| /dports/science/py-nilearn/nilearn-0.8.1/examples/01_plotting/ |
| H A D | plot_demo_more_plotting.py | 49 from nilearn import plotting
79 plotting.plot_stat_map(stat_img, display_mode='x',
97 plotting.plot_stat_map(stat_img, display_mode='z',
107 plotting.plot_stat_map(stat_img, display_mode='xz',
116 plotting.plot_stat_map(stat_img, display_mode='yx',
220 display = plotting.plot_anat(mean_haxby_img,
254 display = plotting.plot_anat(mean_haxby_img,
263 display = plotting.plot_anat(mean_haxby_img,
276 plotting.plot_stat_map(stat_img,
282 display = plotting.plot_stat_map(stat_img,
[all …]
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| H A D | plot_demo_glass_brain_extensive.py | 44 from nilearn import plotting
47 plotting.plot_glass_brain(stat_img, threshold=3)
69 plotting.plot_glass_brain(stat_img, threshold=3,
78 plotting.plot_glass_brain(stat_img,
96 display = plotting.plot_glass_brain(None)
105 display = plotting.plot_glass_brain(None)
117 display = plotting.plot_glass_brain(None)
123 display = plotting.plot_glass_brain(None)
132 display = plotting.plot_glass_brain(None, black_bg=True)
138 display = plotting.plot_glass_brain(None, black_bg=True)
[all …]
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| H A D | plot_3d_map_to_surface_projection.py | 40 from nilearn import plotting
42 plotting.plot_surf_stat_map(fsaverage.infl_right, texture, hemi='right',
50 plotting.plot_glass_brain(stat_img, display_mode='r', plot_abs=False,
53 plotting.plot_stat_map(stat_img, display_mode='x', threshold=1.,
87 plotting.show()
101 plotting.plot_surf_stat_map(big_fsaverage.infl_right,
117 plotting.plot_img_on_surf(stat_img,
121 plotting.show()
132 view = plotting.view_surf(fsaverage.infl_right, texture, threshold='90%',
147 view = plotting.view_img_on_surf(stat_img, threshold='90%')
[all …]
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| H A D | plot_multiscale_parcellations.py | 33 from nilearn import plotting
37 plotting.plot_roi(networks_64, cmap=plotting.cm.bwr,
40 plotting.plot_roi(networks_197, cmap=plotting.cm.bwr,
43 plotting.plot_roi(networks_444, cmap=plotting.cm.bwr_r,
46 plotting.show()
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| H A D | plot_overlay.py | 35 from nilearn import plotting, image
38 display = plotting.plot_stat_map(image.index_img(atlas_filename, 4),
45 cmap=plotting.cm.black_blue)
47 cmap=plotting.cm.black_green)
49 cmap=plotting.cm.black_pink)
51 plotting.show()
69 display = plotting.plot_prob_atlas(dmn_nodes,
72 plotting.show()
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| H A D | plot_demo_plotting.py | 41 from nilearn import plotting
45 plotting.plot_stat_map(stat_img,
57 view = plotting.view_img(stat_img, threshold=3)
74 plotting.plot_glass_brain(stat_img, title='plot_glass_brain',
82 plotting.plot_anat(haxby_anat_filename, title="plot_anat")
91 plotting.plot_roi(haxby_mask_filename, bg_img=haxby_anat_filename,
106 plotting.plot_epi(mean_haxby_img, title="plot_epi")
111 plotting.show()
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| H A D | plot_surf_atlas.py | 51 from nilearn import plotting
53 plotting.plot_surf_roi(fsaverage['pial_left'], roi_map=parcellation,
60 plotting.plot_surf_roi(fsaverage['infl_left'], roi_map=parcellation,
67 plotting.plot_surf_roi(fsaverage['infl_left'], roi_map=parcellation,
74 plotting.plot_surf_roi(fsaverage['infl_left'], roi_map=parcellation,
78 plotting.show()
112 plotting.plot_connectome(corr, coordinates,
115 plotting.show()
125 view = plotting.view_surf(fsaverage.infl_left, parcellation,
140 view = plotting.view_connectome(corr, coordinates, edge_threshold='90%')
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| H A D | plot_atlas.py | 27 from nilearn import plotting
29 plotting.plot_roi(atlas_ho_filename, title="Harvard Oxford atlas")
35 plotting.plot_roi(atlas_ju_filename, title="Juelich atlas")
40 plotting.plot_roi(atlas_ho_filename, view_type='contours',
42 plotting.show()
47 plotting.plot_roi(atlas_ju_filename, view_type='contours',
49 plotting.show()
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| H A D | plot_dim_plotting.py | 31 from nilearn import plotting
32 plotting.plot_stat_map(localizer_tmap_filename,
41 plotting.plot_stat_map(localizer_tmap_filename,
50 plotting.plot_stat_map(localizer_tmap_filename,
59 plotting.plot_stat_map(localizer_tmap_filename,
65 plotting.show()
