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[coverage] covering all of gpy_plot

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mzwiessele 2015-10-11 11:57:29 +01:00
parent 21690e2408
commit 81dc576ec4
9 changed files with 58 additions and 19 deletions
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44
GPy/testing/plotting_tests.py
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@ -33,6 +33,7 @@ from nose import SkipTest
from ..util.config import config
from ..plotting import change_plotting_library
import unittest
change_plotting_library('matplotlib')
if config.get('plotting', 'library') != 'matplotlib':
@ -93,6 +94,49 @@ def _image_comparison(baseline_images, extensions=['pdf','svg','ong'], tol=11):
yield do_test
plt.close('all')
def test_figure():
np.random.seed(1239847)
from GPy.plotting import plotting_library as pl
import matplotlib
matplotlib.rcParams.update(matplotlib.rcParamsDefault)
matplotlib.rcParams[u'figure.figsize'] = (4,3)
matplotlib.rcParams[u'text.usetex'] = False
ax, _ = pl().new_canvas(num=1)
def test_func(x):
return x[:, 0].reshape(3,3)
pl().imshow_interact(ax, test_func, extent=(-1,1,-1,1), resolution=3)
ax, _ = pl().new_canvas()
def test_func_2(x):
y = x[:, 0].reshape(3,3)
anno = np.argmax(x, axis=1).reshape(3,3)
return y, anno
pl().annotation_heatmap_interact(ax, test_func_2, extent=(-1,1,-1,1), resolution=3)
pl().annotation_heatmap_interact(ax, test_func_2, extent=(-1,1,-1,1), resolution=3, imshow_kwargs=dict(interpolation='nearest'))
ax, _ = pl().new_canvas(figsize=(4,3))
x = np.linspace(0,1,100)
y = [0,1,2]
array = np.array([.4,.5])
cmap = matplotlib.colors.LinearSegmentedColormap.from_list('WhToColor', ('r', 'b'), N=array.size)
pl().fill_gradient(ax, x, y, facecolors=['r', 'g'], array=array, cmap=cmap)
try:
pl().show_canvas(ax, tight_layout=True)
except:
# macosx tight layout not stable
pl().show_canvas(ax, tight_layout=False)
ax, _ = pl().new_canvas(num=4, figsize=(4,3), projection='3d', xlabel='x', ylabel='y', zlabel='z', title='awsome title', xlim=(-1,1), ylim=(-1,1), zlim=(-3,3))
z = 2-np.abs(np.linspace(-2,2,(100)))+1
x, y = z*np.sin(np.linspace(-2*np.pi,2*np.pi,(100))), z*np.cos(np.linspace(-np.pi,np.pi,(100)))
pl().plot(ax, x, y, z, linewidth=2)
for do_test in _image_comparison(
baseline_images=['coverage_{}'.format(sub) for sub in ["imshow_interact",'annotation_interact','gradient','3d_plot',]],
extensions=extensions):
yield (do_test, )
def test_kernel():
np.random.seed(1239847)
import matplotlib