def plot(self, axis=None, **kwargs):
"""Plot centroids scatter points over earth.
Parameters
----------
axis : matplotlib.axes._subplots.AxesSubplot, optional
axis to use
kwargs : optional
arguments for scatter matplotlib function
Returns
-------
axis : matplotlib.axes._subplots.AxesSubplot
"""
if self.meta and not self.coord.size:
self.set_meta_to_lat_lon()
pad = np.abs(u_coord.get_resolution(self.lat, self.lon)).min()
proj_data, _ = u_plot.get_transformation(self.crs)
proj_plot = proj_data
if isinstance(proj_data, ccrs.PlateCarree):
# use different projections for plot and data to shift the central lon in the plot
xmin, ymin, xmax, ymax = u_coord.latlon_bounds(self.lat, self.lon, buffer=pad)
proj_plot = ccrs.PlateCarree(central_longitude=0.5 * (xmin + xmax))
else:
xmin, ymin, xmax, ymax = (self.lon.min() - pad, self.lat.min() - pad,
self.lon.max() + pad, self.lat.max() + pad)
if not axis:
_, axis = u_plot.make_map(proj=proj_plot)
axis.set_extent((xmin, xmax, ymin, ymax), crs=proj_data)
u_plot.add_shapes(axis)
axis.scatter(self.lon, self.lat, transform=proj_data, **kwargs)
return axis
def plot_scatter(self,
mask=None,
ignore_zero=False,
pop_name=True,
buffer=0.0,
extend='neither',
axis=None,
figsize=(9, 13),
adapt_fontsize=True,
**kwargs):
"""Plot exposures geometry's value sum scattered over Earth's map.
The plot will we projected according to the current crs.
Parameters:
mask (np.array, optional): mask to apply to eai_exp plotted.
ignore_zero (bool, optional): flag to indicate if zero and negative
values are ignored in plot. Default: False
pop_name : bool, optional
add names of the populated places, by default True.
buffer (float, optional): border to add to coordinates. Default: 0.0.
extend (str, optional): extend border colorbar with arrows.
[ 'neither' | 'both' | 'min' | 'max' ]
axis (matplotlib.axes._subplots.AxesSubplot, optional): axis to use
figsize (tuple, optional): figure size for plt.subplots
adapt_fontsize : bool, optional
If set to true, the size of the fonts will be adapted to the size of the figure. Otherwise
the default matplotlib font size is used. Default is True.
kwargs (optional): arguments for scatter matplotlib function, e.g.
cmap='Greys'. Default: 'Wistia'
Returns:
cartopy.mpl.geoaxes.GeoAxesSubplot
"""
crs_epsg, _ = u_plot.get_transformation(self.crs)
title = self.tag.description
cbar_label = 'Value (%s)' % self.value_unit
if mask is None:
mask = np.ones((self.gdf.shape[0], ), dtype=bool)
if ignore_zero:
pos_vals = self.gdf.value[mask].values > 0
else:
pos_vals = np.ones((self.gdf.value[mask].values.size, ),
dtype=bool)
value = self.gdf.value[mask][pos_vals].values
coord = np.stack([
self.gdf.latitude[mask][pos_vals].values,
self.gdf.longitude[mask][pos_vals].values
],
axis=1)
return u_plot.geo_scatter_from_array(value,
coord,
cbar_label,
title,
pop_name,
buffer,
extend,
proj=crs_epsg,
axes=axis,
figsize=figsize,
adapt_fontsize=adapt_fontsize,
**kwargs)
def plot_raster(self, res=None, raster_res=None, save_tiff=None,
raster_f=lambda x: np.log10((np.fmax(x+1, 1))),
label='value (log10)', scheduler=None, axis=None, **kwargs):
""" Generate raster from points geometry and plot it using log10 scale:
np.log10((np.fmax(raster+1, 1))).
