From f66031bb5a16ef8273d2b67bd6c96df1c945c4bc Mon Sep 17 00:00:00 2001 From: carocamargo <47150926+carocamargo@users.noreply.github.com> Date: Fri, 12 Nov 2021 18:33:43 +0100 Subject: [PATCH 1/4] Example spatio-temporal climate data SOM example on climate data, which is usually 2D (time, lat, lon) --- .../SOM-spatiotemporal_climate_example.ipynb | 20668 ++++++++++++++++ 1 file changed, 20668 insertions(+) create mode 100644 examples/SOM-spatiotemporal_climate_example.ipynb diff --git a/examples/SOM-spatiotemporal_climate_example.ipynb b/examples/SOM-spatiotemporal_climate_example.ipynb new file mode 100644 index 0000000..49144cf --- /dev/null +++ b/examples/SOM-spatiotemporal_climate_example.ipynb @@ -0,0 +1,20668 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# load libraries\n", + "import xarray as xr\n", + "from minisom import MiniSom\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib as mpl\n", + "from matplotlib.gridspec import GridSpec\n", + "from sklearn.preprocessing import MinMaxScaler, scale\n", + "import numpy as np\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Open and Explore data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Air temperature data from the US" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Dimensions: (lat: 25, lon: 53, time: 2920)\n", + "Coordinates:\n", + " * lat (lat) float32 75.0 72.5 70.0 67.5 65.0 ... 25.0 22.5 20.0 17.5 15.0\n", + " * lon (lon) float32 200.0 202.5 205.0 207.5 ... 322.5 325.0 327.5 330.0\n", + " * time (time) datetime64[ns] 2013-01-01 ... 2014-12-31T18:00:00\n", + "Data variables:\n", + " Tair (time, lat, lon) float32 ...\n", + "Attributes:\n", + " Conventions: COARDS\n", + " title: 4x daily NMC reanalysis (1948)\n", + " description: Data is from NMC initialized reanalysis\\n(4x/day). These a...\n", + " platform: Model\n", + " references: http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanaly...\n" + ] + } + ], + "source": [ + "# open xarray tutorial dataset\n", + "ds = xr.tutorial.open_dataset(\"air_temperature.nc\").rename({\"air\": \"Tair\"})\n", + "print(ds)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Data is from NMC initialized reanalysis\n", + "(4x/day). These are the 0.9950 sigma level values.\n" + ] + } + ], + "source": [ + "print(ds.description)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([ 2182., 60537., 195026., 233763., 315219., 635948.,\n", + " 778807., 1192236., 453381., 1901.]),\n", + " array([221. , 230.64 , 240.28 , 249.92 , 259.56 , 269.2 ,\n", + " 278.84 , 288.47998, 298.12 , 307.76 , 317.4 ],\n", + " dtype=float32),\n", + " )" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot histogram\n", + "ds.Tair.plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot at initial time\n", + "ds.Tair.isel(time=1).plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# group by month and plot it:\n", + "monthly_means = ds.groupby(\"time.month\").mean()\n", + "# xarray's groupby reductions drop attributes. Let's assign them back so we get nice labels.\n", + "monthly_means.Tair.attrs = ds.Tair.attrs\n", + "\n", + "fg = monthly_means.Tair.plot(\n", + " col=\"month\",\n", + " col_wrap=4, # each row has a maximum of 4 columns\n", + " # The remaining kwargs customize the plot just as for not-faceted plots\n", + " robust=True,\n", + " cmap=mpl.cm.RdYlBu_r,\n", + " cbar_kwargs={\n", + " \"orientation\": \"horizontal\",\n", + " \"shrink\": 0.8,\n", + " \"aspect\": 40,\n", + " \"pad\": 0.1,\n", + " },\n", + ")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# SOM Clustering" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will apply SOM first on time domain, that is, find spatial clusters that are correlated in time, and later in spatial domain. " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "# define SOM parameters\n", + "som_map = (3,3) # we will try a 3x3 neural map\n", + "x,y=som_map\n", + "sigma = 1 # default value\n", + "learning_rate = 0.5 # default value\n", + "ngb_function = 'gaussian' # choosing between ['gaussian' ,'bubble','mexican_hat']\n", + "init = 'random' # we will initialize SOM randomly. Option: 'pca'\n", + "train = 'batch' # perform batch traning instead of random (default)\n", + "iterations = 10000 # lenght of training\n", + "topology = 'hexagonal' # to ensure equidistant ditance neighbors\n", + "activation_distance = 'euclidean'\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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xarray.Dataset
    • lat: 25
    • lon: 53
    • time: 2920
    • lat
      (lat)
      float32
      75.0 72.5 70.0 ... 20.0 17.5 15.0
      standard_name :
      latitude
      long_name :
      Latitude
      units :
      degrees_north
      axis :
      Y
      array([75. , 72.5, 70. , 67.5, 65. , 62.5, 60. , 57.5, 55. , 52.5, 50. , 47.5,\n",
+       "       45. , 42.5, 40. , 37.5, 35. , 32.5, 30. , 27.5, 25. , 22.5, 20. , 17.5,\n",
+       "       15. ], dtype=float32)
    • lon
      (lon)
      float32
      200.0 202.5 205.0 ... 327.5 330.0
      standard_name :
      longitude
      long_name :
      Longitude
      units :
      degrees_east
      axis :
      X
      array([200. , 202.5, 205. , 207.5, 210. , 212.5, 215. , 217.5, 220. , 222.5,\n",
+       "       225. , 227.5, 230. , 232.5, 235. , 237.5, 240. , 242.5, 245. , 247.5,\n",
+       "       250. , 252.5, 255. , 257.5, 260. , 262.5, 265. , 267.5, 270. , 272.5,\n",
+       "       275. , 277.5, 280. , 282.5, 285. , 287.5, 290. , 292.5, 295. , 297.5,\n",
+       "       300. , 302.5, 305. , 307.5, 310. , 312.5, 315. , 317.5, 320. , 322.5,\n",
+       "       325. , 327.5, 330. ], dtype=float32)
    • time
      (time)
      datetime64[ns]
      2013-01-01 ... 2014-12-31T18:00:00
      standard_name :
      time
      long_name :
      Time
      array(['2013-01-01T00:00:00.000000000', '2013-01-01T06:00:00.000000000',\n",
+       "       '2013-01-01T12:00:00.000000000', ..., '2014-12-31T06:00:00.000000000',\n",
+       "       '2014-12-31T12:00:00.000000000', '2014-12-31T18:00:00.000000000'],\n",
+       "      dtype='datetime64[ns]')
    • Tair
      (time, lat, lon)
      float32
      ...
      long_name :
      4xDaily Air temperature at sigma level 995
      units :
      degK
      precision :
      2
      GRIB_id :
      11
      GRIB_name :
      TMP
      var_desc :
      Air temperature
      dataset :
      NMC Reanalysis
      level_desc :
      Surface
      statistic :
      Individual Obs
      parent_stat :
      Other
      actual_range :
      [185.16 322.1 ]
      [3869000 values with dtype=float32]
  • Conventions :
    COARDS
    title :
    4x daily NMC reanalysis (1948)
    description :
    Data is from NMC initialized reanalysis\n", + "(4x/day). These are the 0.9950 sigma level values.
    platform :
    Model
    references :
    http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.html
" + ], + "text/plain": [ + "\n", + "Dimensions: (lat: 25, lon: 53, time: 2920)\n", + "Coordinates:\n", + " * lat (lat) float32 75.0 72.5 70.0 67.5 65.0 ... 25.0 22.5 20.0 17.5 15.0\n", + " * lon (lon) float32 200.0 202.5 205.0 207.5 ... 322.5 325.0 327.5 330.0\n", + " * time (time) datetime64[ns] 2013-01-01 ... 2014-12-31T18:00:00\n", + "Data variables:\n", + " Tair (time, lat, lon) float32 ...\n", + "Attributes:\n", + " Conventions: COARDS\n", + " title: 4x daily NMC reanalysis (1948)\n", + " description: Data is from NMC initialized reanalysis\\n(4x/day). These a...\n", + " platform: Model\n", + " references: http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanaly..." + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ds" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "data_in=np.array(ds['Tair'])\n", + "dimlon=len(ds['lon'])\n", + "dimlat= len(ds['lat'])\n", + "dimtime = len(ds['time'])" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(2920, 25, 53)\n" + ] + } + ], + "source": [ + "print(data_in.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "# data preprocessing\n", + "\n", + "# we need to concatenate the dataset to 2D:\n", + "data=data_in.reshape(dimtime,dimlat*dimlon)\n", + "\n", + "# normalize dataset:\n", + "# using MinMaxScaler\n", + "# sc = MinMaxScaler (feature_range = (0,1))\n", + "# data_norm = sc.fit_transform (data)\n", + "# scale data\n", + "# X_scale= scale(data.T)\n", + "# manually\n", + "data = (data - np.nanmean(data, axis=0)) / np.nanstd(data, axis=0)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Time domain" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", + " [ 0 / 10000 ] 0% - ? it/s\r", + " [ 0 / 10000 ] 0% - ? it/s\r", + " [ 1 / 10000 ] 0% - 0:00:06 left \r", + " [ 2 / 10000 ] 0% - 0:00:05 left \r", + " [ 3 / 10000 ] 0% - 0:00:05 left \r", + " [ 4 / 10000 ] 0% - 0:00:04 left \r", + " [ 5 / 10000 ] 0% - 0:00:04 left \r", + " [ 6 / 10000 ] 0% - 0:00:04 left \r", + " [ 7 / 10000 ] 0% - 0:00:04 left \r", + " [ 8 / 10000 ] 0% - 0:00:04 left \r", + " [ 9 / 10000 ] 0% - 0:00:04 left \r", + " [ 10 / 10000 ] 0% - 0:00:04 left \r", + " [ 11 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[ + " [ 10000 / 10000 ] 100% - 0:00:00 left \n", + " quantization error: 29.1143042357806\n" + ] + } + ], + "source": [ + "# to analyse in time domain we need to transpose it:\n", + "X = data.T\n", + "input_len=X.shape[1]\n", + "\n", + "# create som\n", + "som = MiniSom(x=x,y=y,input_len=input_len,\n", + " sigma=sigma,learning_rate=learning_rate,\n", + " neighborhood_function=ngb_function,\n", + " topology=topology,\n", + " activation_distance=activation_distance,\n", + " random_seed=None)\n", + "# init