| /dports/math/unuran/unuran-1.8.1/src/distr/ |
| H A D | cemp.c | 431 unur_distr_cemp_set_hist_bins( struct unur_distr *distr, const double *bins, int n_bins ) in unur_distr_cemp_set_hist_bins() argument
458 if (n_bins != (DISTR.n_hist+1)) { in unur_distr_cemp_set_hist_bins()
464 for( i=1; i<n_bins; i++ ) in unur_distr_cemp_set_hist_bins()
471 if (unur_distr_cemp_set_hist_domain(distr, bins[0], bins[n_bins-1]) != UNUR_SUCCESS) in unur_distr_cemp_set_hist_bins()
475 DISTR.hist_bins = _unur_xmalloc( n_bins * sizeof(double) ); in unur_distr_cemp_set_hist_bins()
479 memcpy( DISTR.hist_bins, bins, n_bins * sizeof(double) ); in unur_distr_cemp_set_hist_bins()
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| /dports/math/py-matplotlib/matplotlib-3.4.3/examples/images_contours_and_fields/ |
| H A D | image_transparency_blend.py | 30 n_bins = 100 variable
31 xx = np.linspace(xmin, xmax, n_bins)
32 yy = np.linspace(ymin, ymax, n_bins)
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| /dports/graphics/py-scikit-image/scikit-image-0.19.0/skimage/filters/rank/ |
| H A D | core_cy.pyx | 58 Py_ssize_t n_bins) except *: argument
78 cdef Py_ssize_t mid_bin = n_bins / 2
106 cdef Py_ssize_t [::1] histo = np.zeros(n_bins, dtype=np.intp)
130 for i in range(n_bins):
162 kernel(&out[r, c, 0], odepth, histo, pop, image[r, c], n_bins, mid_bin,
183 kernel(&out[r, c, 0], odepth, histo, pop, image[r, c], n_bins,
203 kernel(&out[r, c, 0], odepth, histo, pop, image[r, c], n_bins,
220 kernel(&out[r, c, 0], odepth, histo, pop, image[r, c], n_bins,
241 n_bins, mid_bin, p0, p1, s0, s1)
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| H A D | core_cy_3d.pyx | 173 Py_ssize_t n_bins) except *: argument
204 cdef Py_ssize_t mid_bin = n_bins // 2
216 cdef Py_ssize_t [::1] histo = np.zeros(n_bins, dtype=np.intp)
242 n_bins, mid_bin, p0, p1, s0, s1)
255 image[p, r, c], n_bins, mid_bin, p0, p1, s0, s1)
266 image[p, r, c], n_bins, mid_bin, p0, p1, s0, s1)
274 image[p, r, c], n_bins, mid_bin, p0, p1, s0, s1)
285 n_bins, mid_bin, p0, p1, s0, s1)
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| /dports/graphics/py-scikit-image/scikit-image-0.19.0/doc/examples/features_detection/ |
| H A D | plot_windowed_histogram.py | 51 def windowed_histogram_similarity(image, footprint, reference_hist, n_bins): argument
53 px_histograms = rank.windowed_histogram(image, footprint, n_bins=n_bins)
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| /dports/biology/py-pysam/pysam-0.18.0/samtools/ |
| H A D | coverage.c | 524 int64_t n_bins = opt_n_bins; in main_coverage() local
533 n_bins = s->end - s->beg; in main_coverage()
535 s->bin_width = (s->end-s->beg) / (n_bins > 0 ? n_bins : 1); in main_coverage()
565 print_hist(file_out, h, stats, old_tid, hist, n_bins, opt_full_utf); in main_coverage()
572 memset(hist, 0, n_bins*sizeof(uint32_t)); in main_coverage()
580 … n_bins = opt_n_bins > stats[tid].end-stats[tid].beg? stats[tid].end-stats[tid].beg : opt_n_bins; in main_coverage()
581 stats[tid].bin_width = (stats[tid].end-stats[tid].beg) / n_bins; in main_coverage()
614 if (opt_print_histogram && current_bin < n_bins) in main_coverage()
625 print_hist(file_out, h, stats, tid, hist, n_bins, opt_full_utf); in main_coverage()
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| H A D | coverage.c.pysam.c | 526 int64_t n_bins = opt_n_bins; in main_coverage() local
535 n_bins = s->end - s->beg; in main_coverage()
537 s->bin_width = (s->end-s->beg) / (n_bins > 0 ? n_bins : 1); in main_coverage()
567 print_hist(file_out, h, stats, old_tid, hist, n_bins, opt_full_utf); in main_coverage()
574 memset(hist, 0, n_bins*sizeof(uint32_t)); in main_coverage()
