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Merged
stefangolas merged 5 commits into from
May 23, 2024
Merged

Added Draft1 of OT2 Notebook (Lab 0) #1

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133922d
Added OT2 Deck Intro
May 15, 2024
200b53d
Merge branch 'main' into OT2_Notebook
stefangolas May 15, 2024
13d1a22
removed scratch
May 15, 2024
59f902e
Merge branch 'OT2_Notebook' of github.com:joelaforet/PyLabRobot_Tutor…
May 15, 2024
6797a6c
finished draft 1 of OT2 notebook (Lab 0)
May 17, 2024
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288 changes: 144 additions & 144 deletions DataSimulations/Introduction_to_Decks.ipynb
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@@ -1,144 +1,144 @@
{
"cells": [
{
"cell_type": "markdown",
"id": "baf9fb61-2fc5-446c-9c4a-18801c7d7afa",
"metadata": {},
"source": [
"**Welcome to PyLabRobot!**\n",
"\n",
"PyLabRobot is a universal Python interface to liquid-handling robots. Liquid-handling robots aspirate and dispense precise volumes\n",
"of liquid in a Cartesian coordinate system, essentially the same as hand pipetting.\n",
"\n",
"PLR defines a universal interface class called LiquidHandler that provides generic methods for controlling robots\n",
"such as aspirate and dispense. This class can be instantiated with one of several backends (or drivers)\n",
"that convert generic commands to machine-specific commands. This makes it easy to write code that will\n",
"be translatable across many different machines.\n",
"\n",
"First we will import `LiquidHandler`, a backend called `ChatterBoxBackend` that prints the text\n",
"output of our commands, a class `Visualizer` that provides a visualization of the robot deck as we\n",
"run commands, and a class `STARLetDeck` that will represent the deck of a Hamilton Microlab STARLet, one of\n",
"the most widely used liquid handling robots."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f8bcf094-3c3a-41c4-b0e8-5d2caeee9ca9",
"metadata": {},
"outputs": [],
"source": [
"from pylabrobot.liquid_handling import LiquidHandler\n",
"from pylabrobot.liquid_handling.backends import ChatterBoxBackend\n",
"from pylabrobot.visualizer.visualizer import Visualizer\n",
"from pylabrobot.resources.hamilton import STARLetDeck\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8b372972-d6dc-454b-95eb-d9941405621b",
"metadata": {},
"outputs": [],
"source": [
"lh = LiquidHandler(backend=ChatterBoxBackend(), deck=STARLetDeck())\n",
"await lh.setup()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0324171c-101d-4b3d-9103-a0137c620174",
"metadata": {},
"outputs": [],
"source": [
"vis = Visualizer(resource=lh)\n",
"await vis.setup()"
]
},
{
"cell_type": "markdown",
"id": "59b03cfb-8e42-441e-9887-e7a87453d7f7",
"metadata": {},
"source": [
"Now we will import a tip carrier, a plate carrier, a plate, and a tip rack."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7bb36402-2303-4d2e-bd3e-4e10a29e891c",
"metadata": {},
"outputs": [],
"source": [
"from pylabrobot.resources import (\n",
" TIP_CAR_480_A00,\n",
" PLT_CAR_L5AC_A00,\n",
" Cos_96_DW_1mL,\n",
" HTF_L\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "25faa001-8f09-43af-ac2a-5b6b6b21d47a",
"metadata": {},
"outputs": [],
"source": [
"tip_car = TIP_CAR_480_A00(name='tip carrier')\n",
"tip_car[0] = tip_rack1 = HTF_L(name='tips_01', with_tips=False)\n",
"tip_car[1] = tip_rack2 = HTF_L(name='tips_02', with_tips=False)\n",
"tip_car[2] = tip_rack3 = HTF_L(name='tips_03', with_tips=False)\n",
"tip_car[3] = tip_rack4 = HTF_L(name='tips_04', with_tips=False)\n",
"tip_car[4] = tip_rack5 = HTF_L(name='tips_05', with_tips=False)\n",
"lh.deck.assign_child_resource(tip_car, rails=15)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5e7c1218-70e9-4905-b15a-16af3259c79f",
"metadata": {},
"outputs": [],
"source": [
"plt_car = PLT_CAR_L5AC_A00(name='plate carrier')\n",
"plt_car[0] = plate_1 = Cos_96_DW_1mL(name='plate_01')\n",
"plt_car[1] = plate_2 = Cos_96_DW_1mL(name='plate_02')\n",
"plt_car[2] = plate_3 = Cos_96_DW_1mL(name='plate_03')\n",