som\n", + "if init=='pca':\n", + " som.pca_weights_init(X)\n", + "else:\n", + " som.random_weights_init(X)\n", + "\n", + "# train som\n", + "if train=='random':\n", + " som.train_random(X,iterations,verbose=True)\n", + "else:\n", + " som.train_batch(X,iterations,verbose=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Clusters of different temporal variability\n", + "Considering the time series 3x3 SOM analysis" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requested network: 3x3\n", + " Identified: 9 regions\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# extract clusters of winning neurons:\n", + "# each neuron represents a cluster\n", + "winner_coordinates = np.array([som.winner(x) for x in X]).T\n", + "# with np.ravel_multi_index we convert the bidimensional\n", + "# coordinates to a monodimensional index\n", + "cluster_index = np.ravel_multi_index(winner_coordinates, (x,y))\n", + "# cluster_index=winner_coordinates[1,:]\n", + "n_cluster=len(np.unique(cluster_index))\n", + "print('Requested network: {}x{}\\n Identified: {} regions'.format(x,y,n_cluster))\n", + "plt.pcolor(ds.lon,ds.lat,cluster_index.reshape(dimlat,dimlon),\n", + " vmin=0,vmax=x*y,cmap='tab10');\n", + "plt.colorbar()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# extract time series of each cluster\n", + "win_map = som.win_map(X)\n", + "win_ts=np.zeros((len(win_map),input_len,3))\n", + "# cluster_index = np.ravel_multi_index(win_ts, (x,y))\n", + "\n", + "# plto time series\n", + "plt.figure(figsize=(50, 20))\n", + "the_grid = GridSpec(8, 8)\n", + "\n", + "for i,position in enumerate(win_map.keys()):\n", + " win_ts[i,:,0]=np.min(win_map[position], axis=0) \n", + " win_ts[i,:,1]=np.mean(win_map[position], axis=0)\n", + " win_ts[i,:,2]=np.max(win_map[position], axis=0)\n", + " \n", + " plt.subplot(the_grid[6-position[1], position[0]])\n", + " plt.plot(np.min(win_map[position], axis=0), color='gray', alpha=.5)\n", + " plt.plot(np.mean(win_map[position], axis=0))\n", + " plt.plot(np.max(win_map[position], axis=0), color='gray', alpha=.5)\n", + " \n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Space domain" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", + " [ 0 / 10000 ] 0% - ? it/s\r", + " [ 0 / 10000 ] 0% - ? it/s\r", + " [ 1 / 10000 ] 0% - 0:00:09 left \r", + " [ 2 / 10000 ] 0% - 0:00:06 left \r", + " [ 3 / 10000 ] 0% - 0:00:05 left \r", + " [ 4 / 10000 ] 0% - 0:00:04 left \r", + " [ 5 / 10000 ] 0% - 0:00:03 left \r", + " [ 6 / 10000 ] 0% - 0:00:03 left \r", + " [ 7 / 10000 ] 0% - 0:00:03 left \r", + " [ 8 / 10000 ] 0% - 0:00:03 left \r", + " [ 9 / 10000 ] 0% - 0:00:03 left \r", + " [ 10 / 10000 ] 0% - 0:00:03 left \r", + " [ 11 / 10000 ] 0% - 0:00:03 left \r", + " [ 12 / 10000 ] 0% - 0:00:03 left \r", + " [ 13 / 10000 ] 0% - 0:00:03 left \r", + " [ 14 / 10000 ] 0% - 0:00:03 left \r", + " [ 15 / 10000 ] 0% - 0:00:03 left \r", + " [ 16 / 10000 ] 0% - 0:00:03 left \r", + " [ 17 / 10000 ] 0% - 0:00:03 left \r", + " [ 18 / 10000 ] 0% - 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init=='pca':\n", + " som.pca_weights_init(X)\n", + "else:\n", + " som.random_weights_init(X)\n", + "\n", + "# train som\n", + "if train=='random':\n", + " som.train_random(X,iterations,verbose=True)\n", + "else:\n", + " som.train_batch(X,iterations,verbose=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requested network: 3x3\n", + " Identified: 9 regions\n" + ] + } + ], + "source": [ + "# extract clusters of winning neurons:\n", + "# each neuron represents a cluster\n", + "winner_coordinates = np.array([som.winner(x) for x in X]).T\n", + "# with np.ravel_multi_index we convert the bidimensional\n", + "# coordinates to a monodimensional index\n", + "cluster_index = np.ravel_multi_index(winner_coordinates, (x,y))\n", + "# cluster_index=winner_coordinates[1,:]\n", + "n_cluster=len(np.unique(cluster_index))\n", + "print('Requested network: {}x{}\\n Identified: {} regions'.format(x,y,n_cluster))\n", + "# plt.pcolor(ds.lon,ds.lat,cluster_index.reshape(dimlat,dimlon),\n", + "# vmin=0,vmax=x*y,cmap='tab10');\n", + "# plt.colorbar()\n", + "# plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Spatial patterns of a 3x3 SOM" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# extract results\n", + "win_map = som.win_map(data)\n", + "win_ts=np.zeros((len(win_map),input_len,3))\n", + "# cluster_index = np.ravel_multi_index(win_ts, (x,y))\n", + "\n", + "plt.figure(figsize=(50, 20))\n", + "the_grid = GridSpec(8,8)\n", + "\n", + "for i,position in enumerate(win_map.keys()):\n", + " win_ts[i,:,0]=np.min(win_map[position], axis=0)\n", + " win_ts[i,:,1]=np.mean(win_map[position], axis=0)\n", + " win_ts[i,:,2]=np.max(win_map[position], axis=0)\n", + "\n", + " \n", + " # plt.plot(win_ts[:,:,0].T);plt.show()\n", + " # plot spatial pattern of each neuron\n", + " plt.subplot(the_grid[6-position[1], position[0]])\n", + " plt.pcolor(ds.lon,ds.lat,win_ts[i,:,1].reshape(dimlat,dimlon));\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Reference" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Hernandez-Carrasco, I., & Orfila, A. (2018). The role of an intense front on the connectivity of the western Mediterranean Sea: The Cartagena- Tenes front. Journal of Geophysical Research: Oceans, 123, 4398–4422. https://doi.org/10.1029/2017JC013613" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From 55013ebf44e242bf67737914cd011f93af10636b Mon Sep 17 00:00:00 2001 From: carocamargo <47150926+carocamargo@users.noreply.github.com> Date: Mon, 15 Nov 2021 16:06:51 +0100 Subject: [PATCH 2/4] update spatio-temporal example Added a bit of descriptions to plots + one example of a 2D SOM (only spatial data, not temporal) --- .../SOM-spatiotemporal_climate_example.ipynb | 16592 ++++++++-------- 1 file changed, 8647 insertions(+), 7945 deletions(-) diff --git a/examples/SOM-spatiotemporal_climate_example.ipynb b/examples/SOM-spatiotemporal_climate_example.ipynb index 49144cf..eafaa25 100644 --- a/examples/SOM-spatiotemporal_climate_example.ipynb +++ b/examples/SOM-spatiotemporal_climate_example.ipynb @@ -16,6 +16,13 @@ "import numpy as np\n" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# SOM Spatio-Temporal Example" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -126,7 +133,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 5, @@ -197,13 +204,6 @@ "# SOM Clustering" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We will apply SOM first on time domain, that is, find spatial clusters that are correlated in time, and later in spatial domain. " - ] - }, { "cell_type": "code", "execution_count": 7, @@ -220,396 +220,16 @@ "train = 'batch' # perform batch traning instead of random (default)\n", "iterations = 10000 # lenght of training\n", "topology = 'hexagonal' # to ensure equidistant ditance neighbors\n", - "activation_distance = 'euclidean'\n" + "activation_distance = 'euclidean'" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - "Show/Hide data repr\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "Show/Hide attributes\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
xarray.Dataset
    • lat: 25
    • lon: 53
    • time: 2920
    • lat
      (lat)
      float32
      75.0 72.5 70.0 ... 20.0 17.5 15.0
      standard_name :
      latitude
      long_name :
      Latitude
      units :
      degrees_north
      axis :
      Y
      array([75. , 72.5, 70. , 67.5, 65. , 62.5, 60. , 57.5, 55. , 52.5, 50. , 47.5,\n",
-       "       45. , 42.5, 40. , 37.5, 35. , 32.5, 30. , 27.5, 25. , 22.5, 20. , 17.5,\n",
-       "       15. ], dtype=float32)
    • lon
      (lon)
      float32
      200.0 202.5 205.0 ... 327.5 330.0
      standard_name :
      longitude
      long_name :
      Longitude
      units :
      degrees_east
      axis :
      X
      array([200. , 202.5, 205. , 207.5, 210. , 212.5, 215. , 217.5, 220. , 222.5,\n",
-       "       225. , 227.5, 230. , 232.5, 235. , 237.5, 240. , 242.5, 245. , 247.5,\n",
-       "       250. , 252.5, 255. , 257.5, 260. , 262.5, 265. , 267.5, 270. , 272.5,\n",
-       "       275. , 277.5, 280. , 282.5, 285. , 287.5, 290. , 292.5, 295. , 297.5,\n",
-       "       300. , 302.5, 305. , 307.5, 310. , 312.5, 315. , 317.5, 320. , 322.5,\n",
-       "       325. , 327.5, 330. ], dtype=float32)
    • time
      (time)
      datetime64[ns]
      2013-01-01 ... 2014-12-31T18:00:00
      standard_name :
      time
      long_name :
      Time
      array(['2013-01-01T00:00:00.000000000', '2013-01-01T06:00:00.000000000',\n",
-       "       '2013-01-01T12:00:00.000000000', ..., '2014-12-31T06:00:00.000000000',\n",
-       "       '2014-12-31T12:00:00.000000000', '2014-12-31T18:00:00.000000000'],\n",
-       "      dtype='datetime64[ns]')
    • Tair
      (time, lat, lon)
      float32
      ...
      long_name :
      4xDaily Air temperature at sigma level 995
      units :
      degK
      precision :
      2
      GRIB_id :
      11
      GRIB_name :
      TMP
      var_desc :
      Air temperature
      dataset :
      NMC Reanalysis
      level_desc :
      Surface
      statistic :
      Individual Obs
      parent_stat :
      Other
      actual_range :
      [185.16 322.1 ]
      [3869000 values with dtype=float32]
  • Conventions :
    COARDS
    title :
    4x daily NMC reanalysis (1948)
    description :
    Data is from NMC initialized reanalysis\n", - "(4x/day). These are the 0.9950 sigma level values.
