def _process(self, p, element, ranges={}):
# Creates a unified Dataset.data attribute
# to draw the data from
if isinstance(element.data, np.ndarray):
if 'dataframe' in Dataset.datatype:
el_data = element.table('dataframe')
else:
el_data = element.table('dictionary')
else:
el_data = element.data
# Get dimensions to plot against each other
dims = [
d for d in element.dimensions() if _is_number(element.range(d)[0])
]
permuted_dims = [(d1, d2) for d1 in dims for d2 in dims[::-1]]
data = {}
for d1, d2 in permuted_dims:
if d1 == d2:
if p.diagonal_type is Histogram:
bin_range = ranges.get(d1.name, element.range(d1))
el = element.hist(
dimension=d1.name, bin_range=bin_range,
adjoin=False)(norm=dict(axiswise=True, framewise=True))
else:
values = element.dimension_values(d1)
el = p.diagonal_type(values, vdims=[d1])
else:
el = p.chart_type(el_data,
kdims=[d1],
vdims=[d2],
datatype=['dataframe', 'dictionary'])
data[(d1.name, d2.name)] = el
return data
def _process(self, p, element, ranges={}):
# Creates a unified Columns.data attribute
# to draw the data from
if isinstance(element.data, np.ndarray):
if 'dataframe' in Columns.datatype:
el_data = element.table('dataframe')
else:
el_data = element.table('ndelement')
el_data = element.data
# Get dimensions to plot against each other
dims = [d for d in element.dimensions()
if _is_number(element.range(d)[0])]
permuted_dims = [(d1, d2) for d1 in dims
for d2 in dims[::-1]]
data = {}
for d1, d2 in permuted_dims:
if d1 == d2:
if p.diagonal_type is Histogram:
bin_range = ranges.get(d1.name, element.range(d1))
el = element.hist(dimension=d1.name,
bin_range=bin_range,
adjoin=False)
else:
values = element.dimension_values(d1)
el = p.diagonal_type(values, kdims=[d1])
else:
el = p.chart_type(el_data, kdims=[d1],
vdims=[d2])
data[(d1.name, d2.name)] = el
return data
def ObjectSelector(pobj):
"""
Determines param.ObjectSelector widget depending on whether all values
are numeric.
"""
options = list(pobj.objects.values()) if isinstance(pobj.objects, dict) else pobj.objects
if options and all(param._is_number(o) for o in options):
return DiscreteSlider
else:
return Select
def _process(self, p, element, ranges={}):
# Creates a unified Dataset.data attribute
# to draw the data from
if isinstance(element.data, np.ndarray):
if 'dataframe' in Dataset.datatype:
el_data = element.table('dataframe')
else:
el_data = element.table('dictionary')
else:
el_data = element.data
# Get dimensions to plot against each other
types = (str, basestring, np.str_, np.object_) + datetime_types
dims = [
d for d in element.dimensions() if _is_number(element.range(d)[0])
and not issubclass(element.get_dimension_type(d), types)
]
permuted_dims = [(d1, d2) for d1 in dims for d2 in dims[::-1]]
# Convert Histogram type to operation to avoid one case in the if below.
if p.diagonal_type is Histogram:
p.diagonal_type = None
p.diagonal_operation = histogram
data = {}
for d1, d2 in permuted_dims:
if d1 == d2:
if p.diagonal_type is not None:
if p.diagonal_type._auto_indexable_1d:
el = p.diagonal_type(
el_data,
kdims=[d1],
vdims=[d2],
datatype=['dataframe', 'dictionary'])
else:
values = element.dimension_values(d1)
el = p.diagonal_type(values, kdims=[d1])
elif p.diagonal_operation is histogram or isinstance(
p.diagonal_operation, histogram):
bin_range = ranges.get(d1.name, element.range(d1))
el = p.diagonal_operation(element,
dimension=d1.name,
bin_range=bin_range)
else:
el = p.diagonal_operation(element, dimension=d1.name)
else:
kdims, vdims = ([d1, d2],
[]) if len(p.chart_type.kdims) == 2 else (d1,
d2)
el = p.chart_type(el_data,
kdims=kdims,
vdims=vdims,
datatype=['dataframe', 'dictionary'])
data[(d1.name, d2.name)] = el
return data
def widget_from_iterable(o, name):
"""Make widgets from an iterable. This should not be done for
a string or tuple."""
