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use UE example data for trials tutorial
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@Moritz-Alexander-Kern
Moritz-Alexander-Kern committed Sep 30, 2024
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97 changes: 64 additions & 33 deletions doc/tutorials/trials.ipynb
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},
{
"cell_type": "code",
"execution_count": 24,
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import neo\n",
"from neo.core import Block, Segment, SpikeTrain, AnalogSignal\n",
"from quantities import ms, mV, Hz\n",
"from elephant.trials import TrialsFromBlock, TrialsFromLists\n",
"from elephant.datasets import download_datasets\n",
"\n",
"# Helper function to create example spike trains and analog signals\n",
"def create_example_data():\n",
Expand All @@ -46,6 +48,40 @@
" return spike_trains, analog_signals\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Download example data"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/kern/git/inm-6/elephant/elephant/datasets.py:154: UserWarning: No corresponding version of elephant-data found.\n",
"Elephant version: 1.2.0b1. Data URL:https://gin.g-node.org/NeuralEnsemble/elephant-data/raw/v1.2.0b1/README.md, error: HTTP Error 404: Not Found.\n",
"Using elephant-data latest instead (This is expected for elephant development versions).\n",
" warnings.warn(f\"No corresponding version of elephant-data found.\\n\"\n",
"Downloading https://datasets.python-elephant.org/raw/master/tutorials/tutorial_unitary_event_analysis/data/dataset-1.nix to '/tmp/elephant/dataset-1.nix': 1.69MB [00:02, 804kB/s] \n"
]
}
],
"source": [
"# Download data\n",
"repo_path='tutorials/tutorial_unitary_event_analysis/data/dataset-1.nix'\n",
"filepath=download_datasets(repo_path)\n",
"\n",
"# Load data\n",
"io = neo.io.NixIO(f\"{filepath}\",'ro')\n",
"block = io.read_block()"
]
},
{
"cell_type": "markdown",
"metadata": {},
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},
{
"cell_type": "code",
"execution_count": 25,
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of trials: 3\n",
"Number of spike trains in each trial: [2, 2, 2]\n",
"Number of analog signals in each trial: [2, 2, 2]\n",
"Trial 1 Segment: <neo.core.segment.Segment object at 0x7af0a0e4fac0>\n",
"All spike trains from trial 2: [<SpikeTrain(array([10., 20., 30.]) * ms, [0.0 ms, 40.0 ms])>, <SpikeTrain(array([15., 25., 35.]) * ms, [0.0 ms, 40.0 ms])>]\n"
"Number of trials: 36\n",
"Number of spike trains in each trial: [2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]\n",
"Number of analog signals in each trial: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
"Trial 1 Segment: <neo.core.segment.Segment object at 0x7f210c179520>\n",
"All spike trains from trial 2: [<SpikeTrain(array([ 4., 45., 85., 123., 156., 185., 226., 274., 296.,\n",
" 323., 348., 371., 404., 471., 499., 530., 560., 581.,\n",
" 601., 626., 654., 700., 727., 762., 792., 805., 827.,\n",
" 828., 847., 869., 899., 920., 933., 972., 1001., 1023.,\n",
" 1031., 1051., 1086., 1152., 1172., 1176., 1199., 1223., 1245.,\n",
" 1273., 1304., 1379., 1400., 1401., 1417., 1424., 1444., 1449.,\n",
" 1483., 1546., 1564., 1583., 1588., 1615., 1629., 1660., 1683.,\n",
