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 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 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)