    platform :
    Model
    references :
    http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.html
" - ], - "text/plain": [ - "\n", - "Dimensions: (lat: 25, lon: 53, time: 2920)\n", - "Coordinates:\n", - " * lat (lat) float32 75.0 72.5 70.0 67.5 65.0 ... 25.0 22.5 20.0 17.5 15.0\n", - " * lon (lon) float32 200.0 202.5 205.0 207.5 ... 322.5 325.0 327.5 330.0\n", - " * time (time) datetime64[ns] 2013-01-01 ... 2014-12-31T18:00:00\n", - "Data variables:\n", - " Tair (time, lat, lon) float32 ...\n", - "Attributes:\n", - " Conventions: COARDS\n", - " title: 4x daily NMC reanalysis (1948)\n", - " description: Data is from NMC initialized reanalysis\\n(4x/day). These a...\n", - " platform: Model\n", - " references: http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanaly..." - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ds" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, "outputs": [], "source": [ + "# data params\n", "data_in=np.array(ds['Tair'])\n", "dimlon=len(ds['lon'])\n", "dimlat= len(ds['lat'])\n", @@ -617,53 +237,56 @@ ] }, { - "cell_type": "code", - "execution_count": 10, + "cell_type": "markdown", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(2920, 25, 53)\n" - ] - } - ], "source": [ - "print(data_in.shape)" + "Most SOM tutorials are found on image classification (see the tree example). \n", + "Let's try applying SOM to the mean field first:" ] }, { "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "# data preprocessing\n", - "\n", - "# we need to concatenate the dataset to 2D:\n", - "data=data_in.reshape(dimtime,dimlat*dimlon)\n", - "\n", - "# normalize dataset:\n", - "# using MinMaxScaler\n", - "# sc = MinMaxScaler (feature_range = (0,1))\n", - "# data_norm = sc.fit_transform (data)\n", - "# scale data\n", - "# X_scale= scale(data.T)\n", - "# manually\n", - "data = (data - np.nanmean(data, axis=0)) / np.nanstd(data, axis=0)\n" - ] - }, - { - "cell_type": "markdown", + "execution_count": 9, "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Mean Air Temperature')" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "## Time domain" + "data = np.nanmean(data_in,axis=0)\n", + "# normalize data\n", + "data = (data - np.nanmean(data, axis=0)) / np.nanstd(data, axis=0)\n", + "plt.pcolor(ds.lon,ds.lat,data,\n", + " cmap='RdBu',\n", + " # vmin=-300,vmax=300\n", + " )\n", + "plt.colorbar()\n", + "plt.title('Mean Air Temperature')" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -673,864 +296,1841 @@ "\r", " [ 0 / 10000 ] 0% - ? it/s\r", " [ 0 / 10000 ] 0% - ? it/s\r", - " [ 1 / 10000 ] 0% - 0:00:06 left \r", - " [ 2 / 10000 ] 0% - 0:00:05 left \r", - " [ 3 / 10000 ] 0% - 0:00:05 left \r", - " [ 4 / 10000 ] 0% - 0:00:04 left \r", - " [ 5 / 10000 ] 0% - 0:00:04 left \r", - " [ 6 / 10000 ] 0% - 0:00:04 left \r", - " [ 7 / 10000 ] 0% - 0:00:04 left \r", - " [ 8 / 10000 ] 0% - 0:00:04 left \r", - " [ 9 / 10000 ] 0% - 0:00:04 left 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69% - 0:00:00 left \r", + " [ 6870 / 10000 ] 69% - 0:00:00 left \r", + " [ 6871 / 10000 ] 69% - 0:00:00 left \r", + " [ 6872 / 10000 ] 69% - 0:00:00 left \r", " [ 6873 / 10000 ] 69% - 0:00:00 left \r", " [ 6874 / 10000 ] 69% - 0:00:00 left \r", " [ 6875 / 10000 ] 69% - 0:00:00 left \r", @@ -7728,14 +7232,7 @@ " [ 6906 / 10000 ] 69% - 0:00:00 left \r", " [ 6907 / 10000 ] 69% - 0:00:00 left \r", " [ 6908 / 10000 ] 69% - 0:00:00 left \r", - " [ 6909 / 10000 ] 69% - 0:00:00 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 6909 / 10000 ] 69% - 0:00:00 left \r", " [ 6910 / 10000 ] 69% - 0:00:00 left \r", " [ 6911 / 10000 ] 69% - 0:00:00 left \r", " [ 6912 / 10000 ] 69% - 0:00:00 left \r", @@ -7979,14 +7476,7 @@ " [ 7150 / 10000 ] 72% - 0:00:00 left \r", " [ 7151 / 10000 ] 72% - 0:00:00 left \r", " [ 7152 / 10000 ] 72% - 0:00:00 left \r", - " [ 7153 / 10000 ] 72% - 0:00:00 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 7153 / 10000 ] 72% - 0:00:00 left \r", " [ 7154 / 10000 ] 72% - 0:00:00 left \r", " [ 7155 / 10000 ] 72% - 0:00:00 left \r", " [ 7156 / 10000 ] 72% - 0:00:00 left \r", @@ -8050,7 +7540,14 @@ " [ 7214 / 10000 ] 72% - 0:00:00 left \r", " [ 7215 / 10000 ] 72% - 0:00:00 left \r", " [ 7216 / 10000 ] 72% - 0:00:00 left \r", - " [ 7217 / 10000 ] 72% - 0:00:00 left \r", + " [ 7217 / 10000 ] 72% - 0:00:00 left " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", " [ 7218 / 10000 ] 72% - 0:00:00 left \r", " [ 7219 / 10000 ] 72% - 0:00:00 left \r", " [ 7220 / 10000 ] 72% - 0:00:00 left \r", @@ -8349,14 +7846,7 @@ " [ 7513 / 10000 ] 75% - 0:00:00 left \r", " [ 7514 / 10000 ] 75% - 0:00:00 left \r", " [ 7515 / 10000 ] 75% - 0:00:00 left \r", - " [ 7516 / 10000 ] 75% - 0:00:00 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 7516 / 10000 ] 75% - 0:00:00 left \r", " [ 7517 / 10000 ] 75% - 0:00:00 left \r", " [ 7518 / 10000 ] 75% - 0:00:00 left \r", " [ 7519 / 10000 ] 75% - 0:00:00 left \r", @@ -8600,14 +8090,7 @@ " [ 7757 / 10000 ] 78% - 0:00:00 left \r", " [ 7758 / 10000 ] 78% - 0:00:00 left \r", " [ 7759 / 10000 ] 78% - 0:00:00 left \r", - " [ 7760 / 10000 ] 78% - 0:00:00 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 7760 / 10000 ] 78% - 0:00:00 left \r", " [ 7761 / 10000 ] 78% - 0:00:00 left \r", " [ 7762 / 10000 ] 78% - 0:00:00 left \r", " [ 7763 / 10000 ] 78% - 0:00:00 left \r", @@ -8989,14 +8472,7 @@ " [ 8139 / 10000 ] 81% - 0:00:00 left \r", " [ 8140 / 10000 ] 81% - 0:00:00 left \r", " [ 8141 / 10000 ] 81% - 0:00:00 left \r", - " [ 8142 / 10000 ] 81% - 0:00:00 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 8142 / 10000 ] 81% - 0:00:00 left \r", " [ 8143 / 10000 ] 81% - 0:00:00 left \r", " [ 8144 / 10000 ] 81% - 0:00:00 left \r", " [ 8145 / 10000 ] 81% - 0:00:00 left \r", @@ -9269,14 +8745,7 @@ " [ 8412 / 10000 ] 84% - 0:00:00 left \r", " [ 8413 / 10000 ] 84% - 0:00:00 left \r", " [ 8414 / 10000 ] 84% - 0:00:00 left \r", - " [ 8415 / 10000 ] 84% - 0:00:00 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 8415 / 10000 ] 84% - 0:00:00 left \r", " [ 8416 / 10000 ] 84% - 0:00:00 left \r", " [ 8417 / 10000 ] 84% - 0:00:00 left \r", " [ 8418 / 10000 ] 84% - 0:00:00 left \r", @@ -9436,7 +8905,14 @@ " [ 8572 / 10000 ] 86% - 0:00:00 left \r", " [ 8573 / 10000 ] 86% - 0:00:00 left \r", " [ 8574 / 10000 ] 86% - 0:00:00 left \r", - " [ 8575 / 10000 ] 86% - 0:00:00 left \r", + " [ 8575 / 10000 ] 86% - 0:00:00 left " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", " [ 8576 / 10000 ] 86% - 0:00:00 left \r", " [ 8577 / 10000 ] 86% - 0:00:00 left \r", " [ 8578 / 10000 ] 86% - 0:00:00 left \r", @@ -9643,14 +9119,7 @@ " [ 8779 / 10000 ] 88% - 0:00:00 left \r", " [ 8780 / 10000 ] 88% - 0:00:00 left \r", " [ 8781 / 10000 ] 88% - 0:00:00 left \r", - " [ 8782 / 10000 ] 88% - 0:00:00 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 8782 / 10000 ] 88% - 0:00:00 left \r", " [ 8783 / 10000 ] 88% - 0:00:00 left \r", " [ 8784 / 10000 ] 88% - 0:00:00 left \r", " [ 8785 / 10000 ] 88% - 0:00:00 left \r", @@ -9897,14 +9366,7 @@ " [ 9026 / 10000 ] 90% - 0:00:00 left \r", " [ 9027 / 10000 ] 90% - 0:00:00 left \r", " [ 9028 / 10000 ] 90% - 0:00:00 left \r", - " [ 9029 / 10000 ] 90% - 0:00:00 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 9029 / 10000 ] 90% - 0:00:00 left \r", " [ 9030 / 10000 ] 90% - 0:00:00 left \r", " [ 9031 / 10000 ] 90% - 0:00:00 left \r", " [ 9032 / 10000 ] 90% - 0:00:00 left \r", @@ -10292,7 +9754,1224 @@ " [ 9414 / 10000 ] 94% - 0:00:00 left \r", " [ 9415 / 10000 ] 94% - 0:00:00 left \r", " [ 9416 / 10000 ] 94% - 0:00:00 left \r", - " [ 9417 / 10000 ] 94% - 0:00:00 left " + " [ 9417 / 10000 ] 94% - 0:00:00 left \r", + " [ 9418 / 10000 ] 94% - 0:00:00 left \r", + " [ 9419 / 10000 ] 94% - 0:00:00 left \r", + " [ 9420 / 10000 ] 94% - 0:00:00 left \r", + " [ 9421 / 10000 ] 94% - 0:00:00 left \r", + " [ 9422 / 10000 ] 94% - 0:00:00 left \r", + " [ 9423 / 10000 ] 94% - 0:00:00 left \r", + " [ 9424 / 10000 ] 94% - 0:00:00 left \r", + " [ 9425 / 10000 ] 94% - 0:00:00 left \r", + " [ 9426 / 10000 ] 94% - 0:00:00 left \r", + " [ 9427 / 10000 ] 94% - 0:00:00 left \r", + " [ 9428 / 10000 ] 94% - 0:00:00 left \r", + " [ 9429 / 10000 ] 94% - 0:00:00 left \r", + " [ 9430 / 10000 ] 94% - 0:00:00 left \r", + " [ 9431 / 10000 ] 94% - 0:00:00 left \r", + " [ 9432 / 10000 ] 94% - 0:00:00 left \r", + " [ 9433 / 10000 ] 94% - 0:00:00 left \r", + " [ 9434 / 10000 ] 94% - 0:00:00 left \r", + " [ 9435 / 10000 ] 94% - 0:00:00 left \r", + " [ 9436 / 10000 ] 94% - 0:00:00 left \r", + " [ 9437 / 10000 ] 94% - 0:00:00 left \r", + " [ 