def setUp(self): self.path_prefix = os.path.dirname(visualization.__file__) + \ '/tests/images/' np.random.seed(0) self.X, self.y = make_classification(n_features=2, n_redundant=0, random_state=0) train_indices = np.random.randint(0, len(self.X), size=20) cand_indices = np.setdiff1d(np.arange(len(self.X)), train_indices) self.X_train = self.X[train_indices] self.y_train = self.y[train_indices] self.X_cand = self.X[cand_indices] self.clf = PWC() self.clf.fit(self.X_train, self.y_train) self.qs = UncertaintySampling() self.qs_dict = {'clf': self.clf, 'X': self.X_train, 'y': self.y_train} x1_min = min(self.X[:, 0]) x1_max = max(self.X[:, 0]) x2_min = min(self.X[:, 1]) x2_max = max(self.X[:, 1]) self.bound = [[x1_min, x2_min], [x1_max, x2_max]] self.cmap = 'jet' testing.set_font_settings_for_testing() testing.set_reproducibility_for_testing() testing.setup()
def setUp(self): self.path_prefix = os.path.dirname(visualization.__file__) + \ '/multi/tests/images/' self.X, self.y_true = make_classification(n_features=2, n_redundant=0, random_state=0) self.n_samples = self.X.shape[0] self.n_annotators = 5 rng = np.random.default_rng(seed=0) noise = rng.binomial(n=1, p=.2, size=(self.n_samples, self.n_annotators)) self.y = (self.y_true.reshape(-1, 1) + noise) % 2 estimators = [] for a in range(self.n_annotators): estimators.append((f'pwc_{a}', PWC(random_state=0))) self.clf_multi = MultiAnnotEnsemble(estimators=estimators, voting='soft') self.clf = PWC(random_state=0) self.ma_qs = IEThresh(random_state=0, n_annotators=self.n_annotators) testing.set_font_settings_for_testing() testing.set_reproducibility_for_testing() testing.setup()
from pathlib import Path from itertools import repeat, chain, combinations import pytest from matplotlib.testing import setup setup() from matplotlib.testing.compare import compare_images import matplotlib.pyplot as plt import numpy as np import pandas as pd from anndata import AnnData import scanpy as sc HERE: Path = Path(__file__).parent ROOT = HERE / '_images' FIGS = HERE / 'figures' sc.pl.set_rcParams_defaults() sc.set_figure_params(dpi=40, color_map='viridis') ##### # Test images are saved under the folder ./figures # if test images need to be updated, simply copy them from # the ./figures folder to ./_images/ def test_heatmap(image_comparer): save_and_compare_images = image_comparer(ROOT, FIGS, tol=15)
def setupMpl(): setup() plt.clf()
def clean_mpl(): rcdefaults() pyplot.close("all") setup() yield pyplot.close("all")