582 … n_bins = opt_n_bins > stats[tid].end-stats[tid].beg? stats[tid].end-stats[tid].beg : opt_n_bins; in main_coverage()
583 stats[tid].bin_width = (stats[tid].end-stats[tid].beg) / n_bins; in main_coverage()
616 if (opt_print_histogram && current_bin < n_bins) in main_coverage()
627 print_hist(file_out, h, stats, tid, hist, n_bins, opt_full_utf); in main_coverage()
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| /dports/biology/samtools/samtools-1.14/ |
| H A D | coverage.c | 524 int64_t n_bins = opt_n_bins; in main_coverage() local
533 n_bins = s->end - s->beg; in main_coverage()
535 s->bin_width = (s->end-s->beg) / (n_bins > 0 ? n_bins : 1); in main_coverage()
565 print_hist(file_out, h, stats, old_tid, hist, n_bins, opt_full_utf); in main_coverage()
572 memset(hist, 0, n_bins*sizeof(uint32_t)); in main_coverage()
580 … n_bins = opt_n_bins > stats[tid].end-stats[tid].beg? stats[tid].end-stats[tid].beg : opt_n_bins; in main_coverage()
581 stats[tid].bin_width = (stats[tid].end-stats[tid].beg) / n_bins; in main_coverage()
614 if (opt_print_histogram && current_bin < n_bins) in main_coverage()
625 print_hist(file_out, h, stats, tid, hist, n_bins, opt_full_utf); in main_coverage()
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| /dports/science/py-scikit-learn/scikit-learn-1.0.2/sklearn/ |
| H A D | calibration.py | 869 def calibration_curve(y_true, y_prob, *, normalize=False, n_bins=5, strategy="uniform"): argument
953 quantiles = np.linspace(0, 1, n_bins + 1)
957 bins = np.linspace(0.0, 1.0 + 1e-8, n_bins + 1)
1113 n_bins=5, argument
1217 n_bins=n_bins,
1231 n_bins=5, argument
1318 y_true, y_prob, n_bins=n_bins, strategy=strategy
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| /dports/misc/py-xgboost/xgboost-1.5.1/tests/cpp/common/ |
| H A D | test_quantile.cc | 41 size_t n_bins = 64; in TestDistributedQuantile() local
52 column_size, n_bins, m->Info().feature_types.ConstHostSpan(), false, in TestDistributedQuantile()
65 column_size, n_bins, m->Info().feature_types.ConstHostSpan(), false, in TestDistributedQuantile()
133 kRows, [=](int32_t seed, size_t n_bins, MetaInfo const &info) { in TEST() argument
140 auto cuts = SketchOnDMatrix(m.get(), n_bins); in TEST()
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| /dports/misc/xgboost/xgboost-1.5.1/tests/cpp/common/ |
| H A D | test_quantile.cc | 41 size_t n_bins = 64; in TestDistributedQuantile() local
52 column_size, n_bins, m->Info().feature_types.ConstHostSpan(), false, in TestDistributedQuantile()
65 column_size, n_bins, m->Info().feature_types.ConstHostSpan(), false, in TestDistributedQuantile()
133 kRows, [=](int32_t seed, size_t n_bins, MetaInfo const &info) { in TEST() argument
140 auto cuts = SketchOnDMatrix(m.get(), n_bins); in TEST()
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| /dports/math/py-matplotlib2/matplotlib-2.2.4/examples/images_contours_and_fields/ |
| H A D | image_transparency_blend.py | 31 n_bins = 100 variable
32 xx = np.linspace(xmin, xmax, n_bins)
33 yy = np.linspace(ymin, ymax, n_bins)
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| /dports/math/py-matplotlib2/matplotlib-2.2.4/lib/mpl_examples/images_contours_and_fields/ |
| H A D | image_transparency_blend.py | 31 n_bins = 100 variable
32 xx = np.linspace(xmin, xmax, n_bins)
33 yy = np.linspace(ymin, ymax, n_bins)
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| /dports/graphics/opencv/opencv-4.5.3/contrib/modules/xobjdetect/src/ |
| H A D | waldboost.cpp | 66 static void compute_min_step(const Mat &data_pos, const Mat &data_neg, size_t n_bins, in compute_min_step() argument
70 assert(n_bins <= 256); in compute_min_step()
