From abb9aa0a1503c89e8837492157a02a3d494717ac Mon Sep 17 00:00:00 2001 From: Marcos Duarte Date: Wed, 2 Aug 2023 01:56:49 -0300 Subject: [PATCH] similarity --- functions/similarity.py | 21 +-- notebooks/Similarity.ipynb | 309 +++++++++++++++++++++---------------- 2 files changed, 188 insertions(+), 142 deletions(-) diff --git a/functions/similarity.py b/functions/similarity.py index 1104fd6..8b72999 100644 --- a/functions/similarity.py +++ b/functions/similarity.py @@ -88,7 +88,7 @@ def similarity(y: np.ndarray, axis1: int=0, axis2: int=1, threshold: float=0, recursive :bool, optional (default = True) Whether to calculate similarity `metric` recursevely, updating the score calculation each time a vector is discarded. - With `recursive` True, the output `score_all` will contain at each row + With `recursive` True, the output `scores` will contain at each row the updated score values for the used `metric` for each data vector. The first row will contain the calculated original scores before any vector was discarded. On the subsequent rows, the vector discarded is @@ -96,7 +96,7 @@ def similarity(y: np.ndarray, axis1: int=0, axis2: int=1, threshold: float=0, The last row will contain the updated scores of the final vectors kept. With the `recursive` False, the comparison of score values with `threshold` are made only once and vectors are discarded accordingly at once. - In this case, the output `score_all` will contain only two rows, the + In this case, the output `scores` will contain only two rows, the first row will contain the calculated original scores before any vectors were discarded. At the second row, the vectors discarded are represented with NaN values and the kept vectors by their updated scores. @@ -105,7 +105,7 @@ def similarity(y: np.ndarray, axis1: int=0, axis2: int=1, threshold: float=0, msg : bool, optional (default = True) Whether to print some messages. kwargs : optional - Options for the metric function (see mse function). + Options for the metric function (e.g., see `_mse` function). Returns ------- @@ -115,8 +115,9 @@ def similarity(y: np.ndarray, axis1: int=0, axis2: int=1, threshold: float=0, Indexes of kept vectors. inotkept : numpy array Indexes of not kept (discarded) vectors. - score_all : numpy array - Mean Squared Error values. + scores : 2-D numpy array + Metric score values of each vector (as columns) for each round of + vector selection (one row per round plus the final values). References ---------- @@ -135,7 +136,7 @@ def similarity(y: np.ndarray, axis1: int=0, axis2: int=1, threshold: float=0, >>> p = rng.integers(20) >>> y[j:j+p, i] = y[j:j+p, i] + rng.integers(10) - 5 >>> y[:, i] += rng.integers(4) - 2 - >>> ys, ikept, inotkept, score_all = similarity(y) + >>> ys, ikept, inotkept, scores = similarity(y) >>> fig, axs = plt.subplots(2, 1, sharex=True) >>> axs[0].plot(y, label=list(range(n))) >>> axs[0].legend(loc=(1.01, 0)) @@ -154,7 +155,7 @@ def similarity(y: np.ndarray, axis1: int=0, axis2: int=1, threshold: float=0, raise ValueError('The input array must be at least a 2-D array.') y = y.copy() score = metric(y, axis1=axis1, axis2=axis2, **kwargs) - score_all = np.atleast_2d(score) + scores = np.atleast_2d(score) ikept = np.where(~np.isnan(score))[0] # indexes of kept vectors # indexes of not kept (discarded) vectors inotkept = np.where(np.isnan(score))[0] @@ -177,7 +178,7 @@ def similarity(y: np.ndarray, axis1: int=0, axis2: int=1, threshold: float=0, inotkept = np.r_[inotkept, idx[idx2[-(y.shape[axis2] - nmin):]][::-1]] y.swapaxes(0, axis2)[inotkept, ...] = np.nan score = metric(y, axis1=axis1, axis2=axis2, **kwargs) - score_all = np.vstack((score_all, score)) + scores = np.vstack((scores, score)) elif msg: print( f'Number of vectors to discard is greater than number to keep ({nkept}).') @@ -186,7 +187,7 @@ def similarity(y: np.ndarray, axis1: int=0, axis2: int=1, threshold: float=0, inotkept = np.r_[inotkept, idx[nkept-1]] y.swapaxes(0, axis2)[inotkept[-1], ...] = np.nan score = metric(y, axis1=axis1, axis2=axis2, **kwargs) - score_all = np.vstack((score_all, score)) + scores = np.vstack((scores, score)) idx = np.argsort(score) score = score[idx] nkept = nkept - 1 @@ -201,4 +202,4 @@ def similarity(y: np.ndarray, axis1: int=0, axis2: int=1, threshold: float=0, print( f'Vectors discarded (in dimension {axis2}, n={len(inotkept)}): {inotkept}') - return y, ikept, inotkept, score_all + return y, ikept, inotkept, scores diff --git a/notebooks/Similarity.ipynb b/notebooks/Similarity.ipynb index 130ae7e..fb2db35 100644 --- a/notebooks/Similarity.ipynb +++ b/notebooks/Similarity.ipynb @@ -30,7 +30,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Last updated: 2023-08-01 04:56:58\n", + "Last updated: 2023-08-01 23:05:49\n", "\n", "Python implementation: CPython\n", "Python version : 3.11.4\n", @@ -44,8 +44,8 @@ "CPU cores : 16\n", "Architecture: 64bit\n", "\n", - "numpy : 1.25.1\n", "matplotlib: 3.7.2\n", + "numpy : 1.25.1\n", "sys : 3.11.4 | packaged by conda-forge | (main, Jun 10 2023, 18:08:17) [GCC 12.2.0]\n", "\n" ] @@ -76,7 +76,7 @@ "text": [ "Help on function similarity in module similarity:\n", "\n", - "similarity(y: numpy.ndarray, axis1: int = 0, axis2: int = 1, threshold: float = 0, nmin: int = 3, recursive: bool = True, metric: = , msg: bool = True, **kwargs: ) -> tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray, numpy.ndarray]\n", + "similarity(y: numpy.ndarray, axis1: int = 0, axis2: int = 1, threshold: float = 0, nmin: int = 3, recursive: bool = True, metric: = , msg: bool = True, **kwargs: ) -> tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray, numpy.ndarray]\n", " Select data vectors by similarity using a metric score.\n", " \n", " Parameters\n", @@ -100,7 +100,7 @@ " recursive :bool, optional (default = True)\n", " Whether to calculate similarity `metric` recursevely, updating the score\n", " calculation each time a vector is discarded.\n", - " With `recursive` True, the output `score_all` will contain at each row\n", + " With `recursive` True, the output `scores` will contain at each row\n", " the updated score values for the used `metric` for each data vector.\n", " The first row will contain the calculated original scores before any\n", " vector was discarded. On the subsequent rows, the vector discarded is\n", @@ -108,7 +108,7 @@ " The last row will contain the updated scores of the final vectors kept.