def set_rgb(self,
img=None,
crs=None,
interp='nearest',
natural_earth=None):
"""Manually force to a rgb img
Parameters
----------
img : array
the image to plot
crs : Grid
the image reference system
interp : str, default 'nearest'
'nearest', 'linear', or 'spline'
natural_earth : str
'lr', 'mr' or 'hr' (low res, medium or high res)
natural earth background img
"""
if natural_earth is not None:
from matplotlib.image import imread
with warnings.catch_warnings():
# DecompressionBombWarning
warnings.simplefilter("ignore")
img = imread(utils.get_natural_earth_file(natural_earth))
ny, nx = img.shape[0], img.shape[1]
dx, dy = 360. / nx, 180. / ny
grid = Grid(nxny=(nx, ny),
dxdy=(dx, -dy),
x0y0=(-180., 90.),
pixel_ref='corner').center_grid
return self.set_rgb(img, grid, interp='linear')
if (len(img.shape) != 3) or (img.shape[-1] not in [3, 4]):
raise ValueError('img should be of shape (y, x, 3) or (y, x, 4)')
# Unefficient but by far easiest right now
out = []
for i in range(img.shape[-1]):
out.append(self._check_data(img[..., i], crs=crs, interp=interp))
self._rgb = np.dstack(out)
def set_rgb(self, img=None, crs=None, interp='nearest',
natural_earth=None):
"""Manually force to a rgb img
Parameters
----------
img : array
the image to plot
crs : Grid
the image reference system
interp : str, default 'nearest'
'nearest', 'linear', or 'spline'
natural_earth : str
'lr', 'mr' or 'hr' (low res, medium or high res)
natural earth background img
"""
if natural_earth is not None:
from matplotlib.image import imread
with warnings.catch_warnings():
# DecompressionBombWarning
warnings.simplefilter("ignore")
img = imread(utils.get_natural_earth_file(natural_earth))
ny, nx = img.shape[0], img.shape[1]
dx, dy = 360. / nx, 180. / ny
grid = Grid(nxny=(nx, ny), dxdy=(dx, -dy), ul_corner=(-180., 90.),
pixel_ref='corner').center_grid
return self.set_rgb(img, grid, interp='linear')
if (len(img.shape) != 3) or (img.shape[-1] not in [3, 4]):
raise ValueError('img should be of shape (y, x, 3) or (y, x, 4)')
# Unefficient but by far easiest right now
out = []
for i in range(img.shape[-1]):
out.append(self._check_data(img[..., i], crs=crs, interp=interp))
self._rgb = np.dstack(out)