Parameters:
res (float, optional): resolution of current data in units of latitude
and longitude, approximated if not provided.
raster_res (float, optional): desired resolution of the raster
save_tiff (str, optional): file name to save the raster in tiff
format, if provided
raster_f (lambda function): transformation to use to data. Default:
log10 adding 1.
label (str): colorbar label
scheduler (str): used for dask map_partitions. “threads”,
“synchronous” or “processes”
axis (matplotlib.axes._subplots.AxesSubplot, optional): axis to use
kwargs (optional): arguments for imshow matplotlib function
Returns:
matplotlib.figure.Figure, cartopy.mpl.geoaxes.GeoAxesSubplot
"""
if self.meta and self.meta['height']*self.meta['width'] == len(self):
raster = self.value.values.reshape((self.meta['height'],
self.meta['width']))
# check raster starts by upper left corner
if self.latitude.values[0] < self.latitude.values[-1]:
raster = np.flip(raster, axis=0)
if self.longitude.values[0] > self.longitude.values[-1]:
LOGGER.error('Points are not ordered according to meta raster.')
raise ValueError
else:
raster, meta = co.points_to_raster(self, ['value'], res, raster_res,
scheduler)
raster = raster.reshape((meta['height'], meta['width']))
# save tiff
if save_tiff is not None:
ras_tiff = rasterio.open(save_tiff, 'w', driver='GTiff', \
height=meta['height'], width=meta['width'], count=1, \
dtype=np.float32, crs=self.crs, transform=meta['transform'])
ras_tiff.write(raster.astype(np.float32), 1)
ras_tiff.close()
# make plot
crs_epsg, _ = u_plot.get_transformation(self.crs)
xmin, ymin, xmax, ymax = self.longitude.min(), self.latitude.min(), \
self.longitude.max(), self.latitude.max()
if not axis:
_, axis = u_plot.make_map(proj=crs_epsg)
cbar_ax = make_axes_locatable(axis).append_axes('right', size="6.5%", \
pad=0.1, axes_class=plt.Axes)
axis.set_extent([max(xmin, crs_epsg.x_limits[0]), \
min(xmax, crs_epsg.x_limits[1]), max(ymin, crs_epsg.y_limits[0]), \
min(ymax, crs_epsg.y_limits[1])], crs_epsg)
u_plot.add_shapes(axis)
imag = axis.imshow(raster_f(raster), **kwargs, origin='upper',
extent=[xmin, xmax, ymin, ymax], transform=crs_epsg)
plt.colorbar(imag, cax=cbar_ax, label=label)
plt.draw()
return axis
def plot_hexbin(self,
mask=None,
ignore_zero=False,
pop_name=True,
buffer=0.0,
extend='neither',
axis=None,
figsize=(9, 13),
**kwargs):
"""Plot exposures geometry's value sum binned over Earth's map.
An other function for the bins can be set through the key reduce_C_function.
The plot will we projected according to the current crs.
Parameters:
mask (np.array, optional): mask to apply to eai_exp plotted.
ignore_zero (bool, optional): flag to indicate if zero and negative
values are ignored in plot. Default: False
pop_name (bool, optional): add names of the populated places
buffer (float, optional): border to add to coordinates. Default: 0.0.
extend (str, optional): extend border colorbar with arrows.
[ 'neither' | 'both' | 'min' | 'max' ]
axis (matplotlib.axes._subplots.AxesSubplot, optional): axis to use
figsize (tuple): figure size for plt.subplots
kwargs (optional): arguments for hexbin matplotlib function, e.g.
reduce_C_function=np.average. Default: reduce_C_function=np.sum
Returns:
cartopy.mpl.geoaxes.GeoAxesSubplot
"""
crs_epsg, _ = u_plot.get_transformation(self.crs)
title = self.tag.description
cbar_label = 'Value (%s)' % self.value_unit
if 'reduce_C_function' not in kwargs:
kwargs['reduce_C_function'] = np.sum
if mask is None:
mask = np.ones((self.gdf.shape[0], ), dtype=bool)
if ignore_zero:
pos_vals = self.gdf.value[mask].values > 0
else:
pos_vals = np.ones((self.gdf.value[mask].values.size, ),
dtype=bool)
value = self.gdf.value[mask][pos_vals].values
coord = np.stack([
self.gdf.latitude[mask][pos_vals].values,
self.gdf.longitude[mask][pos_vals].values
],
axis=1)
return u_plot.geo_bin_from_array(value,
coord,
cbar_label,
title,
pop_name,
buffer,
extend,
proj=crs_epsg,
axes=axis,
figsize=figsize,
**kwargs)
def test_get_transform_3035_pass(self):
""" Check that assigned attribute is correctly set."""
res, unit = u_plot.get_transformation({'init': 'epsg:3035'})
self.assertIsInstance(res, cartopy._epsg._EPSGProjection)
self.assertEqual(unit, 'm')
def test_get_transform_3395_pass(self):
""" Check that assigned attribute is correctly set."""