"lh.deck.assign_child_resource(plt_car, rails=8)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "08fb2161-4fc7-4312-9864-e85a46f02bcc",
"metadata": {},
"outputs": [],
"source": [
"await vis.stop()\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.0"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
{
"cells": [
{
"cell_type": "markdown",
"id": "baf9fb61-2fc5-446c-9c4a-18801c7d7afa",
"metadata": {},
"source": [
"**Welcome to PyLabRobot!**\n",
"\n",
"PyLabRobot is a universal Python interface to liquid-handling robots. Liquid-handling robots aspirate and dispense precise volumes\n",
"of liquid in a Cartesian coordinate system, essentially the same as hand pipetting.\n",
"\n",
"PLR defines a universal interface class called LiquidHandler that provides generic methods for controlling robots\n",
"such as aspirate and dispense. This class can be instantiated with one of several backends (or drivers)\n",
"that convert generic commands to machine-specific commands. This makes it easy to write code that will\n",
"be translatable across many different machines.\n",
"\n",
"First we will import `LiquidHandler`, a backend called `ChatterBoxBackend` that prints the text\n",
"output of our commands, a class `Visualizer` that provides a visualization of the robot deck as we\n",
"run commands, and a class `STARLetDeck` that will represent the deck of a Hamilton Microlab STARLet, one of\n",
"the most widely used liquid handling robots."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f8bcf094-3c3a-41c4-b0e8-5d2caeee9ca9",
"metadata": {},
"outputs": [],
"source": [
"from pylabrobot.liquid_handling import LiquidHandler\n",
"from pylabrobot.liquid_handling.backends import ChatterBoxBackend\n",
"from pylabrobot.visualizer.visualizer import Visualizer\n",
"from pylabrobot.resources.hamilton import STARLetDeck\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8b372972-d6dc-454b-95eb-d9941405621b",
"metadata": {},
"outputs": [],
"source": [
"lh = LiquidHandler(backend=ChatterBoxBackend(), deck=STARLetDeck())\n",
"await lh.setup()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0324171c-101d-4b3d-9103-a0137c620174",
"metadata": {},
"outputs": [],
"source": [
"vis = Visualizer(resource=lh)\n",
"await vis.setup()"
]
},
{
"cell_type": "markdown",
"id": "59b03cfb-8e42-441e-9887-e7a87453d7f7",
"metadata": {},
"source": [
"Now we will import a tip carrier, a plate carrier, a plate, and a tip rack."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7bb36402-2303-4d2e-bd3e-4e10a29e891c",
"metadata": {},
"outputs": [],
"source": [
"from pylabrobot.resources import (\n",
" TIP_CAR_480_A00,\n",
" PLT_CAR_L5AC_A00,\n",
" Cos_96_DW_1mL,\n",
" HTF_L\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "25faa001-8f09-43af-ac2a-5b6b6b21d47a",
"metadata": {},
"outputs": [],
"source": [
"tip_car = TIP_CAR_480_A00(name='tip carrier')\n",
"tip_car[0] = tip_rack1 = HTF_L(name='tips_01', with_tips=False)\n",
"tip_car[1] = tip_rack2 = HTF_L(name='tips_02', with_tips=False)\n",
"tip_car[2] = tip_rack3 = HTF_L(name='tips_03', with_tips=False)\n",
"tip_car[3] = tip_rack4 = HTF_L(name='tips_04', with_tips=False)\n",
"tip_car[4] = tip_rack5 = HTF_L(name='tips_05', with_tips=False)\n",
"lh.deck.assign_child_resource(tip_car, rails=15)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5e7c1218-70e9-4905-b15a-16af3259c79f",
"metadata": {},
"outputs": [],
"source": [
"plt_car = PLT_CAR_L5AC_A00(name='plate carrier')\n",
"plt_car[0] = plate_1 = Cos_96_DW_1mL(name='plate_01')\n",
"plt_car[1] = plate_2 = Cos_96_DW_1mL(name='plate_02')\n",
"plt_car[2] = plate_3 = Cos_96_DW_1mL(name='plate_03')\n",
"lh.deck.assign_child_resource(plt_car, rails=8)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "08fb2161-4fc7-4312-9864-e85a46f02bcc",
"metadata": {},
"outputs": [],
"source": [
"await vis.stop()\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.0"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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