✨ add plotting module

LICENSE

@@ -186,7 +186,7 @@ Apache License
       same "printed page" as the copyright notice for easier
       identification within third-party archives.
 
-   Copyright [yyyy] [name of copyright owner]
+   Copyright [2022] [Maren Buettner]
 
    Licensed under the Apache License, Version 2.0 (the "License");
    you may not use this file except in compliance with the License.

docs/tutorials/quickstart.ipynb

@@ -58,6 +58,56 @@
     "assert isinstance(adata, anndata._core.anndata.AnnData)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ef471352",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pm.pp.split_signal(adata)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5d94e857",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pm.pp.compensate(adata)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ac74dd0e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "adata_arcsinh = pm.tl.normalize_arcsinh(adata, cofactor=150, inplace=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4a6efc35",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "adata_biexp = pm.tl.normalize_biExp(adata, inplace=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "828cf9c1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "adata_logicle = pm.tl.normalize_logicle(adata, inplace=False)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "995de332",
@@ -79,7 +129,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.9.13 64-bit",
+   "display_name": "Python 3.9.7 ('pyto_dev')",
    "language": "python",
    "name": "python3"
   },
@@ -93,11 +143,11 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.9.7"
   },
   "vscode": {
    "interpreter": {
-    "hash": "b0fa6594d8f4cbf19f97940f81e996739fb7646882a419484c72d19e05852a7e"
+    "hash": "48c3c4927e81daf79217bae0bb1c93e3ab00a11990990ff2e155253980f357b0"
    }
   }
  },

pytometry/__init__.py

@@ -20,8 +20,9 @@
 
 """
 
-__version__ = "0.0.1"  # denote a pre-release for 0.1.0 with 0.1a1
+__version__ = "0.1.0"  # denote a pre-release for 0.1.0 with 0.1a1
 
+from . import plotting as pl
 from . import preprocessing as pp
 from . import read_write as io
 from . import tools as tl

pytometry/plotting/__init__.py

@@ -0,0 +1 @@
+from ._histogram import plotdata

pytometry/plotting/_histogram.py

@@ -0,0 +1,93 @@
+import numpy as np
+import seaborn as sns
+from anndata import AnnData
+from matplotlib import pyplot as plt
+from matplotlib import rcParams
+
+from ..preprocessing._process_data import find_indexes
+from ..tools._normalization import normalize_arcsinh, normalize_biExp, normalize_logicle
+
+
+# Plot data. Choose between Area, Height both(default)
+def plotdata(
+    adata: AnnData,
+    key="signal_type",
+    normalize: str = None,
+    cofactor=10,
+    figsize=(15, 6),
+    option="area",
+    save="",
+    **kwargs,
+):
+    """Creating histogram plot from Anndata object.
+
+    :param adata: AnnData object containing data.
+    :param cofactor: float value to normalize with in arcsinh-transform
+    :param normalize: choose between "arcsinh", "biExp" and "logicle"
+    :param option: Switch to choose directly between area and height data.
+    :param save: Filename to save the shown figure
+    :param kwargs: Passed to :func:`matplotlib.pyplot.savefig`
+    """
+    option_key = option
+    key_in = key
+    adata_ = adata.copy()
+
+    # Check if indices for area and height have been computed
+    if key_in not in adata_.var_keys():
+        find_indexes(adata_)
+
+    if normalize is not None:
+        if normalize.lower().count("arcsinh") > 0:
+            normalize_arcsinh(adata_, cofactor)
+        elif normalize.lower().count("biexp") > 0:
+            normalize_biExp(adata_)
+        elif normalize.lower().count("logicle") > 0:
+            normalize_logicle(adata_)
+        else:
+            print(
+                f"{normalize} is not a valid normalization type. Continue without"
+                " normalization."
+            )
+
+    if option_key not in ["area", "height", "other"]:
+        print(f"Option {option_key} is not a valid category. Return all.")
+        datax = adata_.X
+        var_names = adata_.var_names.values
+    else:
+        index = adata_.var[key_in] == option_key
+        datax = adata_.X[:, index]
+        var_names = adata_.var_names[index].values
+
+    if len(var_names) == 0:
+        print(
+            f"Option {option_key} led to the selection of 0 variables.              "
+            " Nothing to plot."
+        )
+        return
+
+    rcParams["figure.figsize"] = figsize
+
+    names = var_names
+    number = len(names)
+
+    columns = 3
+    rows = np.ceil(number / columns)
+
+    fig = plt.figure()
+    fig.subplots_adjust(hspace=0.4, wspace=0.6)
+
+    for idx in range(number):
+        ax = fig.add_subplot(rows, columns, idx + 1)
+        sns.distplot(
+            datax[:, names == names[idx]],
+            kde=False,
+            norm_hist=False,
+            bins=400,
+            ax=ax,
+            axlabel=names[idx],
+        )
+    if save != "":
+        plt.savefig(save, bbox_inches="tight", **kwargs)
+    plt.show()
+
+    return