res, unit = u_plot.get_transformation({'init': 'epsg:3395'})
self.assertIsInstance(res, cartopy.crs.Mercator)
self.assertEqual(unit, 'm')
def test_get_transform_4326_pass(self):
""" Check _get_transformation for 4326 epsg."""
res, unit = u_plot.get_transformation({'init': 'epsg:4326'})
self.assertIsInstance(res, cartopy.crs.PlateCarree)
self.assertEqual(unit, '°')
def test_get_transform_3035_pass(self):
"""Check that assigned attribute is correctly set."""
res, unit = u_plot.get_transformation('epsg:3035')
self.assertIsInstance(res, cartopy.crs.Projection)
self.assertEqual(res.epsg_code, 3035)
self.assertEqual(unit, 'm')
def plot_raster(self,
res=None,
raster_res=None,
save_tiff=None,
raster_f=lambda x: np.log10((np.fmax(x + 1, 1))),
label='value (log10)',
scheduler=None,
axis=None,
figsize=(9, 13),
**kwargs):
"""Generate raster from points geometry and plot it using log10 scale:
np.log10((np.fmax(raster+1, 1))).
Parameters:
res (float, optional): resolution of current data in units of latitude
and longitude, approximated if not provided.
raster_res (float, optional): desired resolution of the raster
save_tiff (str, optional): file name to save the raster in tiff
format, if provided
raster_f (lambda function): transformation to use to data. Default:
log10 adding 1.
label (str): colorbar label
scheduler (str): used for dask map_partitions. “threads”,
“synchronous” or “processes”
axis (matplotlib.axes._subplots.AxesSubplot, optional): axis to use
figsize (tuple, optional): figure size for plt.subplots
kwargs (optional): arguments for imshow matplotlib function
Returns:
matplotlib.figure.Figure, cartopy.mpl.geoaxes.GeoAxesSubplot
"""
if self.meta and self.meta.get('height', 0) * self.meta.get(
'height', 0) == len(self.gdf):
raster = self.gdf.value.values.reshape(
(self.meta['height'], self.meta['width']))
# check raster starts by upper left corner
if self.gdf.latitude.values[0] < self.gdf.latitude.values[-1]:
raster = np.flip(raster, axis=0)
if self.gdf.longitude.values[0] > self.gdf.longitude.values[-1]:
LOGGER.error(
'Points are not ordered according to meta raster.')
raise ValueError
else:
raster, meta = u_coord.points_to_raster(self.gdf, ['value'], res,
raster_res, scheduler)
raster = raster.reshape((meta['height'], meta['width']))
# save tiff
if save_tiff is not None:
with rasterio.open(save_tiff,
'w',
driver='GTiff',
height=meta['height'],
width=meta['width'],
count=1,
dtype=np.float32,
crs=self.crs,
transform=meta['transform']) as ras_tiff:
ras_tiff.write(raster.astype(np.float32), 1)
# make plot
proj_data, _ = u_plot.get_transformation(self.crs)
proj_plot = proj_data
if isinstance(proj_data, ccrs.PlateCarree):
# use different projections for plot and data to shift the central lon in the plot
xmin, ymin, xmax, ymax = u_coord.latlon_bounds(
self.gdf.latitude.values, self.gdf.longitude.values)
proj_plot = ccrs.PlateCarree(central_longitude=0.5 * (xmin + xmax))
else:
xmin, ymin, xmax, ymax = (self.gdf.longitude.min(),
self.gdf.latitude.min(),
self.gdf.longitude.max(),
self.gdf.latitude.max())
if not axis:
_, axis = u_plot.make_map(proj=proj_plot, figsize=figsize)
cbar_ax = make_axes_locatable(axis).append_axes('right',
size="6.5%",
pad=0.1,
axes_class=plt.Axes)
axis.set_extent((xmin, xmax, ymin, ymax), crs=proj_data)
u_plot.add_shapes(axis)
imag = axis.imshow(raster_f(raster),
**kwargs,
origin='upper',
extent=(xmin, xmax, ymin, ymax),
transform=proj_data)
plt.colorbar(imag, cax=cbar_ax, label=label)
plt.draw()
return axis
def plot_raster(self,
res=None,
raster_res=None,
save_tiff=None,
raster_f=lambda x: np.log10((np.fmax(x + 1, 1))),
label='value (log10)',
scheduler=None,
axis=None,
figsize=(9, 13),
fill=True,
adapt_fontsize=True,
**kwargs):
"""Generate raster from points geometry and plot it using log10 scale:
np.log10((np.fmax(raster+1, 1))).