9438 / 10000 ] 94% - 0:00:00 left \r", + " [ 9439 / 10000 ] 94% - 0:00:00 left \r", 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100% - 0:00:00 left \r", + " [ 9993 / 10000 ] 100% - 0:00:00 left \r", + " [ 9994 / 10000 ] 100% - 0:00:00 left \r", + " [ 9995 / 10000 ] 100% - 0:00:00 left \r", + " [ 9996 / 10000 ] 100% - 0:00:00 left \r", + " [ 9997 / 10000 ] 100% - 0:00:00 left \r", + " [ 9998 / 10000 ] 100% - 0:00:00 left \r", + " [ 9999 / 10000 ] 100% - 0:00:00 left \r", + " [ 10000 / 10000 ] 100% - 0:00:00 left \n", + " quantization error: 0.9535273382870869\n" + ] + } + ], + "source": [ + "X=np.array(data)\n", + "input_len=X.shape[1]\n", + "\n", + "# create som\n", + "som = MiniSom(x=x,y=y,input_len=input_len,\n", + " sigma=sigma,learning_rate=learning_rate,\n", + " neighborhood_function=ngb_function,\n", + " topology=topology,\n", + " activation_distance=activation_distance,\n", + " random_seed=None)\n", + "# init som\n", + "if init=='pca':\n", + " som.pca_weights_init(X)\n", + "else:\n", + " som.random_weights_init(X)\n", + "\n", + "# train som\n", + "if train=='random':\n", + " som.train_random(X,iterations,verbose=True)\n", + "else:\n", + " som.train_batch(X,iterations,verbose=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(15, 5))\n", + "plt.subplot(121)\n", + "plt.title('original')\n", + "plt.pcolor(ds.lon,ds.lat,X,\n", + " cmap='RdBu',)\n", + "plt.title('Original colors')\n", + "plt.subplot(122)\n", + "plt.pcolor(ds.lon,ds.lat,som.quantization(X),\n", + " cmap='RdBu',)\n", + "plt.title('Learned colors')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 3D SOM\n", + "Now, let's use the entire 3D matrix (time,lat,lon).\n", + "\n", + "We will apply SOM first on time domain, that is, find spatial clusters that are correlated in time, and later in spatial domain. " + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(2920, 25, 53)\n" + ] + } + ], + "source": [ + "data=np.array(data_in)\n", + "print(data_in.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "# data preprocessing\n", + "\n", + "# we need to concatenate the dataset to 2D:\n", + "data=data_in.reshape(dimtime,dimlat*dimlon)\n", + "\n", + "# normalize dataset:\n", + "# using MinMaxScaler\n", + "# sc = MinMaxScaler (feature_range = (0,1))\n", + "# data_norm = sc.fit_transform (data)\n", + "# scale data\n", + "# X_scale= scale(data.T)\n", + "# manually\n", + "data = (data - np.nanmean(data, axis=0)) / np.nanstd(data, axis=0)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Time domain" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", + " [ 0 / 10000 ] 0% - 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" + ] + }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -10420,6 +11107,13 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Mean (blue), max and min (in grey) time series of each cluster. " + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -10429,7 +11123,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -10439,199 +11133,199 @@ "\r", " [ 0 / 10000 ] 0% - ? it/s\r", " [ 0 / 10000 ] 0% - ? it/s\r", - " [ 1 / 10000 ] 0% - 0:00:09 left \r", - " [ 2 / 10000 ] 0% - 0:00:06 left \r", - " [ 3 / 10000 ] 0% - 0:00:05 left \r", - " [ 4 / 10000 ] 0% - 0:00:04 left \r", - " [ 5 / 10000 ] 0% - 0:00:03 left \r", - " [ 6 / 10000 ] 0% - 0:00:03 left \r", - " [ 7 / 10000 ] 0% - 0:00:03 left \r", - " [ 8 / 10000 ] 0% - 0:00:03 left \r", - " [ 9 / 10000 ] 0% - 0:00:03 left \r", - " [ 10 / 10000 ] 0% - 0:00:03 left \r", - " [ 11 / 10000 ] 0% - 0:00:03 left \r", - " [ 12 / 10000 ] 0% - 0:00:03 left \r", - " [ 13 / 10000 ] 0% - 0:00:03 left \r", - " [ 14 / 10000 ] 0% - 0:00:03 left \r", - " [ 15 / 10000 ] 0% - 0:00:03 left \r", - " [ 16 / 10000 ] 0% - 0:00:03 left \r", - " [ 17 / 10000 ] 0% - 0:00:03 left \r", - " [ 18 / 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" [ 178 / 10000 ] 2% - 0:00:03 left \r", + " [ 179 / 10000 ] 2% - 0:00:03 left \r", + " [ 180 / 10000 ] 2% - 0:00:03 left \r", + " [ 181 / 10000 ] 2% - 0:00:03 left \r", + " [ 182 / 10000 ] 2% - 0:00:03 left \r", + " [ 183 / 10000 ] 2% - 0:00:03 left \r", + " [ 184 / 10000 ] 2% - 0:00:03 left \r", + " [ 185 / 10000 ] 2% - 0:00:03 left \r", + " [ 186 / 10000 ] 2% - 0:00:03 left \r", + " [ 187 / 10000 ] 2% - 0:00:03 left \r", + " [ 188 / 10000 ] 2% - 0:00:03 left \r", + " [ 189 / 10000 ] 2% - 0:00:03 left \r", + " [ 190 / 10000 ] 2% - 0:00:03 left \r", + " [ 191 / 10000 ] 2% - 0:00:03 left \r", + " [ 192 / 10000 ] 2% - 0:00:03 left \r", + " [ 193 / 10000 ] 2% - 0:00:03 left \r", " [ 194 / 10000 ] 2% - 0:00:02 left \r", " [ 195 / 10000 ] 2% - 0:00:02 left \r", " [ 196 / 10000 ] 2% - 0:00:02 left \r", @@ -11330,11 +12024,7 @@ " [ 889 / 10000 ] 9% - 0:00:02 left \r", " [ 890 / 10000 ] 9% - 0:00:02 left \r", " [ 891 / 10000 ] 9% - 0:00:02 left \r", - " [ 892 / 10000 ] 9% - 0:00:02 left \r", - " [ 893 / 10000 ] 9% - 0:00:02 left \r", - " [ 894 / 10000 ] 9% - 0:00:02 left \r", - " [ 895 / 10000 ] 9% - 0:00:02 left \r", - " [ 896 / 10000 ] 9% - 0:00:02 left " + " [ 892 / 10000 ] 9% - 0:00:02 left " ] }, { @@ -11342,6 +12032,10 @@ "output_type": "stream", "text": [ "\r", + " [ 893 / 10000 ] 9% - 0:00:02 left \r", + " [ 894 / 10000 ] 9% - 0:00:02 left \r", + " [ 895 / 10000 ] 9% - 0:00:02 left \r", + " [ 896 / 10000 ] 9% - 0:00:02 left \r", " [ 897 / 10000 ] 9% - 0:00:02 left \r", " [ 898 / 10000 ] 9% - 0:00:02 left \r", " [ 899 / 10000 ] 9% - 0:00:02 left \r", @@ -11592,18 +12286,18 @@ " [ 1144 / 10000 ] 11% - 0:00:02 left \r", " [ 1145 / 10000 ] 11% - 0:00:02 left \r", " [ 1146 / 10000 ] 11% - 0:00:02 left \r", - " [ 1147 / 10000 ] 11% - 0:00:02 left \r", - " [ 1148 / 10000 ] 11% - 0:00:02 left \r", - " [ 1149 / 10000 ] 11% - 0:00:02 left \r", - " [ 1150 / 10000 ] 12% - 0:00:02 left \r", - " [ 1151 / 10000 ] 12% - 0:00:02 left \r", - " [ 1152 / 10000 ] 12% - 0:00:02 left \r", - " [ 1153 / 10000 ] 12% - 0:00:02 left \r", - " [ 1154 / 10000 ] 12% - 0:00:02 left \r", - " [ 1155 / 10000 ] 12% - 0:00:02 left \r", - " [ 1156 / 10000 ] 12% - 0:00:02 left \r", - " [ 1157 / 10000 ] 12% - 0:00:02 left \r", - " [ 1158 / 10000 ] 12% - 0:00:02 left \r", + " [ 1147 / 10000 ] 11% - 0:00:01 left \r", + " [ 1148 / 10000 ] 11% - 0:00:01 left \r", + " [ 1149 / 10000 ] 11% - 0:00:01 left \r", + " [ 1150 / 10000 ] 12% - 0:00:01 left \r", + " [ 1151 / 10000 ] 12% - 0:00:01 left \r", + " [ 1152 / 10000 ] 12% - 0:00:01 left \r", + " [ 1153 / 10000 ] 12% - 0:00:01 left \r", + " [ 1154 / 10000 ] 12% - 0:00:01 left \r", + " [ 1155 / 10000 ] 12% - 0:00:01 left \r", + " [ 1156 / 10000 ] 12% - 0:00:01 left \r", + " [ 1157 / 10000 ] 12% - 0:00:01 left \r", + " [ 1158 / 10000 ] 12% - 0:00:01 left \r", " [ 1159 / 10000 ] 12% - 0:00:01 left \r", " [ 1160 / 10000 ] 12% - 0:00:01 left \r", " [ 1161 / 10000 ] 12% - 0:00:01 left \r", @@ -12247,14 +12941,7 @@ " [ 1799 / 10000 ] 18% - 0:00:01 left \r", " [ 1800 / 10000 ] 18% - 0:00:01 left \r", " [ 1801 / 10000 ] 18% - 0:00:01 left \r", - " [ 1802 / 10000 ] 18% - 0:00:01 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 1802 / 10000 ] 18% - 0:00:01 left \r", " [ 1803 / 10000 ] 18% - 0:00:01 left \r", " [ 1804 / 10000 ] 18% - 0:00:01 left \r", " [ 1805 / 10000 ] 18% - 0:00:01 left \r", @@ -12280,7 +12967,14 @@ " [ 1825 / 10000 ] 18% - 0:00:01 left \r", " [ 1826 / 10000 ] 18% - 0:00:01 left \r", " [ 1827 / 10000 ] 18% - 0:00:01 left \r", - " [ 1828 / 10000 ] 18% - 0:00:01 left \r", + " [ 1828 / 10000 ] 18% - 0:00:01 left " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", " [ 1829 / 10000 ] 18% - 0:00:01 left \r", " [ 1830 / 10000 ] 18% - 0:00:01 left \r", " [ 1831 / 10000 ] 18% - 0:00:01 left \r", @@ -13203,14 +13897,7 @@ " [ 2748 / 10000 ] 27% - 0:00:01 left \r", " [ 2749 / 10000 ] 27% - 0:00:01 left \r", " [ 2750 / 10000 ] 28% - 0:00:01 left \r", - " [ 2751 / 10000 ] 28% - 0:00:01 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 2751 / 10000 ] 28% - 0:00:01 left \r", " [ 2752 / 10000 ] 28% - 0:00:01 left \r", " [ 2753 / 10000 ] 28% - 0:00:01 left \r", " [ 2754 / 10000 ] 28% - 0:00:01 left \r", @@ -13231,7 +13918,14 @@ " [ 2769 / 10000 ] 28% - 0:00:01 left \r", " [ 2770 / 10000 ] 28% - 0:00:01 left \r", " [ 2771 / 10000 ] 28% - 0:00:01 left \r", - " [ 2772 / 10000 ] 28% - 0:00:01 left \r", + " [ 2772 / 10000 ] 28% - 0:00:01 left " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", " [ 2773 / 10000 ] 28% - 0:00:01 left \r", " [ 2774 / 10000 ] 28% - 0:00:01 left \r", " [ 2775 / 10000 ] 28% - 0:00:01 left \r", @@ -14168,14 +14862,7 @@ " [ 3706 / 10000 ] 37% - 0:00:01 left \r", " [ 3707 / 10000 ] 37% - 0:00:01 left \r", " [ 3708 / 10000 ] 37% - 0:00:01 left \r", - " [ 3709 / 10000 ] 37% - 0:00:01 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 3709 / 10000 ] 37% - 0:00:01 left \r", " [ 3710 / 10000 ] 37% - 0:00:01 left \r", " [ 3711 / 10000 ] 37% - 0:00:01 left \r", " [ 3712 / 10000 ] 37% - 0:00:01 left \r", @@ -14184,7 +14871,14 @@ " [ 3715 / 10000 ] 37% - 0:00:01 left \r", " [ 3716 / 10000 ] 37% - 0:00:01 left \r", " [ 3717 / 10000 ] 37% - 0:00:01 left \r", - " [ 3718 / 10000 ] 37% - 0:00:01 left \r", + " [ 3718 / 10000 ] 37% - 0:00:01 left " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", " [ 3719 / 10000 ] 37% - 0:00:01 left \r", " [ 3720 / 10000 ] 37% - 0:00:01 left \r", " [ 3721 / 10000 ] 37% - 0:00:01 left \r", @@ -15098,7 +15792,14 @@ " [ 4629 / 10000 ] 46% - 0:00:01 left \r", " [ 4630 / 10000 ] 46% - 0:00:01 left \r", " [ 4631 / 10000 ] 46% - 0:00:01 left \r", - " [ 4632 / 10000 ] 46% - 0:00:01 left \r", + " [ 4632 / 10000 ] 46% - 0:00:01 left " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", " [ 4633 / 10000 ] 46% - 0:00:01 left \r", " [ 4634 / 10000 ] 46% - 0:00:01 left \r", " [ 4635 / 10000 ] 46% - 0:00:01 left \r", @@ -15128,14 +15829,7 @@ " [ 4659 / 10000 ] 47% - 0:00:01 left \r", " [ 4660 / 10000 ] 47% - 0:00:01 left \r", " [ 4661 / 10000 ] 47% - 0:00:01 left \r", - " [ 4662 / 10000 ] 47% - 0:00:01 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 4662 / 10000 ] 47% - 0:00:01 left \r", " [ 4663 / 10000 ] 47% - 0:00:01 left \r", " [ 4664 / 10000 ] 47% - 0:00:01 left \r", " [ 4665 / 10000 ] 47% - 0:00:01 left \r", @@ -15770,161 +16464,161 @@ " [ 5294 / 10000 ] 53% - 0:00:01 left \r", " [ 5295 / 10000 ] 53% - 0:00:01 left \r", " [ 5296 / 10000 ] 53% - 0:00:01 left \r", - " [ 5297 / 10000 ] 53% - 0:00:01 left \r", - " [ 5298 / 10000 ] 53% - 0:00:01 left \r", - " [ 5299 / 10000 ] 53% - 0:00:01 left \r", - " [ 5300 / 10000 ] 53% - 0:00:01 left \r", - " [ 5301 / 10000 ] 53% - 0:00:01 left \r", - " [ 5302 / 10000 ] 53% - 0:00:01 left \r", - " [ 5303 / 10000 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- " [ 5370 / 10000 ] 54% - 0:00:00 left \r", - " [ 5371 / 10000 ] 54% - 0:00:00 left \r", - " [ 5372 / 10000 ] 54% - 0:00:00 left \r", - " [ 5373 / 10000 ] 54% - 0:00:00 left \r", - " [ 5374 / 10000 ] 54% - 0:00:00 left \r", - " [ 5375 / 10000 ] 54% - 0:00:00 left \r", - " [ 5376 / 10000 ] 54% - 0:00:00 left \r", - " [ 5377 / 10000 ] 54% - 0:00:00 left \r", - " [ 5378 / 10000 ] 54% - 0:00:00 left \r", - " [ 5379 / 10000 ] 54% - 0:00:00 left \r", - " [ 5380 / 10000 ] 54% - 0:00:00 left \r", - " [ 5381 / 10000 ] 54% - 0:00:00 left \r", - " [ 5382 / 10000 ] 54% - 0:00:00 left \r", - " [ 5383 / 10000 ] 54% - 0:00:00 left \r", - " [ 5384 / 10000 ] 54% - 0:00:00 left \r", - " [ 5385 / 10000 ] 54% - 0:00:00 left \r", - " [ 5386 / 10000 ] 54% - 0:00:00 left \r", - " [ 5387 / 10000 ] 54% - 0:00:00 left \r", - " [ 5388 / 10000 ] 54% - 0:00:00 left \r", - " [ 5389 / 10000 ] 54% - 0:00:00 left \r", - " [ 5390 / 10000 ] 54% - 0:00:00 left \r", - " [ 5391 / 10000 ] 54% - 0:00:00 left \r", - " [ 5392 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+ " [ 5437 / 10000 ] 54% - 0:00:01 left \r", + " [ 5438 / 10000 ] 54% - 0:00:01 left \r", + " [ 5439 / 10000 ] 54% - 0:00:01 left \r", + " [ 5440 / 10000 ] 54% - 0:00:01 left \r", + " [ 5441 / 10000 ] 54% - 0:00:01 left \r", + " [ 5442 / 10000 ] 54% - 0:00:01 left \r", + " [ 5443 / 10000 ] 54% - 0:00:01 left \r", + " [ 5444 / 10000 ] 54% - 0:00:01 left \r", + " [ 5445 / 10000 ] 54% - 0:00:01 left \r", + " [ 5446 / 10000 ] 54% - 0:00:01 left \r", + " [ 5447 / 10000 ] 54% - 0:00:01 left \r", + " [ 5448 / 10000 ] 54% - 0:00:01 left \r", + " [ 5449 / 10000 ] 54% - 0:00:01 left \r", + " [ 5450 / 10000 ] 54% - 0:00:01 left \r", + " [ 5451 / 10000 ] 55% - 0:00:01 left \r", " [ 5452 / 10000 ] 55% - 0:00:00 left \r", " [ 5453 / 10000 ] 55% - 0:00:00 left \r", " [ 5454 / 10000 ] 55% - 0:00:00 left \r", @@ -15956,7 +16650,14 @@ " [ 5480 / 10000 ] 55% - 0:00:00 left \r", " [ 5481 / 10000 ] 55% - 0:00:00 left \r", " [ 5482 / 10000 ] 55% - 0:00:00 left \r", - " [ 5483 / 10000 ] 55% - 0:00:00 left \r", + " [ 5483 / 10000 ] 55% - 0:00:00 left " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", " [ 5484 / 10000 ] 55% - 0:00:00 left \r", " [ 5485 / 10000 ] 55% - 0:00:00 left \r", " [ 5486 / 10000 ] 55% - 0:00:00 left \r", @@ -16087,14 +16788,7 @@ " [ 5611 / 10000 ] 56% - 0:00:00 left \r", " [ 5612 / 10000 ] 56% - 0:00:00 left \r", " [ 5613 / 10000 ] 56% - 0:00:00 left \r", - " [ 5614 / 10000 ] 56% - 0:00:00 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 5614 / 10000 ] 56% - 0:00:00 left \r", " [ 5615 / 10000 ] 56% - 0:00:00 left \r", " [ 5616 / 10000 ] 56% - 0:00:00 left \r", " [ 5617 / 10000 ] 56% - 0:00:00 left \r", @@ -16931,7 +17625,14 @@ " [ 6448 / 10000 ] 64% - 0:00:00 left \r", " [ 6449 / 10000 ] 64% - 0:00:00 left \r", " [ 6450 / 10000 ] 64% - 0:00:00 left \r", - " [ 6451 / 10000 ] 65% - 0:00:00 left \r", + " [ 6451 / 10000 ] 65% - 0:00:00 left " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", " [ 6452 / 10000 ] 65% - 0:00:00 left \r", " [ 6453 / 10000 ] 65% - 0:00:00 left \r", " [ 6454 / 10000 ] 65% - 0:00:00 left \r", @@ -17021,14 +17722,7 @@ " [ 6538 / 10000 ] 65% - 0:00:00 left \r", " [ 6539 / 10000 ] 65% - 0:00:00 left \r", " [ 6540 / 10000 ] 65% - 0:00:00 left \r", - " [ 6541 / 10000 ] 65% - 0:00:00 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 6541 / 10000 ] 65% - 0:00:00 left \r", " [ 6542 / 10000 ] 65% - 0:00:00 left \r", " [ 6543 / 10000 ] 65% - 0:00:00 left \r", " [ 6544 / 10000 ] 65% - 0:00:00 left \r", @@ -17833,7 +18527,14 @@ " [ 7343 / 10000 ] 73% - 0:00:00 left \r", " [ 7344 / 10000 ] 73% - 0:00:00 left \r", " [ 7345 / 10000 ] 73% - 0:00:00 left \r", - " [ 7346 / 10000 ] 73% - 0:00:00 left \r", + " [ 7346 / 10000 ] 73% - 0:00:00 left " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", " [ 7347 / 10000 ] 73% - 0:00:00 left \r", " [ 7348 / 10000 ] 73% - 0:00:00 left \r", " [ 7349 / 10000 ] 73% - 0:00:00 left \r", @@ -17953,14 +18654,7 @@ " [ 7463 / 10000 ] 75% - 0:00:00 left \r", " [ 7464 / 10000 ] 75% - 0:00:00 left \r", " [ 7465 / 10000 ] 75% - 0:00:00 left \r", - " [ 7466 / 10000 ] 75% - 0:00:00 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 7466 / 10000 ] 75% - 0:00:00 left \r", " [ 7467 / 10000 ] 75% - 0:00:00 left \r", " [ 7468 / 10000 ] 75% - 0:00:00 left \r", " [ 7469 / 10000 ] 75% - 0:00:00 left \r", @@ -18575,7 +19269,14 @@ " [ 8078 / 10000 ] 81% - 0:00:00 left \r", " [ 8079 / 10000 ] 81% - 0:00:00 left \r", " [ 8080 / 10000 ] 81% - 0:00:00 left \r", - " [ 8081 / 10000 ] 81% - 0:00:00 left \r", + " [ 8081 / 10000 ] 81% - 0:00:00 left " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", " [ 8082 / 10000 ] 81% - 0:00:00 left \r", " [ 8083 / 10000 ] 81% - 0:00:00 left \r", " [ 8084 / 10000 ] 81% - 0:00:00 left \r", @@ -18779,14 +19480,7 @@ " [ 8282 / 10000 ] 83% - 0:00:00 left \r", " [ 8283 / 10000 ] 83% - 0:00:00 left \r", " [ 8284 / 10000 ] 83% - 0:00:00 left \r", - " [ 8285 / 10000 ] 83% - 0:00:00 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 8285 / 10000 ] 83% - 0:00:00 left \r", " [ 8286 / 10000 ] 83% - 0:00:00 left \r", " [ 8287 / 10000 ] 83% - 0:00:00 left \r", " [ 8288 / 10000 ] 83% - 0:00:00 left \r", @@ -19456,7 +20150,14 @@ " [ 8952 / 10000 ] 90% - 0:00:00 left \r", " [ 8953 / 10000 ] 90% - 0:00:00 left \r", " [ 8954 / 10000 ] 90% - 0:00:00 left \r", - " [ 8955 / 10000 ] 90% - 0:00:00 left \r", + " [ 8955 / 10000 ] 90% - 0:00:00 left " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", " [ 8956 / 10000 ] 90% - 0:00:00 left \r", " [ 8957 / 10000 ] 90% - 0:00:00 left \r", " [ 8958 / 10000 ] 90% - 0:00:00 left \r", @@ -19687,14 +20388,7 @@ " [ 9183 / 10000 ] 92% - 0:00:00 left \r", " [ 9184 / 10000 ] 92% - 0:00:00 left \r", " [ 9185 / 10000 ] 92% - 0:00:00 left \r", - " [ 9186 / 10000 ] 92% - 0:00:00 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", + " [ 9186 / 10000 ] 92% - 0:00:00 left \r", " [ 9187 / 10000 ] 92% - 0:00:00 left \r", " [ 9188 / 10000 ] 92% - 0:00:00 left \r", " [ 9189 / 10000 ] 92% - 0:00:00 left \r", @@ -20398,7 +21092,14 @@ " [ 9887 / 10000 ] 99% - 0:00:00 left \r", " [ 9888 / 10000 ] 99% - 0:00:00 left \r", " [ 9889 / 10000 ] 99% - 0:00:00 left \r", - " [ 9890 / 10000 ] 99% - 0:00:00 left \r", + " [ 9890 / 10000 ] 99% - 0:00:00 left " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", " [ 9891 / 10000 ] 99% - 0:00:00 left \r", " [ 9892 / 10000 ] 99% - 0:00:00 left \r", " [ 9893 / 10000 ] 99% - 0:00:00 left \r", @@ -20508,14 +21209,7 @@ " [ 9997 / 10000 ] 100% - 0:00:00 left \r", " [ 9998 / 10000 ] 100% - 0:00:00 left \r", " [ 9999 / 10000 ] 100% - 0:00:00 left \r", - " [ 10000 / 10000 ] 100% - 0:00:00 left " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", + " [ 10000 / 10000 ] 100% - 0:00:00 left \n", " quantization error: 23.971422068680223\n" ] } @@ -20547,7 +21241,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -20584,12 +21278,12 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 21, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -20618,10 +21312,18 @@ " # plt.plot(win_ts[:,:,0].T);plt.show()\n", " # plot spatial pattern of each neuron\n", " plt.subplot(the_grid[6-position[1], position[0]])\n", - " plt.pcolor(ds.lon,ds.lat,win_ts[i,:,1].reshape(dimlat,dimlon));\n", + " plt.pcolor(ds.lon,ds.lat,win_ts[i,:,1].reshape(dimlat,dimlon),\n", + " cmap='RdBu',vmin=-1,vmax=1);\n", "plt.show()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The above image shows the spatial patterns of the dominant time periods, when we make the SOM analyses over space, instead of time. SOM algorithm will find the most dominant patterns (instead of the most dominant time series, like previously). " + ] + }, { "cell_type": "markdown", "metadata": {}, From d106af1ed32b6a263f8830d08b31a80914e35c1e Mon Sep 17 00:00:00 2001 From: carocamargo <47150926+carocamargo@users.noreply.github.com> Date: Mon, 15 Nov 2021 16:08:05 +0100 Subject: [PATCH 3/4] Spatiotemporal climate - Paramters Tunning example Second notebook of the spatio-temporal climate data example, now focusing on finding the best parameters for the SOM --- ...atiotemporal_climate_example-Part_II.ipynb | 32753 ++++++++++++++++ 1 file changed, 32753 insertions(+) create mode 100644 examples/SOM-spatiotemporal_climate_example-Part_II.ipynb diff --git a/examples/SOM-spatiotemporal_climate_example-Part_II.ipynb b/examples/SOM-spatiotemporal_climate_example-Part_II.ipynb new file mode 100644 index 0000000..75f61ec --- /dev/null +++ b/examples/SOM-spatiotemporal_climate_example-Part_II.ipynb @@ -0,0 +1,32753 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# load libraries\n", + "import xarray as xr\n", + "from minisom import MiniSom\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib as mpl\n", + "from matplotlib.gridspec import GridSpec\n", + "from sklearn.preprocessing import MinMaxScaler, scale\n", + "import numpy as np\n", + "\n", + "from hyperopt import fmin, tpe, hp, Trials , STATUS_OK\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# SOM Spatio-Temporal Example -- Parameters tunning" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Open and Explore data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Air temperature data from the US" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Dimensions: (lat: 25, lon: 53, time: 2920)\n", + "Coordinates:\n", + " * lat (lat) float32 75.0 72.5 70.0 67.5 65.0 ... 25.0 22.5 20.0 17.5 15.0\n", + " * lon (lon) float32 200.0 202.5 205.0 207.5 ... 322.5 325.0 327.5 330.0\n", + " * time (time) datetime64[ns] 2013-01-01 ... 2014-12-31T18:00:00\n", + "Data variables:\n", + " Tair (time, lat, lon) float32 ...\n", + "Attributes:\n", + " Conventions: COARDS\n", + " title: 4x daily NMC reanalysis (1948)\n", + " description: Data is from NMC initialized reanalysis\\n(4x/day). These a...\n", + " platform: Model\n", + " references: http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanaly...\n" + ] + } + ], + "source": [ + "# open xarray tutorial dataset\n", + "ds = xr.tutorial.open_dataset(\"air_temperature.nc\").rename({\"air\": \"Tair\"})\n", + "print(ds)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Data is from NMC initialized reanalysis\n", + "(4x/day). These are the 0.9950 sigma level values.\n" + ] + } + ], + "source": [ + "print(ds.description)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([ 2182., 60537., 195026., 233763., 315219., 635948.,\n", + " 778807., 1192236., 453381., 1901.]),\n", + " array([221. , 230.64 , 240.28 , 249.92 , 259.56 , 269.2 ,\n", + " 278.84 , 288.47998, 298.12 , 307.76 , 317.4 ],\n", + " dtype=float32),\n", + " )" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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hHOxmZoVxsJuZFcbBbmZWGAe7mVlhHOxmZoVxsJuZFcbBbmZWmFrfeWqbdM2+qtNVMDPrk3vsZmaFcbCbmRXGwW5mVhgHu5lZYRzsZmaFcbCbmRWmVrBLmiZphaSVkmY32S9JZ+f9t0o6oP1VNTOzOloGu6QRwLnAdGAyMFPS5IZi04FJ+TELOL/N9TQzs5rq9NinACsjYlVEPAVcDMxoKDMD+FYki4CdJe3R5rqamVkNde48HQusrqyvAf66RpmxwAPVQpJmkXr0AOslrehHXUcDD/ejfEmGc9theLffbd9KdObWOnJb9NX2l7R6cp1gV5NtMYAyRMRcYG6Ncz67EtKSiOgeyHOHuuHcdhje7Xfb3faBqDMUswYYX1kfB6wdQBkzM3sO1An2xcAkSRMljQKOBBY0lFkAvC9fHXMQ8HhEPNB4IDMz2/paDsVExAZJJwBXAyOAeRGxXNKxef8cYCFwOLASeBL44Fao64CGcAoxnNsOw7v9bvvwtEVtV8SzhsLNzGwI852nZmaFcbCbmRVmUAS7pPGSfirpDknLJZ2Ut58l6c48TcEPJO1cec6peQqDFZL+tnO133K9tb+y/xRJIWl0ZVsR7e+r7ZJOzO1bLukLle1Ft13S/pIWSbpZ0hJJUyrPKaXtz5f0K0m35Lafnre/SNKPJd2df+5SeU7pbW9f3kVExx/AHsABefmFwF2k6QveDIzM288EzszLk4FbgG2BicBvgBGdbke725/Xx5M+uL4PGF1a+/v43b8e+Amwbd632zBq+zXA9Lz9cODaAtsuYIe8vA3wS+Ag4AvA7Lx9don/5/toe9vyblD02CPigYj4dV7+PXAHMDYiromIDbnYItL18ZCmMLg4Iv4cEfeQrsaZ0njcoaK39ufdXwY+yuY3fBXT/j7afhxwRkT8Oe97KD9lOLQ9gB1zsZ3YdE9ISW2PiFifV7fJjyC18Zt5+zeBv8/Lxbe9nXk3KIK9SlIX8CrSX7GqDwE/zMu9TWEw5FXbL+nvgPsj4paGYkW2v+F3vydwiKRfSrpO0qtzseHQ9g8DZ0laDXwRODUXK6rtkkZIuhl4CPhxRPwS2D3yPTD55265+HBoe9UW5d2gCnZJOwDfBz4cEU9Utn8M2ABc1LOpydOH/HWb1faT2vsx4JPNijbZNqTb3+R3PxLYhfQW9SPApZLE8Gj7ccDJETEeOBn4vz1Fmzx9yLY9Ip6OiP1JPdMpkvbuo/iwaXs78m7QBLukbUj/uC+KiMsq298PvBU4KvKAEwVOYdCk/S8jjafdIuleUht/LemvKKz9vfzu1wCX5betvwI2kiZGGg5tfz/Qs/xdNr3tLqrtPSLiMeBaYBrwoPLMsPlnzxDccGh7+/Ku0x8kVD5M+BbwlYbt04DbgTEN2/di8w8TVjFEP0jpq/0NZe5l04enxbS/j9/9scCn8/KepLeiGiZtvwOYmpcPA5YW+HsfA+ycl7cDfpYD7Sw2//D0C8Oo7W3Lu443Mlf8daS3FrcCN+dHzxQFqyvb5lSe8zHSp8MryFcQDNVHb+1vKPNMsJfU/j5+96OAC4FlwK+BNwyjtr8OWJr/M/8SOLDAtu8L3JTbvgz4ZN6+K/A/wN3554uGUdvblneeUsDMrDCDZozdzMzaw8FuZlYYB7uZWWEc7GZmhXGwm5kVxsFuz5Jvd75J0pU1yl6bZ5y7Nc9Md051Vro+nrewp5yk9a3KN3n+yZL+JGmnyrZuSWfXeG6XpHf395ydIOnfO3DOqZJe81yf19rHwW7NnES6SaauoyJiX9L1uX8G/rvVEyLi8Eh33Q3UTNL38b69cswlEfGvjQUlNX4FZBcwKIJd0ogWRfod7E3a219TAQf7EOZgt81IGge8Bbigsm2kpMWSpub1z0v6bONzI+Ip0kyUEyTtl8teLmlpnnd6VuWY96oyv3ze9m1JMyrrF+WJ0Brr+DJgB+DjpIDv2T61512GpNMkzZV0DenuzqozSBOM3Zx7/iPyXNiL8zuPf64c7zpJl0q6S9IZko7Kc2nfluuBpPmS5kj6WS731ry9r+P+VNJ/Abf19jpJOgPYLtfzovxOY1mlvadIOi0vXyvpc5KuA06SdGCu+1JJV/fcpt/wOr5NaZK1myT9RNLuSpORHQucnM97SOPzbAjo9F1YfgyuB/A94EBSr+3Kyva9SL34N5HumhuVt18LdDcc43LgXXn5RfnndqS77HbN6/eyaYqE9fnnocDleXkn4B7y/NQNx/848AlSx+ReNs3V/kydgdNId29u1+T5jW2bBXw8L28LLCHduj0VeIw0b/q2wP3A6bncSeSpAID5wI9yfSaR5vZ4fovj/gGYWKlDb6/T+kqZLmBZZf0U4LTK7+G8vLwNcAP51nTgXaQvoW98HXZh0/ceHwP8R+W1O6XT/xb9GPhjS9+yWUFyT/OhiFja0zvvERHLJX0buAI4OFLvvNdDVZb/VVLPcMl4UvA90uxJEXGdpHMl7Qb8A/D92DQ/ddWRwNsjYqOky4B3AOc2KbcgIv7YRz17vBnYV9IReX2nXM+ngMWRp5GV9BvSl2BA6mm/vnKMSyNiI3C3pFXAK1oc91eR5tbuUft16sMl+efLgb2BH0sCGAE80KT8OOCS3JsfRfpDagVwsFvVa4G/k3Q4qce5o6QLI+I9ef8+pB7s7r0dII8Z7wPckf84vJH0h+BJSdfm4/bl28BRpPD+UJPj70sKvZ7QGkWaFKlZsP+hxbmeOSxwYkRc3XCuqaTPDHpsrKxvZPP/P41zc0SL4/6hYb3O67SBzYdPG8v0HFPA8og4uMkxqr4GfCkiFuQ6nNaivA0RHmO3Z0TEqRExLiK6SMH6vz2hLukfSBM0/Q1wdrMrX5SmoP08sDoibiX1UB/NYfUK0tzqrcwnzUdPRCxvsn8mafihKz9eDIyV9JJ+NPX3pK+i63E1cFyuP5L2lLR9P44H8A5Jz8vj7i8lTdZU97h9vU5/6Xk+8CCwm6RdJW1LmhGwmRXAGEkH5/NuI2mvXs57f15+f2V74+tjQ4yD3VrKH3KeARwdEXcB5wBfrRS5SFLPTHXbk77KC9K488i87zOkr/vqU0Q8SBrL/0YvRY4EftCw7Qd5e123AhuUvkz4ZNIHxbeT5rtfBnyd/r+bXQFcR/rWm2Mj4k/9OG5fr9Nc4FZJF0XEX4BPk2Z8vBK4s1lF8jDZEcCZkm4hzRTY7CqX04DvSvoZ8HBl+xXA2/3h6dDl2R1tUJH0AtL49QER8Xin61OHpPmkD2O/1+m6mIF77DaISHojqRf6taES6maDkXvsZmaFcY/d2kLSBZImP4fnm1+5jHCrHlPSfpJuzDclXSFpx7x9lKRv5O23VC8R1aapFm7Oj92aHPc0SfdL+nQv9XnWTVz9aMtpkk7Jy8+X9GNJn5LUc8PTUwM9tg1+vtzR2iIijul0HbaiC0g37Fwn6UPAR0g3SP0TQETsk4P7h5Jena9nhzTVwpIWx/5yRHxxa1Vc0ijSl2UvjYjT8+b9lb4g3QrlHrv1i6TtJV2Ve6jLJL0rb79WUndePlrp1vprJf2npHPy9vmSzle6nX6VpEMlzZN0R/4Asucc50taonR7/elNK7J5nZ51+7ykV0r6VaVMV77qpGn5Fqd4OXB9Xv4x8I95eTLpezmJiIdI1/h3t3wRe2/HrpKuUbrF/+tUbvSS9B6lqQxulvR15Tlmenuts5HAxcDdETF7oPWyocfBbv01DVgbEftFxN6kS/WeIenFpN7sQaTpB17R8PxdgDcAJ5Muq/syabqCfSTtn8t8LCK6SZOKHap0U1JT+RrvrwFHRMSBwDzgsxFxBzBK0ktz0XcBl/ZWvkWblwE9c9a8g3RnKKQvm56hNJfORNJUDOMrz/tGDuJPSKrejdubTwE/j4hXAQuACbmNr8z1f21E7A88DRxV47X+KLAhIj5c49xWEAe79ddtwBslnSnpkCZXr0wBrouI3+Xrrr/bsP+KSJ/Y3wY8GBG35aGL5aS5UADeKenXpDlp9iL1jHtTvX3+ZtI8MuPyvkuBd+bld5Fuue+rfG8+BBwvaSnpxp2e6RTmkeaFWQJ8hTQ/S88UCEdFxD7AIfnx3hbngHTz14UAEXEV8Gjefhjpj8biXOfDSDdBtXqtfw4cLGnPGue2gniM3folIu6SdCBwOPB5SddERPXDv1Y90+ot+Y236/f0fE8BXh0Rj+Yhmr6mIejr9vlLSDfgXJaqHndL2qeP8k1FxJ2keV/IIfmWvH0D6Z0Hed8NwN153/355++VZnGcwrNnmWx6uibbBHwzIk7dbOOmuWV6cz3wTdLY/yERsbbG+a0A7rFbv+S3/09GxIXAF4EDGor8ijR8sovSvOD/2HiMFnYkzXnyuKTdgektyvd6+3xE/IY0bPEJNk2QVfd2+2f0XNEi6XmkHv6cvP4C5SkCJL2JNOxxex6aGd1zfNKt/8uaHnxz15PmyUHSdNKwFaRx/CMq9XiR0hQKLV/riPg+cBbwI9X4AhQrg3vs1l/7AGdJ2gj8BTiuujMi7pf0OdJt72tJt9TXvtkoIm6RdBNpaGYV8IsW5Z9SukTxbKVvUxpJGhbpmWfmElKwTaxZvpmZko7Py5exabqD3YCr82txP5uGW7bN27chzaz4E+A/azT/dOA7eRjqOuC3uc63S/o4cE3+4/IX4PiIWFTntY6IOZL+Clgg6c15ugMrmG9QsraTtENErM+9yB+Q5gJvnN9l2FP6koz1W3K540Bfa6XLHbsj4uFWZW3o8VCMbQ2n5Q/5lpHm+L68w/UZrNYDs9TLDUo19eu1Vr5BifRlHBv7KmtDl3vsZmaFcY/dzKwwDnYzs8I42M3MCuNgNzMrjIPdzKwwDnYzs8L8f7L7YX93Tz3/AAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot histogram\n", + "ds.Tair.plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot at initial time\n", + "ds.Tair.isel(time=1).plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# group by month and plot it:\n", + "monthly_means = ds.groupby(\"time.month\").mean()\n", + "# xarray's groupby reductions drop attributes. Let's assign them back so we get nice labels.