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")
