def PrintBasins(DataDirectory,
fname_prefix,
add_basin_labels=True,
cmap="jet",
cbar_loc="right",
size_format="ESURF",
fig_format="png",
dpi=250,
out_fname_prefix=""):
"""
This function makes a shaded relief plot of the DEM with the basins coloured
by the basin ID.
IMPORTANT: To get this to run you need to set the flags in chi mapping tool to:
write_hillshade: true
print_basin_raster: true
print_chi_data_maps: true
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_lox (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
Returns:
Shaded relief plot with the basins coloured by basin ID. Uses a colourbar to show each basin
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
print(BasinsName)
Basins = LSDP.GetBasinOutlines(DataDirectory, BasinsName)
# If wanted, add the labels
if add_basin_labels:
print("I am going to add basin labels, there will be no colourbar.")
MF = MapFigure(HillshadeName,
DataDirectory,
coord_type="UTM_km",
colourbar_location="None")
MF.plot_polygon_outlines(Basins, linewidth=0.8)
MF.add_drape_image(BasinsName,
DataDirectory,
colourmap=cmap,
alpha=0.8,
colorbarlabel='Basin ID',
discrete_cmap=True,
n_colours=len(basin_keys),
show_colourbar=False,
modify_raster_values=True,
old_values=basin_junctions,
new_values=basin_keys,
cbar_type=int)
# This is used to label the basins
label_dict = dict(zip(basin_junctions, basin_keys))
# this dict has the basin junction as the key and the basin_key as the value
Points = LSDP.GetPointWithinBasins(DataDirectory, BasinsName)
MF.add_text_annotation_from_shapely_points(Points,
text_colour='k',
label_dict=label_dict)
else:
print("I am showing the basins without text labels.")
MF = MapFigure(HillshadeName,
DataDirectory,
coord_type="UTM_km",
colourbar_location=cbar_loc)
MF.plot_polygon_outlines(Basins, linewidth=0.8)
MF.add_drape_image(BasinsName,
DataDirectory,
colourmap=cmap,
alpha=0.8,
colorbarlabel='Basin ID',
discrete_cmap=True,
n_colours=len(basin_keys),
show_colourbar=True,
modify_raster_values=True,
old_values=basin_junctions,
new_values=basin_keys,
cbar_type=int)
# Save the image
if len(out_fname_prefix) == 0:
ImageName = DataDirectory + fname_prefix + "_basins." + fig_format
else:
ImageName = DataDirectory + out_fname_prefix + "_basins." + fig_format
MF.save_fig(fig_width_inches=fig_width_inches,
FigFileName=ImageName,
FigFormat=fig_format,
Fig_dpi=dpi) # Save the figure
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]
# get a discrete colormap
cmap = plt.cm.viridis
# 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='none')
# 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 = False,
# value_dict = BasinsDict, discrete_cmap=True, n_colours=len(basin_keys),
# colorbarlabel = "Basin ID", cbar_type=int, tickspacefactor=2,
# colourmap = cmap, edgecolour='none', adjust_text = True, parallel=parallel)
# add the channel network
if not parallel:
ChannelDF = Helper.ReadChiDataMapCSV(DataDirectory, fname_prefix)
else:
ChannelDF = Helper.AppendChiDataMapCSVs(DataDirectory)
# remove chi no data values
ChannelDF = ChannelDF[ChannelDF.chi != -9999]
ChannelPoints = LSDP.LSDMap_PointData(ChannelDF,
data_type="pandas",
PANDEX=True)
# add chi map
MF.add_point_data(ChannelPoints,
column_for_plotting="chi",
column_for_scaling="chi",
colorbarlabel="$\chi$ (m)",
show_colourbar=True,
this_colourmap=cmap,
colourbar_location="top")
# 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")
MF.plot_polygon_outlines(RelayBasins,
colour='r',
linewidth=0.5,
alpha=1,
legend=True,
label="Relay Catchments")
# Add the legend
MF.add_legend()
# Save the figure
ImageName = raster_directory + fname_prefix + '_chi_map.' + FigFormat
MF.save_fig(fig_width_inches=fig_width_inches,
FigFileName=ImageName,
FigFormat=FigFormat,
Fig_dpi=300)
def PrintChannelsAndBasins(DataDirectory,
fname_prefix,
add_basin_labels=True,
cmap="jet",
cbar_loc="right",
size_format="ESURF",
fig_format="png",
