Implement HorizontalEffectPlot
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@ -18,7 +18,7 @@ from .bayes_factors import bayesfactor_afbf
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from .config import config
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from .descriptives import auto_correlations, auto_descriptives
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from .distributions import beta_oddsratio, beta_ratio, hdi, transformed_dist
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from .graphs import init_fonts
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from .graphs import init_fonts, HorizontalEffectPlot
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from .io import pickle_read_compressed, pickle_read_encrypted, pickle_write_compressed, pickle_write_encrypted
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from .regress import IntervalCensoredCox, Logit, OLS, OrdinalLogit, PenalisedLogit, Poisson, regress, vif
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from .sig_tests import anova_oneway, auto_univariable, chi2, mannwhitney, pearsonr, spearman, ttest_ind, ttest_ind_multiple
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161
yli/graphs.py
161
yli/graphs.py
@ -1,3 +1,21 @@
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# scipy-yli: Helpful SciPy utilities and recipes
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# Copyright © 2022–2023 Lee Yingtong Li (RunasSudo)
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU Affero General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU Affero General Public License for more details.
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#
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# You should have received a copy of the GNU Affero General Public License
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# along with this program. If not, see <https://www.gnu.org/licenses/>.
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from collections import namedtuple
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def init_fonts():
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import matplotlib.pyplot as plt
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@ -5,3 +23,146 @@ def init_fonts():
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plt.rcParams['text.latex.preamble'] = r'\usepackage{tgheros}\usepackage{newtxmath}'
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plt.rcParams['font.size'] = 11
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plt.rcParams['figure.dpi'] = 100
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EffectPlotData = namedtuple('EffectPlotData', ['y', 'mean', 'ci0', 'ci1', 'pvalue'])
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class EffectPlotText:
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def __init__(self, y, text, skip_width=False, **kwargs):
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self.y = y
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self.text = text
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self.skip_width = skip_width
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self.kwargs = kwargs
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class HorizontalEffectPlot:
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# TODO: Documentation
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def __init__(self, measure_name, xlabel, *, header_y=1):
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self.measure_name = measure_name
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self.xlabel = xlabel
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self.text_left = [[]] # [EffectPlotText]
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#self.text_right = [[], [], [], [], [], [], []] # [EffectPlotText]
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self.text_right = [[], [], [], [], [], []] # [EffectPlotText]
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self.data = []
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#self.space_right = [0.15, 0.05, 0, 0, 0.1, 0, 0] # Space in inches between each right text column
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self.space_right = [0.15, 0.05, 0, 0, 0.1, 0] # Space in inches between each right text column
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# Add headings
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self.text_right[0].append(EffectPlotText(header_y, measure_name, skip_width=True, ha='center', fontweight='medium'))
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self.text_right[2].append(EffectPlotText(header_y, '(95% CI)', skip_width=True, ha='center', fontweight='medium'))
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self.text_right[5].append(EffectPlotText(header_y, 'p', skip_width=True, ha='center', fontweight='medium', fontstyle='italic'))
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def add_nobar(self, y, label, mean=None, ci0=None, ci1=None, pvalue=None):
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# Label
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self.text_left[0].append(EffectPlotText(y, label, ha='right'))
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# Mean
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if mean is not None:
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self.text_right[0].append(EffectPlotText(y, mean, ha='right'))
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# Confidence intervals
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if ci0 is not None:
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self.text_right[1].append(EffectPlotText(y, '({}'.format(ci0), ha='right'))
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self.text_right[2].append(EffectPlotText(y, '–', ha='left'))
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self.text_right[3].append(EffectPlotText(y, '{})'.format(ci1), ha='left'))
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# P value and flag
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if pvalue is not None:
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self.text_right[5].append(EffectPlotText(y, pvalue, ha='right'))
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def add_bar(self, y, label, mean, ci0, ci1, pvalue):
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self.data.append(EffectPlotData(y=y, mean=mean, ci0=ci0, ci1=ci1, pvalue=pvalue))
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# Label
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self.text_left[0].append(EffectPlotText(y, label, ha='right'))
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# Mean
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self.text_right[0].append(EffectPlotText(y, '{:.2f}'.format(mean), ha='right'))
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# Confidence intervals
