class MatrixDisplayFilter(object):
def __init__(self, view_box, data_fields):
self.output = None
self._signalHandler = SignalHandler()
self.sigOutputChanged = self._signalHandler.sigOutputChanged
self.view_box = view_box
self.legend = None
self.colorMap = ColorMapParameter()
self.data_fields = data_fields
self.field_names = [field[0] for field in self.data_fields]
self.colorMap.setFields(self.data_fields)
self.params = Parameter.create(name='Matrix Display', type='group', children=[
self.colorMap,
{'name': 'Text format', 'type': 'str'},
{'name': 'Show Confidence', 'type': 'list', 'values': [field[0] for field in self.data_fields]},
{'name': 'log_scale', 'type': 'bool'},
])
self.params.sigTreeStateChanged.connect(self.invalidate_output)
def element_display_output(self, result, default_bgcolor):
colormap = self.colorMap
show_confidence = self.params['Show Confidence']
text_format = self.params['Text format']
self.output = {}
# if show_confidence != 'None':
# default_bgcolor = np.array([128., 128., 128., 255.])
# else:
# default_bgcolor = np.array([220., 220., 220.])
# if result['no_data'] is False:
# self.output['bgcolor'] = tuple(default_bgcolor)
# self.output['fgcolor'] = 0.6
# self.output['text'] = ''
# else:
result_vals = result.loc[:, 'metric_summary']
mappable_result = {k:v for k,v in result_vals.iteritems() if np.isscalar(v)}
color = colormap.map(mappable_result)[0]
# desaturate low confidence cells
if show_confidence != 'None':
lower, upper = result[show_confidence, 'metric_conf']
confidence = (1.0 - (upper - lower)) ** 2
color = color * confidence + default_bgcolor * (1.0 - confidence)
# invert text color for dark background
self.output['fgcolor'] = 'w' if sum(color[:3]) < 384 else 'k'
text_result = {k:FormattableNumber(v) if isinstance(v, float) else v for k, v in result_vals.iteritems()}
self.output['text'] = text_format.format(**text_result)
self.output['bgcolor'] = tuple(color)
return self.output
def colormap_legend(self):
if self.legend is not None:
self.view_box.removeItem(self.legend)
cmap_item = [cmap for cmap in self.colorMap.children() if cmap['Enabled'] is True][0]
log_scale = self.params.child('log_scale').value()
colors = cmap_item.value().color
x_min = cmap_item['Min']
x_max = cmap_item['Max']
x = np.linspace(x_min, x_max, len(colors))
name = cmap_item.name()
# units = self.colorMap.fields[name].get('units', None)
scale, prefix = pg.siScale(x_min)
# if units is not None:
# units = scale + units
# else:
# units = ''
self.legend = pg.GradientLegend([25, 300], [-20, -30])
if log_scale is True:
cmap2 = pg.ColorMap(x, colors)
self.legend.setGradient(cmap2.getGradient())
self.legend.setLabels({'%0.02f' % (a*scale):b for a,b in zip(cmap_item.value().pos, x)})
else:
self.legend.setGradient(cmap_item.value().getGradient())
self.legend.setLabels({'%0.02f' % (a*scale):b for a,b in zip(x, cmap_item.value().pos)})
self.view_box.addItem(self.legend)
def get_colormap_field(self):
color_map_fields = self.colorMap.children()
if len(color_map_fields) > 1:
field_name = [field.name() for field in color_map_fields if field['Enabled'] is True][0]
else:
field_name = color_map_fields[0].name()
return field_name
def invalidate_output(self):
self.output = None
class MatrixDisplayFilter(object):
def __init__(self, main_window, data_fields, text_fields):
self.output = None
self._signalHandler = SignalHandler()
self.sigOutputChanged = self._signalHandler.sigOutputChanged
self.view_box = main_window.matrix_widget.view_box
self.main_window = main_window
self.legend = None
self.colorMap = ColorMapParameter()
self.data_fields = data_fields
self.text_fields = text_fields
self.field_names = [field[0] for field in self.data_fields]
self.colorMap.setFields(self.data_fields)
self.params = Parameter.create(
name='Matrix Display',
type='group',
children=[
self.colorMap,
{
'name': 'Text format',
'type': 'str'
},
{
'name': 'Show Confidence',
'type': 'list',
'values': [field[0] for field in self.data_fields],
'value': 'None'
},
# {'name': 'log_scale', 'type': 'bool'},
])
self.params.sigTreeStateChanged.connect(self.invalidate_output)
self.colorMap.sigColorMapChanged.connect(self.set_default_text)
def set_default_text(self):
map_field = self.get_colormap_field()
default_text = self.text_fields.get(map_field, '')
self.params.child('Text format').setValue(default_text)
def element_display_output(self, result, default_bgcolor):
colormap = self.colorMap
show_confidence = self.params['Show Confidence']
text_format = self.params['Text format']