dpi=250,
out_fname_prefix=""):
"""
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_lox (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
Returns:
Shaded relief plot with the basins coloured by basin ID. Uses a colourbar to show each basin
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
print(BasinsName)
Basins = LSDP.GetBasinOutlines(DataDirectory, BasinsName)
ChannelFileName = fname_prefix + "_chi_data_map.csv"
chi_csv_fname = DataDirectory + ChannelFileName
thisPointData = LSDMap_PD.LSDMap_PointData(chi_csv_fname)
# 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")
MF.plot_polygon_outlines(Basins, linewidth=0.8)
MF.add_drape_image(BasinsName,
DataDirectory,
colourmap=cmap,
alpha=0.1,
discrete_cmap=False,
n_colours=len(basin_keys),
show_colourbar=False,
modify_raster_values=True,
old_values=basin_junctions,
new_values=basin_keys,
cbar_type=int)
MF.add_point_data(thisPointData,
column_for_plotting="basin_key",
scale_points=True,
column_for_scaling="drainage_area",
this_colourmap=cmap,
scaled_data_in_log=True,
max_point_size=3,
min_point_size=1)
# Save the image
if len(out_fname_prefix) == 0:
ImageName = DataDirectory + fname_prefix + "_channels_with_basins." + fig_format
else:
ImageName = DataDirectory + out_fname_prefix + "_channels_with_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 MakeRasterLithoBasinMap(DataDirectory,
fname_prefix,
lname_prefix,
lithodict,
size_format='ESURF',
FigFormat='png',
basins=True,
m_chi=False,
mancol=[],
log_scale_river=False,
minmax_m_chi=[]):
"""
This function makes a shaded relief plot of the DEM with lithologic map on the top and basin outline
Args:
DataDirectory (str): the data directory with the m/n csv files
fname_prefix (str): The prefix for the m/n csv files
size_format (str): Can be "big" (16 inches wide), "geomorphology" (6.25 inches wide), or "ESURF" (4.92 inches wide) (defualt esurf).
FigFormat (str): The format of the figure. Usually 'png' or 'pdf'. If "show" then it calls the matplotlib show() command.
Basins (bool): Do you want the basin on top
minmax_m_chi (list): define a minimum/maximum for plotting m_chi on the top of litho (at the moment this plot is generated from knickpoint dataset)
Returns:
Shaded relief plot with the basins coloured by basin ID
Author: BG, FJC
"""
# 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 = 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
raster_ext = '.bil'
# get the basin IDs to make a discrete colourmap for each ID
if (basins):
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 = [float(x) for x in basin_junctions]
print('Basin keys are: ')
print(basin_keys)
BasinsName = fname_prefix + '_AllBasins.bil'
# 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
LithoMap = lname_prefix + raster_ext
# create the map figure
MF = MapFigure(HillshadeName,
DataDirectory,
coord_type="UTM_km",
colourbar_location='None')
MF.add_drape_image(HillshadeName,
DataDirectory,
NFF_opti=True,
custom_min_max=[90, 240],
alpha=1)
# add the geology drape
# MF.add_basin_plot(BasinsName,fname_prefix,DataDirectory,
# use_keys_not_junctions = True, show_colourbar = True,
# discrete_cmap=True, n_colours=len(basin_keys), colorbarlabel = "Basin ID",
# colourmap = cmap, adjust_text = False)
# getting the right color now
color_map_litho = getLithoColorMap(fname_prefix, DataDirectory)
df_litho_size = pd.read_csv(DataDirectory + fname_prefix + "_lithokey.csv")
MF.add_drape_image(LithoMap,
DataDirectory,
colourmap=color_map_litho,
alpha=0.6,
show_colourbar=False,
colorbarlabel="Colourbar",
discrete_cmap=False,
norm="None",
colour_min_max=[0, df_litho_size["rocktype"].max() - 1],
modify_raster_values=False,
old_values=[],
new_values=[],
cbar_type=int,
NFF_opti=True,
custom_min_max=[])
if (basins):
# add the basin outlines
Basins = LSDP.GetBasinOutlines(DataDirectory, BasinsName)
MF.plot_polygon_outlines(Basins, linewidth=0.8)
