Coverage for pesummary/core/plots/interactive.py: 63.8%
47 statements
« prev ^ index » next coverage.py v7.4.4, created at 2025-11-05 13:38 +0000
1# Licensed under an MIT style license -- see LICENSE.md
3from pesummary.utils.utils import logger, import_error_msg
4try:
5 import plotly.graph_objects as go
6 import plotly
7except ImportError:
8 logger.warning(import_error_msg.format("plotly"))
10__author__ = ["Charlie Hoy <charlie.hoy@ligo.org>"]
13def write_to_html(fig, filename):
14 """Write a plotly.graph.objects.go.Figure to a html file
16 Parameters
17 ----------
18 fig: plotly.graph.objects.go.Figure object
19 figure containing the plot that you wish to save to html
20 filename: str
21 name of the file that you wish to write the figure to
22 """
23 div = plotly.offline.plot(fig, include_plotlyjs=False, output_type='div')
24 data = "<script src='https://cdn.plot.ly/plotly-latest.min.js'></script>\n"
25 data += (
26 "<script src='https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/"
27 "MathJax.js?config=TeX-MML-AM_SVG'></script>"
28 )
29 with open(filename, "w") as f:
30 data += div
31 f.write(data)
34def histogram2d(
35 x, y, xlabel='x', ylabel='y', contour=False, contour_color='Blues',
36 marker_color='rgba(248,148,6,1)', dimensions={'width': 900, 'height': 900},
37 write_to_html_file="interactive_2d_histogram.html", showgrid=False,
38 showlegend=False
39):
40 """Build an interactive 2d histogram plot
42 Parameters
43 ----------
44 x: np.ndarray
45 An array containing the x coordinates of the points to be histogrammed
46 y: np.ndarray
47 An array containing the y coordinates of the points to be histogrammed
48 xlabel: str
49 The label for the x coordinates
50 ylabel: str
51 The label for the y coordinates
52 contour: Bool
53 Whether or not to show contours on the scatter plot
54 contour_color: str
55 Name of the matplotlib palette to use for contour colors
56 marker_color: str
57 Color to use for the markers
58 dimensions: dict
59 A dictionary giving the width and height of the figure.
60 write_to_html_file: str
61 Name of the html file you wish to write the figure to
62 showgrid: Bool
63 Whether or not to show a grid on the plot
64 showlegend: Bool
65 Whether or not to add a legend to the plot
66 """
67 fig = go.Figure()
68 if contour:
69 fig.add_trace(
70 go.Histogram2dContour(
71 x=x, y=y, colorscale=contour_color, reversescale=True,
72 xaxis='x', yaxis='y', histnorm="probability density"
73 )
74 )
75 fig.add_trace(
76 go.Scatter(
77 x=x, y=y, xaxis='x', yaxis='y', mode='markers',
78 marker=dict(color=marker_color, size=3)
79 )
80 )
81 fig.add_trace(
82 go.Histogram(
83 y=y, xaxis='x2', marker=dict(color=marker_color),
84 histnorm="probability density"
85 )
86 )
87 fig.add_trace(
88 go.Histogram(
89 x=x, yaxis='y2', marker=dict(color=marker_color),
90 histnorm="probability density"
91 )
92 )
94 fig.update_layout(
95 autosize=False,
96 xaxis=dict(
97 zeroline=False, domain=[0, 0.85], showgrid=showgrid
98 ),
99 yaxis=dict(
100 zeroline=False, domain=[0, 0.85], showgrid=showgrid
101 ),
102 xaxis2=dict(
103 zeroline=False, domain=[0.85, 1], showgrid=showgrid
104 ),
105 yaxis2=dict(
106 zeroline=False, domain=[0.85, 1], showgrid=showgrid
107 ),
108 height=dimensions["height"],
109 width=dimensions["width"],
110 bargap=0,
111 hovermode='closest',
112 showlegend=showlegend,
113 font=dict(
114 size=10
115 ),
116 xaxis_title=xlabel,
117 yaxis_title=ylabel,
118 )
119 if write_to_html_file is not None:
120 write_to_html(fig, write_to_html_file)
121 return
122 return fig
125def ridgeline(
126 data, labels, xlabel='x', palette='colorblind', colors=None, width=3,
