def test_is_regular_pass(self):
""" Test is_regular function. """
coord = np.array([[1, 2], [4.4, 5.4], [4, 5]])
self.assertFalse(grid_is_regular(coord))
coord = np.array([[1, 2], [4.4, 5], [4, 5]])
self.assertFalse(grid_is_regular(coord))
coord = np.array([[1, 2], [4, 5]])
self.assertFalse(grid_is_regular(coord))
coord = np.array([[1, 2], [4, 5], [1, 5], [4, 3]])
self.assertFalse(grid_is_regular(coord))
coord = np.array([[1, 2], [4, 5], [1, 5], [4, 2]])
self.assertTrue(grid_is_regular(coord))
grid_x, grid_y = np.mgrid[10:100:complex(0, 5), 0:10:complex(0, 5)]
grid_x = grid_x.reshape(-1, )
grid_y = grid_y.reshape(-1, )
coord = np.array([grid_x, grid_y]).transpose()
self.assertTrue(grid_is_regular(coord))
grid_x, grid_y = np.mgrid[10:100:complex(0, 4), 0:10:complex(0, 5)]
grid_x = grid_x.reshape(-1, )
grid_y = grid_y.reshape(-1, )
coord = np.array([grid_x, grid_y]).transpose()
self.assertTrue(grid_is_regular(coord))
def resolution(self):
""" Returns a tuple of the resolution in the same unit as the coords.
"""
if self._resolution is None:
assert grid_is_regular(self.coord), 'Centroids not a regular grid'
lats = np.unique(self.lat)
lons = np.unique(self.lon)
res_lat = lats[1] - lats[0]
res_lon = lons[1] - lons[0]
self._resolution = (res_lat, res_lon)
return self._resolution
def test_is_regular_pass(self):
""" Test is_regular function. """
coord = np.array([[1, 2], [4.4, 5.4], [4, 5]])
reg, hei, wid = grid_is_regular(coord)
self.assertFalse(reg)
self.assertEqual(hei, 1)
self.assertEqual(wid, 1)
coord = np.array([[1, 2], [4.4, 5], [4, 5]])
reg, hei, wid = grid_is_regular(coord)
self.assertFalse(reg)
self.assertEqual(hei, 1)
self.assertEqual(wid, 1)
coord = np.array([[1, 2], [4, 5]])
reg, hei, wid = grid_is_regular(coord)
self.assertFalse(reg)
self.assertEqual(hei, 1)
self.assertEqual(wid, 1)
coord = np.array([[1, 2], [4, 5], [1, 5], [4, 3]])
reg, hei, wid = grid_is_regular(coord)
self.assertFalse(reg)
self.assertEqual(hei, 2)
self.assertEqual(wid, 1)
coord = np.array([[1, 2], [4, 5], [1, 5], [4, 2]])
reg, hei, wid = grid_is_regular(coord)
self.assertTrue(reg)
self.assertEqual(hei, 2)
self.assertEqual(wid, 2)
grid_x, grid_y = np.mgrid[10 : 100 : complex(0, 5),
0 : 10 : complex(0, 5)]
grid_x = grid_x.reshape(-1,)
grid_y = grid_y.reshape(-1,)
coord = np.array([grid_x, grid_y]).transpose()
reg, hei, wid = grid_is_regular(coord)
self.assertTrue(reg)
self.assertEqual(hei, 5)
self.assertEqual(wid, 5)
grid_x, grid_y = np.mgrid[10 : 100 : complex(0, 4),
0 : 10 : complex(0, 5)]
grid_x = grid_x.reshape(-1,)
grid_y = grid_y.reshape(-1,)
coord = np.array([grid_x, grid_y]).transpose()
reg, hei, wid = grid_is_regular(coord)
self.assertTrue(reg)
self.assertEqual(hei, 5)
self.assertEqual(wid, 4)
def geo_im_from_array(array_sub, geo_coord, var_name, title,
proj=ccrs.PlateCarree(), smooth=True, axes=None, **kwargs):
"""Image(s) plot defined in array(s) over input coordinates.