\n", + "monthly_means.Tair.attrs = ds.Tair.attrs\n", + "\n", + "fg = monthly_means.Tair.plot(\n", + " col=\"month\",\n", + " col_wrap=4, # each row has a maximum of 4 columns\n", + " # The remaining kwargs customize the plot just as for not-faceted plots\n", + " robust=True,\n", + " cmap=mpl.cm.RdYlBu_r,\n", + " cbar_kwargs={\n", + " \"orientation\": \"horizontal\",\n", + " \"shrink\": 0.8,\n", + " \"aspect\": 40,\n", + " \"pad\": 0.1,\n", + " },\n", + ")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# SOM Parameters Optmization\n", + "\n", + "A way to find the ideal sigma and learning rate, is by searching the values that will give us the smaller Quantification Error (QE), given a neighborhood function and neural map size. \n", + "\n", + "We can use the python package **hyperopt** for this.\n", + "\n", + "Read more [here](https://towardsdatascience.com/algorithms-for-hyperparameter-optimisation-in-python-edda4bdb167)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "# define SOM parameters\n", + "som_map = (3,3) # we will try a 3x3 neural map\n", + "x,y=som_map\n", + "sigma = 1 # default value\n", + "learning_rate = 0.5 # default value\n", + "ngb_function = 'gaussian' # choosing between ['gaussian' ,'bubble','mexican_hat']\n", + "init = 'pca' # we will initialize SOM randomly. Option: 'pca'\n", + "train = 'batch' # perform batch traning instead of random (default)\n", + "iterations = 10000 # lenght of training\n", + "topology = 'rectangular' # to ensure equidistant ditance neighbors\n", + "topology='hexagonal'\n", + "activation_distance = 'euclidean'" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# data params\n", + "data_in=np.array(ds['Tair'])\n", + "dimlon=len(ds['lon'])\n", + "dimlat= len(ds['lat'])\n", + "dimtime = len(ds['time'])" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/ccamargo/anaconda3/lib/python3.7/site-packages/minisom.py:370: ComplexWarning: Casting complex values to real discards the imaginary part\n", + " self._weights[i, j] = c1*pc[pc_order[0]] + c2*pc[pc_order[1]]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", + " [ 0 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100% - 0:00:00 left \n", + " quantization error: 0.9535273382870869\n" + ] + } + ], + "source": [ + "# use simple SOM as example\n", + "data = np.nanmean(data_in,axis=0)\n", + "# normalize data\n", + "data = (data - np.nanmean(data, axis=0)) / np.nanstd(data, axis=0)\n", + "X=np.array(data)\n", + "input_len=X.shape[1]\n", + "init='pca'\n", + "# create som\n", + "som = MiniSom(x=x,y=y,input_len=input_len,\n", + " sigma=sigma,learning_rate=learning_rate,\n", + " neighborhood_function=ngb_function,\n", + " topology=topology,\n", + " activation_distance=activation_distance,\n", + " random_seed=None)\n", + "\n", + "starting_weights = som.get_weights()\n", + "\n", + "# init som\n", + "if init=='pca':\n", + " som.pca_weights_init(X)\n", + "else:\n", + " som.random_weights_init(X)\n", + "\n", + "# train som\n", + "if train=='random':\n", + " som.train_random(X,iterations,verbose=True)\n", + "else:\n", + " som.train_batch(X,iterations,verbose=True)\n", + " \n", + "qnt1 = som.quantization(X)\n", + "weights1 = som.get_weights()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 25%|██▌ | 5/20 [00:03<00:09, 1.63trial/s, best loss: 0.8420693218652582]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/ccamargo/anaconda3/lib/python3.7/site-packages/minisom.py:249: RuntimeWarning: divide by zero encountered in true_divide\n", + " ax = exp(-power(self._xx-self._xx.T[c], 2)/d)\n", + "\n", + "/Users/ccamargo/anaconda3/lib/python3.7/site-packages/minisom.py:249: RuntimeWarning: invalid value encountered in true_divide\n", + " ax = exp(-power(self._xx-self._xx.T[c], 2)/d)\n", + "\n", + "/Users/ccamargo/anaconda3/lib/python3.7/site-packages/minisom.py:250: RuntimeWarning: divide by zero encountered in true_divide\n", + " ay = exp(-power(self._yy-self._yy.T[c], 2)/d)\n", + "\n", + "/Users/ccamargo/anaconda3/lib/python3.7/site-packages/minisom.py:250: RuntimeWarning: invalid value encountered in true_divide\n", + " ay = exp(-power(self._yy-self._yy.T[c], 2)/d)\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 90%|█████████ | 18/20 [00:09<00:01, 1.95trial/s, best loss: 0.8420693218652582]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/ccamargo/anaconda3/lib/python3.7/site-packages/minisom.py:486: RuntimeWarning: invalid value encountered in sqrt\n", + " return sqrt(-2 * cross_term + input_data_sq + weights_flat_sq.T)\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "100%|██████████| 20/20 [00:10<00:00, 1.83trial/s, best loss: 0.8420693218652582]\n", + "best: {'learning_rate': 0.5, 'sigma': 0.5}\n" + ] + } + ], + "source": [ + "from hyperopt import fmin, tpe, hp, Trials , STATUS_OK\n", + "\n", + "### Define the search space\n", + "space = {\n", + " # hp.choice.choice will select 1 value from the given list\n", + " # hp.hp.quniform returns a float between a given range\n", + " 'sigma':hp.quniform('sigma',0.0,1.0,0.05),\n", + " # 'sigma':hp.choice('sigma', np.arange(0.1, 3,0.5, dtype=float)),\n", + " 'learning_rate':hp.quniform('learning_rate',0.1,1,0.05),\n", + "\n", + "}\n", + "\n", + "\n", + "### define the objective function\n", + "def som_fn(space):\n", + "\n", + " sigma = space['sigma']\n", + " learning_rate = space['learning_rate']\n", + " som = MiniSom(x, y, input_len, \n", + " sigma=sigma,\n", + " learning_rate=learning_rate, \n", + " neighborhood_function=ngb_function,\n", + " topology=topology,\n", + " activation_distance=activation_distance,\n", + " random_seed=None\n", + " )\n", + " \n", + " # initialize SOM\n", + " som.pca_weights_init(X)\n", + " # train SOM\n", + " som.train_batch(X, iterations, verbose=False)\n", + " \n", + " # remember to use the same parameters as you are using out of the tuning function\n", + " \n", + " # use QE as a measure of best model\n", + " loss = som.quantization_error(X)\n", + " return {'loss': loss, 'status': STATUS_OK}\n", + " \n", + "### Storing the results of every iteration \n", + "trials = Trials()\n", + "MAX_EVALS = 20\n", + "\n", + "# Optimize\n", + "best = fmin(fn=som_fn,\n", + " space=space,\n", + " algo=tpe.suggest,\n", + " max_evals=MAX_EVALS,\n", + " trials=trials)\n", + "\n", + "\n", + "### best will the return the the best hyperparameter set\n", + "print('best: {}'.format(best))\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", + " [ 0 / 10000 ] 0% - ? it/s\r", + " [ 0 / 10000 ] 0% - ? it/s\r", + " [ 1 / 10000 ] 0% - 0:00:01 left \r", + " [ 2 / 10000 ] 0% - 0:00:01 left \r", + " [ 3 / 10000 ] 0% - 0:00:01 left \r", + " [ 4 / 10000 ] 0% - 0:00:01 left \r", + " [ 5 / 10000 ] 0% - 0:00:01 left \r", + " [ 6 / 10000 ] 0% - 0:00:01 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som.train_batch(X,iterations,verbose=True)\n", + " \n", + "qnt2 = som.quantization(X)\n", + "weights2 = som.get_weights()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(15, 5))\n", + "plt.subplot(131)\n", + "plt.title('original')\n", + "plt.pcolor(ds.lon,ds.lat,X,\n", + " cmap='RdBu',)\n", + "plt.title('Original colors')\n", + "plt.subplot(132)\n", + "plt.pcolor(ds.lon,ds.lat,qnt1,\n", + " cmap='RdBu',)\n", + "plt.title('Learned colors \\n default parameters')\n", + "\n", + "plt.subplot(133)\n", + "plt.pcolor(ds.lon,ds.lat,qnt2,\n", + " cmap='RdBu',)\n", + "plt.title('Learned colors \\n optmized parameters')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Spatial