,r in enumerate(radius_array[::-1]):\n", + " for j, r in enumerate(radius_array[::-1]):\n", " settings = Settings(\n", - " planet=new_Earth,\n", - " r_wet= r,\n", - " mass_of_dry_air= 1e5*si.kg,\n", - " coord= \"WaterMassLogarithm\",\n", - " initial_water_vapour_mixing_ratio= initial_water_vapour_mixing_ratio,\n", - " pcloud= pcloud,\n", - " Zcloud= Zcloud,\n", - " Tcloud= Tcloud,\n", - " formulae=formulae,\n", + " planet=new_Earth,\n", + " r_wet=r,\n", + " mass_of_dry_air=1e5 * si.kg,\n", + " coord=\"WaterMassLogarithm\",\n", + " initial_water_vapour_mixing_ratio=initial_water_vapour_mixing_ratio,\n", + " pcloud=pcloud,\n", + " Zcloud=Zcloud,\n", + " Tcloud=Tcloud,\n", + " formulae=formulae,\n", " )\n", " simulation = Simulation(settings)\n", " try:\n", " output = simulation.run()\n", - " if output['z'][-1] > 0:\n", + " if output[\"z\"][-1] > 0:\n", " row_data[j] = np.nan\n", " break\n", " else:\n", - " row_data[j] = 1 - (output['r'][-1] /(r*1e6))\n", + " row_data[j] = 1 - (output[\"r\"][-1] / (r * 1e6))\n", " except Exception as _:\n", " break\n", "\n", @@ -174,7 +181,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 15, "id": "8e6027d8", "metadata": {}, "outputs": [ @@ -182,23 +189,13036 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/8p/ctsxm4l530g0pklqbwhg1fg00000gn/T/ipykernel_3283/3000932436.py:7: UserWarning: The following kwargs were not used by contour: 'aspect', 'interpolation'\n", + "/var/folders/8p/ctsxm4l530g0pklqbwhg1fg00000gn/T/ipykernel_3283/370885032.py:7: UserWarning: The following kwargs were not used by contour: 'aspect', 'interpolation'\n", " h = ax[1].contourf(\n", - "/var/folders/8p/ctsxm4l530g0pklqbwhg1fg00000gn/T/ipykernel_3283/3000932436.py:24: UserWarning: The following kwargs were not used by contour: 'label'\n", + "/var/folders/8p/ctsxm4l530g0pklqbwhg1fg00000gn/T/ipykernel_3283/370885032.py:24: UserWarning: The following kwargs were not used by contour: 'label'\n", " ax[1].contour(radius_array,RH_array[::-1],output_matrix[:,::-1], levels=contour_levels, colors=\"red\", linewidths=1.5,label=\"10% mass evaporated\")\n", - "/var/folders/8p/ctsxm4l530g0pklqbwhg1fg00000gn/T/ipykernel_3283/3000932436.py:25: UserWarning: No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", + "/var/folders/8p/ctsxm4l530g0pklqbwhg1fg00000gn/T/ipykernel_3283/370885032.py:25: UserWarning: No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", " ax[1].legend()\n" ] }, { "data": { - "image/png": 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\"), HTML(value…" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -227,24 +13247,1443 @@ "contour_levels = [0.1] # Define the level for the contour\n", "ax[1].contour(radius_array,RH_array[::-1],output_matrix[:,::-1], levels=contour_levels, colors=\"red\", linewidths=1.5,label=\"10% mass evaporated\")\n", "ax[1].legend()\n", - "plt.show()" + "show_plot()" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 16, "id": "369fa24a", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\"), HTML(value…" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -261,7 +14700,7 @@ "axs[2].set_ylabel(\"Height (m)\")\n", "axs[2].set_xlabel(\"Time (s)\")\n", "axs[2].legend()\n", - "plt.tight_layout()" + "show_plot()" ] } ], From 02a6dcb36557868051a55f73c5307a4ee245f326 Mon Sep 17 00:00:00 2001 From: lursz Date: Sat, 7 Jun 2025 19:33:00 +0200 Subject: [PATCH 7/7] black, black used everywhere --- .../Loftus_and_Wordsworth_2021/parcel.py | 12 ++++++------ .../Loftus_and_Wordsworth_2021/settings.py | 15 ++++++--------- .../Loftus_and_Wordsworth_2021/simulation.py | 16 ++++++---------- 3 files changed, 18 insertions(+), 25 deletions(-) diff --git a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/parcel.py b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/parcel.py index 4c62f9ae3b..a7da9826bf 100644 --- a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/parcel.py +++ b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/parcel.py @@ -1,4 +1,3 @@ -from typing import List, Optional from PySDM.environments.parcel import Parcel @@ -13,7 +12,6 @@ def __init__( w: float = 0, zcloud: float = 0, mixed_phase=False, - ): super().__init__( dt=dt, @@ -24,7 +22,7 @@ def __init__( w=w, z0=zcloud, mixed_phase=mixed_phase, - variables=None + variables=None, ) def advance_parcel_vars(self): @@ -37,7 +35,9 @@ def advance_parcel_vars(self): T = self["T"][0] p = self["p"][0] - dz_dt = - self.particulator.attributes["terminal velocity"].to_ndarray()[0]#*dt#formulae.trivia.terminal_velocity(self.particulator.#self.w((self.particulator.n_steps + 1 / 2) * dt) + self["terminal_velocity"][0] + dz_dt = -self.particulator.attributes["terminal velocity"].to_ndarray()[ + 0 + ] # *dt#formulae.trivia.terminal_velocity(self.particulator.