\n", " With the `recursive` False, the comparison of score values with `threshold`\n", " are made only once and vectors are discarded accordingly at once.\n", - " In this case, the output `score_all` will contain only two rows, the\n", + " In this case, the output `scores` will contain only two rows, the\n", " first row will contain the calculated original scores before any vectors\n", " were discarded. At the second row, the vectors discarded are represented\n", " with NaN values and the kept vectors by their updated scores.\n", @@ -117,7 +117,7 @@ " msg : bool, optional (default = True)\n", " Whether to print some messages.\n", " kwargs : optional\n", - " Options for the metric function (see mse function).\n", + " Options for the metric function (e.g., see `_mse` function).\n", " \n", " Returns\n", " -------\n", @@ -127,8 +127,9 @@ " Indexes of kept vectors.\n", " inotkept : numpy array\n", " Indexes of not kept (discarded) vectors.\n", - " score_all : numpy array\n", - " Mean Squared Error values.\n", + " scores : 2-D numpy array\n", + " Metric score values of each vector (as columns) for each round of\n", + " vector selection (one row per round plus the final values).\n", " \n", " References\n", " ----------\n", @@ -147,7 +148,7 @@ " >>> p = rng.integers(20)\n", " >>> y[j:j+p, i] = y[j:j+p, i] + rng.integers(10) - 5\n", " >>> y[:, i] += rng.integers(4) - 2\n", - " >>> ys, ikept, inotkept, score_all = similarity(y)\n", + " >>> ys, ikept, inotkept, scores = similarity(y)\n", " >>> fig, axs = plt.subplots(2, 1, sharex=True)\n", " >>> axs[0].plot(y, label=list(range(n)))\n", " >>> axs[0].legend(loc=(1.01, 0))\n", @@ -196,12 +197,12 @@ "output_type": "stream", "text": [ "Calculated threshold: 3.0\n", - "Vectors discarded (in dimension 1, n=5): [4 0 6 2 8]\n" + "Vectors discarded (in dimension 1, n=5): [4 2 6 8 0]\n" ] }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -241,13 +242,13 @@ "output_type": "stream", "text": [ "Calculated threshold: 3.0\n", - "Vectors discarded (in dimension 1, n=5): [4 0 6 2 8]\n" + "Vectors discarded (in dimension 1, n=5): [4 2 6 8 0]\n" ] } ], "source": [ - "ys, ikept, inotkept, score_all = similarity(y, threshold=0, nmin=3, recursive=True, metric=mse_,\n", - " msg=1, central=np.nanmedian, normalization=np.nanmedian)" + "ys, ikept, inotkept, scores = similarity(y, threshold=0, nmin=3, recursive=True, metric=mse_,\n", + " msg=1, central=np.nanmedian, normalization=np.nanmedian)" ] }, { @@ -298,7 +299,7 @@ { "data": { "text/plain": [ - "array([4, 0, 6, 2, 8])" + "array([4, 2, 6, 8, 0])" ] }, "execution_count": 7, @@ -318,18 +319,18 @@ { "data": { "text/plain": [ - "array([[ 7.194, 0.333, 4.295, 0.364, 22.617, 0.495, 4.866, 0.296,\n", - " 1.505, 0.432],\n", - " [10.858, 0.675, 6.247, 0.72 , nan, 1. , 7.237, 0.657,\n", - " 2.668, 0.916],\n", - " [ nan, 0.736, 9.218, 0.807, nan, 1.063, 10.438, 0.651,\n", - " 3.267, 0.937],\n", - " [ nan, 0.939, 13.044, 0.941, nan, 1.334, nan, 0.744,\n", - " 3.981, 1. ],\n", - " [ nan, 1.006, nan, 0.994, nan, 1.323, nan, 0.734,\n", - " 4.391, 0.942],\n", - " [ nan, 1.057, nan, 1. , nan, 1.355, nan, 0.655,\n", - " nan, 0.909]])" + "array([[ 1.764, 0.205, 14.473, 0.17 , 18.362, 0.209, 9.315, 0.207,\n", + " 2.828, 0.236],\n", + " [ 7.232, 0.786, 59.048, 0.691, nan, 