def PrintBasins_Complex(DataDirectory,fname_prefix,
use_keys_not_junctions = True, show_colourbar = False,
Remove_Basins = [], Rename_Basins = {}, Value_dict= {},
cmap = "jet", colorbarlabel = "colourbar", size_format = "ESURF",
fig_format = "png", dpi = 250, out_fname_prefix = "", include_channels = False, label_basins = True):
"""
This function makes a shaded relief plot of the DEM with the basins coloured
by the basin ID.
Args:
DataDirectory (str): the data directory with the m/n csv files
fname_prefix (str): The prefix for the m/n csv files
use_keys_not_junctions (bool): If true use basin keys to locate basins, otherwise use junction indices
show_colourbar (bool): if true show the colourbar
Remove_Basins (list): A lists containing either key or junction indices of basins you want to remove from plotting
Rename_Basins (dict): A dict where the key is either basin key or junction index, and the value is a new name for the basin denoted by the key
Value_dict (dict): A dict where the key is either basin key or junction index, and the value is a value of the basin that is used to colour the basins
add_basin_labels (bool): If true, label the basins with text. Otherwise use a colourbar.
cmap (str or colourmap): The colourmap to use for the plot
cbar_loc (str): where you want the colourbar. Options are none, left, right, top and botton. The colourbar will be of the elevation.
If you want only a hillshade set to none and the cmap to "gray"
size_format (str): Either geomorphology or big. Anything else gets you a 4.9 inch wide figure (standard ESURF size)
fig_format (str): An image format. png, pdf, eps, svg all valid
dpi (int): The dots per inch of the figure
out_fname_prefix (str): The prefix of the image file. If blank uses the fname_prefix
include_channels (bool): If true, adds a channel plot. It uses the chi_data_maps file
label_basins (bool): If true, the basins get labels
Returns:
Shaded relief plot with the basins coloured by basin ID. Uses a colourbar to show each basin. This allows more complex plotting with renamed and excluded basins.
Author: FJC, SMM
"""
#import modules
from LSDMapFigure.PlottingRaster import MapFigure
# set figure sizes based on format
if size_format == "geomorphology":
fig_width_inches = 6.25
elif size_format == "big":
fig_width_inches = 16
else:
fig_width_inches = 4.92126
# get the basin IDs to make a discrete colourmap for each ID
BasinInfoDF = PlotHelp.ReadBasinInfoCSV(DataDirectory, fname_prefix)
basin_keys = list(BasinInfoDF['basin_key'])
basin_keys = [int(x) for x in basin_keys]
basin_junctions = list(BasinInfoDF['outlet_junction'])
basin_junctions = [float(x) for x in basin_junctions]
print ('Basin keys are: ')
print (basin_keys)
# going to make the basin plots - need to have bil extensions.
print("I'm going to make the basin plots. Your topographic data must be in ENVI bil format or I'll break!!")
# get the rasters
raster_ext = '.bil'
#BackgroundRasterName = fname_prefix+raster_ext
HillshadeName = fname_prefix+'_hs'+raster_ext
BasinsName = fname_prefix+'_AllBasins'+raster_ext
# This initiates the figure
MF = MapFigure(HillshadeName, DataDirectory,coord_type="UTM_km", colourbar_location="None")
# This adds the basins
MF.add_basin_plot(BasinsName,fname_prefix,DataDirectory, mask_list = Remove_Basins,
rename_dict = Rename_Basins, value_dict = Value_dict,
use_keys_not_junctions = use_keys_not_junctions, show_colourbar = show_colourbar,
discrete_cmap=True, n_colours=15, colorbarlabel = colorbarlabel,
colourmap = cmap, adjust_text = False, label_basins = label_basins)
# See if you need the channels
if include_channels:
print("I am going to add some channels for you")
ChannelFileName = fname_prefix+"_chi_data_map.csv"
chi_csv_fname = DataDirectory+ChannelFileName
thisPointData = LSDMap_PD.LSDMap_PointData(chi_csv_fname)
MF.add_point_data(thisPointData,column_for_plotting = "basin_key",
scale_points = True,column_for_scaling = "drainage_area",
this_colourmap = "Blues_r", scaled_data_in_log = True,
max_point_size = 3, min_point_size = 1, discrete_colours = True, NColours = 1, zorder = 5)
# Save the image
if len(out_fname_prefix) == 0:
ImageName = DataDirectory+fname_prefix+"_selected_basins."+fig_format
else:
ImageName = DataDirectory+out_fname_prefix+"_selected_basins."+fig_format
MF.save_fig(fig_width_inches = fig_width_inches, FigFileName = ImageName, FigFormat=fig_format, Fig_dpi = dpi, transparent=True) # Save the figure
basemap_colourmap="gray",
plot_title='None',
NFF_opti=False,
alpha=1) # load and display the background hillslope raster
MF.add_basin_plot(RasterName=RasterNameCatch,
BasinInfoPrefix=BasinInfoPrefix,
Directory=Import_Directory,
colourmap="gray",
alpha=1,
show_colourbar="False",
colorbarlabel="Colourbar",
discrete_cmap=False,
n_colours=10,
cbar_type=float,
use_keys_not_junctions=True,
label_basins=False,
adjust_text=False,
rename_dict={0: '13'},
value_dict={},
mask_list=[],
edgecolour='black',
linewidth=2,
cbar_dict={},
parallel=False,
outlines_only=True,
zorder=3)
MF.add_point_data(
thisPointData=thisPointData,
column_for_plotting='m_chi',
this_colourmap="rainbow",
def PrintBasins_Complex(DataDirectory,
fname_prefix,
use_keys_not_junctions=True,
show_colourbar=False,
Remove_Basins=[],
Rename_Basins={},
Value_dict={},
cmap="jet",
colorbarlabel="colourbar",
size_format="ESURF",
fig_format="png",
dpi=250,
out_fname_prefix="",
include_channels=False,
label_basins=True):
"""
This function makes a shaded relief plot of the DEM with the basins coloured
by the basin ID.
