def test_get_climatology_line_for_reliability_curve(self):
"""Ensures correctness of get_climatology_line_for_reliability_curve."""
these_x_values, these_y_values = (
model_eval.get_climatology_line_for_reliability_curve(
MEAN_OBSERVED_LABEL))
self.assertTrue(
numpy.allclose(these_x_values,
X_VALUES_FOR_CLIMATOLOGY_LINE,
atol=TOLERANCE))
self.assertTrue(
numpy.allclose(these_y_values,
Y_VALUES_FOR_CLIMATOLOGY_LINE,
atol=TOLERANCE))
def _plot_background_of_attributes_diagram(
axes_object,
climatology,
no_skill_line_colour=DEFAULT_ZERO_BSS_COLOUR,
no_skill_line_width=DEFAULT_ZERO_BSS_WIDTH,
other_line_colour=DEFAULT_CLIMATOLOGY_COLOUR,
other_line_width=DEFAULT_CLIMATOLOGY_WIDTH):
"""Plots background (references lines and polygons) of attributes diagram.
For more on the attributes diagram, see Hsu and Murphy (1986).
BSS = Brier skill score. For more on the BSS, see
`model_evaluation.get_brier_skill_score`.
:param axes_object: Instance of `matplotlib.axes._subplots.AxesSubplot`.
:param climatology: Event frequency for the entire dataset.
:param no_skill_line_colour: Colour (in any format accepted by
`matplotlib.colors`) of no-skill line, where BSS = 0.
:param no_skill_line_width: Width (real positive number) of no-skill line.
:param other_line_colour: Colour of climatology and no-resolution lines.
:param other_line_width: Width of climatology and no-resolution lines.
"""
error_checking.assert_is_geq(climatology, 0.)
error_checking.assert_is_leq(climatology, 1.)
(x_vertices_for_left_skill_area, y_vertices_for_left_skill_area,
x_vertices_for_right_skill_area, y_vertices_for_right_skill_area
) = model_eval.get_skill_areas_in_reliability_curve(climatology)
skill_area_colour = matplotlib.colors.to_rgba(
plotting_utils.colour_from_numpy_to_tuple(no_skill_line_colour),
TRANSPARENCY_FOR_POSITIVE_BSS_AREA)
left_polygon_object = polygons.vertex_arrays_to_polygon_object(
x_vertices_for_left_skill_area, y_vertices_for_left_skill_area)
left_polygon_patch = PolygonPatch(left_polygon_object,
lw=0,
ec=skill_area_colour,
fc=skill_area_colour)
axes_object.add_patch(left_polygon_patch)
right_polygon_object = polygons.vertex_arrays_to_polygon_object(
x_vertices_for_right_skill_area, y_vertices_for_right_skill_area)
right_polygon_patch = PolygonPatch(right_polygon_object,
lw=0,
ec=skill_area_colour,
fc=skill_area_colour)
axes_object.add_patch(right_polygon_patch)
no_skill_x_coords, no_skill_y_coords = (
model_eval.get_no_skill_reliability_curve(climatology))
axes_object.plot(
no_skill_x_coords,
no_skill_y_coords,
color=plotting_utils.colour_from_numpy_to_tuple(no_skill_line_colour),
linestyle='solid',
linewidth=no_skill_line_width)
climo_x_coords, climo_y_coords = (
model_eval.get_climatology_line_for_reliability_curve(climatology))
axes_object.plot(
climo_x_coords,
climo_y_coords,
color=plotting_utils.colour_from_numpy_to_tuple(other_line_colour),
linestyle='dashed',
linewidth=other_line_width)
no_resolution_x_coords, no_resolution_y_coords = (
model_eval.get_no_resolution_line_for_reliability_curve(climatology))
axes_object.plot(
no_resolution_x_coords,
no_resolution_y_coords,
color=plotting_utils.colour_from_numpy_to_tuple(other_line_colour),
linestyle='dashed',
linewidth=other_line_width)
def _plot_background_of_attributes_diagram(axes_object, climatology):
"""Plots background (references lines and polygons) of attributes diagram.
For more on the attributes diagram, see Hsu and Murphy (1986).
BSS = Brier skill score. For more on the BSS, see
`model_evaluation.get_brier_skill_score`.
:param axes_object: Instance of `matplotlib.axes._subplots.AxesSubplot`.
:param climatology: Event frequency for the entire dataset.
"""
error_checking.assert_is_geq(climatology, 0.)
error_checking.assert_is_leq(climatology, 1.)
(x_coords_left_skill_area, y_coords_left_skill_area,
x_coords_right_skill_area, y_coords_right_skill_area
) = model_eval.get_skill_areas_in_reliability_curve(climatology)
skill_area_colour = matplotlib.colors.to_rgba(
plotting_utils.colour_from_numpy_to_tuple(ZERO_BSS_COLOUR),
POSITIVE_BSS_OPACITY)
left_polygon_object = polygons.vertex_arrays_to_polygon_object(
x_coords_left_skill_area, y_coords_left_skill_area)
left_polygon_patch = PolygonPatch(left_polygon_object,
lw=0,
ec=skill_area_colour,
fc=skill_area_colour)
axes_object.add_patch(left_polygon_patch)
right_polygon_object = polygons.vertex_arrays_to_polygon_object(
x_coords_right_skill_area, y_coords_right_skill_area)
right_polygon_patch = PolygonPatch(right_polygon_object,
lw=0,
ec=skill_area_colour,
fc=skill_area_colour)
axes_object.add_patch(right_polygon_patch)
no_skill_x_coords, no_skill_y_coords = (
model_eval.get_no_skill_reliability_curve(climatology))
axes_object.plot(
no_skill_x_coords,
no_skill_y_coords,
color=plotting_utils.colour_from_numpy_to_tuple(ZERO_BSS_COLOUR),
linestyle='solid',
linewidth=ZERO_BSS_LINE_WIDTH)
climo_x_coords, climo_y_coords = (
model_eval.get_climatology_line_for_reliability_curve(climatology))
axes_object.plot(
climo_x_coords,
climo_y_coords,
color=plotting_utils.colour_from_numpy_to_tuple(CLIMO_COLOUR),
linestyle='dashed',
linewidth=CLIMO_LINE_WIDTH)
no_resolution_x_coords, no_resolution_y_coords = (
model_eval.get_no_resolution_line_for_reliability_curve(climatology))
axes_object.plot(
no_resolution_x_coords,
no_resolution_y_coords,
color=plotting_utils.colour_from_numpy_to_tuple(CLIMO_COLOUR),
linestyle='dashed',
linewidth=CLIMO_LINE_WIDTH)
