def GenerateExtentShapefile(DataDirectory, RasterFile):
"""
This just wraps a LSDMap_GDALIO script
Args:
DataDirectory (str): the data directory with the basin raster
RasterFile (str): the name of the raster
Returns:
Shapefile of the raster footprint. Has "_footprint" in filename.
Author: SMM
Date: 24/01/2018
"""
LSDMGDAL.CreateShapefileOfRasterFootprint(DataDirectory, RasterFile)
def GenerateBasemapImage(DataDirectory, RasterFile, FigWidthInches = 4, FigHeightInches = 3, bm_width = 2000000, bm_height = 2000000, projection = 'lcc',resolution = 'l', lat_0 = 0, lon_0 = 0, lat_1 = 45,lat_2 = 55, satellite_height = 10000000, FigFormat = "png", fig_dpi = 500, out_fname_prefix = ""):
"""
This makes the basemap image.
Args:
DataDirectory (str): The directory of the raster file
RasterFile (str): the name of the raster file (include extension)
FigWidthInches (float): How wide you want the basemap
FigHeightInches (float): How high you want your basemap
bm_width (float): The width in metres of your basemap
bm_height (float): The height in metres covered by your basemap
projection (str): The projection of your basemap. See basemap docs for details
resolution (str): Resolution. See basmap documentation. Default is "l" (for low) since higher resolution ("high" or "full") must be installed separately with basemap (and is very large)
lat_0 (flt): Latitude of centre of your map
lon_0 (flt): Longitude of centre of your map
lat_1 (flt): See basemap documentation
lon_1 (flt): See basemap documentation
satellite_height (flt): The satellite height in metres for geostationary projections
FigFormat (str): Figure format, can be `png`, `svg`, `pdf`, etc.
fig_dpi (int): Dots per inch of your figure
out_fname_prefix (str): The prefix of the image file. If blank uses the fname_prefix
Author: SMM
Date: 24/01/2018
"""
# Make sure data directory is in correct format
if not DataDirectory.endswith(os.sep):
print("You forgot the separator at the end of the directory, appending...")
DataDirectory = DataDirectory+os.sep
# Set up the figure. This is needed to both size the figure and get the axis handle for plotting polygons
fig, ax = plt.subplots(figsize=(FigWidthInches, FigHeightInches))
# get some filenames
RasterSplit = RasterFile.split(".")
Raster_prefix = RasterSplit[0]
Shape_name = DataDirectory+Raster_prefix+"_footprint"
SName = "Shape"
Full_Shape_name = Shape_name+".shp"
# Get the name of the image
if len(out_fname_prefix) == 0:
FigFileName = DataDirectory+Base_file+"_basemap."+fig_format
else:
FigFileName = DataDirectory+out_fname_prefix+"_basemap."+fig_format
# Now for the basemap
# setup Lambert Conformal basemap.
#m = Basemap(width=bm_width,height=bm_width,projection=projection,
# resolution=resolution,lat_1=lat_1 ,lat_2=lat_2,lat_0=lat_0,lon_0=lon_0, satellite_height = satellite_height, area_thresh = 100000)
# create the shapefile
LSDMGDAL.CreateShapefileOfRasterFootprint(DataDirectory, RasterFile)
#shape_feature = ShapelyFeature(Reader(fname).geometries(),ccrs.PlateCarree(), facecolor='none')
#ax.add_feature(shape_feature)
# draw coastlines.
#m.drawcoastlines(linewidth = 0.5)
# draw a boundary around the map, fill the background.
# this background will end up being the ocean color, since
# the continents will be drawn on top.
#m.drawmapboundary(fill_color='snow')
# fill continents, set lake color same as ocean color.
#m.fillcontinents(color='lightgray',lake_color='snow')
# draw parallels and meridians.
# label parallels on right and top
# meridians on bottom and left
parallels = np.arange(0.,90,5.)
# labels = [left,right,top,bottom]
#m.drawparallels(parallels,labels=[False,True,True,False])
meridians = np.arange(10.,351.,5.)