Args:
DataDirectory (str): the data directory with the m/n csv files
fname_prefix (str): The prefix for the m/n csv files
use_keys_not_junctions (bool): If true use basin keys to locate basins, otherwise use junction indices
show_colourbar (bool): if true show the colourbar
Remove_Basins (list): A lists containing either key or junction indices of basins you want to remove from plotting
Rename_Basins (dict): A dict where the key is either basin key or junction index, and the value is a new name for the basin denoted by the key
Value_dict (dict): A dict where the key is either basin key or junction index, and the value is a value of the basin that is used to colour the basins
add_basin_labels (bool): If true, label the basins with text. Otherwise use a colourbar.
cmap (str or colourmap): The colourmap to use for the plot
cbar_loc (str): where you want the colourbar. Options are none, left, right, top and botton. The colourbar will be of the elevation.
If you want only a hillshade set to none and the cmap to "gray"
size_format (str): Either geomorphology or big. Anything else gets you a 4.9 inch wide figure (standard ESURF size)
fig_format (str): An image format. png, pdf, eps, svg all valid
dpi (int): The dots per inch of the figure
out_fname_prefix (str): The prefix of the image file. If blank uses the fname_prefix
include_channels (bool): If true, adds a channel plot. It uses the chi_data_maps file
label_basins (bool): If true, the basins get labels
Returns:
Shaded relief plot with the basins coloured by basin ID. Uses a colourbar to show each basin. This allows more complex plotting with renamed and excluded basins.
Author: FJC, SMM
"""
#import modules
from LSDMapFigure.PlottingRaster import MapFigure
# set figure sizes based on format
if size_format == "geomorphology":
fig_width_inches = 6.25
elif size_format == "big":
fig_width_inches = 16
else:
fig_width_inches = 4.92126
# get the basin IDs to make a discrete colourmap for each ID
BasinInfoDF = PlotHelp.ReadBasinInfoCSV(DataDirectory, fname_prefix)
basin_keys = list(BasinInfoDF['basin_key'])
basin_keys = [int(x) for x in basin_keys]
basin_junctions = list(BasinInfoDF['outlet_junction'])
basin_junctions = [float(x) for x in basin_junctions]
print('Basin keys are: ')
print(basin_keys)
# going to make the basin plots - need to have bil extensions.
print(
"I'm going to make the basin plots. Your topographic data must be in ENVI bil format or I'll break!!"
)
# get the rasters
raster_ext = '.bil'
#BackgroundRasterName = fname_prefix+raster_ext
HillshadeName = fname_prefix + '_hs' + raster_ext
BasinsName = fname_prefix + '_AllBasins' + raster_ext
# This initiates the figure
MF = MapFigure(HillshadeName,
DataDirectory,
coord_type="UTM_km",
colourbar_location="None")
# This adds the basins
MF.add_basin_plot(BasinsName,
fname_prefix,
DataDirectory,
mask_list=Remove_Basins,
rename_dict=Rename_Basins,
value_dict=Value_dict,
use_keys_not_junctions=use_keys_not_junctions,
show_colourbar=show_colourbar,
discrete_cmap=True,
n_colours=15,
colorbarlabel=colorbarlabel,
colourmap=cmap,
adjust_text=False,
label_basins=label_basins)
# See if you need the channels
if include_channels:
print("I am going to add some channels for you")
ChannelFileName = fname_prefix + "_chi_data_map.csv"
chi_csv_fname = DataDirectory + ChannelFileName
thisPointData = LSDMap_PD.LSDMap_PointData(chi_csv_fname)
MF.add_point_data(thisPointData,
column_for_plotting="basin_key",
scale_points=True,
column_for_scaling="drainage_area",
this_colourmap="Blues_r",
scaled_data_in_log=True,
max_point_size=3,
min_point_size=1,
discrete_colours=True,
NColours=1,
zorder=5)
# Save the image
if len(out_fname_prefix) == 0:
ImageName = DataDirectory + fname_prefix + "_selected_basins." + fig_format
else:
ImageName = DataDirectory + out_fname_prefix + "_selected_basins." + fig_format
MF.save_fig(fig_width_inches=fig_width_inches,
FigFileName=ImageName,
FigFormat=fig_format,
Fig_dpi=dpi,
transparent=True) # Save the figure
def ExampleOne_PartFive_MaskBasinsMF(DataDirectory, fname_prefix):
"""
This function makes a shaded relief plot of the DEM with the basins coloured
by the basin ID.
