def _plot_imp_map(
self,
run_datetime,
title,
cbar_label,
polygon_file=None,
polygon_file_crs="epsg:4326",
proj=ccrs.PlateCarree(),
figsize=(9, 13),
adapt_fontsize=True,
):
# select hazard with run_datetime
# pylint: disable=protected-access
if run_datetime is None:
run_datetime = self.run_datetime[0]
haz_ind = np.argwhere(np.isin(self.run_datetime, run_datetime))[0][0]
# tryout new plot with right projection
extend = "neither"
value = self._impact[haz_ind].eai_exp
# value[np.invert(mask)] = np.nan
coord = self._impact[haz_ind].coord_exp
# Generate array of values used in each subplot
array_sub = value
shapes = True
if not polygon_file:
shapes = False
var_name = cbar_label
geo_coord = coord
num_im, list_arr = u_plot._get_collection_arrays(array_sub)
list_tit = to_list(num_im, title, "title")
list_name = to_list(num_im, var_name, "var_name")
list_coord = to_list(num_im, geo_coord, "geo_coord")
kwargs = dict()
kwargs["cmap"] = CMAP_IMPACT
kwargs["s"] = 5
kwargs["marker"] = ","
kwargs["norm"] = BoundaryNorm(
np.append(
np.append([0], [10**x for x in np.arange(0, 2.9, 2.9 / 9)]),
[10**x for x in np.arange(3, 7, 4 / 90)],
),
CMAP_IMPACT.N,
clip=True,
)
# Generate each subplot
fig, axis_sub, _fontsize = u_plot.make_map(
num_im, proj=proj, figsize=figsize, adapt_fontsize=adapt_fontsize)
if not isinstance(axis_sub, np.ndarray):
axis_sub = np.array([[axis_sub]])
fig.set_size_inches(9, 8)
for array_im, axis, tit, name, coord in zip(list_arr,
axis_sub.flatten(),
list_tit, list_name,
list_coord):
if coord.shape[0] != array_im.size:
raise ValueError("Size mismatch in input array: %s != %s." %
(coord.shape[0], array_im.size))
# Binned image with coastlines
extent = u_plot._get_borders(coord)
axis.set_extent((extent), ccrs.PlateCarree())
hex_bin = axis.scatter(coord[:, 1],
coord[:, 0],
c=array_im,
transform=ccrs.PlateCarree(),
**kwargs)
if shapes:
# add warning regions
shp = shapereader.Reader(polygon_file)
transformer = pyproj.Transformer.from_crs(
polygon_file_crs,
self._impact[haz_ind].crs,
always_xy=True)
for geometry, _ in zip(shp.geometries(), shp.records()):
geom2 = shapely.ops.transform(transformer.transform,
geometry)
axis.add_geometries(
[geom2],
crs=ccrs.PlateCarree(),
facecolor="none",
edgecolor="gray",
)
else: # add country boundaries
u_plot.add_shapes(axis)
# Create colorbar in this axis
cbax = make_axes_locatable(axis).append_axes("bottom",
size="6.5%",
pad=0.3,
axes_class=plt.Axes)
cbar = plt.colorbar(hex_bin,
cax=cbax,
orientation="horizontal",
extend=extend)
cbar.set_label(name)
cbar.formatter.set_scientific(False)
cbar.set_ticks([0, 1000, 10000, 100000, 1000000])
cbar.set_ticklabels(
["0", "1 000", "10 000", "100 000", "1 000 000"])
title_position = {
"model_text": [0.02, 0.85],
"explain_text": [0.02, 0.81],
"event_day": [0.98, 0.85],
"run_start": [0.98, 0.81],
}
left_right = {
"model_text": "left",
"explain_text": "left",
"event_day": "right",
"run_start": "right",
}
color = {
"model_text": "k",
"explain_text": "k",
"event_day": "r",
"run_start": "k",
}
for t_i in tit:
plt.figtext(