Parameters:
array_sub (np.array(1d or 2d) or list(np.array)): Each array (in a row
or in the list) are values at each point in corresponding
geo_coord that are ploted in one subplot.
geo_coord (2d np.array or list(2d np.array)): (lat, lon) for each
point in a row. If one provided, the same grid is used for all
subplots. Otherwise provide as many as subplots in array_sub.
var_name (str or list(str)): label to be shown in the colorbar. If one
provided, the same is used for all subplots. Otherwise provide as
many as subplots in array_sub.
title (str or list(str)): subplot title. If one provided, the same is
used for all subplots. Otherwise provide as many as subplots in
array_sub.
proj (ccrs): coordinate reference system used in coordinates
smooth (bool, optional): smooth plot to RESOLUTIONxRESOLUTION. Default:
True.
kwargs (optional): arguments for pcolormesh matplotlib function.
Returns:
cartopy.mpl.geoaxes.GeoAxesSubplot
Raises:
ValueError
"""
# Generate array of values used in each subplot
num_im, list_arr = _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')
if 'vmin' not in kwargs:
kwargs['vmin'] = np.min(array_sub)
if 'vmax' not in kwargs:
kwargs['vmax'] = np.max(array_sub)
if axes is None:
_, axes = make_map(num_im, proj=proj)
axes_iter = axes
if not isinstance(axes, np.ndarray):
axes_iter = np.array([[axes]])
# Generate each subplot
for array_im, axis, tit, name, coord in \
zip(list_arr, axes_iter.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))
is_reg, height, width = grid_is_regular(coord)
extent = _get_borders(coord, proj=proj)
if smooth or not is_reg:
# Create regular grid where to interpolate the array
grid_x, grid_y = np.mgrid[
extent[0] : extent[1] : complex(0, RESOLUTION),
extent[2] : extent[3] : complex(0, RESOLUTION)]
grid_im = griddata((coord[:, 1], coord[:, 0]), array_im, \
(grid_x, grid_y))
else:
grid_x = coord[:, 1].reshape((width, height)).transpose()
grid_y = coord[:, 0].reshape((width, height)).transpose()
grid_im = np.array(array_im.reshape((width, height)).transpose())
if grid_y[0, 0] > grid_y[0, -1]:
grid_y = np.flip(grid_y)
grid_im = np.flip(grid_im, 1)
grid_im = np.resize(grid_im, (height, width, 1))
# Add coastline to axis
axis.set_extent((extent), proj)
add_shapes(axis)
# Create colormesh, colorbar and labels in axis
cbax = make_axes_locatable(axis).append_axes('right', size="6.5%", \
pad=0.1, axes_class=plt.Axes)
cbar = plt.colorbar(axis.pcolormesh(grid_x, grid_y, np.squeeze(grid_im), \
transform=proj, **kwargs), cax=cbax, orientation='vertical')
cbar.set_label(name)
axis.set_title(tit)
return axes
def geo_im_from_array(array_sub,
coord,
var_name,
title,
proj=None,
smooth=True,
axes=None,
figsize=(9, 13),
adapt_fontsize=True,
**kwargs):
"""Image(s) plot defined in array(s) over input coordinates.
Parameters
----------
array_sub : np.array(1d or 2d) or list(np.array)
Each array (in a row or in the list) are values at each point in corresponding
geo_coord that are ploted in one subplot.
coord : 2d np.array
(lat, lon) for each point in a row. The same grid is used for all subplots.
var_name : str or list(str)
label to be shown in the colorbar. If one provided, the same is used for all subplots.
Otherwise provide as many as subplots in array_sub.
title : str or list(str)
subplot title. If one provided, the same is used for all subplots.
