def regress_predict(exp, field, model):
pred = model.predict(exp.data)
df = pd.DataFrame({
'Y_PRED': pred,
'Y_TRUE': exp.sample_metadata[field].values,
'SAMPLE': exp.sample_metadata[field].index.values,
'CV': 0
})
plot_scatter(df, cv=False)
return df
def test_plot_scatter(self):
res = pd.read_table(join(self.test_data_dir, 'diabetes_pred.txt'), index_col=0)
title = 'foo'
ax = plot_scatter(res, title=title)
self.assertEqual(title, ax.get_title())
cor = 'r=-0.62 p-value=0.078'
self.assertEqual(cor, ax.texts[0].get_text())
dots = []
for collection in ax.collections:
dots.append(collection.get_offsets())
assert_array_equal(np.concatenate(dots, axis=0),
res[['Y_TRUE', 'Y_PRED']].values)