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mengaldomengaldo
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removed setuptools find_packages
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-62
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3 files changed

+125
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‎setup.py‎

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import sys
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from setuptools import setup
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from setuptools import Command
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from setuptools import find_packages
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# GLOBAL VARIABLES
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NAME = "pyspod"
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keywords=KEYWORDS,
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url=URL,
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license='MIT',
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# packages=[NAME],
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packages=find_packages(),
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packages=[NAME],
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package_data={'': [
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'plotting_support/coast.mat',
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'plotting_support/coast_centred.mat'

‎tutorials/climate/ERA20C_MEI_2D/ERA20C_MEI_2D.ipynb‎

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‎tutorials/fluidmechanics/jet_2D/jet_2D.ipynb‎

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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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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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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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"execution_count": 5,
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"metadata": {
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"scrolled": false
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},
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"outputs": [
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{
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"ename": "NameError",
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"evalue": "name 'SPOD_streaming' is not defined",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m<ipython-input-1-8189a6bbb6a8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# Perform SPOD analysis using low storage module\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mSPOD_analysis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSPOD_streaming\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata_handler\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvariables\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvariables\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0mspod\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSPOD_analysis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mNameError\u001b[0m: name 'SPOD_streaming' is not defined"
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"SPOD parameters\n",
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"------------------------------------\n",
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"Spectrum type : one-sided (real-valued signal)\n",
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"No. of snaphots per block : 64\n",
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"Block overlap : 32\n",
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"No. of blocks : 30\n",
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"Windowing fct. (time) : hamming\n",
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"Weighting fct. (space) : user-specified\n",
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"Mean : blockwise\n",
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"Time-step : 0.2\n",
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"Number of Frequencies : 33\n",
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"------------------------------------\n",
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"\n",
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"DATA MATRIX DIMENSIONS\n",
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"------------------------------------\n",
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"Problem size : 0.013113021850585958 GB. (double)\n",
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"data matrix dimensions: (1, 20, 88, 1)\n",
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"Make sure that first column of data matrix is time and last column is number of variables. \n",
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"First column dimension: 1 must correspond to number of time snapshots.\n",
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"Last column dimension: 1 must correspond to number of variables.\n",
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"------------------------------------\n",
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" \n",
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"Calculating temporal DFT (streaming)\n",
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"------------------------------------\n",
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"--> Updating left singular vectors Time 63 / block 1\n"
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]
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},
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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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"/usr/local/lib/python3.8/site-packages/pyspod/spod_streaming.py:203: RuntimeWarning: divide by zero encountered in true_divide\n",
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" mse_prev[block_i,:,:] = (np.abs(S_hat_prev**2 - self._eigs**2)**2) / (S_hat_prev**2)\n",
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"/usr/local/lib/python3.8/site-packages/pyspod/spod_streaming.py:203: RuntimeWarning: invalid value encountered in true_divide\n",
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" mse_prev[block_i,:,:] = (np.abs(S_hat_prev**2 - self._eigs**2)**2) / (S_hat_prev**2)\n"
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]
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},
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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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"--> Updating left singular vectors Time 95 / block 2\n",
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"--> Updating left singular vectors Time 128 / block 3\n",
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"--> Updating left singular vectors Time 160 / block 4\n",
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"--> Updating left singular vectors Time 193 / block 5\n",
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"--> Updating left singular vectors Time 225 / block 6\n",
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"--> Updating left singular vectors Time 258 / block 7\n",
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"--> Updating left singular vectors Time 290 / block 8\n",
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"--> Updating left singular vectors Time 323 / block 9\n",
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"--> Updating left singular vectors Time 355 / block 10\n",
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"--> Updating left singular vectors Time 388 / block 11\n",
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"--> Updating left singular vectors Time 420 / block 12\n",
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"--> Updating left singular vectors Time 453 / block 13\n",
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"--> Updating left singular vectors Time 485 / block 14\n",
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"--> Updating left singular vectors Time 518 / block 15\n",
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"--> Updating left singular vectors Time 550 / block 16\n",
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"--> Updating left singular vectors Time 583 / block 17\n",
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"--> Updating left singular vectors Time 615 / block 18\n",
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"--> Updating left singular vectors Time 648 / block 19\n",
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"--> Updating left singular vectors Time 680 / block 20\n",
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"--> Updating left singular vectors Time 713 / block 21\n",
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"--> Updating left singular vectors Time 745 / block 22\n",
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"--> Updating left singular vectors Time 778 / block 23\n",
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"--> Updating left singular vectors Time 810 / block 24\n",
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"--> Updating left singular vectors Time 843 / block 25\n",
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"--> Updating left singular vectors Time 875 / block 26\n",
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"--> Updating left singular vectors Time 908 / block 27\n",
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"--> Updating left singular vectors Time 940 / block 28\n",
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"--> Updating left singular vectors Time 973 / block 29\n",
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"--> Data stream ended.\n",
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"Elapsed time: 3.8960890769958496 s.\n"
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]
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}
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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": 7,
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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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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"- RAM required for loading all modes ~ 0.0001573562622070315 GB\n",
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"- Available RAM memory ~ 14.751468658447289 GB\n"
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]
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}
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],
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"source": [
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"# Show results\n",
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"T_approx = 12.5 # approximate period\n",
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": 7,
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"metadata": {
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"scrolled": true
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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": 9,
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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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": 10,
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{

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