clusters" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.9999999" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data=np.array(data_in)\n", + "# we need to concatenate the dataset to 2D:\n", + "data=data_in.reshape(dimtime,dimlat*dimlon)\n", + "\n", + "# normalize dataset:\n", + "data = (data - np.nanmean(data)) / np.nanstd(data)\n", + "\n", + "np.std(data)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-5.6814283e-06" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.mean(data)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", + " [ 0 / 10000 ] 0% - ? it/s\r", + " [ 0 / 10000 ] 0% - ? it/s\r", + " [ 1 / 10000 ] 0% - 0:00:07 left \r", + " [ 2 / 10000 ] 0% - 0:00:05 left \r", + " [ 3 / 10000 ] 0% - 0:00:05 left \r", + " [ 4 / 10000 ] 0% - 0:00:04 left \r", + " [ 5 / 10000 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"input_len=X.shape[1]\n", + "\n", + "# create som\n", + "# default parameters\n", + "som = MiniSom(x=x,y=y,input_len=input_len,\n", + " sigma=sigma,learning_rate=learning_rate,\n", + " neighborhood_function=ngb_function,\n", + " topology=topology,\n", + " activation_distance=activation_distance,\n", + " random_seed=None)\n", + "\n", + "starting_weights = som.get_weights()\n", + "\n", + "# init som\n", + "if init=='pca':\n", + " som.pca_weights_init(X)\n", + "else:\n", + " som.random_weights_init(X)\n", + "weights1 = som.get_weights() \n", + "# train som\n", + "if train=='random':\n", + " som.train_random(X,iterations,verbose=True)\n", + "else:\n", + " som.train_batch(X,iterations,verbose=True)\n", + "\n", + "qnt1 = som.quantization(X)\n", + "\n", + "# extract clusters of winning neurons:\n", + "# each neuron represents a cluster\n", + "winner_coordinates = np.array([som.winner(x) for x in X]).T\n", + "# with np.ravel_multi_index we convert the bidimensional\n", + "# coordinates to a monodimensional index\n", + "cluster_index1 = np.ravel_multi_index(winner_coordinates, (x,y))\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "100%|██████████| 20/20 [03:17<00:00, 9.90s/trial, best loss: 27.748766109556758]\n", + "best: {'learning_rate': 0.25, 'sigma': 0.9500000000000001}\n" + ] + } + ], + "source": [ + "### Define the search space\n", + "space = {\n", + " # hp.choice.choice will select 1 value from the given list\n", + " # hp.hp.quniform returns a float between a given range\n", + " 'sigma':hp.quniform('sigma',0.0,1.0,0.05),\n", + " # 'sigma':hp.choice('sigma', np.arange(0.1, 3,0.5, dtype=float)),\n", + " 'learning_rate':hp.quniform('learning_rate',0.1,1,0.05),\n", + "\n", + "}\n", + "\n", + "\n", + "### define the objective function\n", + "def som_fn(space):\n", + "\n", + " sigma = space['sigma']\n", + " learning_rate = space['learning_rate']\n", + " som = MiniSom(x, y, input_len, \n", + " sigma=sigma,\n", + " learning_rate=learning_rate, \n", + " neighborhood_function=ngb_function,\n", + " topology=topology,\n", + " activation_distance=activation_distance,\n", + " random_seed=None\n", + " )\n", + " \n", + " # initialize SOM\n", + " if init=='pca':\n", + " som.pca_weights_init(X)\n", + " else:\n", + " som.random_weights_init(X)\n", + " # train som\n", + " if train=='random':\n", + " som.train_random(X,iterations,verbose=False)\n", + " else:\n", + " som.train_batch(X,iterations,verbose=False)\n", + " \n", + " # remember to use the same parameters as you are using out of the tuning function\n", + " \n", + " # use QE as a measure of best model\n", + " loss = som.quantization_error(X)\n", + " return loss\n", + " \n", + "### Storing the results of every iteration \n", + "trials = Trials()\n", + "MAX_EVALS = 20\n", + "\n", + "# Optimize\n", + "best = fmin(fn=som_fn,\n", + " space=space,\n", + " algo=tpe.suggest,\n", + " max_evals=MAX_EVALS,\n", + " trials=trials)\n", + "\n", + "\n", + "### best will the return the the best hyperparameter set\n", + "print('best: {}'.format(best))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", + " [ 0 / 10000 ] 0% - ? it/s\r", + " [ 0 / 10000 ] 0% - ? it/s\r", + " [ 1 / 10000 ] 0% - 0:00:06 left \r", + " [ 2 / 10000 ] 0% - 0:00:05 left \r", + " [ 3 / 10000 ] 0% - 0:00:04 left \r", + " [ 4 / 10000 ] 0% - 0:00:04 left \r", + " [ 5 / 10000 ] 0% - 0:00:04 left \r", + " [ 6 / 10000 ] 0% - 0:00:04 left \r", + " [ 7 / 10000 ] 0% - 0:00:04 left \r", + " [ 8 / 10000 ] 0% - 0:00:04 left \r", + " [ 9 / 10000 ] 0% - 0:00:04 left \r", + " [ 10 / 10000 ] 0% - 0:00:04 left \r", + " [ 11 / 10000 ] 0% - 0:00:04 left \r", + " [ 12 / 10000 ] 0% - 0:00:04 left \r", + " [ 13 / 10000 ] 0% - 0:00:04 left \r", + " [ 14 / 10000 ] 0% - 0:00:04 left \r", + " [ 15 / 10000 ] 0% - 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left \r", + " [ 10000 / 10000 ] 100% - 0:00:00 left \n", + " quantization error: 27.748766109556758\n" + ] + } + ], + "source": [ + "# Run SOM with optmized values\n", + "som = MiniSom(x=x,y=y,input_len=input_len,\n", + " sigma=best['sigma'],learning_rate=best['learning_rate'],\n", + " neighborhood_function=ngb_function,\n", + " topology=topology,\n", + " activation_distance=activation_distance,\n", + " random_seed=None)\n", + "# init som\n", + "if init=='pca':\n", + " som.pca_weights_init(X)\n", + "else:\n", + " som.random_weights_init(X)\n", + "weights2 = som.get_weights() \n", + "# train som\n", + "if train=='random':\n", + " som.train_random(X,iterations,verbose=True)\n", + "else:\n", + " som.train_batch(X,iterations,verbose=True)\n", + "\n", + "qnt2 = som.quantization(X)\n", + "\n", + "# extract clusters of winning neurons:\n", + "# each neuron represents a cluster\n", + "winner_coordinates = np.array([som.winner(x) for x in X]).T\n", + "# with np.ravel_multi_index we convert the bidimensional\n", + "# coordinates to a monodimensional index\n", + "cluster_index2 = np.ravel_multi_index(winner_coordinates, (x,y))\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot clusters\n", + "plt.figure(figsize=(15, 5))\n", + "plt.subplot(121)\n", + "plt.title('Clusters \\n default parameters')\n", + "plt.pcolor(ds.lon,ds.lat,cluster_index1.reshape(dimlat,dimlon),\n", + " vmin=0,vmax=x*y,cmap='tab10');\n", + "\n", + "plt.subplot(122)\n", + "plt.title('Clusters \\n optimized parameters')\n", + "plt.pcolor(ds.lon,ds.lat,cluster_index2.reshape(dimlat,dimlon),\n", + " vmin=0,vmax=x*y,cmap='tab10');\n", + "\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From 8577aab9d14a50c04ed8fa24eb02bdc7778941ba Mon Sep 17 00:00:00 2001 From: carocamargo <47150926+carocamargo@users.noreply.github.com> Date: Mon, 15 Nov 2021 16:15:48 +0100 Subject: [PATCH 4/4] update spatio-temporal example --- .../SOM-spatiotemporal_climate_example.ipynb | 42 +++++++++++++++++-- 1 file changed, 39 insertions(+), 3 deletions(-) diff --git a/examples/SOM-spatiotemporal_climate_example.ipynb b/examples/SOM-spatiotemporal_climate_example.ipynb index eafaa25..b562aa4 100644 --- a/examples/SOM-spatiotemporal_climate_example.ipynb +++ b/examples/SOM-spatiotemporal_climate_example.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -39,7 +39,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -125,6 +125,13 @@ "ds.Tair.plot()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Histogram plot of air temperature. Data seems to have a skewed distribution (not normally distributed)" + ] + }, { "cell_type": "code", "execution_count": 5, @@ -158,6 +165,13 @@ "ds.Tair.isel(time=1).plot()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Plot of Air temperature at the first measurement (jan 2013). The difference in air temperature over land and ocean is clear, with the shape of North America visible in the plot. Note: temperature is given in degrees Kelvin. " + ] + }, { "cell_type": "code", "execution_count": 6, @@ -197,6 +211,13 @@ ")\n" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Monthly mean air temperature. Visible increase of temperature during the summer months (month 6-9 (jun-sept, summer in North Hermisphere)), and decrease of temperature during winter. " + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -281,7 +302,15 @@ " # vmin=-300,vmax=300\n", " )\n", "plt.colorbar()\n", - "plt.title('Mean Air Temperature')" + "plt.title('Mean Air Temperature')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Mean air temperature anomaly ver the years 2013 and 2014. Data is normalized to have 1 unit standard deviation. " ] }, { @@ -10405,6 +10434,13 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "On the right we have the original plot, and on the left the learned colors from SOM quantizaton" + ] + }, { "cell_type": "markdown", "metadata": {},