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self.text_right[1].append(EffectPlotText(y, '({:.2f}'.format(ci0), ha='right'))
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self.text_right[2].append(EffectPlotText(y, '–', ha='left'))
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self.text_right[3].append(EffectPlotText(y, '{:.2f})'.format(ci1), ha='left'))
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# P value and flag
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if pvalue < 0.0005:
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self.text_right[4].append(EffectPlotText(y, '<', ha='left'))
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self.text_right[5].append(EffectPlotText(y, '0.001*', ha='left'))
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elif pvalue < 0.01:
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self.text_right[5].append(EffectPlotText(y, '{:.3f}*'.format(pvalue), ha='left'))
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elif pvalue < 0.05:
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self.text_right[5].append(EffectPlotText(y, '{:.2f}*'.format(pvalue), ha='left'))
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else:
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self.text_right[5].append(EffectPlotText(y, '{:.2f}'.format(pvalue), ha='left'))
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#if pvalue < 0.05:
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# self.text_right[6].append(EffectPlotText(y, '*', ha='left'))
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def add_group_heading(self, y, label):
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self.text_left[0].append(EffectPlotText(y, label, ha='right', fontweight='medium'))
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def _width_of(self, text):
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txt = self.ax.text(9999, 9999, text, in_layout=False, transform=self.ax.transAxes)
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txt_width_px = txt.get_window_extent(renderer=self.fig.canvas.get_renderer()).width
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txt_width_in = self.fig.dpi_scale_trans.inverted().transform([txt_width_px, 0])[0]
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txt.remove()
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return txt_width_in
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def render(
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self,
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width=4,
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xscale='log', xlim=(0.5, 4), xticks=['0.5', '1', '2', '4'], minorticks=[],
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):
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import matplotlib.pyplot as plt
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fig_height = 0.3 * max(d.y for d in self.data) + 0.2
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self.fig, self.ax = plt.subplots(figsize=(width, fig_height))
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if xscale == 'log':
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self.ax.axvline(1, color='grey', linewidth=1)
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else:
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self.ax.axvline(0, color='grey', linewidth=1)
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self.ax.set_xscale(xscale)
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self.ax.set_xlim(*xlim)
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self.ax.set_xticks([float(x) for x in xticks])
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self.ax.set_xticks(minorticks, minor=True)
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self.ax.set_xticklabels(xticks)
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self.ax.set_xticklabels([], minor=True)
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self.ax.set_xlabel(self.xlabel)
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self.ax.set_ylim(-max(d.y for d in self.data) - 1, 0)
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self.ax.set_yticks([])
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# Render data bars
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for data in self.data:
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self.ax.errorbar(x=[data.mean], y=[-data.y], xerr=[[data.mean-data.ci0], [data.ci1-data.mean]], fmt='o', color='C0', capsize=4, capthick=1.5)
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# Left text
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tmp = self.fig.dpi_scale_trans.inverted().transform(self.ax.transAxes.transform([0, 0]))
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tmp[0] -= 0.15
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x = self.ax.transAxes.inverted().transform(self.fig.dpi_scale_trans.transform(tmp))[0]
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for text in self.text_left[0]:
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y = self.ax.transAxes.inverted().transform(self.ax.transData.transform([1, -text.y]))[1]
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self.ax.text(x, y, text.text, transform=self.ax.transAxes, va='center_baseline', **text.kwargs)
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# Get width of right columns
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widths_right = [max(self._width_of(t.text) if not t.skip_width else 0 for t in col) if len(col) > 0 else 0 for col in self.text_right]
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# Right text
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for i, col in enumerate(self.text_right):
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for text in col:
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tmp = self.fig.dpi_scale_trans.inverted().transform(self.ax.transAxes.transform([1, 0]))
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tmp[0] += sum(self.space_right[0:i+1])
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tmp[0] += sum(widths_right[0:i]) or 0
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if text.kwargs['ha'] == 'center':
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tmp[0] += widths_right[i] / 2
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if text.kwargs['ha'] == 'right':
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tmp[0] += widths_right[i]
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x = self.ax.transAxes.inverted().transform(self.fig.dpi_scale_trans.transform(tmp))[0]
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y = self.ax.transAxes.inverted().transform(self.ax.transData.transform([1, -text.y]))[1]
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self.ax.text(x, y, text.text, transform=self.ax.transAxes, va='center_baseline', **text.kwargs)
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