| /dports/math/octave-forge-statistics/statistics-1.4.3/inst/ |
| H A D | squareform.m | 47 function y = squareform (x, method) function
72 warning ("squareform:symmetric",
101 %!assert (squareform (v), m)
102 %!assert (squareform (squareform (v)), v)
103 %!assert (squareform (m), v)
106 %!assert (squareform (v'), m)
109 %!assert (squareform (1), [0 1;1 0])
110 %!assert (squareform (1, "tomatrix"), [0 1; 1 0])
111 %!assert (squareform (0, "tovector"), zeros (1, 0))
119 %! assert (squareform (f (v)), f (m))
[all …]
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| H A D | silhouette.m | 105 distMatrix = squareform (metric);
125 distMatrix = squareform (pdist (X, metric, varargin{:}));
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| H A D | cmdscale.m | 92 D = squareform (D);
148 %!assert(norm(pdist(cmdscale(squareform(D)))), norm(D), sqrt(eps))
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| /dports/math/py-fastcluster/fastcluster-1.2.4/tests/ |
| H A D | vectortest.py | 13 from scipy.spatial.distance import pdist, squareform
41 DD = squareform(D)
43 D = squareform(DD)
126 Ds = squareform(D)
144 format(Z2[i,2], gmin,i), squareform(D))
147 raise AssertionError('Negative index i1.', squareform(D))
149 raise AssertionError('Negative index i2.', squareform(D))
151 raise AssertionError('Convention violated.', squareform(D))
160 squareform(D))
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| H A D | test.py | 11 from scipy.spatial.distance import pdist, squareform
45 Ds = squareform(D)
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| /dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/stats/ |
| H A D | dist_dependence_measures.py | 21 from scipy.spatial.distance import pdist, squareform
280 x_dist = squareform(pdist(x, "euclidean"))
355 a = x_dist if x_dist is not None else squareform(pdist(x, "euclidean"))
356 b = y_dist if y_dist is not None else squareform(pdist(y, "euclidean"))
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| /dports/math/py-seriate/seriate-1.1.2/ |
| H A D | seriate.py | 92 squareform = len(dists.shape) == 2
93 if squareform:
114 if squareform:
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| H A D | test_seriate.py | 4 from scipy.spatial.distance import pdist, squareform
19 dists = squareform(pdist(self.elements))
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| /dports/science/py-skrebate/skrebate-0.62/skrebate/ |
| H A D | relieff.py | 291 from scipy.spatial.distance import pdist, squareform
310 return squareform(pdist(self._X, metric='hamming'))
312 d_dist = squareform(pdist(xd, metric='hamming'))
314 c_dist = squareform(pdist(pre_normalize(xc), metric='cityblock'))
319 return squareform(pdist(pre_normalize(xc), metric='cityblock'))
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| /dports/science/py-scikit-learn/scikit-learn-1.0.2/examples/inspection/ |
| H A D | plot_permutation_importance_multicollinear.py | 27 from scipy.spatial.distance import squareform
93 dist_linkage = hierarchy.ward(squareform(distance_matrix))
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| /dports/misc/orange3/orange3-3.29.1/Orange/projection/ |
| H A D | freeviz.py | 56 def squareform(cls, d): member in FreeViz
73 return scipy.spatial.distance.squareform(d, checks=False)
156 diff_norm = cls.squareform(embedding_dist)
163 forces = cls.squareform(forces)
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| /dports/misc/orange3/orange3-3.29.1/Orange/tests/ |
| H A D | test_clustering_hierarchical.py | 35 matrix = hierarchical.squareform(dist, mode="lower")
94 hierarchical.squareform(dist, mode="lower"), m)
98 hierarchical.squareform(dist, mode="upper"), m)
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| /dports/science/py-scipy/scipy-1.7.1/scipy/spatial/tests/ |
| H A D | test_distance.py | 106 _ytdist = squareform(_tdist)
1680 rA = squareform(A)
1716 A = squareform(Y)
1845 D = squareform(y)
1852 D = squareform(y)
1859 D = squareform(y)
1865 D = squareform(y)
1875 D = squareform(y)
1880 D = squareform(y)
1885 D = squareform(y)
[all …]
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| /dports/science/py-scipy/scipy-1.7.1/scipy/interpolate/ |
| H A D | rbf.py | 50 from scipy.spatial.distance import cdist, pdist, squareform
272 r = squareform(pdist(self.xi.T, self.norm)) # Pairwise norm
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| /dports/biology/py-scikit-bio/scikit-bio-0.5.6/skbio/stats/distance/ |
| H A D | _base.py | 16 from scipy.spatial.distance import squareform
101 data = squareform(data, force='tomatrix', checks=False)
1006 return squareform(self._data, force='tovector', checks=False)
1045 return squareform(permuted, force='tovector', checks=False)
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| /dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/gaussian_process/ |
| H A D | kernels.py | 29 from scipy.spatial.distance import pdist, cdist, squareform
1539 K = squareform(K)
1552 K_gradient = (K * squareform(dists))[:, :, np.newaxis]
1717 K = squareform(K)
1732 D = squareform(dists ** 2)[:, :, np.newaxis]
1890 dists = squareform(pdist(X, metric="sqeuclidean"))
2035 dists = squareform(pdist(X, metric="euclidean"))
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| /dports/science/py-obspy/obspy-1.2.2/misc/docs/source/tutorial/code_snippets/ |
| H A D | hierarchical_clustering.py | 22 dissimilarity = distance.squareform(dissimilarity)
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| H A D | hierarchical_clustering.rst | 41 >>> dissimilarity = distance.squareform(dissimilarity)
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| /dports/graphics/py-scikit-image/scikit-image-0.19.0/skimage/segmentation/ |
| H A D | slic_superpixels.py | 7 from scipy.spatial.distance import pdist, squareform
66 dist = squareform(pdist(centroids))
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| /dports/math/py-networkx/networkx-2.6.3/examples/algorithms/ |
| H A D | plot_blockmodel.py | 41 Y = distance.squareform(distances)
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| /dports/science/py-pymatgen/pymatgen-2022.0.15/pymatgen/core/ |
| H A D | interface.py | 14 from scipy.spatial.distance import squareform
479 condensed_m = squareform(dist_matrix)
521 condensed_m = squareform(dist_matrix)
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| /dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/manifold/ |
| H A D | _t_sne.py | 16 from scipy.spatial.distance import squareform
65 P = np.maximum(squareform(P) / sum_P, MACHINE_EPSILON)
193 PQd = squareform((P - Q) * dist)
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| /dports/math/octave-forge-statistics/statistics-1.4.3/ |
| H A D | INDEX.in | 122 squareform
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| /dports/math/py-spopt/spopt-0.2.1/spopt/region/ |
| H A D | maxp.py | 21 from scipy.spatial.distance import pdist, squareform
92 distance_matrix = squareform(pdist(attr, metric="cityblock"))
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| /dports/science/py-scoria/scoria-1.0.5/scoria/dumbpy/ |
| H A D | __init__.py | 166 from scipy.spatial.distance import squareform
|