1. , 36.248, 0.794,\n", + " 9.583, 0.914],\n", + " [ 7.488, 0.817, nan, 0.833, nan, 1.07 , 36.797, 0.856,\n", + " 8.355, 0.93 ],\n", + " [ 8.527, 0.901, nan, 0.878, nan, 1.062, nan, 0.807,\n", + " 10.089, 1. ],\n", + " [ 9.793, 1.008, nan, 0.845, nan, 0.992, nan, 0.921,\n", + " nan, 1.069],\n", + " [ nan, 1.124, nan, 0.815, nan, 0.922, nan, 1.024,\n", + " nan, 1. ]])" ] }, "execution_count": 8, @@ -338,7 +339,49 @@ } ], "source": [ - "score_all" + "scores" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 1.764, 0.205, 14.473, 0.17 , 18.362, 0.209, 9.315, 0.207,\n", + " 2.828, 0.236])" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scores[0, :]" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 7.232, 0.786, 59.048, 0.691, nan, 1. , 36.248, 0.794,\n", + " 9.583, 0.914])" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scores[1]" ] }, { @@ -350,7 +393,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 11, "metadata": { "editable": true, "slideshow": { @@ -363,7 +406,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "2.21 ms ± 37.3 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" + "2.23 ms ± 11.7 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" ] } ], @@ -374,7 +417,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -382,7 +425,7 @@ "text/plain": [ "Timer unit: 1e-09 s\n", "\n", - "Total time: 0.00565326 s\n", + "Total time: 0.0057253 s\n", "File: /home/marcos/adrive/Python/BMC/notebooks/./../functions/similarity.py\n", "Function: similarity at line 64\n", "\n", @@ -415,7 +458,7 @@ " 88 recursive :bool, optional (default = True)\n", " 89 Whether to calculate similarity `metric` recursevely, updating the score\n", " 90 calculation each time a vector is discarded.\n", - " 91 With `recursive` True, the output `score_all` will contain at each row\n", + " 91 With `recursive` True, the output `scores` will contain at each row\n", " 92 the updated score values for the used `metric` for each data vector.\n", " 93 The first row will contain the calculated original scores before any\n", " 94 vector was discarded. On the subsequent rows, the vector discarded is\n", @@ -423,7 +466,7 @@ " 96 The last row will contain the updated scores of the final vectors kept.\n", " 97 With the `recursive` False, the comparison of score values with `threshold`\n", " 98 are made only once and vectors are discarded accordingly at once.\n", - " 99 In this case, the output `score_all` will contain only two rows, the\n", + " 99 In this case, the output `scores` will contain only two rows, the\n", " 100 first row will contain the calculated original scores before any vectors\n", " 101 were discarded. At the second row, the vectors discarded are represented\n", " 102 with NaN values and the kept vectors by their updated scores.\n", @@ -432,7 +475,7 @@ " 105 msg : bool, optional (default = True)\n", " 106 Whether to print some messages.\n", " 107 kwargs : optional\n", - " 108 Options for the metric function (see mse function).\n", + " 108 Options for the metric function (e.g., see `_mse` function).\n", " 109 \n", " 110 Returns\n", " 111 -------\n", @@ -442,93 +485,94 @@ " 115 Indexes of kept vectors.\n", " 116 inotkept : numpy array\n", " 117 Indexes of not kept (discarded) vectors.