def createMask(xxC, yyC, spatialRefProj):
"""
This will create a mask for a given basin, which will be defined by grib.basin
:param xxC: <np array> The center points of the x grid
:param yyC: <np array> The center points in the y grid
:param spatialRefProj: <gdal obj> Current Projection
Note:
Make sure the .geojson basin files exist. The files were created using the USGS streamstats online app:
https://water.usgs.gov/osw/streamstats/
:return: <np array> masked array.
"""
# Get the lat / lon of each grid box's center point.
lons_centerPt, lats_centerPt = Proj(spatialRefProj)(xxC, yyC, inverse=True)
# given a bunch of lat/lons in the geotiff, we can get the polygon points.
try:
sf = fiona.open(
os.path.join(dir_path, 'Shapefiles', grib.basin,
grib.basin + '.geojson'))
except:
logger.error('No basin shapefile found in ' + dir_path +
'/Shapefiles/' + grib.basin + '/' + grib.basin +
'.geojson' + '\n A mask was not created.')
return
geoms = [feature["geometry"] for feature in sf]
poly = Polygon(
geoms[0]['coordinates'][0]
) # For a simple square, this would be 4 points, but it can be thousands of points for other objects.
polyMinLon, polyMinLat, polyMaxLon, polyMaxLat = sf.bounds # Get the bounds to speed up the process of generating a mask.
# create a 1D numpy mask filled with zeros that is the exact same size as the lat/lon array from our projection.
mask = np.zeros(lons_centerPt.flatten().shape)
# Debugging: FOR CENTER POINT OF GRID BOX
# These are test variables to see where the center points are (plot with basemaps to prove to yourself they're in the right spot).
#debugCenterX = np.zeros(lats_centerPt.flatten().shape)
#debugCenterY = np.zeros(lons_centerPt.flatten().shape)
# Create Mask by checking whether points in the raster are within the bounds of the polygon. Instead of checking
# every single point in the raster, just focus on points within the max/min bounds of the polygon (it's slow as hell
# if you don't do that).
i = 0 # counter
for xp, yp in zip(lons_centerPt.flatten(), lats_centerPt.flatten()):
if ((polyMinLon <= xp <= polyMaxLon)
and (polyMinLat <= yp <= polyMaxLat)):
mask[i] = (Point(xp, yp).within(poly))
# Debugging FOR CENTER POINT OF GRID BOX: If you want to visualize the center point
# of each grid box that's found in the polygon,
# include this below and then you can put a dot (via m.plot)
#if (Point(xp, yp).within(poly)):
#debugCenterX[i] = xp
#debugCenterY[i] = yp
i += 1
# mask = ([Point(xp, yp).within(poly) for xp, yp in zip(lons.flatten(), lats.flatten()) if
# ((polyMinLon <= xp <= polyMaxLat) and (polyMinLat <= yp <= polyMaxLat))])
mask = np.reshape(mask, (xxC.shape))
return mask
def createMask(xxC, yyC, spatialRefProj):
# Get the lat / lon of each grid box's center point.
lons_centerPt, lats_centerPt = Proj(spatialRefProj)(xxC, yyC, inverse=True)
# given a bunch of lat/lons in the geotiff, we can get the polygon points.
sf = fiona.open(dir_path + '/Shapefiles/' + grib.basin + '/' + grib.basin +
'.geojson')
geoms = [feature["geometry"] for feature in sf]
poly = Polygon(
geoms[0]['coordinates'][0]
) # For a simple square, this would be 4 points, but it can be thousands of points for other objects.
grib.basinArea = ops.transform(
partial(
pyproj.transform, pyproj.Proj(init='EPSG:4326'),
pyproj.Proj(proj='aea', lat_1=poly.bounds[1],
lat_2=poly.bounds[3])), poly).area
# NOTE: Calculating area in the mercator projection (ESPG:3587) will lead to large errors due to inaccuracies in
# that projections distance measurements. Instead, you must convert over to 4326 or equal area coordinates (whci is best)
# For example, if instead of proj='aea' (in code below) you used proj = 'merc' the area for French Meadows
# increases from roughly . 30,000 acres to over 50,000 acres. Alternatively, you could calculate the area by
# counting the grid boxes in the polygon and summing up the area of one grid where
# xres = 0.008333 deg * 111,111 m and yres = 0.008333 deg * 111,111 m * cos(latitude of grid box).
# The method below is the easiest way to do this.
polyMinLon, polyMinLat, polyMaxLon, polyMaxLat = sf.bounds # Get the bounds to speed up the process of generating a mask.
