def get_roi(self, minlon, maxlon, minlat, maxlat):
"""Return numpy array of data specified by its geographical bounds
Parameters
----------
minlon : int or float
Western longitude bound [degrees].
maxlon : int or float
Eastern longitude bound [degrees].
minlat : int or float
Southern latitude bound [degrees].
maxlat : int or float
Northern latitude bound [degrees].
Returns
-------
roi : numpy 2D array
Numpy array specified by extent given.
Examples
--------
# TODO
"""
if (not self.inbounds(minlat, minlon)
or not self.inbounds(maxlat, maxlon)):
raise DataImportError("Roi extent out of dataset bounds.")
topind = ch.deg2pix(self.nlat - maxlat, self.ppd)
height = ch.deg2pix(maxlat - minlat, self.ppd)
if self.is_global() and (minlon < self.wlon or maxlon > self.elon):
roi = self._wrap_roi_360(minlon, maxlon, topind, height)
else:
leftind = ch.deg2pix(minlon - self.wlon, self.ppd)
width = ch.deg2pix(maxlon - minlon, self.ppd)
roi = self.ReadAsArray(leftind, topind, width, height)
return roi.astype(float)
def test_deg2pix(self):
"""Test deg2pix function"""
actual = ch.deg2pix(10, 20)
expected = 200
self.assertEqual(actual, expected)
actual = ch.deg2pix(5.5, 2.5)
expected = 13
self.assertEqual(actual, expected)
def polygon_mask(croi, poly_verts):
"""Mask the region inside a polygon given by poly_verts.
Uses the matplotlib.Path module and included contains_points() method to
calculate the interior of a polygon specified as a list of (lat, lon)
vertices.
Parameters
==========
croi : CraterRoi
Crater region of interest being masked.
poly_verts : list of tuple
List of (lon, lat) polygon vertices.
Returns
-------
mask : numpy 2D array
Example
=======
>>> import os.path as p
>>> f = p.join(p.dirname(p.abspath('__file__')), 'examples', 'moon.tif')
>>> cds = CraterpyDataset(f, radius=1737)
>>> croi = CraterRoi(cds, -27.2, 80.9, 207) # Humboldt crater
>>> poly = [[-27.5, 80.5], [-28, 80.5], [-28, 81], [-27.5, 81]]
>>> mask = polygon_mask(cds, roi, extent, poly)
>>> croi.mask(mask)
>>> croi.plot()
"""
from matplotlib.path import Path
minlon, maxlon, minlat, maxlat = croi.extent
# Create grid
nlat, nlon = croi.roi.shape
x, y = np.meshgrid(np.arange(nlon), np.arange(nlat))
x, y = x.flatten(), y.flatten()
gridpoints = np.vstack((x, y)).T
poly_pix = [(ch.deg2pix(lon - minlon, croi.cds.ppd),
ch.deg2pix(lat - minlat, croi.cds.ppd))
for lon, lat in poly_verts]
path = Path(poly_pix)
mask = path.contains_points(gridpoints).reshape((nlat, nlon))
return mask
def _wrap_roi_360(self, minlon, maxlon, topind, height):
"""Return roi that is split by the 360 degree edge of a global dataset.
Read the left and right sub-arrays and then concatenate them into
the full roi.
Parameters
----------
minlon : int or float
Western longitude bound [degrees].
maxlon : int or float
Eastern longitude bound [degrees].
topind : int
Top index of returned roi.
height : int
Height of returned roi.
Returns
--------
roi: 2Darray
Concatenated roi wrapped around lon bound.
"""
if minlon < self.wlon:
leftind = ch.deg2pix(minlon - (self.wlon - 360), self.ppd)
leftwidth = ch.deg2pix(self.wlon - minlon, self.ppd)
rightind = 0
rightwidth = ch.deg2pix(maxlon - self.wlon, self.ppd)
elif maxlon > self.elon:
leftind = ch.deg2pix(self.elon - minlon, self.ppd)
leftwidth = ch.deg2pix(self.elon - minlon, self.ppd)
rightind = 0
rightwidth = ch.deg2pix(maxlon - self.elon, self.ppd)
left_roi = self.ReadAsArray(leftind, topind, leftwidth, height)
right_roi = self.ReadAsArray(rightind, topind, rightwidth, height)
return np.concatenate((left_roi, right_roi), axis=1)