Args:
DataDirectory (str): the data directory with the m/n csv files
fname_prefix (str): The prefix for the m/n csv files
Returns:
Shaded relief plot with the basins coloured by basin ID
Author: SMM
"""
FigFormat = "png"
size_format = "geomorphology"
# Set up fonts for plots
label_size = 10
rcParams['font.family'] = 'sans-serif'
rcParams['font.sans-serif'] = ['arial']
rcParams['font.size'] = label_size
# set figure sizes based on format
if size_format == "geomorphology":
fig_width_inches = 6.25
elif size_format == "big":
fig_width_inches = 16
else:
fig_width_inches = 4.92126
# going to make the basin plots - need to have bil extensions.
print("I'm going to make the basin plots. Your topographic data must be in ENVI bil format or I'll break!!")
# get the rasters
raster_ext = '.bil'
#BackgroundRasterName = fname_prefix+raster_ext
HillshadeName = fname_prefix+'_hs'+raster_ext
BasinsName = fname_prefix+'_AllBasins'+raster_ext
print (BasinsName)
# create the map figure
# We set colourbar location to none since we are labelling the figures
MF = MapFigure(HillshadeName, DataDirectory,coord_type="UTM_km", colourbar_location='bottom',basemap_colourmap = "gray")
# add the basins drape
#MF.add_drape_image(HillshadeName, DataDirectory, colourmap = cmap, alpha = 0.8, colorbarlabel='Basin ID', discrete_cmap=True, n_colours=len(basin_keys), show_colourbar = False)
Remove_Basins = [4,8]
Rename_Basins = { 12: 'chumbox', 14: 'zeppo'}
Value_dict= { 1: 0.2, 2:0.3, 3:0.4, 5:0.9,6:0.7, 7:0.3, 9:0.5, 10:0.5}
MF.add_basin_plot(BasinsName,fname_prefix,DataDirectory, mask_list = Remove_Basins,
rename_dict = Rename_Basins, value_dict = Value_dict,
use_keys_not_junctions = True, show_colourbar = True,
discrete_cmap=True, n_colours=8, colorbarlabel = "$m/n$",
colourmap = plt.cm.jet, adjust_text = False)
# Save the figure
ImageName = DataDirectory+fname_prefix+'_test_Coloured_basins.'+FigFormat
MF.save_fig(fig_width_inches = fig_width_inches, FigFileName = ImageName, FigFormat=FigFormat, Fig_dpi = 250)
def ExampleOne_PartFive_MaskBasinsMF(DataDirectory, fname_prefix):
"""
This function makes a shaded relief plot of the DEM with the basins coloured
by the basin ID.
Args:
DataDirectory (str): the data directory with the m/n csv files
fname_prefix (str): The prefix for the m/n csv files
Returns:
Shaded relief plot with the basins coloured by basin ID
Author: SMM
"""
FigFormat = "png"
size_format = "geomorphology"
# Set up fonts for plots
label_size = 10
rcParams['font.family'] = 'sans-serif'
rcParams['font.sans-serif'] = ['Liberation Sans']
rcParams['font.size'] = label_size
# set figure sizes based on format
if size_format == "geomorphology":
fig_width_inches = 6.25
elif size_format == "big":
fig_width_inches = 16
else:
fig_width_inches = 4.92126
# going to make the basin plots - need to have bil extensions.
print("I'm going to make the basin plots. Your topographic data must be in ENVI bil format or I'll break!!")