127 write_to_html_file="interactive_ridgeline.html", showlegend=False,
128 dimensions={'width': 1100, 'height': 700}
129):
130 """Build an interactive ridgeline plot
132 Parameters
133 ----------
134 data: list, np.ndarray
135 The samples you wish to produce a ridgline plot for. This should be a 2
136 dimensional array where the zeroth axis is the list of samples and
137 the next axis is are the dimensions of the space
138 labels: list
139 List of labels corresponding to each set of samples
140 xlabel: str
141 The label for the x coordinates
142 palette: str
143 Name of the seaborn colorpalette to use for the different posterior
144 distributions
145 colors: list
146 List of colors to use for the different posterior distributions
147 width: float
148 Width of the violin plots
149 write_to_html_file: str
150 Name of the html file you wish to write the figure to
151 showlegend: Bool
152 Whether or not to add a legend to the plot
153 dimensions: dict
154 A dictionary giving the width and height of the figure
155 """
156 fig = go.Figure()
157 if colors is None:
158 from pesummary.core.plots.palette import color_palette
160 colors = color_palette(
161 palette=palette, n_colors=len(data)
162 ).as_hex()
164 for dd, label, color in zip(data, labels, colors):
165 fig.add_trace(go.Violin(x=dd, line_color=color, name=label))
167 fig.update_traces(
168 orientation='h', side='positive', width=width, points=False
169 )
170 fig.update_layout(
171 xaxis_showgrid=False, xaxis_zeroline=False, xaxis_title=xlabel,
172 width=dimensions["width"], height=dimensions["height"],
173 font=dict(size=18), showlegend=showlegend
174 )
175 if write_to_html_file is not None:
176 write_to_html(fig, write_to_html_file)
177 return
178 return fig
181def corner(
182 data, labels, dimensions={'width': 900, 'height': 900}, show_diagonal=False,
183 colors={'selected': 'rgba(248,148,6,1)', 'not_selected': 'rgba(0,0,0,1)'},
184 show_upper_half=False, write_to_html_file="interactive_corner.html"
185):
186 """Build an interactive corner plot
188 Parameters
189 ----------
190 data: list, np.ndarray
191 The samples you wish to produce a corner plot for. This should be a 2
192 dimensional array where the zeroth axis is the list of samples and
193 the next axis is are the dimensions of the space
194 labels: list, np.ndarray
195 A list of names for each dimension
196 dimensions: dict
197 A dictionary giving the width and height of the figure.
198 show_diagonal: Bool
199 Whether or not to show the diagonal scatter plots
200 colors: dict
201 A dictionary of colors for the individual samples. The dictionary should
202 have keys 'selected' and 'not_selected' to indicate the colors to be
203 used when the markers are selected and not selected respectively
204 show_upper_half: Bool
205 Whether or not to show the upper half of scatter plots
206 write_to_html_file: str
207 Name of the html file you wish to write the figure to
208 """
209 data_structure = [
210 dict(label=label, values=value) for label, value in zip(
211 labels, data
212 )
213 ]
214 fig = go.Figure(
215 data=go.Splom(
216 dimensions=data_structure,
217 marker=dict(
218 color=colors["not_selected"], showscale=False,
219 line_color='white', line_width=0.5,
220 size=3
221 ),
222 selected=dict(marker=dict(color=colors["selected"])),
223 diagonal_visible=show_diagonal,
224 showupperhalf=show_upper_half,
225 )
226 )
227 fig.update_layout(
228 dragmode='select',
229 width=dimensions["width"],
230 height=dimensions["height"],
231 hovermode='closest',
232 font=dict(
233 size=10
234 )
235 )
236 if write_to_html_file is not None:
237 write_to_html(fig, write_to_html_file)
238 return
239 return fig