#m.drawmeridians(meridians,labels=[True,False,False,True])
#m.drawcountries()
# Make a patch from the shapefile
# All this stuff from:
# http://www.datadependence.com/2016/06/creating-map-visualisations-in-python/
df_poly = pd.DataFrame({
'shapes': [Polygon(np.array(shape), True) for shape in m.footprint]})
#df_poly = df_poly.merge(new_areas, on='area', how='left')
#cmap = plt.get_cmap('Oranges')
pc = PatchCollection(df_poly.shapes, zorder=2, alpha = 0.5)
pc.set_facecolor("crimson")
ax.add_collection(pc)
plt.savefig(FigFileName,format=FigFormat,dpi=fig_dpi)
def GenerateBasemapImageAutomated(DataDirectory, RasterFile, FigWidthInches = 4, FigHeightInches = 3, FigFormat = "png", fig_dpi = 500, regional_extent_multiplier = 5, label_spacing_multiplier = 0.5, out_fname_prefix = "", is_orthographic = False):
"""
This makes the basemap image. Uses data from the raster to size the figure and locate the centrepoint
Args:
DataDirectory (str): The directory of the raster file
RasterFile (str): the name of the raster file (include extension)
FigWidthInches (flt): How wide you want the basemap
FigHeightInches (float): How high you want your basemap
FigFormat (str): Figure format, can be `png`, `svg`, `pdf`, etc.
fig_dpi (int): Dots per inch of your figure
regional_extent_multiplier (float): How much bigger you want the extent vs the size of the raster
label_spacing_multiplier (float): If the meridians and parallels are too close, increase this number. Default of 0.5
out_fname_prefix (str): The prefix of the image file. If blank uses the fname_prefix
Author: SMM
Date: 01/02/2018
"""
# Make sure data directory is in correct format
if not DataDirectory.endswith(os.sep):
print("You forgot the separator at the end of the directory, appending...")
DataDirectory = DataDirectory+os.sep
# Set up the figure. This is needed to both size the figure and get the axis handle for plotting polygons
fig = plt.figure(figsize=(FigWidthInches, FigHeightInches))
print("The size is: " +str(FigWidthInches)+", "+str(FigHeightInches))
# get some filenames
RasterSplit = RasterFile.split(".")
Raster_prefix = RasterSplit[0]
Shape_name = DataDirectory+Raster_prefix+"_footprint.shp"
SName = "Shape"
# Get the name of the image
if len(out_fname_prefix) == 0:
FigFileName = DataDirectory+Base_file+"_basemap."+FigFormat
else:
FigFileName = DataDirectory+out_fname_prefix+"_basemap."+FigFormat
# Now we get the extents from the raster
centre_lat, centre_long, extent_lat, extent_long, xproj_extent, yproj_extent = LSDMGDAL.GetCentreAndExtentOfRaster(DataDirectory, RasterFile)
# Calculate the aspect ratio
aspect_ratio = BasemapExtentSizer(FigWidthInches, FigHeightInches)
# Figure out the longest dimension
long_dimension = xproj_extent
if yproj_extent > long_dimension:
long_dimension = yproj_extent
print("The long dimension is: "+str(long_dimension))
# Get the full extent by mulitplying the longest extent by the multiplier
full_dimension = long_dimension*regional_extent_multiplier
# now get the two dimensions for the extent of the figure
print("The aspect ratio is: "+str(aspect_ratio))
if aspect_ratio > 1:
# This is when the figure is wider than tall
x_ext = full_dimension*aspect_ratio
y_ext = full_dimension
full_extent_long = extent_long*aspect_ratio*regional_extent_multiplier
full_extent_lat = extent_long*regional_extent_multiplier
else:
x_ext = full_dimension
y_ext = full_dimension*aspect_ratio
full_extent_long = extent_lat*regional_extent_multiplier
full_extent_lat = extent_lat*aspect_ratio*regional_extent_multiplier
extents = [centre_long-0.5*full_extent_long,
centre_long+0.5*full_extent_long,
centre_lat-0.5*full_extent_lat,
centre_lat+0.5*full_extent_lat]
