def test_mpl_bokeh_mpl_via_builders_opts_method(self):
img = Image(np.random.rand(10,10))
mpl_opts = opts.Image(cmap='Blues', backend='matplotlib')
bokeh_opts = opts.Image(cmap='Purple', backend='bokeh')
self.assertEqual(mpl_opts.kwargs['backend'], 'matplotlib')
self.assertEqual(bokeh_opts.kwargs['backend'], 'bokeh')
img.opts(mpl_opts, bokeh_opts)
mpl_lookup = Store.lookup_options('matplotlib', img, 'style').options
self.assertEqual(mpl_lookup['cmap'], 'Blues')
bokeh_lookup = Store.lookup_options('bokeh', img, 'style').options
self.assertEqual(bokeh_lookup['cmap'], 'Purple')
self.assert_output_options_group_empty(img)
def test_opts_clear_clone(self):
im = Image(np.random.rand(10, 10))
styled_im = im.opts(style=dict(cmap='jet',
interpolation='nearest',
option1='A',
option2='B'),
clone=False)
self.assertEqual(
self.lookup_options(im, 'style').options, {
'cmap': 'jet',
'interpolation': 'nearest',
'option1': 'A',
'option2': 'B'
})
assert styled_im is im
cleared = im.opts.clear(clone=True)
assert cleared is not im
self.assertEqual(
self.lookup_options(im, 'style').options, {
'cmap': 'jet',
'interpolation': 'nearest',
'option1': 'A',
'option2': 'B'
})
cleared_options = self.lookup_options(cleared, 'style').options
self.assertEqual(
not any(k in ['option1', 'option2']
for k in cleared_options.keys()), True)
def test_opts_method_with_utility(self):
im = Image(np.random.rand(10,10))
imopts = opts.Image(cmap='Blues')
styled_im = im.opts(imopts)
assert styled_im is im
self.assertEqual(self.lookup_options(im, 'style').options,
{'cmap': 'Blues', 'interpolation': 'nearest'})
def test_opts_method_with_utility(self):
im = Image(np.random.rand(10,10))
imopts = opts.Image(cmap='Blues')
styled_im = im.opts(imopts)
assert styled_im is im
self.assertEqual(self.lookup_options(im, 'style').options,
{'cmap': 'Blues', 'interpolation': 'nearest'})
def test_simple_clone_disabled(self):
im = Image(np.random.rand(10,10))
styled_im = im.opts(interpolation='nearest', cmap='jet', clone=False)
self.assertEqual(self.lookup_options(im, 'plot').options, {})
self.assertEqual(self.lookup_options(styled_im, 'plot').options, {})
assert styled_im is im
self.assertEqual(self.lookup_options(im, 'style').options,
{'cmap': 'jet', 'interpolation': 'nearest'})
def test_simple_clone_disabled(self):
im = Image(np.random.rand(10,10))
styled_im = im.opts(interpolation='nearest', cmap='jet', clone=False)
self.assertEqual(self.lookup_options(im, 'plot').options, {})
self.assertEqual(self.lookup_options(styled_im, 'plot').options, {})
assert styled_im is im
self.assertEqual(self.lookup_options(im, 'style').options,
{'cmap': 'jet', 'interpolation': 'nearest'})
def test_simple_opts_clone_enabled(self):
im = Image(np.random.rand(10, 10))
styled_im = im.opts(interpolation='nearest', cmap='jet', clone=True)
self.assertEqual(self.lookup_options(im, 'plot').options, {})
self.assertEqual(self.lookup_options(styled_im, 'plot').options, {})
assert styled_im is not im
im_lookup = self.lookup_options(im, 'style').options
self.assertEqual(im_lookup['cmap'] == 'jet', False)
styled_im_lookup = self.lookup_options(styled_im, 'style').options
self.assertEqual(styled_im_lookup['cmap'] == 'jet', True)
def test_simple_opts_clone_enabled(self):
im = Image(np.random.rand(10,10))
styled_im = im.opts(interpolation='nearest', cmap='jet', clone=True)
self.assertEqual(self.lookup_options(im, 'plot').options, {})
self.assertEqual(self.lookup_options(styled_im, 'plot').options, {})
assert styled_im is not im
im_lookup = self.lookup_options(im, 'style').options
self.assertEqual(im_lookup['cmap'] == 'jet', False)
styled_im_lookup = self.lookup_options(styled_im, 'style').options
self.assertEqual(styled_im_lookup['cmap'] == 'jet', True)
def test_opts_clear(self):
im = Image(np.random.rand(10,10))
styled_im = im.opts(style=dict(cmap='jet', interpolation='nearest',
option1='A', option2='B'), clone=False)
self.assertEqual(self.lookup_options(im, 'style').options,
{'cmap': 'jet', 'interpolation': 'nearest',
'option1':'A', 'option2':'B'})
assert styled_im is im
cleared = im.opts.clear()
assert cleared is im
cleared_options = self.lookup_options(cleared, 'style').options
self.assertEqual(not any(k in ['option1', 'option2']
for k in cleared_options.keys()), True)
def test_custom_opts_to_default_inheritance(self):
"""
Checks customs inheritance backs off to default tree correctly
using .opts.
"""
options = self.initialize_option_tree()
options.Image.A.B = Options('style', alpha=0.2)
obj = Image(np.random.rand(10, 10), group='A', label='B')
expected_obj = {'alpha': 0.2, 'cmap': 'hot', 'interpolation': 'nearest'}
obj_lookup = Store.lookup_options('matplotlib', obj, 'style')
self.assertEqual(obj_lookup.kwargs, expected_obj)
# Customize this particular object
custom_obj = obj.opts(style=dict(clims=(0, 0.5)))
expected_custom_obj = dict(clims=(0,0.5), **expected_obj)
custom_obj_lookup = Store.lookup_options('matplotlib', custom_obj, 'style')
self.assertEqual(custom_obj_lookup.kwargs, expected_custom_obj)
def test_custom_opts_to_default_inheritance(self):
"""
Checks customs inheritance backs off to default tree correctly
using .opts.
"""
options = self.initialize_option_tree()
options.Image.A.B = Options('style', alpha=0.2)
obj = Image(np.random.rand(10, 10), group='A', label='B')
expected_obj = {'alpha': 0.2, 'cmap': 'hot', 'interpolation': 'nearest'}
obj_lookup = Store.lookup_options('matplotlib', obj, 'style')
self.assertEqual(obj_lookup.kwargs, expected_obj)
# Customize this particular object
custom_obj = obj.opts(style=dict(clims=(0, 0.5)))
expected_custom_obj = dict(clims=(0,0.5), **expected_obj)
custom_obj_lookup = Store.lookup_options('matplotlib', custom_obj, 'style')
self.assertEqual(custom_obj_lookup.kwargs, expected_custom_obj)