# get the rasters
raster_ext = '.bil'
#BackgroundRasterName = fname_prefix+raster_ext
HillshadeName = fname_prefix+'_hs'+raster_ext
BasinsName = fname_prefix+'_AllBasins'+raster_ext
print (BasinsName)
# create the map figure
# We set colourbar location to none since we are labelling the figures
MF = MapFigure(HillshadeName, DataDirectory,coord_type="UTM_km", colourbar_location='bottom',basemap_colourmap = "gray")
# add the basins drape
#MF.add_drape_image(HillshadeName, DataDirectory, colourmap = cmap, alpha = 0.8, colorbarlabel='Basin ID', discrete_cmap=True, n_colours=len(basin_keys), show_colourbar = False)
Remove_Basins = [4,8]
Rename_Basins = { 12: 'chumbox', 14: 'zeppo'}
Value_dict= { 1: 0.2, 2:0.3, 3:0.4, 5:0.9,6:0.7, 7:0.3, 9:0.5, 10:0.5}
MF.add_basin_plot(BasinsName,fname_prefix,DataDirectory, mask_list = Remove_Basins,
rename_dict = Rename_Basins, value_dict = Value_dict,
use_keys_not_junctions = True, show_colourbar = True,
discrete_cmap=True, n_colours=8, colorbarlabel = "$m/n$",
colourmap = plt.cm.jet, adjust_text = False)
# Save the figure
ImageName = DataDirectory+fname_prefix+'_test_Coloured_basins.'+FigFormat
MF.save_fig(fig_width_inches = fig_width_inches, FigFileName = ImageName, FigFormat=FigFormat, Fig_dpi = 250)
cbar_type=float,
NFF_opti=False,
custom_min_max=[],
zorder=2)
MF.add_basin_plot(RasterName=RasterName_NogPal,
BasinInfoPrefix=BasinInfoPrefix_NogPal,
Directory=Import_Directory,
colourmap="gray",
alpha=0.2,
show_colourbar="False",
colorbarlabel="Colourbar",
discrete_cmap=False,
n_colours=10,
cbar_type=float,
use_keys_not_junctions=True,
label_basins=False,
adjust_text=False,
rename_dict={0: '13'},
value_dict={},
mask_list=[],
edgecolour='black',
linewidth=1,
cbar_dict={},
parallel=False,
outlines_only=True,
zorder=3)
MF.add_basin_plot(RasterName=RasterName_NogRib,
BasinInfoPrefix=BasinInfoPrefix_NogRib,
Directory=Import_Directory,
colourmap="gray",
alpha=0.2,
def main(argv):
# If there are no arguments, send to the welcome screen
if not len(sys.argv) > 1:
full_paramfile = print_welcome()
sys.exit()
# Get the arguments
import argparse
parser = argparse.ArgumentParser()
# The location of the data files
parser.add_argument("-dir", "--base_directory", type=str, help="The base directory. If not defined, current directory.")
parser.add_argument("-fname", "--fname_prefix", type=str, help="The prefix of your DEM WITHOUT EXTENSION!")
parser.add_argument("-fmt", "--FigFormat", type=str, default='png', help="Set the figure format for the plots. Default is png")
args = parser.parse_args()
# get the base directory
if args.base_directory:
DataDirectory = args.base_directory
# check if you remembered a / at the end of your path_name
if not DataDirectory.endswith("/"):
print("You forgot the '/' at the end of the directory, appending...")
DataDirectory = this_dir+"/"
else:
this_dir = os.getcwd()
if not args.fname_prefix:
print("WARNING! You haven't supplied your DEM name. Please specify this with the flag '-fname'")
sys.exit()
else:
fname_prefix = args.fname_prefix
# set to not parallel
parallel = False
faults = True
FigFormat = args.FigFormat
# check if a directory exists for the chi plots. If not then make it.
raster_directory = DataDirectory+'raster_plots/'
if not os.path.isdir(raster_directory):
os.makedirs(raster_directory)
# Set up fonts for plots
label_size = 8
rcParams['font.family'] = 'sans-serif'
rcParams['font.sans-serif'] = ['Liberation Sans']
rcParams['font.size'] = label_size
# set figure sizes based on format
size_format = ""
if size_format == "geomorphology":
fig_width_inches = 6.25
elif size_format == "big":
fig_width_inches = 16
else:
fig_width_inches = 4.92126
# get the basin IDs to make a discrete colourmap for each ID
BasinInfoDF = Helper.ReadBasinInfoCSV(DataDirectory, fname_prefix)
basin_keys = list(BasinInfoDF['basin_key'])
basin_keys = [int(x) for x in basin_keys]
basin_junctions = list(BasinInfoDF['outlet_junction'])
basin_junctions = [int(x) for x in basin_junctions]
print("\n\n")
print(basin_keys)
print(basin_junctions)
print("\n\n")
# get a discrete colormap
cmap = plt.cm.Blues
# going to make the basin plots - need to have bil extensions.
print("I'm going to make the basin plots. Your topographic data must be in ENVI bil format or I'll break!!")