print("Extents are: ")
print(extents)
# Now we set up the extents and coordinate system
#if (is_orthographic):
# ax = fig.add_axes([0, 0, 1, 1], projection=ccrs.Orthographic(centre_lat, #centre_long))
#
# ax.add_feature(cfeature.LAND)
# ax.add_feature(cfeature.OCEAN, edgecolor='black')
# ax.set_global()
# ax.gridlines()
if(is_orthographic):
ax = fig.add_axes([0, 0, 1, 1], projection=ccrs.NearsidePerspective(
central_latitude=centre_lat,
central_longitude=centre_long,
satellite_height=10000000.0))
ax.coastlines(resolution='110m',linewidth=0.5)
borders_110m = cfeature.NaturalEarthFeature('cultural', 'admin_0_boundary_lines_land', '110m',edgecolor='face', facecolor=cfeature.COLORS['land'])
ax.add_feature(borders_110m, edgecolor='black', facecolor = "none",linewidth=0.5)
ax.gridlines()
else:
ax = fig.add_axes([0, 0, 1, 1], projection=ccrs.PlateCarree())
ax.set_extent([centre_long-0.5*full_extent_long,
centre_long+0.5*full_extent_long,
centre_lat-0.5*full_extent_lat,
centre_lat+0.5*full_extent_lat], ccrs.PlateCarree())
land_50m = cfeature.NaturalEarthFeature('physical', 'land', '50m',
edgecolor='face',
facecolor=cfeature.COLORS['land'])
borders_50m = cfeature.NaturalEarthFeature('cultural', 'admin_0_boundary_lines_land', '50m',
edgecolor='face',
facecolor=cfeature.COLORS['land'])
ax.add_feature(land_50m, edgecolor='black', linewidth=0.5)
ax.add_feature(borders_50m, edgecolor='black', facecolor = "none",linewidth=0.5)
#ax.add_feature(cfeature.LAND)
#ax.add_feature(cfeature.OCEAN)
#ax.add_feature(cfeature.COASTLINE)
#ax.add_feature(cfeature.BORDERS, linestyle='--')
#ax.add_feature(cfeature.LAKES, alpha=0.5)
#ax.add_feature(cfeature.RIVERS)
# create the shapefile
LSDMGDAL.CreateShapefileOfRasterFootprint(DataDirectory, RasterFile)
ax.add_geometries(
shpreader.Reader(Shape_name).geometries(),
ccrs.PlateCarree(),edgecolor='black', facecolor='green', alpha=0.5, linewidth=0.5)
#==========================================
# draw parallels and meridians.
# Calculate the spacing of the meridians and parallels
# THIS IS ALL FROM BASEMAP AND NOT USED BY CARTOPY
max_latlong_ext = extent_lat
if extent_long < max_latlong_ext:
max_latlong_ext = extent_long
max_latlong_ext = max_latlong_ext*regional_extent_multiplier
print("The maximum extent is:"+str(max_latlong_ext))
latlong_label_spacing = int(label_spacing_multiplier*max_latlong_ext+0.5)
print("And the label spacing is: "+str(latlong_label_spacing))
start_lat = int(centre_lat - max_latlong_ext*2 - 0.5)
end_lat = int(centre_lat + max_latlong_ext*2+0.5)
start_long = int(centre_long - max_latlong_ext*2 -0.5)
end_long = int(centre_long + max_latlong_ext*2+0.5)
# label parallels on right and top
# meridians on bottom and left
parallels = np.arange(start_lat,end_lat,latlong_label_spacing)
# labels = [left,right,top,bottom]
#m.drawparallels(parallels,labels=[False,True,True,False])
meridians = np.arange(start_long,end_long,latlong_label_spacing)
#m.drawmeridians(meridians,labels=[True,False,False,True])
#==========================================
#==========================================
# THIS IS ALL FROM BASEMAP AND NOT USED BY CARTOPY
# Make a patch from the shapefile
# All this stuff from:
# http://www.datadependence.com/2016/06/creating-map-visualisations-in-python/
#df_poly = pd.DataFrame({
# 'shapes': [Polygon(np.array(shape), True) for shape in m.footprint]})
#df_poly = df_poly.merge(new_areas, on='area', how='left')
#cmap = plt.get_cmap('Oranges')
#pc = PatchCollection(df_poly.shapes, zorder=2, alpha = 0.5)
#pc.set_facecolor("crimson")
#ax.add_collection(pc)
#==========================================
plt.savefig(FigFileName,format=FigFormat,dpi=fig_dpi)