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+{
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+ "cells": [
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+ {
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+ "cell_type": "markdown",
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+ "id": "723581d7",
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+ "metadata": {},
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+ "source": [
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+ "# Conversion\n",
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+ "This Notebook converts the dataset for the unitary events tutorial from .h5 to.nix format"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 1,
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+ "id": "6c6d2774",
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "import neo\n",
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+ "from neo.core import Block, Segment, Group, AnalogSignal\n",
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+ "import numpy as np\n",
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+ "import quantities as pq\n",
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+ "\n",
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+ "import random\n",
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+ "import string\n",
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+ "import matplotlib.pyplot as plt\n",
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+ "import elephant.unitary_event_analysis as ue\n",
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+ "# Fix random seed to guarantee fixed output\n",
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+ "random.seed(1224)"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "id": "26914203",
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+ "metadata": {},
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+ "source": [
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+ "## Download data"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 2,
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+ "id": "8c798f2b",
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "name": "stdout",
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+ "output_type": "stream",
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+ "text": [
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+ " % Total % Received % Xferd Average Speed Time Time Time Current\n",
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+ " Dload Upload Total Spent Left Speed\n",
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+ "100 369 100 369 0 0 7096 0 --:--:-- --:--:-- --:--:-- 7096\n",
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+ "100 289k 0 289k 0 0 255k 0 --:--:-- 0:00:01 --:--:-- 1562k\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "!curl https://web.gin.g-node.org/INM-6/elephant-data/raw/master/dataset-1/dataset-1.h5 --output dataset-1.h5 --location"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "id": "903fc908",
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+ "metadata": {},
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+ "source": [
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+ "## Load Data"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 3,
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+ "id": "870b8b77",
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "name": "stderr",
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+ "output_type": "stream",
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+ "text": [
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+ "/home/kern/miniconda3/envs/elephant/lib/python3.9/site-packages/neo/io/hdf5io.py:63: FutureWarning: NeoHdf5IO will be removed in the next release of Neo. If you still have data in this format, we recommend saving it using NixIO which is also based on HDF5.\n",
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+ " warn(warning_msg, FutureWarning)\n",
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+ "/home/kern/miniconda3/envs/elephant/lib/python3.9/site-packages/numpy/core/shape_base.py:121: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.\n",
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+ " ary = asanyarray(ary)\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "block = neo.io.NeoHdf5IO(\"./dataset-1.h5\")\n",
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+ "sts1 = block.read_block().segments[0].spiketrains\n",
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+ "sts2 = block.read_block().segments[1].spiketrains\n",
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+ "spiketrains = np.vstack((sts1,sts2)).T"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 4,
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+ "id": "c52a2a89",
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "# create empty block\n",
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+ "blk = Block()\n",
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+ "# add segments and spike trains\n",
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+ "for ind in range (len(sts1)):\n",
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+ " seg = Segment(name='segment %d' % ind, index=ind)\n",
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+ " seg.spiketrains.append(sts1[ind])\n",
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+ " seg.spiketrains.append(sts2[ind])\n",
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+ " blk.segments.append(seg)\n"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "id": "28a2e17f",
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+ "metadata": {},
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+ "source": [
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+ "## Save as .nix"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 5,
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+ "id": "2a06477e",
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "filename = 'dataset-1.nix'\n",
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+ "with neo.io.NixIO(filename, 'ow') as io:\n",
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+ " io.write_block(blk)"
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+ ]
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+ }
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+ ],
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+ "metadata": {
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+ "kernelspec": {
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+ "display_name": "elephant_old",
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+ "language": "python",
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+ "name": "elephant_old"
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+ },
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+ "language_info": {
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+ "codemirror_mode": {
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+ "name": "ipython",
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+ "version": 3
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+ },
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+ "file_extension": ".py",
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+ "mimetype": "text/x-python",
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+ "name": "python",
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+ "nbconvert_exporter": "python",
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+ "pygments_lexer": "ipython3",
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+ "version": "3.9.6"
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+ }
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+ },
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+ "nbformat": 4,
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+ "nbformat_minor": 5
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+}
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Moritz-Alexander-Kern