Parameters
----------
res : float, optional
resolution of current data in units of latitude
and longitude, approximated if not provided.
raster_res : float, optional
desired resolution of the raster
save_tiff : str, optional
file name to save the raster in tiff
format, if provided
raster_f : lambda function
transformation to use to data. Default:
log10 adding 1.
label : str
colorbar label
scheduler : str
used for dask map_partitions. “threads”,
“synchronous” or “processes”
axis : matplotlib.axes._subplots.AxesSubplot, optional
axis to use
figsize : tuple, optional
figure size for plt.subplots
fill : bool, optional
If false, the areas with no data will be plotted
in white. If True, the areas with missing values are filled as 0s.
The default is True.
adapt_fontsize : bool, optional
If set to true, the size of the fonts will be adapted to the size of the figure.
Otherwise the default matplotlib font size is used. Default is True.
kwargs : optional
arguments for imshow matplotlib function
Returns
-------
matplotlib.figure.Figure, cartopy.mpl.geoaxes.GeoAxesSubplot
"""
if self.meta and self.meta.get('height', 0) * self.meta.get(
'height', 0) == len(self.gdf):
raster = self.gdf.value.values.reshape(
(self.meta['height'], self.meta['width']))
# check raster starts by upper left corner
if self.gdf.latitude.values[0] < self.gdf.latitude.values[-1]:
raster = np.flip(raster, axis=0)
if self.gdf.longitude.values[0] > self.gdf.longitude.values[-1]:
raise ValueError(
'Points are not ordered according to meta raster.')
else:
raster, meta = u_coord.points_to_raster(self.gdf, ['value'], res,
raster_res, scheduler)
raster = raster.reshape((meta['height'], meta['width']))
# save tiff
if save_tiff is not None:
with rasterio.open(save_tiff,
'w',
driver='GTiff',
height=meta['height'],
width=meta['width'],
count=1,
dtype=np.float32,
crs=self.crs,
transform=meta['transform']) as ras_tiff:
ras_tiff.write(raster.astype(np.float32), 1)
# make plot
proj_data, _ = u_plot.get_transformation(self.crs)
proj_plot = proj_data
if isinstance(proj_data, ccrs.PlateCarree):
# use different projections for plot and data to shift the central lon in the plot
xmin, ymin, xmax, ymax = u_coord.latlon_bounds(
self.gdf.latitude.values, self.gdf.longitude.values)
proj_plot = ccrs.PlateCarree(central_longitude=0.5 * (xmin + xmax))
else:
xmin, ymin, xmax, ymax = (self.gdf.longitude.min(),
self.gdf.latitude.min(),
self.gdf.longitude.max(),
self.gdf.latitude.max())
if not axis:
_, axis, fontsize = u_plot.make_map(proj=proj_plot,
figsize=figsize,
adapt_fontsize=adapt_fontsize)
else:
fontsize = None
cbar_ax = make_axes_locatable(axis).append_axes('right',
size="6.5%",
pad=0.1,
axes_class=plt.Axes)
axis.set_extent((xmin, xmax, ymin, ymax), crs=proj_data)
u_plot.add_shapes(axis)
if not fill:
raster = np.where(raster == 0, np.nan, raster)
raster_f = lambda x: np.log10((np.maximum(x + 1, 1)))
if 'cmap' not in kwargs:
kwargs['cmap'] = CMAP_RASTER
imag = axis.imshow(raster_f(raster),
**kwargs,
origin='upper',
extent=(xmin, xmax, ymin, ymax),
transform=proj_data)
cbar = plt.colorbar(imag, cax=cbar_ax, label=label)
plt.colorbar(imag, cax=cbar_ax, label=label)
plt.tight_layout()
plt.draw()
if fontsize:
cbar.ax.tick_params(labelsize=fontsize)
cbar.ax.yaxis.get_offset_text().set_fontsize(fontsize)
for item in [axis.title, cbar.ax.xaxis.label, cbar.ax.yaxis.label]:
item.set_fontsize(fontsize)
return axis