\n", - " 118 score_all : numpy array\n", - " 119 Mean Squared Error values.\n", - " 120 \n", - " 121 References\n", - " 122 ----------\n", - " 123 .. [1] https://nbviewer.org/github/BMClab/BMC/blob/master/notebooks/Similarity.ipynb\n", - " 124 \n", - " 125 Examples\n", - " 126 --------\n", - " 127 >>> import numpy as np\n", - " 128 >>> import matplotlib.pyplot as plt\n", - " 129 >>> rng = np.random.default_rng()\n", - " 130 >>> t, n = 100, 10\n", - " 131 >>> y = rng.random((t, n))\n", - " 132 >>> y += np.atleast_2d(2*np.sin(2*np.pi*np.linspace(0, 1, t))).T\n", - " 133 >>> for i in range(0, n, 2):\n", - " 134 >>> j = rng.integers(t-20)\n", - " 135 >>> p = rng.integers(20)\n", - " 136 >>> y[j:j+p, i] = y[j:j+p, i] + rng.integers(10) - 5\n", - " 137 >>> y[:, i] += rng.integers(4) - 2\n", - " 138 >>> ys, ikept, inotkept, score_all = similarity(y)\n", - " 139 >>> fig, axs = plt.subplots(2, 1, sharex=True)\n", - " 140 >>> axs[0].plot(y, label=list(range(n)))\n", - " 141 >>> axs[0].legend(loc=(1.01, 0))\n", - " 142 >>> axs[1].plot(ys, label= ikept.tolist())\n", - " 143 >>> axs[1].legend(loc=(1.01, 0))\n", - " 144 >>> plt.show()\n", - " 145 \n", - " 146 Version history\n", - " 147 ---------------\n", - " 148 '1.0.0':\n", - " 149 First release version\n", - " 150 \"\"\"\n", - " 151 \n", + " 118 scores : 2-D numpy array\n", + " 119 Metric score values of each vector (as columns) for each round of\n", + " 120 vector selection (one row per round plus the final values).\n", + " 121 \n", + " 122 References\n", + " 123 ----------\n", + " 124 .. [1] https://nbviewer.org/github/BMClab/BMC/blob/master/notebooks/Similarity.ipynb\n", + " 125 \n", + " 126 Examples\n", + " 127 --------\n", + " 128 >>> import numpy as np\n", + " 129 >>> import matplotlib.pyplot as plt\n", + " 130 >>> rng = np.random.default_rng()\n", + " 131 >>> t, n = 100, 10\n", + " 132 >>> y = rng.random((t, n))\n", + " 133 >>> y += np.atleast_2d(2*np.sin(2*np.pi*np.linspace(0, 1, t))).T\n", + " 134 >>> for i in range(0, n, 2):\n", + " 135 >>> j = rng.integers(t-20)\n", + " 136 >>> p = rng.integers(20)\n", + " 137 >>> y[j:j+p, i] = y[j:j+p, i] + rng.integers(10) - 5\n", + " 138 >>> y[:, i] += rng.integers(4) - 2\n", + " 139 >>> ys, ikept, inotkept, scores = similarity(y)\n", + " 140 >>> fig, axs = plt.subplots(2, 1, sharex=True)\n", + " 141 >>> axs[0].plot(y, label=list(range(n)))\n", + " 142 >>> axs[0].legend(loc=(1.01, 0))\n", + " 143 >>> axs[1].plot(ys, label= ikept.tolist())\n", + " 144 >>> axs[1].legend(loc=(1.01, 0))\n", + " 145 >>> plt.show()\n", + " 146 \n", + " 147 Version history\n", + " 148 ---------------\n", + " 149 '1.0.0':\n", + " 150 First release version\n", + " 151 \"\"\"\n", " 152 \n", - " 153 1 1093.0 1093.0 0.0 if y.ndim < 2:\n", - " 154 raise ValueError('The input array must be at least a 2-D array.')\n", - " 155 1 6923.0 6923.0 0.1 y = y.copy()\n", - " 156 1 1794376.0 1794376.0 31.7 score = metric(y, axis1=axis1, axis2=axis2, **kwargs)\n", - " 157 1 6547.0 6547.0 0.1 score_all = np.atleast_2d(score)\n", - " 158 1 4045.0 4045.0 0.1 ikept = np.where(~np.isnan(score))[0] # indexes of kept vectors\n", - " 159 # indexes of not kept (discarded) vectors\n", - " 160 1 1802.0 1802.0 0.0 inotkept = np.where(np.isnan(score))[0]\n", - " 161 1 6958.0 6958.0 0.1 idx = np.argsort(score)\n", - " 162 1 738.0 738.0 0.0 score = score[idx]\n", - " 163 1 2942.0 2942.0 0.1 nkept = np.count_nonzero(~np.isnan(score)) # number of kept vectors\n", - " 164 1 265.0 265.0 0.0 if nkept < 3:\n", - " 165 raise ValueError('The input array must have at least 3 valid vectors.')