Coverage for pesummary/core/plots/interactive.py: 65.1%
43 statements
« prev ^ index » next coverage.py v7.4.4, created at 2024-05-02 08:42 +0000
1# Licensed under an MIT style license -- see LICENSE.md
3import plotly.graph_objects as go
4import plotly
6__author__ = ["Charlie Hoy <charlie.hoy@ligo.org>"]
9def write_to_html(fig, filename):
10 """Write a plotly.graph.objects.go.Figure to a html file
12 Parameters
13 ----------
14 fig: plotly.graph.objects.go.Figure object
15 figure containing the plot that you wish to save to html
16 filename: str
17 name of the file that you wish to write the figure to
18 """
19 div = plotly.offline.plot(fig, include_plotlyjs=False, output_type='div')
20 data = "<script src='https://cdn.plot.ly/plotly-latest.min.js'></script>\n"
21 data += (
22 "<script src='https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/"
23 "MathJax.js?config=TeX-MML-AM_SVG'></script>"
24 )
25 with open(filename, "w") as f:
26 data += div
27 f.write(data)
30def histogram2d(
31 x, y, xlabel='x', ylabel='y', contour=False, contour_color='Blues',
32 marker_color='rgba(248,148,6,1)', dimensions={'width': 900, 'height': 900},
33 write_to_html_file="interactive_2d_histogram.html", showgrid=False,
34 showlegend=False
35):
36 """Build an interactive 2d histogram plot
38 Parameters
39 ----------
40 x: np.ndarray
41 An array containing the x coordinates of the points to be histogrammed
42 y: np.ndarray
43 An array containing the y coordinates of the points to be histogrammed
44 xlabel: str
45 The label for the x coordinates
46 ylabel: str
47 The label for the y coordinates
48 contour: Bool
49 Whether or not to show contours on the scatter plot
50 contour_color: str
51 Name of the matplotlib palette to use for contour colors
52 marker_color: str
53 Color to use for the markers
54 dimensions: dict
55 A dictionary giving the width and height of the figure.
56 write_to_html_file: str
57 Name of the html file you wish to write the figure to
58 showgrid: Bool
59 Whether or not to show a grid on the plot
60 showlegend: Bool
61 Whether or not to add a legend to the plot
62 """
63 fig = go.Figure()
64 if contour:
65 fig.add_trace(
66 go.Histogram2dContour(
67 x=x, y=y, colorscale=contour_color, reversescale=True,
68 xaxis='x', yaxis='y', histnorm="probability density"
69 )
70 )
71 fig.add_trace(
72 go.Scatter(
73 x=x, y=y, xaxis='x', yaxis='y', mode='markers',
74 marker=dict(color=marker_color, size=3)
75 )
76 )
77 fig.add_trace(
78 go.Histogram(
79 y=y, xaxis='x2', marker=dict(color=marker_color),
80 histnorm="probability density"
81 )
82 )
83 fig.add_trace(
84 go.Histogram(
85 x=x, yaxis='y2', marker=dict(color=marker_color),
86 histnorm="probability density"
87 )
88 )
90 fig.update_layout(
91 autosize=False,
92 xaxis=dict(
93 zeroline=False, domain=[0, 0.85], showgrid=showgrid
94 ),
95 yaxis=dict(
96 zeroline=False, domain=[0, 0.85], showgrid=showgrid
97 ),
98 xaxis2=dict(
99 zeroline=False, domain=[0.85, 1], showgrid=showgrid
100 ),
101 yaxis2=dict(
102 zeroline=False, domain=[0.85, 1], showgrid=showgrid
103 ),
104 height=dimensions["height"],
105 width=dimensions["width"],
106 bargap=0,
107 hovermode='closest',
108 showlegend=showlegend,
109 font=dict(
110 size=10
111 ),
112 xaxis_title=xlabel,
113 yaxis_title=ylabel,
114 )
115 if write_to_html_file is not None:
116 write_to_html(fig, write_to_html_file)
117 return
118 return fig
121def ridgeline(
122 data, labels, xlabel='x', palette='colorblind', colors=None, width=3,
123 write_to_html_file="interactive_ridgeline.html", showlegend=False,