# get the rasters
raster_ext = '.bil'
BackgroundRasterName = fname_prefix+raster_ext
HillshadeName = fname_prefix+'_hs'+raster_ext
BasinsName = fname_prefix+'_AllBasins'+raster_ext
# create the map figure
MF = MapFigure(HillshadeName, DataDirectory,coord_type="UTM_km", colourbar_location='top')
# add the basins drape
BasinsDict = dict(zip(basin_keys,basin_keys))
MF.add_basin_plot(BasinsName,fname_prefix,DataDirectory, label_basins=False,
use_keys_not_junctions = True, show_colourbar = True,
value_dict = BasinsDict, discrete_cmap=True, n_colours=len(basin_keys),
colorbarlabel = "Basin ID", cbar_type=int,
colourmap = cmap, colorbartickthinfactor=2, edgecolour='none', adjust_text = True, parallel=parallel)
# add the faults
if faults:
LineFileName = DataDirectory + fname_prefix + "_faults.shp"
MF.add_line_data(LineFileName, linestyle="-", linewidth=1.5, zorder=99, legend=True, label="Fault Segments")
# add the basin outlines ### need to parallelise
if not parallel:
Basins = LSDP.GetBasinOutlines(DataDirectory, BasinsName)
else:
Basins = LSDP.GetMultipleBasinOutlines(DataDirectory)
# Find the relay basins and plot separately
RelayBasinIDs = [1248, 4788, 4995, 5185, 6187, 6758, 6805]
RelayBasins = {key:value for key, value in Basins.items() if key in RelayBasinIDs}
# Plot all basins
MF.plot_polygon_outlines(Basins, colour='k', linewidth=0.5, alpha = 1, legend=True, label="Catchments")
# Plot relay basins
MF.plot_polygon_outlines(RelayBasins, colour='r', linewidth=0.5, alpha = 1, legend=True, label="Relay Catchments")
# add the channel network
if not parallel:
ChannelDF = Helper.ReadChiDataMapCSV(DataDirectory,fname_prefix)
else:
ChannelDF = Helper.AppendChiDataMapCSVs(DataDirectory)
ChannelPoints = LSDP.LSDMap_PointData(ChannelDF, data_type = "pandas", PANDEX = True)
MF.add_point_data(ChannelPoints,show_colourbar="False", manual_size=0.5, alpha=0.1,zorder=90, legend=True, label="Stream Network")
# Add the legend
MF.add_legend()
# Save the figure
ImageName = raster_directory+fname_prefix+'_basin_keys.'+FigFormat
MF.save_fig(fig_width_inches = fig_width_inches, FigFileName = ImageName, FigFormat=FigFormat, Fig_dpi = 300)
def main(argv):
# If there are no arguments, send to the welcome screen
if not len(sys.argv) > 1:
full_paramfile = print_welcome()
sys.exit()
# Get the arguments
import argparse
parser = argparse.ArgumentParser()
# The location of the data files
parser.add_argument("-dir", "--base_directory", type=str, help="The base directory. If not defined, current directory.")
parser.add_argument("-fname", "--fname_prefix", type=str, help="The prefix of your DEM WITHOUT EXTENSION!")
parser.add_argument("-fmt", "--FigFormat", type=str, default='png', help="Set the figure format for the plots. Default is png")
args = parser.parse_args()
# get the base directory
if args.base_directory:
DataDirectory = args.base_directory
# check if you remembered a / at the end of your path_name
if not DataDirectory.endswith("/"):
print("You forgot the '/' at the end of the directory, appending...")
DataDirectory = this_dir+"/"
else:
this_dir = os.getcwd()
if not args.fname_prefix:
print("WARNING! You haven't supplied your DEM name. Please specify this with the flag '-fname'")
sys.exit()
else:
fname_prefix = args.fname_prefix
# set to not parallel
parallel = False
faults = True
FigFormat = args.FigFormat
# check if a directory exists for the chi plots. If not then make it.
raster_directory = DataDirectory+'raster_plots/'
if not os.path.isdir(raster_directory):
os.makedirs(raster_directory)
# Set up fonts for plots
label_size = 8
rcParams['font.family'] = 'sans-serif'
rcParams['font.sans-serif'] = ['arial']
rcParams['font.size'] = label_size
# set figure sizes based on format
size_format = ""
if size_format == "geomorphology":
fig_width_inches = 6.25
elif size_format == "big":
fig_width_inches = 16
else:
fig_width_inches = 4.92126
# get the basin IDs to make a discrete colourmap for each ID
BasinInfoDF = Helper.ReadBasinInfoCSV(DataDirectory, fname_prefix)
basin_keys = list(BasinInfoDF['basin_key'])
basin_keys = [int(x) for x in basin_keys]
basin_junctions = list(BasinInfoDF['outlet_junction'])
basin_junctions = [int(x) for x in basin_junctions]
print("\n\n")
print(basin_keys)
print(basin_junctions)
print("\n\n")
# get a discrete colormap
cmap = plt.cm.Blues
# going to make the basin plots - need to have bil extensions.
print("I'm going to make the basin plots. Your topographic data must be in ENVI bil format or I'll break!!")
