9c9070aea2
* Do not derive from unittest.TestCase (not needed for pytest) * assertRaises -> pytest.raises * Simplify test_empty_dmatrix with test parametrization * setUpClass -> setup_class, tearDownClass -> teardown_class * Don't import unittest; import pytest * Use plain assert * Use parametrized tests in more places * Fix test_gpu_with_sklearn.py * Put back run_empty_dmatrix_reg / run_empty_dmatrix_cls * Fix test_eta_decay_gpu_hist * Add parametrized tests for monotone constraints * Fix test names * Remove test parametrization * Revise test_slice to be not flaky
76 lines
2.6 KiB
Python
76 lines
2.6 KiB
Python
# -*- coding: utf-8 -*-
|
|
import numpy as np
|
|
import xgboost as xgb
|
|
import testing as tm
|
|
|
|
import pytest
|
|
|
|
try:
|
|
import matplotlib
|
|
matplotlib.use('Agg')
|
|
from matplotlib.axes import Axes
|
|
from graphviz import Source
|
|
except ImportError:
|
|
pass
|
|
|
|
pytestmark = pytest.mark.skipif(**tm.no_multiple(tm.no_matplotlib(),
|
|
tm.no_graphviz()))
|
|
|
|
dpath = 'demo/data/agaricus.txt.train'
|
|
|
|
|
|
class TestPlotting:
|
|
def test_plotting(self):
|
|
m = xgb.DMatrix(dpath)
|
|
booster = xgb.train({'max_depth': 2, 'eta': 1,
|
|
'objective': 'binary:logistic'}, m,
|
|
num_boost_round=2)
|
|
|
|
ax = xgb.plot_importance(booster)
|
|
assert isinstance(ax, Axes)
|
|
assert ax.get_title() == 'Feature importance'
|
|
assert ax.get_xlabel() == 'F score'
|
|
assert ax.get_ylabel() == 'Features'
|
|
assert len(ax.patches) == 4
|
|
|
|
ax = xgb.plot_importance(booster, color='r',
|
|
title='t', xlabel='x', ylabel='y')
|
|
assert isinstance(ax, Axes)
|
|
assert ax.get_title() == 't'
|
|
assert ax.get_xlabel() == 'x'
|
|
assert ax.get_ylabel() == 'y'
|
|
assert len(ax.patches) == 4
|
|
for p in ax.patches:
|
|
assert p.get_facecolor() == (1.0, 0, 0, 1.0) # red
|
|
|
|
ax = xgb.plot_importance(booster, color=['r', 'r', 'b', 'b'],
|
|
title=None, xlabel=None, ylabel=None)
|
|
assert isinstance(ax, Axes)
|
|
assert ax.get_title() == ''
|
|
assert ax.get_xlabel() == ''
|
|
assert ax.get_ylabel() == ''
|
|
assert len(ax.patches) == 4
|
|
assert ax.patches[0].get_facecolor() == (1.0, 0, 0, 1.0) # red
|
|
assert ax.patches[1].get_facecolor() == (1.0, 0, 0, 1.0) # red
|
|
assert ax.patches[2].get_facecolor() == (0, 0, 1.0, 1.0) # blue
|
|
assert ax.patches[3].get_facecolor() == (0, 0, 1.0, 1.0) # blue
|
|
|
|
g = xgb.to_graphviz(booster, num_trees=0)
|
|
assert isinstance(g, Source)
|
|
|
|
ax = xgb.plot_tree(booster, num_trees=0)
|
|
assert isinstance(ax, Axes)
|
|
|
|
def test_importance_plot_lim(self):
|
|
np.random.seed(1)
|
|
dm = xgb.DMatrix(np.random.randn(100, 100), label=[0, 1] * 50)
|
|
bst = xgb.train({}, dm)
|
|
assert len(bst.get_fscore()) == 71
|
|
ax = xgb.plot_importance(bst)
|
|
assert ax.get_xlim() == (0., 11.)
|
|
assert ax.get_ylim() == (-1., 71.)
|
|
|
|
ax = xgb.plot_importance(bst, xlim=(0, 5), ylim=(10, 71))
|
|
assert ax.get_xlim() == (0., 5.)
|
|
assert ax.get_ylim() == (10., 71.)
|