# Select expects a dict or list, so we convert an arbitrary
# iterable to either of those.
values = list(o.values()) if isinstance(o, Mapping) else list(o)
widget_type = DiscreteSlider if all(param._is_number(v) for v in values) else Select
if isinstance(o, (list, dict)):
return widget_type(options=o, name=name)
elif isinstance(o, Mapping):
return widget_type(options=list(o.items()), name=name)
else:
return widget_type(options=list(o), name=name)
def _process(self, p, element, ranges={}):
# Creates a unified Dataset.data attribute
# to draw the data from
if isinstance(element.data, np.ndarray):
if 'dataframe' in Dataset.datatype:
el_data = element.table('dataframe')
else:
el_data = element.table('dictionary')
else:
el_data = element.data
# Get dimensions to plot against each other
dims = [
d for d in element.dimensions() if _is_number(element.range(d)[0])
]
permuted_dims = [(d1, d2) for d1 in dims for d2 in dims[::-1]]
# Convert Histogram type to operation to avoid one case in the if below.
if p.diagonal_type is Histogram:
p.diagonal_type = None
p.diagonal_operation = histogram
data = {}
for d1, d2 in permuted_dims:
if d1 == d2:
if p.diagonal_type is not None:
if p.diagonal_type._auto_indexable_1d:
el = p.diagonal_type(
el_data,
kdims=[d1],
vdims=[d2],
datatype=['dataframe', 'dictionary'])
else:
values = element.dimension_values(d1)
el = p.diagonal_type(values, vdims=[d1])
elif p.diagonal_operation is histogram or isinstance(
p.diagonal_operation, histogram):
bin_range = ranges.get(d1.name, element.range(d1))
opts = dict(axiswise=True, framewise=True)
el = p.diagonal_operation(element,
dimension=d1.name,
bin_range=bin_range)(norm=opts)
else:
el = p.diagonal_operation(element, dimension=d1.name)
else:
el = p.chart_type(el_data,
kdims=[d1],
vdims=[d2],
datatype=['dataframe', 'dictionary'])
data[(d1.name, d2.name)] = el
return data
def _process(self, p, element, ranges={}):
# Creates a unified Dataset.data attribute
# to draw the data from
if isinstance(element.data, np.ndarray):
if 'dataframe' in Dataset.datatype:
el_data = element.table('dataframe')
else:
el_data = element.table('dictionary')
else:
el_data = element.data
# Get dimensions to plot against each other
types = (str, basestring, np.str_, np.object_)+datetime_types
dims = [d for d in element.dimensions()
if _is_number(element.range(d)[0]) and
not issubclass(element.get_dimension_type(d), types)]
permuted_dims = [(d1, d2) for d1 in dims
for d2 in dims[::-1]]
# Convert Histogram type to operation to avoid one case in the if below.
if p.diagonal_type is Histogram:
p.diagonal_type = None
p.diagonal_operation = histogram
data = {}
for d1, d2 in permuted_dims:
if d1 == d2:
if p.diagonal_type is not None:
if p.diagonal_type._auto_indexable_1d:
el = p.diagonal_type(el_data, kdims=[d1], vdims=[d2],
datatype=['dataframe', 'dictionary'])
else:
values = element.dimension_values(d1)
el = p.diagonal_type(values, kdims=[d1])
elif p.diagonal_operation is histogram or isinstance(p.diagonal_operation, histogram):
bin_range = ranges.get(d1.name, element.range(d1))
el = p.diagonal_operation(element, dimension=d1.name, bin_range=bin_range)
else:
el = p.diagonal_operation(element, dimension=d1.name)
else:
kdims, vdims = ([d1, d2], []) if len(p.chart_type.kdims) == 2 else (d1, d2)
el = p.chart_type(el_data, kdims=kdims, vdims=vdims,
datatype=['dataframe', 'dictionary'])
data[(d1.name, d2.name)] = el
return data