self.output = {}
# if show_confidence != 'None':
# default_bgcolor = np.array([128., 128., 128., 255.])
# else:
# default_bgcolor = np.array([220., 220., 220.])
# if result['no_data'] is False:
# self.output['bgcolor'] = tuple(default_bgcolor)
# self.output['fgcolor'] = 0.6
# self.output['text'] = ''
# else:
result_vals = result.loc[:, 'metric_summary']
result_vals.replace(np.nan, '')
mappable_result = {
k: v
for k, v in result_vals.iteritems() if np.isscalar(v)
}
color = colormap.map(mappable_result)[0]
# desaturate low confidence cells
if show_confidence != 'None':
lower, upper = result[show_confidence, 'metric_conf']
confidence = (1.0 - (upper - lower))**2
color = color * confidence + default_bgcolor * (1.0 - confidence)
# invert text color for dark background
self.output['fgcolor'] = 'w' if sum(color[:3]) < 384 else 'k'
text_result = {
k: FormattableNumber(v) if isinstance(v, float) else v
for k, v in result_vals.iteritems()
}
self.output['text'] = text_format.format(**text_result)
if self.output['text'] == 'nan':
self.output['text'] = ''
self.output['bgcolor'] = tuple(color)
return self.output
def colormap_legend(self):
if self.legend is not None:
self.view_box.removeItem(self.legend)
if len(self.colorMap.children()) == 0:
pg.QtGui.QMessageBox.information(
self.main_window, '',
"No Analysis ColorMap is selected, please add one and Update Results",
pg.QtGui.QMessageBox.Ok)
raise Exception("No color maps are selected.")
cmap_item = [
cmap for cmap in self.colorMap.children()
if cmap['Enabled'] is True
][0]
# log_scale = self.params.child('log_scale').value()
colors = cmap_item.value().color
x_min = cmap_item['Min']
x_max = cmap_item['Max']
x = np.linspace(x_min, x_max, len(colors))
name = cmap_item.name()
if name.endswith('Probability'):
log_scale = True
else:
log_scale = False
# units = self.colorMap.fields[name].get('units', None)
min_scale, _ = pg.siScale(x_min)
max_scale, _ = pg.siScale(x_max)
scale = min_scale if (1 / min_scale) < (1 / max_scale) else max_scale
# if units is not None:
# units = scale + units
# else:
# units = ''
self.legend = pg.GradientLegend([25, 300], [-20, -30])
if log_scale is True:
cmap2 = pg.ColorMap(x, colors)
self.legend.setGradient(cmap2.getGradient())
self.legend.setLabels({
'%0.02f' % (a * scale): b
for a, b in zip(cmap_item.value().pos, x)
})
else:
self.legend.setGradient(cmap_item.value().getGradient())
self.legend.setLabels({
'%0.02f' % (a * scale): b
for a, b in zip(x,
cmap_item.value().pos)
})
self.view_box.addItem(self.legend)
def get_colormap_field(self):
color_map_fields = self.colorMap.children()
if len(color_map_fields) == 0:
field_name = ''
elif len(color_map_fields) > 1:
field_name = [
field.name() for field in color_map_fields
if field['Enabled'] is True
][0]
else:
field_name = color_map_fields[0].name()
return field_name
def invalidate_output(self):
self.output = None
class MatrixDisplayFilter(object):
def __init__(self, view_box, data_fields):
self.output = None
self._signalHandler = SignalHandler()
self.sigOutputChanged = self._signalHandler.sigOutputChanged