" 1706., 1732., 1774., 1816., 1834., 1849., 1884., 1905., 2030.]) * ms, [0.0 ms, 2100.0 ms])>, <SpikeTrain(array([ 54., 155., 183., 251., 341., 434., 494., 613., 746.,\n",
" 1201., 1641.]) * ms, [0.0 ms, 2100.0 ms])>]\n"
]
}
],
"source": [
"# Create example data\n",
"spike_trains, analog_signals = create_example_data()\n",
"\n",
"# Create a neo.Block and add Segments for each trial\n",
"block = Block()\n",
"for i in range(3):\n",
" segment = Segment(name=f'Trial {i}')\n",
" for spike_train in spike_trains:\n",
" segment.spiketrains.append(spike_train)\n",
" for analog_signal in analog_signals:\n",
" segment.analogsignals.append(analog_signal)\n",
" block.segments.append(segment)\n",
"\n",
"# Create a TrialsFromBlock instance\n",
"trials_from_block = TrialsFromBlock(block)\n",
"\n",
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},
{
"cell_type": "code",
"execution_count": 26,
"execution_count": 4,
"metadata": {},
"outputs": [
{
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"Number of trials: 3\n",
"Number of spike trains in each trial: [2, 2, 2]\n",
"Number of analog signals in each trial: [2, 2, 2]\n",
"Trial 1 Segment: <neo.core.segment.Segment object at 0x7af0a0cbe620>\n",
"All trials Block: <neo.core.block.Block object at 0x7af0a0cbe8c0>\n",
"Trial 1 Segment: <neo.core.segment.Segment object at 0x7f20b8c661b0>\n",
"All trials Block: <neo.core.block.Block object at 0x7f210c1b54f0>\n",
"Number of segments in trials_list_from_lists: 3\n",
"Trial 0 Segment: <neo.core.segment.Segment object at 0x7af0a0e4df90>\n",
"Trial 0 Segment: <neo.core.segment.Segment object at 0x7f20b9409700>\n",
" Spike train 0 Spike train: [10. 20. 30.] ms\n",
" Spike train 1 Spike train: [15. 25. 35.] ms\n",
" Analog signal 0 Analog signal: [ 0.69607325 -0.04370697 1.36631824 -0.83783295] mV\n",
" Analog signal 1 Analog signal: [ 0.79122003 0.40844734 1.0958819 -0.83324856] mV\n",
"Trial 1 Segment: <neo.core.segment.Segment object at 0x7af0a0e4dea0>\n",
" Analog signal 0 Analog signal: [-0.35546363 1.69106607 -1.3224601 0.13145046] mV\n",
" Analog signal 1 Analog signal: [ 0.58983451 -1.21403348 -0.2027809 0.27795667] mV\n",
"Trial 1 Segment: <neo.core.segment.Segment object at 0x7f210c1cffb0>\n",
" Spike train 0 Spike train: [10. 20. 30.] ms\n",
" Spike train 1 Spike train: [15. 25. 35.] ms\n",
" Analog signal 0 Analog signal: [ 0.69607325 -0.04370697 1.36631824 -0.83783295] mV\n",
" Analog signal 1 Analog signal: [ 0.79122003 0.40844734 1.0958819 -0.83324856] mV\n",
"Trial 2 Segment: <neo.core.segment.Segment object at 0x7af0a0e4e380>\n",
" Analog signal 0 Analog signal: [-0.35546363 1.69106607 -1.3224601 0.13145046] mV\n",
" Analog signal 1 Analog signal: [ 0.58983451 -1.21403348 -0.2027809 0.27795667] mV\n",
"Trial 2 Segment: <neo.core.segment.Segment object at 0x7f210c1e7440>\n",
" Spike train 0 Spike train: [10. 20. 30.] ms\n",
" Spike train 1 Spike train: [15. 25. 35.] ms\n",
" Analog signal 0 Analog signal: [ 0.69607325 -0.04370697 1.36631824 -0.83783295] mV\n",
" Analog signal 1 Analog signal: [ 0.79122003 0.40844734 1.0958819 -0.83324856] mV\n"
" Analog signal 0 Analog signal: [-0.35546363 1.69106607 -1.3224601 0.13145046] mV\n",
" Analog signal 1 Analog signal: [ 0.58983451 -1.21403348 -0.2027809 0.27795667] mV\n"
]
}
],
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
"version": "3.12.5"
}
},
"nbformat": 4,
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