Otherwise provide as many as subplots in array_sub.
proj : ccrs, optional
coordinate reference system used in coordinates, by default None
smooth : bool, optional
smooth plot to RESOLUTIONxRESOLUTION, by default True
axes : Axes or ndarray(Axes), optional
by default None
figsize : tuple, optional
figure size for plt.subplots, by default (9, 13)
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
arbitrary keyword arguments for pcolormesh matplotlib function
Returns
-------
cartopy.mpl.geoaxes.GeoAxesSubplot
Raises
------
ValueError
"""
# Generate array of values used in each subplot
num_im, list_arr = _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, coord, 'geo_coord')
is_reg, height, width = u_coord.grid_is_regular(coord)
extent = _get_borders(coord, proj_limits=(-360, 360, -90, 90))
mid_lon = 0
if not proj:
mid_lon = 0.5 * sum(extent[:2])
proj = ccrs.PlateCarree(central_longitude=mid_lon)
if 'vmin' not in kwargs:
kwargs['vmin'] = np.nanmin(array_sub)
if 'vmax' not in kwargs:
kwargs['vmax'] = np.nanmax(array_sub)
if axes is None:
if isinstance(proj, ccrs.PlateCarree):
# use different projections for plot and data to shift the central lon in the plot
xmin, xmax = u_coord.lon_bounds(
np.concatenate([c[:, 1] for c in list_coord]))
proj_plot = ccrs.PlateCarree(central_longitude=0.5 * (xmin + xmax))
_, axes, fontsize = make_map(num_im,
proj=proj_plot,
figsize=figsize,
adapt_fontsize=adapt_fontsize)
else:
fontsize = None
axes_iter = axes
if not isinstance(axes, np.ndarray):
axes_iter = np.array([[axes]])
if 'cmap' not in kwargs:
kwargs['cmap'] = CMAP_RASTER
# Generate each subplot
for array_im, axis, tit, name in zip(list_arr, axes_iter.flatten(),
list_tit, list_name):
if coord.shape[0] != array_im.size:
raise ValueError("Size mismatch in input array: %s != %s." %
(coord.shape[0], array_im.size))
if smooth or not is_reg:
# Create regular grid where to interpolate the array
grid_x, grid_y = np.mgrid[
extent[0]:extent[1]:complex(0, RESOLUTION),
extent[2]:extent[3]:complex(0, RESOLUTION)]
grid_im = griddata((coord[:, 1], coord[:, 0]), array_im,
(grid_x, grid_y))
else:
grid_x = coord[:, 1].reshape((width, height)).transpose()
grid_y = coord[:, 0].reshape((width, height)).transpose()
grid_im = np.array(array_im.reshape((width, height)).transpose())
if grid_y[0, 0] > grid_y[0, -1]:
grid_y = np.flip(grid_y)
grid_im = np.flip(grid_im, 1)
grid_im = np.resize(grid_im, (height, width, 1))
axis.set_extent(
(extent[0] - mid_lon, extent[1] - mid_lon, extent[2], extent[3]),
crs=proj)
# Add coastline to axis
add_shapes(axis)
# Create colormesh, colorbar and labels in axis
cbax = make_axes_locatable(axis).append_axes('right',
size="6.5%",
pad=0.1,
axes_class=plt.Axes)
img = axis.pcolormesh(grid_x - mid_lon,
grid_y,
np.squeeze(grid_im),
transform=proj,
**kwargs)
cbar = plt.colorbar(img, cax=cbax, orientation='vertical')
cbar.set_label(name)
axis.set_title("\n".join(wrap(tit)))
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)
plt.tight_layout()
return axes
def shape_grid(self):
"""If the centroids lie on a regular grid, return its shape as a tuple
of the form (n_lat, n_lon), that is, (height, width) """
assert grid_is_regular(self.coord), 'Coords are not on a regular grid'
return (np.unique(self.lat).size, np.unique(self.lon).size)