self.view_box = view_box
self.legend = None
self.colorMap = ColorMapParameter()
self.data_fields = data_fields
self.field_names = [field[0] for field in self.data_fields]
self.colorMap.setFields(self.data_fields)
self.params = Parameter.create(
name='Matrix Display',
type='group',
children=[
self.colorMap,
{
'name': 'Text format',
'type': 'str'
},
{
'name': 'Show Confidence',
'type': 'list',
'values': [field[0] for field in self.data_fields]
},
{
'name': 'log_scale',
'type': 'bool'
},
])
self.params.sigTreeStateChanged.connect(self.invalidate_output)
def element_display_output(self, result, default_bgcolor):
colormap = self.colorMap
show_confidence = self.params['Show Confidence']
text_format = self.params['Text format']
self.output = {}
# if show_confidence != 'None':
# default_bgcolor = np.array([128., 128., 128., 255.])
# else:
# default_bgcolor = np.array([220., 220., 220.])
# if result['no_data'] is False:
# self.output['bgcolor'] = tuple(default_bgcolor)
# self.output['fgcolor'] = 0.6
# self.output['text'] = ''
# else:
result_vals = result.loc[:, 'metric_summary']
mappable_result = {
k: v
for k, v in result_vals.iteritems() if np.isscalar(v)
}
color = colormap.map(mappable_result)[0]
# desaturate low confidence cells
if show_confidence != 'None':
lower, upper = result[show_confidence, 'metric_conf']
confidence = (1.0 - (upper - lower))**2
color = color * confidence + default_bgcolor * (1.0 - confidence)
# invert text color for dark background
self.output['fgcolor'] = 'w' if sum(color[:3]) < 384 else 'k'
text_result = {
k: FormattableNumber(v) if isinstance(v, float) else v
for k, v in result_vals.iteritems()
}
self.output['text'] = text_format.format(**text_result)
self.output['bgcolor'] = tuple(color)
return self.output
def colormap_legend(self):
if self.legend is not None:
self.view_box.removeItem(self.legend)
cmap_item = [
cmap for cmap in self.colorMap.children()
if cmap['Enabled'] is True
][0]
log_scale = self.params.child('log_scale').value()
colors = cmap_item.value().color
x_min = cmap_item['Min']
x_max = cmap_item['Max']
x = np.linspace(x_min, x_max, len(colors))
name = cmap_item.name()
# units = self.colorMap.fields[name].get('units', None)
scale, prefix = pg.siScale(x_min)
# if units is not None:
# units = scale + units
# else:
# units = ''
self.legend = pg.GradientLegend([25, 300], [-20, -30])
if log_scale is True:
cmap2 = pg.ColorMap(x, colors)
self.legend.setGradient(cmap2.getGradient())
self.legend.setLabels({
'%0.02f' % (a * scale): b
for a, b in zip(cmap_item.value().pos, x)
})
else:
self.legend.setGradient(cmap_item.value().getGradient())
self.legend.setLabels({
'%0.02f' % (a * scale): b
for a, b in zip(x,
cmap_item.value().pos)
})
self.view_box.addItem(self.legend)
def get_colormap_field(self):
color_map_fields = self.colorMap.children()
if len(color_map_fields) > 1:
field_name = [
field.name() for field in color_map_fields
if field['Enabled'] is True
][0]
else:
field_name = color_map_fields[0].name()
return field_name
def invalidate_output(self):
self.output = None