#self.w((self.particulator.n_steps + 1 / 2) * dt) + self["terminal_velocity"][0] water_vapour_mixing_ratio = ( self["water_vapour_mixing_ratio"][0] - self.delta_liquid_water_mixing_ratio / 2 @@ -53,7 +53,7 @@ def advance_parcel_vars(self): self.delta_liquid_water_mixing_ratio / dz_dt / dt ), ) - drhod_dz = drho_dz + drhod_dz = drho_dz self.particulator.backend.explicit_euler(self._tmp["z"], dt, dz_dt) self.particulator.backend.explicit_euler( @@ -62,4 +62,4 @@ def advance_parcel_vars(self): self.mesh.dv = formulae.trivia.volume_of_density_mass( (self._tmp["rhod"][0] + self["rhod"][0]) / 2, self.mass_of_dry_air - ) \ No newline at end of file + ) diff --git a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/settings.py b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/settings.py index 725e1ab516..e13b6473f3 100644 --- a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/settings.py +++ b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/settings.py @@ -1,15 +1,12 @@ -#Planetary Properties, Loftus and Wordsworth 2021 Table 1 -from PySDM.physics import constants_defaults, si +# Planetary Properties, Loftus and Wordsworth 2021 Table 1 +from PySDM.physics import si -import numpy as np from pystrict import strict -from types import SimpleNamespace from PySDM import Formulae from PySDM.dynamics import condensation from PySDM.physics.constants import si from PySDM_examples.Loftus_and_Wordsworth_2021.planet import Planet -from scipy.optimize import fsolve @strict @@ -33,13 +30,13 @@ def __init__( ) const = self.formulae.constants - self.initial_water_vapour_mixing_ratio = initial_water_vapour_mixing_ratio + self.initial_water_vapour_mixing_ratio = initial_water_vapour_mixing_ratio self.p0 = planet.p_STP self.RH0 = planet.RH_zref self.kappa = 0.2 self.T0 = planet.T_STP self.z_half = 150 * si.metres - self.dt = 1 *si.second + self.dt = 1 * si.second self.pcloud = pcloud self.Zcloud = Zcloud self.Tcloud = Tcloud @@ -48,7 +45,7 @@ def __init__( self.mass_of_dry_air = mass_of_dry_air self.n_output = 500 - self.rtol_x = 0.5*(condensation.DEFAULTS.rtol_x) + self.rtol_x = 0.5 * (condensation.DEFAULTS.rtol_x) self.rtol_thd = condensation.DEFAULTS.rtol_thd self.coord = "volume logarithm" - self.dt_cond_range = condensation.DEFAULTS.cond_range \ No newline at end of file + self.dt_cond_range = condensation.DEFAULTS.cond_range diff --git a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/simulation.py b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/simulation.py index 22ac08fa52..2d922caef8 100644 --- a/examples/PySDM_examples/Loftus_and_Wordsworth_2021/simulation.py +++ b/examples/PySDM_examples/Loftus_and_Wordsworth_2021/simulation.py @@ -4,14 +4,12 @@ from PySDM.backends import CPU from PySDM.builder import Builder from PySDM.dynamics import AmbientThermodynamics, Condensation -from PySDM.environments import Parcel -from PySDM.initialisation import equilibrate_wet_radii from PySDM.physics import constants as const from PySDM_examples.Loftus_and_Wordsworth_2021.parcel import AlienParcel ## General simulation from Arabas and Shima 2017, also looking at Graf et al. 2019 -#Need to edit Parcel in here to change dz into w +terminalv (should this be a w function? an option?) +# Need to edit Parcel in here to change dz into w +terminalv (should this be a w function? an option?) # Some of this is probably not needed, not sure what yet class Simulation: def __init__(self, settings, backend=CPU): @@ -26,10 +24,10 @@ def __init__(self, settings, backend=CPU): ), n_sd=1, environment=AlienParcel( - dt=settings.dt, #dt_output / self.n_substeps, + dt=settings.dt, # dt_output / self.n_substeps, mass_of_dry_air=settings.mass_of_dry_air, pcloud=settings.pcloud, - zcloud= settings.Zcloud, + zcloud=settings.Zcloud, initial_water_vapour_mixing_ratio=settings.initial_water_vapour_mixing_ratio, Tcloud=settings.Tcloud, ), @@ -46,7 +44,7 @@ def __init__(self, settings, backend=CPU): builder.request_attribute("terminal velocity") attributes = {} - r_dry = 1e-10 #np.array([settings.r_dry]) + r_dry = 1e-10 # np.array([settings.r_dry]) attributes["dry volume"] = settings.formulae.trivia.volume(radius=r_dry) attributes["kappa times dry volume"] = attributes["dry volume"] * settings.kappa attributes["multiplicity"] = np.array([1], dtype=np.int64) @@ -63,7 +61,6 @@ def __init__(self, settings, backend=CPU): self.particulator = builder.build(attributes, products) - def save(self, output): cell_id = 0 output["r"].append( @@ -74,7 +71,6 @@ def save(self, output): output["S"].append(self.particulator.products["RH"].get()[cell_id] / 100 - 1) output["t"].append(self.particulator.products["t"].get()) - def run(self): output = { "r": [], @@ -84,9 +80,9 @@ def run(self): } self.save(output) - while self.particulator.environment["z"][0] >0 and output["r"][-1] > 1e-6: + while self.particulator.environment["z"][0] > 0 and output["r"][-1] > 1e-6: # print(self.particulator.environment["z"][0]) self.particulator.run(1) self.save(output) - return output \ No newline at end of file + return output