# create a 1D numpy mask filled with zeros that is the exact same size as the lat/lon array from our projection.
mask = np.zeros(lons_centerPt.flatten().shape)
# Debugging: FOR CENTER POINT OF GRID BOX
# These are test variables to see where the center points are (plot with basemaps to prove to yourself they're in the right spot).
global debugCenterX, debugCenterY
debugCenterX = np.zeros(lats_centerPt.flatten().shape)
debugCenterY = np.zeros(lons_centerPt.flatten().shape)
# Create Mask by checking whether points in the raster are within the bounds of the polygon. Instead of checking
# every single point in the raster, just focus on points within the max/min bounds of the polygon (it's slow as hell
# if you don't do that).
i = 0 # counter
for xp, yp in zip(lons_centerPt.flatten(), lats_centerPt.flatten()):
if ((polyMinLon <= xp <= polyMaxLon)
and (polyMinLat <= yp <= polyMaxLat)):
mask[i] = (Point(xp, yp).within(poly))
# Debugging FOR CENTER POINT OF GRID BOX: If you want to visualize the center point
# of each grid box that's found in the polygon,
# include this below and then you can put a dot (via m.plot)
if (Point(xp, yp).within(poly)):
debugCenterX[i] = xp
debugCenterY[i] = yp
i += 1
mask = np.reshape(mask, (xxC.shape))
return mask
def createMask(xxC, yyC, spatialRefProj):
# Get the lat / lon of each grid box's center point.
lons_centerPt, lats_centerPt = Proj(spatialRefProj)(xxC, yyC, inverse=True)
# given a bunch of lat/lons in the geotiff, we can get the polygon points.
sf = fiona.open(dir_path + '/Shapefiles/' + grib.basin + '/' + grib.basin +
'.geojson')
geoms = [feature["geometry"] for feature in sf]
poly = Polygon(
geoms[0]['coordinates'][0]
) # For a simple square, this would be 4 points, but it can be thousands of points for other objects.
polyMinLon, polyMinLat, polyMaxLon, polyMaxLat = sf.bounds # Get the bounds to speed up the process of generating a mask.
# create a 1D numpy mask filled with zeros that is the exact same size as the lat/lon array from our projection.
mask = np.zeros(lons_centerPt.flatten().shape)
# Debugging: FOR CENTER POINT OF GRID BOX
# These are test variables to see where the center points are (plot with basemaps to prove to yourself they're in the right spot).
global debugCenterX, debugCenterY
debugCenterX = np.zeros(lats_centerPt.flatten().shape)
debugCenterY = np.zeros(lons_centerPt.flatten().shape)
# Create Mask by checking whether points in the raster are within the bounds of the polygon. Instead of checking
# every single point in the raster, just focus on points within the max/min bounds of the polygon (it's slow as hell
# if you don't do that).
i = 0 # counter
for xp, yp in zip(lons_centerPt.flatten(), lats_centerPt.flatten()):
if ((polyMinLon <= xp <= polyMaxLon)
and (polyMinLat <= yp <= polyMaxLat)):
mask[i] = (Point(xp, yp).within(poly))
# Debugging FOR CENTER POINT OF GRID BOX: If you want to visualize the center point
# of each grid box that's found in the polygon,
# include this below and then you can put a dot (via m.plot)
if (Point(xp, yp).within(poly)):
debugCenterX[i] = xp
debugCenterY[i] = yp
i += 1
mask = np.reshape(mask, (xxC.shape))
return mask