\n", - " 166 1 181.0 181.0 0.0 if nmin < 0:\n", - " 167 nmin = np.max([3, nkept + nmin])\n", - " 168 1 137.0 137.0 0.0 if threshold == 0:\n", - " 169 1 215939.0 215939.0 3.8 q = np.nanquantile(a=score, q=[.25, .50, .75])\n", - " 170 1 14949.0 14949.0 0.3 threshold = np.min([q[1] + 1.5*(q[2]-q[0]), score[-2], 3])\n", - " 171 1 215.0 215.0 0.0 if msg:\n", - " 172 print(f'Calculated threshold: {threshold}')\n", - " 173 1 193.0 193.0 0.0 if not recursive: # discard all vectors at once\n", - " 174 idx2 = np.nonzero(score > threshold)[0] # vectors to discard\n", - " 175 if len(idx2) > 0:\n", - " 176 if nkept > nmin: # keep at least nmin vectors\n", - " 177 inotkept = np.r_[inotkept, idx[idx2[-(y.shape[axis2] - nmin):]][::-1]]\n", - " 178 y.swapaxes(0, axis2)[inotkept, ...] = np.nan\n", - " 179 score = metric(y, axis1=axis1, axis2=axis2, **kwargs)\n", - " 180 score_all = np.vstack((score_all, score))\n", - " 181 elif msg:\n", - " 182 print(\n", - " 183 f'Number of vectors to discard is greater than number to keep ({nkept}).')\n", - " 184 else: # discard vectors with largest updated score one by one\n", - " 185 5 4562.0 912.4 0.1 while nkept > nmin and score[nkept-1] > threshold:\n", - " 186 5 142162.0 28432.4 2.5 inotkept = np.r_[inotkept, idx[nkept-1]]\n", - " 187 5 14617.0 2923.4 0.3 y.swapaxes(0, axis2)[inotkept[-1], ...] = np.nan\n", - " 188 5 3207828.0 641565.6 56.7 score = metric(y, axis1=axis1, axis2=axis2, **kwargs)\n", - " 189 5 63765.0 12753.0 1.1 score_all = np.vstack((score_all, score))\n", - " 190 5 27135.0 5427.0 0.5 idx = np.argsort(score)\n", - " 191 5 3637.0 727.4 0.1 score = score[idx]\n", - " 192 5 1270.0 254.0 0.0 nkept = nkept - 1\n", - " 193 1 194.0 194.0 0.0 if msg and nkept == nmin and score[nkept-1] > threshold:\n", - " 194 print(\n", - " 195 f'Number of vectors to discard is greater than number to keep ({nkept}).')\n", - " 196 \n", - " 197 1 461.0 461.0 0.0 if len(inotkept):\n", - " 198 1 124110.0 124110.0 2.2 ikept = np.setdiff1d(ikept, inotkept)\n", - " 199 1 5800.0 5800.0 0.1 y = y.swapaxes(0, axis2)[ikept, ...].swapaxes(0, axis2)\n", - " 200 1 183.0 183.0 0.0 if msg:\n", - " 201 print(\n", - " 202 f'Vectors discarded (in dimension {axis2}, n={len(inotkept)}): {inotkept}')\n", - " 203 \n", - " 204 1 232.0 232.0 0.0 return y, ikept, inotkept, score_all" + " 153 \n", + " 154 1 1318.0 1318.0 0.0 if y.ndim < 2:\n", + " 155 raise ValueError('The input array must be at least a 2-D array.')\n", + " 156 1 7047.0 7047.0 0.1 y = y.copy()\n", + " 157 1 1132223.0 1132223.0 19.8 score = metric(y, axis1=axis1, axis2=axis2, **kwargs)\n", + " 158 1 7063.0 7063.0 0.1 scores = np.atleast_2d(score)\n", + " 159 1 3893.0 3893.0 0.1 ikept = np.where(~np.isnan(score))[0] # indexes of kept vectors\n", + " 160 # indexes of not kept (discarded) vectors\n", + " 161 1 1614.0 1614.0 0.0 inotkept = np.where(np.isnan(score))[0]\n", + " 162 1 6628.0 6628.0 0.1 idx = np.argsort(score)\n", + " 163 1 760.0 760.0 0.0 score = score[idx]\n", + " 164 1 3145.0 3145.0 0.1 nkept = np.count_nonzero(~np.isnan(score)) # number of kept vectors\n", + " 165 1 332.0 332.0 0.0 if nkept < 3:\n", + " 166 raise ValueError('The input array must have at least 3 valid vectors.')