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| /dports/biology/viennarna/ViennaRNA-2.4.18/src/ViennaRNA/ |
| H A D | Makefile.am | 218 plotting/alignments.h \
219 plotting/layouts.h \
220 plotting/probabilities.h \
221 plotting/structures.h \
222 plotting/utils.h \
223 plotting/naview.h
358 plotting/alignments.c \
359 plotting/layouts.c \
361 plotting/structures.c \
362 plotting/plot_utils.c \
[all …]
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| /dports/math/py-nevergrad/nevergrad-0.4.3.post2/nevergrad/benchmark/ |
| H A D | test_plotting.py | 25 winners = plotting._make_winners_df(df, all_optimizers)
46 winrates = plotting._make_sorted_winrates_df(victories)
58 plotting.create_plots(df, "", max_combsize=1)
76 plotter = plotting.FightPlotter(winrates)
87 data = plotting.XpPlotter.make_data(df)
96 plotter = plotting.XpPlotter(data, title="Title")
110 output = plotting.remove_errors(df)
118 assert isinstance(output, plotting.utils.Selector)
125 output = plotting.remove_errors(df)
133 gen = plotting._make_style_generator()
[all …]
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| /dports/science/py-GPy/GPy-1.10.0/doc/source/ |
| H A D | tuto_plotting.rst | 2 Defining a new plotting function in GPy
5 GPy has a wrapper for different plotting backends.
6 There are some functions you can use for standard plotting.
11 All plotting related code lives in :py:mod:`GPy.plotting` and beneath. No plotting related code nee…
17 Write your plotting function into a module under :py:mod:`GPy.plotting.gpy_plot` ``.<module_name>``
18 using the plotting routines provided in :py:func:`GPy.plotting.plotting_library`.
20 the plotting library.
25 The first argument of the plotting function is always ``self`` for the class this plotting function
45 the real plotting.
94 # 1D plotting:
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| /dports/science/py-nilearn/nilearn-0.8.1/examples/03_connectivity/ |
| H A D | plot_sphere_based_connectome.py | 115 from nilearn import plotting
128 plotting.show()
236 from nilearn import plotting
238 plotting.plot_matrix(matrix, vmin=-1., vmax=1., colorbar=True,
263 plotting.plot_markers(
290 plotting.plot_markers(
298 plotting.plot_markers(
340 plotting.plot_markers(
357 plotting.plot_markers(
365 plotting.plot_markers(
[all …]
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| H A D | plot_extract_regions_dictlearning_maps.py | 52 from nilearn import plotting
54 plotting.plot_prob_atlas(components_img, view_type='filled_contours',
83 plotting.plot_prob_atlas(regions_extracted_img, view_type='filled_contours',
120 display = plotting.plot_matrix(mean_correlations, vmax=1, vmin=-1,
125 coords_connectome = plotting.find_probabilistic_atlas_cut_coords(regions_img)
127 plotting.plot_connectome(mean_correlations, coords_connectome,
138 coords = plotting.find_xyz_cut_coords(img)
139 display = plotting.plot_stat_map(img, cut_coords=coords, colorbar=False,
151 display = plotting.plot_anat(cut_coords=coords,
158 cmap=plotting.cm.alpha_cmap(color))
[all …]
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| H A D | plot_multi_subject_connectome.py | 11 from nilearn import plotting
27 plotting.plot_matrix(cov, cmap=plotting.cm.bwr,
31 plotting.plot_matrix(prec, cmap=plotting.cm.bwr,
97 atlas_region_coords = plotting.find_probabilistic_atlas_cut_coords(atlas_img)
100 plotting.plot_connectome(gl.covariance_,
104 plotting.plot_connectome(-gl.precision_, atlas_region_coords,
112 plotting.plot_connectome(-gsc.precisions_[..., 0],
120 plotting.show()
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| H A D | plot_inverse_covariance_connectome.py | 66 from nilearn import plotting
70 plotting.plot_matrix(estimator.covariance_, labels=labels,
79 plotting.plot_connectome(estimator.covariance_, coords,
87 plotting.plot_matrix(-estimator.precision_, labels=labels,
94 plotting.plot_connectome(-estimator.precision_, coords,
97 plotting.show()
108 view = plotting.view_connectome(-estimator.precision_, coords)
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| /dports/math/py-sympy/sympy-1.9/sympy/plotting/pygletplot/tests/ |
| H A D | test_plotting.py | 17 from sympy.plotting.pygletplot import PygletPlot
23 from sympy.plotting.pygletplot import PygletPlot
29 from sympy.plotting.pygletplot import PygletPlot
35 from sympy.plotting.pygletplot import PygletPlot
41 from sympy.plotting.pygletplot import PygletPlot
47 from sympy.plotting.pygletplot import PygletPlot