87 data_step = (data_max - data_min) / (double)(n_bins - 1); in compute_min_step()
211 int n_bins = 256; in fit() local
213 compute_min_step(data_pos, data_neg, n_bins, data_min, data_step); in fit()
232 Mat1f pos_cdf(1, n_bins), neg_cdf(1, n_bins); in fit()
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| /dports/science/pynn/PyNN-0.10.0/test/system/scenarios/ |
| H A D | test_cell_types.py | 138 n_bins = int(np.sqrt(k * t_stop))
139 values, bins, patches = plt.hist(isi, bins=n_bins,
190 n_bins = int(np.sqrt(beta * t_stop/1000.0))
191 values, bins, patches = plt.hist(isi, bins=n_bins,
255 n_bins = int(np.sqrt(k * t_stop))
256 values, bins, patches = plt.hist(isi, bins=n_bins,
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| /dports/math/py-matplotlib2/matplotlib-2.2.4/examples/statistics/ |
| H A D | histogram_cumulative.py | 44 n_bins = 50 variable
50 n, bins, patches = ax.hist(x, n_bins, density=True, histtype='step',
|
| /dports/math/py-matplotlib2/matplotlib-2.2.4/lib/mpl_examples/statistics/ |
| H A D | histogram_cumulative.py | 44 n_bins = 50 variable
50 n, bins, patches = ax.hist(x, n_bins, density=True, histtype='step',
|
| /dports/math/py-matplotlib/matplotlib-3.4.3/examples/statistics/ |
| H A D | histogram_cumulative.py | 44 n_bins = 50 variable
50 n, bins, patches = ax.hist(x, n_bins, density=True, histtype='step',
|
| /dports/math/py-yt/yt-4.0.1/doc/source/cookbook/ |
| H A D | particle_filter_sfr.py | 26 n_bins = 1000 variable
29 bins=n_bins,
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| /dports/misc/vxl/vxl-3.3.2/contrib/brl/bpro/core/brip_pro/processes/ |
| H A D | brip_image_mutual_info_process.cxx | 57 auto n_bins = pro.get_input<unsigned>(in_i++); in brip_image_mutual_info_process() local
63 double mutual_info = brip_mutual_info(image_a, image_b, min, max, n_bins); in brip_image_mutual_info_process()
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| /dports/math/py-mathics/Mathics3-2.2.0/mathics/builtin/drawing/ |
| H A D | plot.py | 1191 bins = [0] * n_bins
1196 elif b >= n_bins:
1197 b = n_bins - 1
1202 def n_bins(self): member in Histogram.apply.Distribution
1208 n_bins = len(bins)
1209 k = sum(bins) / n_bins
1216 n_bins = len(bins)
1257 def compute_cost(n_bins): argument
1282 n_bins = new_n_bins
1294 n_bins = distributions[0].n_bins()
[all …]
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| /dports/misc/orange3/orange3-3.29.1/Orange/distance/ |
| H A D | base.py | 439 n_bins = max(n_vals, default=0)
441 dist_missing_disc = np.zeros((n_discrete, n_bins), dtype=float)
456 discrete_stats = self.get_discrete_stats(column, n_bins)
479 def get_discrete_stats(column, n_bins): argument
495 dist = util.bincount(column, minlength=n_bins)[0]
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| /dports/math/armadillo/armadillo-10.7.1/include/armadillo_bits/ |
| H A D | fn_hist.hpp | 32 hist(const T1& A, const uword n_bins = 10) in hist() argument
36 return mtOp<uword,T1,op_hist>(A, n_bins, 0); in hist()
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| /dports/math/R-cran-RcppArmadillo/RcppArmadillo/inst/include/armadillo_bits/ |
| H A D | fn_hist.hpp | 32 hist(const T1& A, const uword n_bins = 10) in hist() argument
36 return mtOp<uword,T1,op_hist>(A, n_bins, 0); in hist()
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| /dports/graphics/pcl-pointclouds/pcl-pcl-1.12.0/filters/include/pcl/filters/impl/ |
| H A D | normal_space.hpp | 105 unsigned int n_bins = binsx_ * binsy_ * binsz_; in applyFilter() local
109 normals_hg.reserve (n_bins); in applyFilter()
110 for (unsigned int i = 0; i < n_bins; i++) in applyFilter()
|