\n", + " 167 1 220.0 220.0 0.0 if nmin < 0:\n", + " 168 nmin = np.max([3, nkept + nmin])\n", + " 169 1 157.0 157.0 0.0 if threshold == 0:\n", + " 170 1 380408.0 380408.0 6.6 q = np.nanquantile(a=score, q=[.25, .50, .75])\n", + " 171 1 15685.0 15685.0 0.3 threshold = np.min([q[1] + 1.5*(q[2]-q[0]), score[-2], 3])\n", + " 172 1 211.0 211.0 0.0 if msg:\n", + " 173 print(f'Calculated threshold: {threshold}')\n", + " 174 1 207.0 207.0 0.0 if not recursive: # discard all vectors at once\n", + " 175 idx2 = np.nonzero(score > threshold)[0] # vectors to discard\n", + " 176 if len(idx2) > 0:\n", + " 177 if nkept > nmin: # keep at least nmin vectors\n", + " 178 inotkept = np.r_[inotkept, idx[idx2[-(y.shape[axis2] - nmin):]][::-1]]\n", + " 179 y.swapaxes(0, axis2)[inotkept, ...] = np.nan\n", + " 180 score = metric(y, axis1=axis1, axis2=axis2, **kwargs)\n", + " 181 scores = np.vstack((scores, score))\n", + " 182 elif msg:\n", + " 183 print(\n", + " 184 f'Number of vectors to discard is greater than number to keep ({nkept}).')\n", + " 185 else: # discard vectors with largest updated score one by one\n", + " 186 5 5124.0 1024.8 0.1 while nkept > nmin and score[nkept-1] > threshold:\n", + " 187 5 146978.0 29395.6 2.6 inotkept = np.r_[inotkept, idx[nkept-1]]\n", + " 188 5 15675.0 3135.0 0.3 y.swapaxes(0, axis2)[inotkept[-1], ...] = np.nan\n", + " 189 5 3683617.0 736723.4 64.3 score = metric(y, axis1=axis1, axis2=axis2, **kwargs)\n", + " 190 5 78161.0 15632.2 1.4 scores = np.vstack((scores, score))\n", + " 191 5 69102.0 13820.4 1.2 idx = np.argsort(score)\n", + " 192 5 4241.0 848.2 0.1 score = score[idx]\n", + " 193 5 1504.0 300.8 0.0 nkept = nkept - 1\n", + " 194 1 191.0 191.0 0.0 if msg and nkept == nmin and score[nkept-1] > threshold:\n", + " 195 print(\n", + " 196 f'Number of vectors to discard is greater than number to keep ({nkept}).')\n", + " 197 \n", + " 198 1 547.0 547.0 0.0 if len(inotkept):\n", + " 199 1 152143.0 152143.0 2.7 ikept = np.setdiff1d(ikept, inotkept)\n", + " 200 1 6691.0 6691.0 0.1 y = y.swapaxes(0, axis2)[ikept, ...].swapaxes(0, axis2)\n", + " 201 1 203.0 203.0 0.0 if msg:\n", + " 202 print(\n", + " 203 f'Vectors discarded (in dimension {axis2}, n={len(inotkept)}): {inotkept}')\n", + " 204 \n", + " 205 1 208.0 208.0 0.0 return y, ikept, inotkept, scores" ] }, "metadata": {}, @@ -548,7 +592,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -643,7 +687,7 @@ " recursive :bool, optional (default = True)\n", " Whether to calculate similarity `metric` recursevely, updating the score\n", " calculation each time a vector is discarded.\n", - " With `recursive` True, the output `score_all` will contain at each row\n", + " With `recursive` True, the output `scores` will contain at each row\n", " the updated score values for the used `metric` for each data vector.