55 from sympy.plotting.pygletplot import PygletPlot
64 from sympy.plotting.pygletplot import PygletPlot
70 from sympy.plotting.pygletplot import PygletPlot
76 from sympy.plotting.pygletplot import PygletPlot
[all …]
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| /dports/science/py-nilearn/nilearn-0.8.1/nilearn/plotting/glass_brain_files/ |
| H A D | plot_align_svg.py | 7 from nilearn import plotting
8 from nilearn.plotting import img_plotting, glass_brain, show
40 display = plotting.plot_anat(display_mode='x', cut_coords=[-2])
44 display = plotting.plot_anat(display_mode='z', cut_coords=[20])
48 display = plotting.plot_anat(display_mode='y', cut_coords=[-20])
52 display = plotting.plot_anat(display_mode='ortho', cut_coords=(-2, -20, 20))
56 display = plotting.plot_anat(display_mode='x')
59 display = plotting.plot_anat(display_mode='y')
62 display = plotting.plot_anat(display_mode='z')
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| /dports/science/py-nilearn/nilearn-0.8.1/examples/ |
| H A D | plot_3d_and_4d_niimg.py | 34 from nilearn import plotting
35 plotting.plot_stat_map(tmap_filename)
39 plotting.plot_stat_map(tmap_filename, threshold=3)
66 plotting.plot_stat_map(first_rsn)
80 plotting.plot_stat_map(img, threshold=3, display_mode="z", cut_coords=1,
101 plotting.plot_stat_map(img)
107 plotting.show()
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| /dports/math/py-sympy/sympy-1.9/doc/src/modules/ |
| H A D | plotting.rst | 5 .. module:: sympy.plotting.plot
15 The plotting module has the following functions:
31 .. autoclass:: sympy.plotting.plot::Plot
52 .. autoclass:: sympy.plotting.plot::PlotGrid
58 .. autoclass:: sympy.plotting.plot::BaseSeries
61 .. autoclass:: sympy.plotting.plot::Line2DBaseSeries
91 .. autoclass:: sympy.plotting.plot::BaseBackend
97 .. autoclass:: sympy.plotting.plot::TextBackend
103 .. module:: sympy.plotting.pygletplot
121 it in interactive mode (python -i plotting.py)::
[all …]
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| /dports/science/py-nilearn/nilearn-0.8.1/examples/05_glm_second_level/ |
| H A D | plot_second_level_two_sample_test.py | 27 from nilearn import plotting
75 from nilearn.plotting import plot_design_matrix
82 plotting.show()
116 plotting.plot_glass_brain(
120 plotting.plot_glass_brain(
124 plotting.show()
130 display = plotting.plot_glass_brain(
134 display = plotting.plot_glass_brain(
138 plotting.show()
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| H A D | plot_second_level_one_sample_test.py | 39 from nilearn import plotting
44 plotting.plot_glass_brain(tmap, colorbar=False, threshold=2.0,
78 display = plotting.plot_glass_brain(
81 plotting.show()
110 display = plotting.plot_glass_brain(
113 plotting.show()
129 display = plotting.plot_glass_brain(
133 plotting.show()
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| /dports/math/py-pandas/pandas-1.2.5/pandas/plotting/_matplotlib/ |
| H A D | __init__.py | 3 from pandas.plotting._matplotlib.boxplot import (
9 from pandas.plotting._matplotlib.converter import deregister, register
10 from pandas.plotting._matplotlib.core import (
19 from pandas.plotting._matplotlib.hist import HistPlot, KdePlot, hist_frame, hist_series
20 from pandas.plotting._matplotlib.misc import (
29 from pandas.plotting._matplotlib.tools import table
32 from pandas.plotting._matplotlib.core import MPLPlot
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| /dports/science/py-nilearn/nilearn-0.8.1/examples/06_manipulating_images/ |
| H A D | plot_extract_regions_labels_image.py | 32 from nilearn import plotting
34 plotting.plot_roi(atlas_yeo, title='Original Yeo atlas',
55 plotting.plot_roi(region_labels, title='Relabeled Yeo atlas',
91 plotting.plot_roi(region_labels_not_diag,
112 plotting.plot_roi(region_labels_min_size, title='Relabeling and min_size',
115 plotting.show()
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| /dports/science/py-nilearn/nilearn-0.8.1/doc/plotting/ |
| H A D | index.rst | 27 .. currentmodule:: nilearn.plotting
29 Different plotting functions
145 >>> from nilearn import plotting
379 >>> from nilearn import plotting
385 >>> from nilearn import plotting
402 .. _surface-plotting:
404 Surface plotting
439 .. _interactive-plotting:
462 .. _interactive-surface-plotting:
520 .. _interactive-markers-plotting:
[all …]
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