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mgeiermgeier
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Execute notebooks
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‎audio-files/audio-files-with-audiolab.ipynb

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‎audio-files/audio-files-with-audioread.ipynb

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‎audio-files/audio-files-with-ewave.ipynb

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‎audio-files/audio-files-with-pysoundfile.ipynb

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‎audio-files/audio-files-with-python-wavefile.ipynb

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‎audio-files/audio-files-with-scipy-io.ipynb

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‎audio-files/audio-files-with-wave.ipynb

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‎audio-files/my_float_file.wav

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‎audio-files/my_pcm16_file.wav

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‎audio-files/scipy_float32.wav

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‎audio-files/scipy_pcm16.wav

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‎hdf5/chunking.hdf5

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‎hdf5/hdf5-chunking.ipynb

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"cell_type": "code",
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"True"
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"f['a'].chunks is None"
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]
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},
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{
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"cell_type": "code",
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"outputs": [],
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<HDF5 dataset \"b\": shape (2, 3), type \"<i8\">"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"f.create_dataset('b', data=[[1, 2, 3], [4, 5, 6]], chunks=(2, 1),\n",
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" shuffle=True, compression=9, maxshape=(None, None))"
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"output_type": "execute_result"
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}
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],
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"source": [
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"b = f['b']\n",
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"b.chunks"
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]
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"'gzip'"
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"b.compression"
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],
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"data": {
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"metadata": {},
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"outputs": [
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"data": {
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"text/plain": [
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"array([[1, 2, 3],\n",
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" [4, 5, 6],\n",
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" [0, 0, 0],\n",
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" [0, 0, 0]])"
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},
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"execution_count": 13,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"b[...]"
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"outputs": [
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"data": {
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"array([[1, 2, 3, 0, 0, 0],\n",
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" [4, 5, 6, 0, 0, 0],\n",
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" [0, 0, 0, 0, 0, 0],\n",
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" [0, 0, 0, 0, 0, 0]])"
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"execution_count": 14,
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"metadata": {},
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}
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],
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"source": [
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