# get the rasters
raster_ext = '.bil'
BackgroundRasterName = fname_prefix+raster_ext
HillshadeName = fname_prefix+'_hs'+raster_ext
BasinsName = fname_prefix+'_AllBasins'+raster_ext
# create the map figure
MF = MapFigure(HillshadeName, DataDirectory,coord_type="UTM_km", colourbar_location='top')
# add the basins drape
BasinsDict = dict(zip(basin_keys,basin_keys))
MF.add_basin_plot(BasinsName,fname_prefix,DataDirectory, label_basins=False,
use_keys_not_junctions = True, show_colourbar = True,
value_dict = BasinsDict, discrete_cmap=True, n_colours=len(basin_keys),
colorbarlabel = "Basin ID", cbar_type=int,
colourmap = cmap, colorbartickthinfactor=2, edgecolour='none', adjust_text = True, parallel=parallel)
# add the faults
if faults:
LineFileName = DataDirectory + fname_prefix + "_faults.shp"
MF.add_line_data(LineFileName, linestyle="-", linewidth=1.5, zorder=99, legend=True, label="Fault Segments")
# add the basin outlines ### need to parallelise
if not parallel:
Basins = LSDP.GetBasinOutlines(DataDirectory, BasinsName)
else:
Basins = LSDP.GetMultipleBasinOutlines(DataDirectory)
# Find the relay basins and plot separately
RelayBasinIDs = [1248, 4788, 4995, 5185, 6187, 6758, 6805]
RelayBasins = {key:value for key, value in Basins.items() if key in RelayBasinIDs}
# Plot all basins
MF.plot_polygon_outlines(Basins, colour='k', linewidth=0.5, alpha = 1, legend=True, label="Catchments")
# Plot relay basins
MF.plot_polygon_outlines(RelayBasins, colour='r', linewidth=0.5, alpha = 1, legend=True, label="Relay Catchments")
# add the channel network
if not parallel:
ChannelDF = Helper.ReadChiDataMapCSV(DataDirectory,fname_prefix)
else:
ChannelDF = Helper.AppendChiDataMapCSVs(DataDirectory)
ChannelPoints = LSDP.LSDMap_PointData(ChannelDF, data_type = "pandas", PANDEX = True)
MF.add_point_data(ChannelPoints,show_colourbar="False", manual_size=0.5, alpha=0.1,zorder=90, legend=True, label="Stream Network")
# Add the legend
MF.add_legend()
# Save the figure
ImageName = raster_directory+fname_prefix+'_basin_keys.'+FigFormat
MF.save_fig(fig_width_inches = fig_width_inches, FigFileName = ImageName, FigFormat=FigFormat, Fig_dpi = 300)
def PrintChiCoordChannelsAndBasins(DataDirectory,
fname_prefix,
ChannelFileName,
add_basin_labels=True,
cmap="cubehelix",
cbar_loc="right",
size_format="ESURF",
fig_format="png",
dpi=250,
plotting_column="source_key",
discrete_colours=False,
NColours=10,
colour_log=True,
colorbarlabel="Colourbar",
Basin_remove_list=[],
Basin_rename_dict={},
value_dict={},
plot_chi_raster=False,
out_fname_prefix="",
show_basins=True,
min_channel_point_size=0.5,
max_channel_point_size=2):
"""
This function prints a channel map over a hillshade.
Args:
DataDirectory (str): the data directory with the m/n csv files
fname_prefix (str): The prefix for the m/n csv files
add_basin_labels (bool): If true, label the basins with text. Otherwise use a colourbar.
cmap (str or colourmap): The colourmap to use for the plot
cbar_loc (str): where you want the colourbar. Options are none, left, right, top and botton. The colourbar will be of the elevation.
If you want only a hillshade set to none and the cmap to "gray"
size_format (str): Either geomorphology or big. Anything else gets you a 4.9 inch wide figure (standard ESURF size)
fig_format (str): An image format. png, pdf, eps, svg all valid
dpi (int): The dots per inch of the figure
plotting_column (str): the name of the column to plot
discrete_colours (bool): if true use a discrete colourmap
NColours (int): the number of colours to cycle through when making the colourmap
colour_log (bool): If true the colours are in log scale
Basin_remove_list (list): A lists containing either key or junction indices of basins you want to remove from plotting
Basin_rename_dict (dict): A dict where the key is either basin key or junction index, and the value is a new name for the basin denoted by the key
out_fname_prefix (str): The prefix of the image file. If blank uses the fname_prefix
show_basins (bool): If true, plot the basins
min_channel_point_size (float): The minimum size of a channel point in points
max_channel_point_size (float): The maximum size of a channel point in points
Returns:
Shaded relief plot with the basins coloured by basin ID. Includes channels. These can be plotted by various metrics denoted but the plotting_column parameter.
Author: SMM
"""
# specify the figure size and format
# set figure sizes based on format
if size_format == "geomorphology":
fig_size_inches = 6.25
elif size_format == "big":
fig_size_inches = 16
else:
fig_size_inches = 4.92126
ax_style = "Normal"
# get the basin IDs to make a discrete colourmap for each ID
BasinInfoDF = PlotHelp.ReadBasinInfoCSV(DataDirectory, fname_prefix)
basin_keys = list(BasinInfoDF['basin_key'])
basin_keys = [int(x) for x in basin_keys]
basin_junctions = list(BasinInfoDF['outlet_junction'])
basin_junctions = [float(x) for x in basin_junctions]
print('Basin keys are: ')
print basin_keys
# going to make the basin plots - need to have bil extensions.
print(
"I'm going to make the basin plots. Your topographic data must be in ENVI bil format or I'll break!!"
