def plot(self, objects=None, title="Reverse cumulative distribution of |residual|", show=False):
"""
Plot function for ModelPerformance class.
:param objects: object of ModelPerformance class or list or tuple containing such objects
:param title: str, the plot's title
:param show: True shows the plot, False returns the plotly Figure object that can be edited or saved using `write_image()` method
:return None or plotly Figure (see :param show)
"""
# are there any other objects to plot?
if objects is None:
n = 1
_residuals_df_list = [self.residuals.copy()]
elif isinstance(objects, self.__class__): # allow for objects to be a single element
n = 2
_residuals_df_list = [self.residuals.copy(), objects.residuals.copy()]
else: # objects as tuple or array
n = len(objects) + 1
_residuals_df_list = [self.residuals.copy()]
for ob in objects:
if not isinstance(ob, self.__class__):
raise TypeError("Some explanations aren't of ModelPerformance class")
_residuals_df_list += [ob.residuals.copy()]
fig = go.Figure()
for i in range(n):
_residuals_df = _residuals_df_list[i]
_abs_residuals = np.abs(_residuals_df['residuals'])
_unique_abs_residuals = np.unique(_abs_residuals)
fig.add_scatter(
x=_unique_abs_residuals,
y=1 - ecdf(_abs_residuals)(_unique_abs_residuals),
line_shape='hv',
name=_residuals_df.iloc[0, _residuals_df.columns.get_loc('label')]
)
fig.update_yaxes({'type': 'linear', 'gridwidth': 2, 'zeroline': False, 'automargin': True, 'ticks': 'outside',
'tickcolor': 'white', 'ticklen': 10, 'fixedrange': True, 'tickformat': ',.0%'})
fig.update_xaxes({'type': 'linear', 'gridwidth': 2, 'zeroline': False, 'automargin': True, 'ticks': "outside",
'tickcolor': 'white', 'ticklen': 10, 'fixedrange': True, 'title_text': '|residual|'})
fig.update_layout(title_text=title, title_x=0.15, font={'color': "#371ea3"}, template="none",
margin={'t': 78, 'b': 71, 'r': 30})
if show:
fig.show(config={'displaylogo': False, 'staticPlot': False,
'modeBarButtonsToRemove': ['sendDataToCloud', 'lasso2d', 'autoScale2d', 'select2d',
'zoom2d',
'pan2d', 'zoomIn2d', 'zoomOut2d', 'resetScale2d',
'toggleSpikelines', 'hoverCompareCartesian',
'hoverClosestCartesian']})
else:
return fig
def plot(self,
objects=None,
title="Reverse cumulative distribution of |residual|",
show=False):
"""Plot the Model Performance explanation
Parameters
-----------
objects : ModelPerformance object or array_like of ModelPerformance objects
Additional objects to plot (default is None).
title : str, optional
Title of the plot (default depends on the `type` attribute).
show : bool, optional
True shows the plot; False returns the plotly Figure object that can be
edited or saved using the `write_image()` method (default is True).
Returns
-----------
None or plotly.graph_objects.Figure
Return figure that can be edited or saved. See `show` parameter.
"""
# are there any other objects to plot?
if objects is None:
_df_list = [self.residuals.copy()]
elif isinstance(
objects,
self.__class__): # allow for objects to be a single element
_df_list = [self.residuals.copy(), objects.residuals.copy()]
else: # objects as tuple or array
_df_list = [self.residuals.copy()]
for ob in objects:
if not isinstance(ob, self.__class__):
raise TypeError(
"Some explanations aren't of ModelPerformance class")
_df_list += [ob.residuals.copy()]
colors = get_default_colors(len(_df_list), 'line')
fig = go.Figure()
for i, _df in enumerate(_df_list):
_abs_residuals = np.abs(_df['residuals'])
_unique_abs_residuals = np.unique(_abs_residuals)
fig.add_scatter(x=_unique_abs_residuals,
y=1 - ecdf(_abs_residuals)(_unique_abs_residuals),
line_shape='hv',
name=_df.iloc[0, _df.columns.get_loc('label')],
marker=dict(color=colors[i]))
fig.update_yaxes({
'type': 'linear',
'gridwidth': 2,
'zeroline': False,
'automargin': True,
'ticks': 'outside',
'tickcolor': 'white',
'ticklen': 10,
'fixedrange': True,
'tickformat': ',.0%'
})
fig.update_xaxes({
'type': 'linear',
'gridwidth': 2,
'zeroline': False,
'automargin': True,
'ticks': "outside",
'tickcolor': 'white',
'ticklen': 10,
'fixedrange': True,
'title_text': '|residual|'
})
fig.update_layout(title_text=title,
title_x=0.15,
font={'color': "#371ea3"},
template="none",
margin={
't': 78,
'b': 71,
'r': 30
})
if show:
fig.show(
config={
'displaylogo':
False,
'staticPlot':
False,
'toImageButtonOptions': {
'height': None,
'width': None,
},
'modeBarButtonsToRemove': [
'sendDataToCloud', 'lasso2d', 'autoScale2d',
'select2d', 'zoom2d', 'pan2d', 'zoomIn2d', 'zoomOut2d',
'resetScale2d', 'toggleSpikelines',
'hoverCompareCartesian', 'hoverClosestCartesian'
]
})
else:
return fig
def plot(self,
objects=None,
title="Reverse cumulative distribution of |residual|",
show=False):
"""Plot the Model Performance explanation
Parameters
-----------
objects : ModelPerformance object or array_like of ModelPerformance objects
Additional objects to plot (default is None).
title : str, optional
Title of the plot (default depends on the `type` attribute).
show : bool, optional
True shows the plot; False returns the plotly Figure object that can be
edited or saved using the `write_image()` method (default is True).
Returns
-----------
None or plotly.graph_objects.Figure
Return figure that can be edited or saved. See `show` parameter.
"""
# are there any other objects to plot?
if objects is None:
_df_list = [self.residuals.copy()]
elif isinstance(
objects,
self.__class__): # allow for objects to be a single element
_df_list = [self.residuals.copy(), objects.residuals.copy()]
elif isinstance(objects, (list, tuple)): # objects as tuple or array
_df_list = [self.residuals.copy()]
for ob in objects:
_global_checks.global_check_object_class(ob, self.__class__)
_df_list += [ob.residuals.copy()]
else:
_global_checks.global_raise_objects_class(objects, self.__class__)
colors = _theme.get_default_colors(len(_df_list), 'line')
fig = go.Figure()
for i, _df in enumerate(_df_list):
_abs_residuals = np.abs(_df['residuals'])
_unique_abs_residuals = np.unique(_abs_residuals)
fig.add_scatter(x=_unique_abs_residuals,
y=1 - ecdf(_abs_residuals)(_unique_abs_residuals),
line_shape='hv',
name=_df.iloc[0, _df.columns.get_loc('label')],
marker=dict(color=colors[i]))
fig.update_yaxes({
'type': 'linear',
'gridwidth': 2,
'zeroline': False,
'automargin': True,
'ticks': 'outside',
'tickcolor': 'white',
'ticklen': 10,
'fixedrange': True,
'tickformat': ',.0%'
})
fig.update_xaxes({
'type': 'linear',
'gridwidth': 2,
'zeroline': False,
'automargin': True,
'ticks': "outside",
'tickcolor': 'white',
'ticklen': 10,
'fixedrange': True,
'title_text': '|residual|'
})
fig.update_layout(title_text=title,
title_x=0.15,
font={'color': "#371ea3"},
template="none",
margin={
't': 78,
'b': 71,
'r': 30
})
if show:
fig.show(config=_theme.get_default_config())
else:
return fig