pytometry/preprocessing/__init__.py

@@ -1,7 +1 @@
-from ._process_data import (
-    compensate,
-    create_comp_mat,
-    find_indexes,
-    plotdata,
-    split_signal,
-)
+from ._process_data import compensate, create_comp_mat, find_indexes, split_signal

pytometry/preprocessing/_process_data.py

@@ -3,12 +3,7 @@
 
 import numpy as np
 import pandas as pd
-import seaborn as sb
 from anndata import AnnData
-from matplotlib import pyplot as plt
-from matplotlib import rcParams
-
-from ..tools import normalize_arcsinh
 
 # import getpass
 # import os.path
@@ -249,78 +244,3 @@ def split_signal(
     adata._inplace_subset_var(indx)
 
     return None if inplace else adata
-
-
-# TODO: move function to plotting module
-# Plot data. Choose between Area, Height both(default)
-def plotdata(
-    adata: AnnData,
-    key="signal_type",
-    normalize=False,
-    cofactor=10,
-    figsize=(15, 6),
-    option="area",
-    save="",
-    **kwargs,
-):
-    """Creating histogram plot from Anndata object.
-
-    :param adata: AnnData object containing data.
-    :param cofactor: float value to normalize with in arcsinh-transform
-    :param option: Switch to choose directly between area and height data.
-    :param save: Filename to save the shown figure
-    :param kwargs: Passed to :func:`matplotlib.pyplot.savefig`
-    """
-    option_key = option
-    key_in = key
-    adata_ = adata.copy()
-
-    # Check if indices for area and height have been computed
-    if key_in not in adata_.var_keys():
-        find_indexes(adata_)
-
-    if normalize:
-        normalize_arcsinh(adata_, cofactor)
-
-    if option_key not in ["area", "height", "other"]:
-        print(f"Option {option_key} is not a valid category. Return all.")
-        datax = adata_.X
-        var_names = adata_.var_names.values
-    else:
-        index = adata_.var[key_in] == option_key
-        datax = adata_.X[:, index]
-        var_names = adata_.var_names[index].values
-
-    if len(var_names) == 0:
-        print(
-            f"Option {option_key} led to the selection of 0 variables.              "
-            " Nothing to plot."
-        )
-        return
-
-    rcParams["figure.figsize"] = figsize
-
-    names = var_names
-    number = len(names)
-
-    columns = 3
-    rows = np.ceil(number / columns)
-
-    fig = plt.figure()
-    fig.subplots_adjust(hspace=0.4, wspace=0.6)
-
-    for idx in range(number):
-        ax = fig.add_subplot(rows, columns, idx + 1)
-        sb.distplot(
-            datax[:, names == names[idx]],
-            kde=False,
-            norm_hist=False,
-            bins=400,
-            ax=ax,
-            axlabel=names[idx],
-        )
-    if save != "":
-        plt.savefig(save, bbox_inches="tight", **kwargs)
-    plt.show()
-
-    return