title_position[t_i][0],
title_position[t_i][1],
tit[t_i],
fontsize="xx-large",
color=color[t_i],
ha=left_right[t_i],
)
fig.tight_layout()
fig.subplots_adjust(top=0.8)
return fig, axis_sub
def _plot_exc_prob(
self,
run_datetime,
threshold,
title,
cbar_label,
proj=ccrs.PlateCarree(),
polygon_file=None,
polygon_file_crs="epsg:4326",
mask=None,
figsize=(9, 13),
adapt_fontsize=True,
):
"""plot the probability of reaching a threshold"""
# select hazard with run_datetime
# pylint: disable=protected-access
if run_datetime is None:
run_datetime = self.run_datetime[0]
haz_ind = np.argwhere(np.isin(self.run_datetime, run_datetime))[0][0]
extend = "neither"
value = np.squeeze(
np.asarray(
(self._impact[haz_ind].imp_mat > threshold).sum(axis=0) /
self._impact[haz_ind].event_id.size))
if mask is not None:
value[np.invert(mask)] = np.nan
coord = self._impact[haz_ind].coord_exp
# Generate array of values used in each subplot
array_sub = value
shapes = True
if not polygon_file:
shapes = False
var_name = cbar_label
geo_coord = coord
num_im, list_arr = u_plot._get_collection_arrays(array_sub)
list_tit = to_list(num_im, title, "title")
list_name = to_list(num_im, var_name, "var_name")
list_coord = to_list(num_im, geo_coord, "geo_coord")
kwargs = dict()
kwargs["cmap"] = CMAP_WARNPROB
kwargs["s"] = 5
kwargs["marker"] = ","
kwargs["norm"] = BoundaryNorm(np.linspace(0, 1, 11),
CMAP_WARNPROB.N,
clip=True)
# Generate each subplot
fig, axis_sub, _fontsize = u_plot.make_map(
num_im, proj=proj, figsize=figsize, adapt_fontsize=adapt_fontsize)
if not isinstance(axis_sub, np.ndarray):
axis_sub = np.array([[axis_sub]])
fig.set_size_inches(9, 8)
for array_im, axis, tit, name, coord in zip(list_arr,
axis_sub.flatten(),
list_tit, list_name,
list_coord):
if coord.shape[0] != array_im.size:
raise ValueError("Size mismatch in input array: %s != %s." %
(coord.shape[0], array_im.size))
hex_bin = axis.scatter(coord[:, 1],
coord[:, 0],
c=array_im,
transform=ccrs.PlateCarree(),
**kwargs)
if shapes:
# add warning regions
shp = shapereader.Reader(polygon_file)
transformer = pyproj.Transformer.from_crs(
polygon_file_crs,
self._impact[haz_ind].crs,
always_xy=True)
for geometry, _ in zip(shp.geometries(), shp.records()):
geom2 = shapely.ops.transform(transformer.transform,
geometry)
axis.add_geometries(
[geom2],
crs=ccrs.PlateCarree(),
facecolor="none",
edgecolor="gray",
)
# Create colorbar in this axis
cbax = make_axes_locatable(axis).append_axes("bottom",
size="6.5%",
pad=0.3,
axes_class=plt.Axes)
cbar = plt.colorbar(hex_bin,
cax=cbax,
orientation="horizontal",
extend=extend)
cbar.set_label(name)
title_position = {
"model_text": [0.02, 0.94],
"explain_text": [0.02, 0.9],
"event_day": [0.98, 0.94],
"run_start": [0.98, 0.9],
}
left_right = {
"model_text": "left",
"explain_text": "left",
"event_day": "right",
"run_start": "right",
}
color = {
"model_text": "k",
"explain_text": "k",
"event_day": "r",
"run_start": "k",
}
for t_i in tit:
plt.figtext(
title_position[t_i][0],
title_position[t_i][1],
tit[t_i],
fontsize="xx-large",