)
# get the rasters
raster_ext = '.bil'
#BackgroundRasterName = fname_prefix+raster_ext
HillshadeName = fname_prefix + '_hs' + raster_ext
BasinsName = fname_prefix + '_AllBasins' + raster_ext
ChiCoordName = fname_prefix + '_Maskedchi' + raster_ext
print(BasinsName)
Basins = LSDP.GetBasinOutlines(DataDirectory, BasinsName)
chi_csv_fname = DataDirectory + ChannelFileName
chi_csv_fname = DataDirectory + ChannelFileName
thisPointData = LSDMap_PD.LSDMap_PointData(chi_csv_fname)
#thisPointData.ThinDataSelection("basin_key",[10])
thisPointData.selectValue("basin_key",
value=Basin_remove_list,
operator="!=")
#print("The new point data is:")
#print(thisPointData.GetLongitude())
# clear the plot
plt.clf()
# set up the base image and the map
print("I am showing the basins without text labels.")
MF = MapFigure(HillshadeName,
DataDirectory,
coord_type="UTM_km",
colourbar_location="None")
# This adds the basins
if plot_chi_raster:
if show_basins:
MF.add_basin_plot(BasinsName,
fname_prefix,
DataDirectory,
mask_list=Basin_remove_list,
rename_dict=Basin_rename_dict,
value_dict=value_dict,
label_basins=add_basin_labels,
show_colourbar=False,
colourmap="gray",
alpha=1,
outlines_only=True)
MF.add_drape_image(ChiCoordName,
DataDirectory,
colourmap="cubehelix",
alpha=0.6,
zorder=0.5)
MF.add_point_data(thisPointData,
column_for_plotting=plotting_column,
scale_points=True,
column_for_scaling="drainage_area",
show_colourbar=True,
colourbar_location=cbar_loc,
colorbarlabel=colorbarlabel,
this_colourmap=cmap,
scaled_data_in_log=True,
max_point_size=max_channel_point_size,
min_point_size=min_channel_point_size,
zorder=0.4,
colour_log=colour_log,
discrete_colours=discrete_colours,
NColours=NColours)
else:
if show_basins:
MF.add_basin_plot(BasinsName,
fname_prefix,
DataDirectory,
mask_list=Basin_remove_list,
rename_dict=Basin_rename_dict,
value_dict=value_dict,
label_basins=add_basin_labels,
show_colourbar=False,
colourmap="gray",
alpha=0.7,
outlines_only=False)
MF.add_point_data(thisPointData,
column_for_plotting=plotting_column,
scale_points=True,
column_for_scaling="drainage_area",
show_colourbar=True,
colourbar_location=cbar_loc,
colorbarlabel=colorbarlabel,
this_colourmap=cmap,
scaled_data_in_log=True,
max_point_size=2,
min_point_size=0.5,
zorder=10,
colour_log=colour_log,
discrete_colours=discrete_colours,
NColours=NColours)
# Save the image
if len(out_fname_prefix) == 0:
ImageName = DataDirectory + fname_prefix + "_chicoord_and_basins." + fig_format
else:
ImageName = DataDirectory + out_fname_prefix + "_chicoord_and_basins." + fig_format
MF.save_fig(fig_width_inches=fig_size_inches,
FigFileName=ImageName,
axis_style=ax_style,
FigFormat=fig_format,
Fig_dpi=dpi)
def PrintChiCoordChannelsAndBasins(DataDirectory,fname_prefix, ChannelFileName, add_basin_labels = True, cmap = "cubehelix", cbar_loc = "right", size_format = "ESURF", fig_format = "png", dpi = 250,plotting_column = "source_key",discrete_colours = False, NColours = 10, colour_log = True, colorbarlabel = "Colourbar", Basin_remove_list = [], Basin_rename_dict = {} , value_dict = {}, plot_chi_raster = False, out_fname_prefix = "", show_basins = True, min_channel_point_size = 0.5, max_channel_point_size = 2):
"""
This function prints a channel map over a hillshade.
Args:
DataDirectory (str): the data directory with the m/n csv files
fname_prefix (str): The prefix for the m/n csv files
add_basin_labels (bool): If true, label the basins with text. Otherwise use a colourbar.
cmap (str or colourmap): The colourmap to use for the plot
cbar_loc (str): where you want the colourbar. Options are none, left, right, top and botton. The colourbar will be of the elevation.
