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Merge pull request #73 from anekimken/inset_axes
Inset axes
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| #!/usr/bin/env python3 | ||
| # -*- coding: utf-8 -*- | ||
| """ | ||
| Created on Thu Sep 26 16:57:11 2019 | ||
| @author: adam nekimken | ||
| """ | ||
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| import pytest | ||
| import matplotlib as mpl | ||
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| import numpy as np | ||
| import seaborn as sns | ||
| from .._api import load | ||
| from .utils import create_dummy_dataset, get_swarm_yspans | ||
| import matplotlib.pyplot as plt | ||
| mpl.use('Agg') | ||
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| def test_gardner_altman_inset_plot(): | ||
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| base_mean = np.random.randint(10, 101) | ||
| seed, ptp, df = create_dummy_dataset(base_mean=base_mean) | ||
| print('\nSeed = {}; base mean = {}'.format(seed, base_mean)) | ||
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| for c in df.columns[1:-1]: | ||
| print('{}...'.format(c)) | ||
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| # Create Gardner-Altman plot with specified axes | ||
| f1, ax = plt.subplots(1) | ||
| rand_swarm_ylim = (np.random.uniform(base_mean-10, base_mean, 1), | ||
| np.random.uniform(base_mean, base_mean+10, 1)) | ||
| two_group_unpaired = load(df, idx=(df.columns[0], c)) | ||
| f1 = two_group_unpaired.mean_diff.plot(swarm_ylim=rand_swarm_ylim, | ||
| swarm_label="Raw swarmplot...", | ||
| contrast_label="Contrast!", | ||
| ax=ax) | ||
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| rawswarm_axes = ax | ||
| contrast_axes = ax.contrast_axes | ||
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| # Check ylims match the desired ones. | ||
| assert rawswarm_axes.get_ylim()[0] == pytest.approx(rand_swarm_ylim[0]) | ||
| assert rawswarm_axes.get_ylim()[1] == pytest.approx(rand_swarm_ylim[1]) | ||
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| # Check each swarmplot group matches canonical seaborn swarmplot. | ||
| _, swarmplt = plt.subplots(1) | ||
| swarmplt.set_ylim(rand_swarm_ylim) | ||
| sns.swarmplot(data=df[[df.columns[0], c]], ax=swarmplt) | ||
| sns_yspans = [] | ||
| for coll in swarmplt.collections: | ||
| sns_yspans.append(get_swarm_yspans(coll)) | ||
| dabest_yspans = [get_swarm_yspans(coll) | ||
| for coll in rawswarm_axes.collections] | ||
| for j, span in enumerate(sns_yspans): | ||
| assert span == pytest.approx(dabest_yspans[j]) | ||
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| # Check xtick labels. | ||
| swarm_xticks = [a.get_text() for a in rawswarm_axes.get_xticklabels()] | ||
| assert swarm_xticks[0] == "{}\nN = 30".format(df.columns[0]) | ||
| assert swarm_xticks[1] == "{}\nN = 30".format(c) | ||
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| contrast_xticks = [a.get_text() | ||
| for a in contrast_axes.get_xticklabels()] | ||
| assert contrast_xticks[1] == "{}\nminus\n{}".format(c, df.columns[0]) | ||
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| # Check ylabels. | ||
| assert rawswarm_axes.get_ylabel() == "Raw swarmplot..." | ||
| assert contrast_axes.get_ylabel() == "Contrast!" | ||
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| #def test_cummings_unpaired(): | ||
| # base_mean = np.random.randint(-5, 5) | ||
| # seed, ptp, df = create_dummy_dataset(base_mean=base_mean, expt_groups=7) | ||
| # print('\nSeed = {}; base mean = {}'.format(seed, base_mean)) | ||
| # | ||
| # IDX = (('0','5'), ('3','2'), ('4', '1', '6')) | ||
| # multi_2group_unpaired = load(df, idx=IDX) | ||
| # | ||
| # rand_swarm_ylim = (np.random.uniform(base_mean-10, base_mean, 1), | ||
| # np.random.uniform(base_mean, base_mean+10, 1)) | ||
| # | ||
| # if base_mean == 0: | ||
| # # Have to set the contrast ylim, because the way I dynamically generate | ||
| # # the contrast ylims will flunk out with base_mean = 0. | ||
| # rand_contrast_ylim = (-0.5, 0.5) | ||
| # else: | ||
| # rand_contrast_ylim = (-base_mean/3, base_mean/3) | ||
| # | ||
| # f1 = multi_2group_unpaired.mean_diff.plot(swarm_ylim=rand_swarm_ylim, | ||
| # contrast_ylim=rand_contrast_ylim, | ||
| # swarm_label="Raw swarmplot!", | ||
| # contrast_label="Contrast...") | ||
| # | ||
| # rawswarm_axes = f1.axes[0] | ||
| # contrast_axes = f1.axes[1] | ||
| # | ||
| # # Check swarm ylims match the desired ones. | ||
| # assert rawswarm_axes.get_ylim()[0] == pytest.approx(rand_swarm_ylim[0]) | ||
| # assert rawswarm_axes.get_ylim()[1] == pytest.approx(rand_swarm_ylim[1]) | ||
| # | ||
| # # Check contrast ylims match the desired ones. | ||
| # assert contrast_axes.get_ylim()[0] == pytest.approx(rand_contrast_ylim[0]) | ||
| # assert contrast_axes.get_ylim()[1] == pytest.approx(rand_contrast_ylim[1]) | ||
| # | ||
| # # Check xtick labels. | ||
| # idx_flat = [g for t in IDX for g in t] | ||
| # swarm_xticks = [a.get_text() for a in rawswarm_axes.get_xticklabels()] | ||
| # for j, xtick in enumerate(swarm_xticks): | ||
| # assert xtick == "{}\nN = 30".format(idx_flat[j]) | ||
| # | ||
| # contrast_xticks = [a.get_text() for a in contrast_axes.get_xticklabels()] | ||
| # assert contrast_xticks[1] == "5\nminus\n0" | ||
| # assert contrast_xticks[3] == "2\nminus\n3" | ||
| # assert contrast_xticks[5] == "1\nminus\n4" | ||
| # assert contrast_xticks[6] == "6\nminus\n4" | ||
| # | ||
| # # Check ylabels. | ||
| # assert rawswarm_axes.get_ylabel() == "Raw swarmplot!" | ||
| # assert contrast_axes.get_ylabel() == "Contrast..." | ||
| # | ||
| # | ||
| # | ||
| # | ||
| # | ||
| #def test_gardner_altman_paired(): | ||
| # base_mean = np.random.randint(-5, 5) | ||
| # seed, ptp, df = create_dummy_dataset(base_mean=base_mean) | ||
| # | ||
| # | ||
| # # Check that the plot data matches the raw data. | ||
| # two_group_paired = load(df, idx=("1", "2"), id_col="idcol", paired=True) | ||
| # f1 = two_group_paired.mean_diff.plot() | ||
| # rawswarm_axes = f1.axes[0] | ||
| # contrast_axes = f1.axes[1] | ||
| # assert df['1'].tolist() == [l.get_ydata()[0] for l in rawswarm_axes.lines] | ||
| # assert df['2'].tolist() == [l.get_ydata()[1] for l in rawswarm_axes.lines] | ||
| # | ||
| # | ||
| # # Check that id_col must be specified. | ||
| # err_to_catch = "`id_col` must be specified if `is_paired` is set to True." | ||
| # with pytest.raises(IndexError, match=err_to_catch): | ||
| # this_will_not_work = load(df, idx=("1", "2"), paired=True) |