color=color[t_i],
ha=left_right[t_i],
)
extent = u_plot._get_borders(coord)
axis.set_extent((extent), ccrs.PlateCarree())
fig.tight_layout()
return fig, axis_sub
def _plot_exc_prob(self,
run_datetime,
threshold,
title,
cbar_label,
proj=ccrs.PlateCarree(),
polygon_file=None,
polygon_file_crs='epsg:4326',
mask=None,
figsize=(9, 13)):
""" plot the probability of reaching a threshold """
# select hazard with run_datetime
if run_datetime is None:
run_datetime = self.run_datetime[0]
haz_ind = np.argwhere(np.isin(self.run_datetime, run_datetime))[0][0]
extend = 'neither'
value = np.squeeze(
np.asarray(
(self._impact[haz_ind].imp_mat > threshold).sum(axis=0) /
self._impact[haz_ind].event_id.size))
if mask is not None:
value[np.invert(mask)] = np.nan
coord = self._impact[haz_ind].coord_exp
# Generate array of values used in each subplot
array_sub = value
shapes = True
if not polygon_file:
shapes = False
var_name = cbar_label
geo_coord = coord
num_im, list_arr = u_plot._get_collection_arrays(array_sub)
list_tit = to_list(num_im, title, 'title')
list_name = to_list(num_im, var_name, 'var_name')
list_coord = to_list(num_im, geo_coord, 'geo_coord')
kwargs = dict()
kwargs['cmap'] = CMAP_WARNPROB
kwargs['s'] = 5
kwargs['marker'] = ','
kwargs['norm'] = BoundaryNorm(np.linspace(0, 1, 11),
CMAP_WARNPROB.N,
clip=True)
# Generate each subplot
fig, axis_sub = u_plot.make_map(num_im, proj=proj, figsize=figsize)
if not isinstance(axis_sub, np.ndarray):
axis_sub = np.array([[axis_sub]])
fig.set_size_inches(9, 8)
for array_im, axis, tit, name, coord in zip(list_arr,
axis_sub.flatten(),
list_tit, list_name,
list_coord):
if coord.shape[0] != array_im.size:
raise ValueError("Size mismatch in input array: %s != %s." % \
(coord.shape[0], array_im.size))
hex_bin = axis.scatter(coord[:, 1], coord[:, 0], c=array_im, \
transform=ccrs.PlateCarree(), **kwargs)
if shapes:
# add warning regions
shp = shapereader.Reader(polygon_file)
transformer = pyproj.Transformer.from_crs(
polygon_file_crs,
self._impact[haz_ind].crs,
always_xy=True)
for geometry, _ in zip(shp.geometries(), shp.records()):
geom2 = shapely.ops.transform(transformer.transform,
geometry)
axis.add_geometries([geom2], crs=ccrs.PlateCarree(), facecolor='', \
edgecolor='gray')
# Create colorbar in this axis
cbax = make_axes_locatable(axis).append_axes('bottom', size="6.5%", \
pad=0.3, axes_class=plt.Axes)
cbar = plt.colorbar(hex_bin,
cax=cbax,
orientation='horizontal',
extend=extend)
cbar.set_label(name)
title_position = {
'model_text': [0.02, 0.94],
'explain_text': [0.02, 0.9],
'event_day': [0.98, 0.94],
'run_start': [0.98, 0.9]
}
left_right = {
'model_text': 'left',
'explain_text': 'left',
'event_day': 'right',
'run_start': 'right'
}
color = {
'model_text': 'k',
'explain_text': 'k',
'event_day': 'r',
'run_start': 'k'
}
for t_i in tit:
plt.figtext(title_position[t_i][0],
title_position[t_i][1],
tit[t_i],
fontsize='xx-large',
color=color[t_i],
ha=left_right[t_i])
extent = u_plot._get_borders(coord)
axis.set_extent((extent), ccrs.PlateCarree())
return fig, axis_sub