If you want only a hillshade set to none and the cmap to "gray"
size_format (str): Either geomorphology or big. Anything else gets you a 4.9 inch wide figure (standard ESURF size)
fig_format (str): An image format. png, pdf, eps, svg all valid
dpi (int): The dots per inch of the figure
plotting_column (str): the name of the column to plot
discrete_colours (bool): if true use a discrete colourmap
NColours (int): the number of colours to cycle through when making the colourmap
colour_log (bool): If true the colours are in log scale
Basin_remove_list (list): A lists containing either key or junction indices of basins you want to remove from plotting
Basin_rename_dict (dict): A dict where the key is either basin key or junction index, and the value is a new name for the basin denoted by the key
out_fname_prefix (str): The prefix of the image file. If blank uses the fname_prefix
show_basins (bool): If true, plot the basins
min_channel_point_size (float): The minimum size of a channel point in points
max_channel_point_size (float): The maximum size of a channel point in points
Returns:
Shaded relief plot with the basins coloured by basin ID. Includes channels. These can be plotted by various metrics denoted but the plotting_column parameter.
Author: SMM
"""
# specify the figure size and format
# set figure sizes based on format
if size_format == "geomorphology":
fig_size_inches = 6.25
elif size_format == "big":
fig_size_inches = 16
else:
fig_size_inches = 4.92126
ax_style = "Normal"
# get the basin IDs to make a discrete colourmap for each ID
BasinInfoDF = PlotHelp.ReadBasinInfoCSV(DataDirectory, fname_prefix)
basin_keys = list(BasinInfoDF['basin_key'])
basin_keys = [int(x) for x in basin_keys]
basin_junctions = list(BasinInfoDF['outlet_junction'])
basin_junctions = [float(x) for x in basin_junctions]
print ('Basin keys are: ')
print (basin_keys)
# going to make the basin plots - need to have bil extensions.
print("I'm going to make the basin plots. Your topographic data must be in ENVI bil format or I'll break!!")
# get the rasters
raster_ext = '.bil'
#BackgroundRasterName = fname_prefix+raster_ext
HillshadeName = fname_prefix+'_hs'+raster_ext
BasinsName = fname_prefix+'_AllBasins'+raster_ext
ChiCoordName = fname_prefix+'_Maskedchi'+raster_ext
print (BasinsName)
Basins = LSDP.GetBasinOutlines(DataDirectory, BasinsName)
chi_csv_fname = DataDirectory+ChannelFileName
chi_csv_fname = DataDirectory+ChannelFileName
thisPointData = LSDMap_PD.LSDMap_PointData(chi_csv_fname)
# Remove data that has nodata values
thisPointData.selectValue(plotting_column,value = -9999, operator = "!=")
thisPointData.selectValue("basin_key",value = Basin_remove_list, operator = "!=")
#print("The new point data is:")
#print(thisPointData.GetLongitude())
# clear the plot
plt.clf()
# set up the base image and the map
print("I am showing the basins without text labels.")
MF = MapFigure(HillshadeName, DataDirectory,coord_type="UTM_km", colourbar_location="None")
# This adds the basins
if plot_chi_raster:
if show_basins:
MF.add_basin_plot(BasinsName,fname_prefix,DataDirectory, mask_list = Basin_remove_list, rename_dict = Basin_rename_dict, value_dict = value_dict, label_basins = add_basin_labels, show_colourbar = False, colourmap = "gray", alpha = 1, outlines_only = True)
MF.add_drape_image(ChiCoordName,DataDirectory,colourmap = "cubehelix",alpha=0.6,zorder = 0.5)
MF.add_point_data(thisPointData,column_for_plotting = plotting_column,scale_points = True,column_for_scaling = "drainage_area", show_colourbar = True, colourbar_location = cbar_loc,colorbarlabel = colorbarlabel, this_colourmap = cmap,scaled_data_in_log = True,max_point_size = max_channel_point_size, min_point_size = min_channel_point_size,zorder=0.4, colour_log = colour_log, discrete_colours = discrete_colours, NColours = NColours)
else:
if show_basins:
MF.add_basin_plot(BasinsName,fname_prefix,DataDirectory, mask_list = Basin_remove_list, rename_dict = Basin_rename_dict, value_dict = value_dict, label_basins = add_basin_labels, show_colourbar = False, colourmap = "gray", alpha = 0.7, outlines_only = False)
MF.add_point_data(thisPointData,column_for_plotting = plotting_column,scale_points = True,column_for_scaling = "drainage_area", show_colourbar = True, colourbar_location = cbar_loc,colorbarlabel = colorbarlabel, this_colourmap = cmap,scaled_data_in_log = True,max_point_size = 2, min_point_size = 0.5,zorder=10, colour_log = colour_log, discrete_colours = discrete_colours, NColours = NColours)
# Save the image
if len(out_fname_prefix) == 0:
ImageName = DataDirectory+fname_prefix+"_chicoord_and_basins."+fig_format
else:
ImageName = DataDirectory+out_fname_prefix+"_chicoord_and_basins."+fig_format
MF.save_fig(fig_width_inches = fig_size_inches, FigFileName = ImageName, axis_style = ax_style, FigFormat=fig_format, Fig_dpi = dpi)