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Allow redim.label if no custom label set #1541

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merged 3 commits into from Jun 14, 2017
Merged

Allow redim.label if no custom label set #1541

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8a68214
Allow redim.label if not custom label set
philippjfr Jun 14, 2017
7b654ee
Added unit tests for Dimension relabel
philippjfr Jun 14, 2017
fa1f209
Small fix for redim.label
philippjfr Jun 14, 2017
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7 changes: 7 additions & 0 deletions holoviews/core/dimension.py
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Expand Up @@ -158,6 +158,13 @@ def value_format(self, specs=None, **values):
def range(self, specs=None, **values):
return self._redim('range', specs, **values)

def label(self, specs=None, **values):
for k, v in values.items():
dim = self.parent.get_dimension(k)
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Seems like None is returned if there is no match for dim? In which case a suitable exception/warning should be given if dim==None.

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redim doesn't validate Dimensions so you can apply it nested datastructures. That said I'd possibly be open to tightening that up when explicit specs are supplied, not in this PR though.

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Ah right, thanks for the reminder. It is annoying but I can't see a way around that issue right now...

if dim and dim.name != dim.label and dim.name != v:
raise ValueError('Cannot override an existing Dimension label')
return self._redim('label', specs, **values)

def soft_range(self, specs=None, **values):
return self._redim('soft_range', specs, **values)

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10 changes: 10 additions & 0 deletions tests/testdimensions.py
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Expand Up @@ -245,6 +245,16 @@ def test_dimensioned_redim_string(self):
redimensioned = dimensioned.clone(kdims=['Test'])
self.assertEqual(redimensioned, dimensioned.redim(x='Test'))

def test_dimensioned_redim_dict_label(self):
dimensioned = Dimensioned('Arbitrary Data', kdims=['x'])
redimensioned = dimensioned.clone(kdims=[('x', 'Test')])
self.assertEqual(redimensioned, dimensioned.redim.label(x='Test'))

def test_dimensioned_redim_dict_label_existing_error(self):
dimensioned = Dimensioned('Arbitrary Data', kdims=[('x', 'Test1')])
with self.assertRaisesRegexp(ValueError, 'Cannot override an existing Dimension label'):
dimensioned.redim.label(x='Test2')

def test_dimensioned_redim_dimension(self):
dimensioned = Dimensioned('Arbitrary Data', kdims=['x'])
redimensioned = dimensioned.clone(kdims=['Test'])
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