\n", " The first row will contain the calculated original scores before any\n", " vector was discarded. On the subsequent rows, the vector discarded is\n", @@ -651,7 +695,7 @@ " The last row will contain the updated scores of the final vectors kept.\n", " With the `recursive` False, the comparison of score values with `threshold`\n", " are made only once and vectors are discarded accordingly at once.\n", - " In this case, the output `score_all` will contain only two rows, the\n", + " In this case, the output `scores` will contain only two rows, the\n", " first row will contain the calculated original scores before any vectors\n", " were discarded. At the second row, the vectors discarded are represented\n", " with NaN values and the kept vectors by their updated scores.\n", @@ -660,7 +704,7 @@ " msg : bool, optional (default = True)\n", " Whether to print some messages.\n", " kwargs : optional\n", - " Options for the metric function (see mse function).\n", + " Options for the metric function (e.g., see `_mse` function).\n", "\n", " Returns\n", " -------\n", @@ -670,8 +714,9 @@ " Indexes of kept vectors.\n", " inotkept : numpy array\n", " Indexes of not kept (discarded) vectors.\n", - " score_all : numpy array\n", - " Mean Squared Error values.\n", + " scores : 2-D numpy array\n", + " Metric score values of each vector (as columns) for each round of\n", + " vector selection (one row per round plus the final values).\n", "\n", " References\n", " ----------\n", @@ -690,7 +735,7 @@ " >>> p = rng.integers(20)\n", " >>> y[j:j+p, i] = y[j:j+p, i] + rng.integers(10) - 5\n", " >>> y[:, i] += rng.integers(4) - 2\n", - " >>> ys, ikept, inotkept, score_all = similarity(y)\n", + " >>> ys, ikept, inotkept, scores = similarity(y)\n", " >>> fig, axs = plt.subplots(2, 1, sharex=True)\n", " >>> axs[0].plot(y, label=list(range(n)))\n", " >>> axs[0].legend(loc=(1.01, 0))\n", @@ -709,7 +754,7 @@ " raise ValueError('The input array must be at least a 2-D array.')\n", " y = y.copy()\n", " score = metric(y, axis1=axis1, axis2=axis2, **kwargs)\n", - " score_all = np.atleast_2d(score)\n", + " scores = np.atleast_2d(score)\n", " ikept = np.where(~np.isnan(score))[0] # indexes of kept vectors\n", " # indexes of not kept (discarded) vectors\n", " inotkept = np.where(np.isnan(score))[0]\n", @@ -732,7 +777,7 @@ " inotkept = np.r_[inotkept, idx[idx2[-(y.shape[axis2] - nmin):]][::-1]]\n", " y.swapaxes(0, axis2)[inotkept, ...] = np.nan\n", " score = metric(y, axis1=axis1, axis2=axis2, **kwargs)\n", - " score_all = np.vstack((score_all, score))\n", + " scores = np.vstack((scores, score))\n", " elif msg:\n", " print(\n", " f'Number of vectors to discard is greater than number to keep ({nkept}).')\n", @@ -741,7 +786,7 @@ " inotkept = np.r_[inotkept, idx[nkept-1]]\n", " y.swapaxes(0, axis2)[inotkept[-1], ...] = np.nan\n", " score = metric(y, axis1=axis1, axis2=axis2, **kwargs)\n", - " score_all = np.vstack((score_all, score))\n", + " scores = np.vstack((scores, score))\n", " idx = np.argsort(score)\n", " score = score[idx]\n", " nkept = nkept - 1\n", @@ -756,7 +801,7 @@ " print(\n", " f'Vectors discarded (in dimension {axis2}, n={len(inotkept)}): {inotkept}')\n", "\n", - " return y, ikept, inotkept, score_all\n" + " return y, ikept, inotkept, scores\n" ] }, {