# knickpoints!
if (m_chi):
ChannelDF = pd.read_csv(DataDirectory + fname_prefix +
"_ksnkp_mchi.csv")
ChannelPoints = LSDP.LSDMap_PointData(ChannelDF,
data_type="pandas",
PANDEX=True)
MF.add_point_data(ChannelPoints,
column_for_plotting='m_chi',
show_colourbar=True,
scale_points=True,
column_for_scaling='drainage_area',
alpha=0.5,
zorder=100,
this_colourmap="RdBu_r",
colour_manual_scale=mancol,
scaled_data_in_log=log_scale_river,
max_point_size=minmax_m_chi[1],
min_point_size=minmax_m_chi[0])
else:
# add the channel network
ChannelDF = Helper.ReadChiDataMapCSV(DataDirectory, fname_prefix)
ChannelPoints = LSDP.LSDMap_PointData(ChannelDF,
data_type="pandas",
PANDEX=True)
MF.add_point_data(ChannelPoints,
show_colourbar="False",
scale_points=True,
column_for_scaling='drainage_area',
alpha=0.5,
zorder=100)
if (basins):
# add the basin labelling
label_dict = dict(zip(basin_junctions, basin_keys))
Points = LSDP.GetPointWithinBasins(DataDirectory, BasinsName)
MF.add_text_annotation_from_shapely_points(Points,
text_colour='k',
label_dict=label_dict,
zorder=200)
if (basins):
# Save the figure
ImageName = raster_directory + fname_prefix + '_basin_keys_litho.' + FigFormat
else:
ImageName = raster_directory + fname_prefix + '_litho.' + FigFormat
MF.save_fig(fig_width_inches=fig_width_inches,
FigFileName=ImageName,
FigFormat=FigFormat,
Fig_dpi=500)
def ExampleOne_PartTwo_PrintBasins(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: FJC
"""
#import modules
from LSDMapFigure.PlottingRaster import MapFigure
# Set up fonts for plots
label_size = 10
rcParams['font.family'] = 'sans-serif'
rcParams['font.sans-serif'] = ['Liberation Sans']
rcParams['font.size'] = label_size
size_format = "geomorphology"
# 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
# get a discrete colormap
cmap = plt.cm.jet
# 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
MF = MapFigure(HillshadeName, DataDirectory,coord_type="UTM_km", colourbar_location='bottom')
# add the basins drape
MF.add_drape_image(BasinsName, DataDirectory, colourmap = cmap, alpha = 0.8, colorbarlabel='Basin ID', discrete_cmap=True, n_colours=len(basin_keys), show_colourbar = True, modify_raster_values=True, old_values=basin_junctions, new_values=basin_keys, cbar_type = int)
# add the basin outlines
Basins = LSDP.GetBasinOutlines(DataDirectory, BasinsName)
MF.plot_polygon_outlines(Basins, linewidth=0.8)
FigFormat = "png"
ImageName = DataDirectory+fname_prefix+'_coloured_basins.'+FigFormat
MF.save_fig(fig_width_inches = fig_width_inches, FigFileName = ImageName, FigFormat=FigFormat, Fig_dpi = 250) # Save the figure
def ExampleOne_PartFour_MaskBasins(DataDirectory, fname_prefix):
"""
This function makes a shaded relief plot of the DEM with the basins coloured
by the basin ID. It shows how to mask certain basins.
Search the function for "Basins_to_mask".
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
"""
import numpy as np
Basins_to_mask = [0,4,6]
FigFormat = "png"
size_format = "geomorphology"
#import modules
# from LSDMapFigure.PlottingRaster import MapFigure
# from LSDMapFigure.PlottingRaster import BaseRaster
# import LSDPlottingTools.LSDMap_VectorTools as LSDMap_VT
# import LSDPlottingTools.LSDMap_PointTools as LSDMap_PT
# 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
# 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]
# get the junctions to mask
key_to_index_dict = dict(zip(basin_keys,basin_junctions))
junctions_to_mask = []
for basin in Basins_to_mask:
junctions_to_mask.append( key_to_index_dict[basin])
print("The junctions to mask are")
print(junctions_to_mask)
print ('Basin keys are: ')
print basin_keys
print("Let me mask those for you")
new_keys = []
for key in basin_keys:
if key in Basins_to_mask:
new_keys.append(np.nan)
else:
new_keys.append(key)
print("The new keys are: ")
print(new_keys)
basin_keys = new_keys
# get a discrete colormap
cmap = plt.cm.jet
# 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='none')
# add the basins drape
MF.add_drape_image(BasinsName, DataDirectory, colourmap = cmap, alpha = 0.8, colorbarlabel='Basin ID', discrete_cmap=True, n_colours=len(basin_keys), show_colourbar = True, modify_raster_values=True, old_values=basin_junctions, new_values=basin_keys, cbar_type = int)
# add the basin outlines
Basins = LSDP.GetBasinOutlines(DataDirectory, BasinsName)
# get rid of the basins that are being masked
for junction in junctions_to_mask:
del Basins[junction]
# note that at this stage the Basins are keyed with the junction index
MF.plot_polygon_outlines(Basins, linewidth=0.8)
# add the basin labelling
label_dict = dict(zip(basin_junctions,basin_keys))
# this dict has the basin junction as the key and the basin_key as the value
Points = LSDP.GetPointWithinBasins(DataDirectory, BasinsName)
# get rid of points as well
for junction in junctions_to_mask:
del Points[junction]
del label_dict[junction]
MF.add_text_annotation_from_shapely_points(Points, text_colour='k', label_dict=label_dict)
# Save the figure
ImageName = DataDirectory+fname_prefix+'_labelled_basins.'+FigFormat
MF.save_fig(fig_width_inches = fig_width_inches, FigFileName = ImageName, FigFormat=FigFormat, Fig_dpi = 250)
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)