124 dimensions={'width': 1100, 'height': 700}
125):
126 """Build an interactive ridgeline plot
128 Parameters
129 ----------
130 data: list, np.ndarray
131 The samples you wish to produce a ridgline plot for. This should be a 2
132 dimensional array where the zeroth axis is the list of samples and
133 the next axis is are the dimensions of the space
134 labels: list
135 List of labels corresponding to each set of samples
136 xlabel: str
137 The label for the x coordinates
138 palette: str
139 Name of the seaborn colorpalette to use for the different posterior
140 distributions
141 colors: list
142 List of colors to use for the different posterior distributions
143 width: float
144 Width of the violin plots
145 write_to_html_file: str
146 Name of the html file you wish to write the figure to
147 showlegend: Bool
148 Whether or not to add a legend to the plot
149 dimensions: dict
150 A dictionary giving the width and height of the figure
151 """
152 fig = go.Figure()
153 if colors is None:
154 import seaborn
156 colors = seaborn.color_palette(
157 palette=palette, n_colors=len(data)
158 ).as_hex()
160 for dd, label, color in zip(data, labels, colors):
161 fig.add_trace(go.Violin(x=dd, line_color=color, name=label))
163 fig.update_traces(
164 orientation='h', side='positive', width=width, points=False
165 )
166 fig.update_layout(
167 xaxis_showgrid=False, xaxis_zeroline=False, xaxis_title=xlabel,
168 width=dimensions["width"], height=dimensions["height"],
169 font=dict(size=18), showlegend=showlegend
170 )
171 if write_to_html_file is not None:
172 write_to_html(fig, write_to_html_file)
173 return
174 return fig
177def corner(
178 data, labels, dimensions={'width': 900, 'height': 900}, show_diagonal=False,
179 colors={'selected': 'rgba(248,148,6,1)', 'not_selected': 'rgba(0,0,0,1)'},
180 show_upper_half=False, write_to_html_file="interactive_corner.html"
181):
182 """Build an interactive corner plot
184 Parameters
185 ----------
186 data: list, np.ndarray
187 The samples you wish to produce a corner plot for. This should be a 2
188 dimensional array where the zeroth axis is the list of samples and
189 the next axis is are the dimensions of the space
190 labels: list, np.ndarray
191 A list of names for each dimension
192 dimensions: dict
193 A dictionary giving the width and height of the figure.
194 show_diagonal: Bool
195 Whether or not to show the diagonal scatter plots
196 colors: dict
197 A dictionary of colors for the individual samples. The dictionary should
198 have keys 'selected' and 'not_selected' to indicate the colors to be
199 used when the markers are selected and not selected respectively
200 show_upper_half: Bool
201 Whether or not to show the upper half of scatter plots
202 write_to_html_file: str
203 Name of the html file you wish to write the figure to
204 """
205 data_structure = [
206 dict(label=label, values=value) for label, value in zip(
207 labels, data
208 )
209 ]
210 fig = go.Figure(
211 data=go.Splom(
212 dimensions=data_structure,
213 marker=dict(
214 color=colors["not_selected"], showscale=False,
215 line_color='white', line_width=0.5,
216 size=3
217 ),
218 selected=dict(marker=dict(color=colors["selected"])),
219 diagonal_visible=show_diagonal,
220 showupperhalf=show_upper_half,
221 )
222 )
223 fig.update_layout(
224 dragmode='select',
225 width=dimensions["width"],
226 height=dimensions["height"],
227 hovermode='closest',
228 font=dict(
229 size=10
230 )
231 )
232 if write_to_html_file is not None:
233 write_to_html(fig, write_to_html_file)
234 return
235 return fig