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Output_cohorts_by_year.py
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Output_cohorts_by_year.py
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import numpy as np
import gdal, os, sys, glob, random
import pylab as pl
import matplotlib.animation as animation
import subprocess
def Output_cohorts_by_year(self, time):#, Gra_NPG, Gra_LCP, Gra_FCP, Gra_HCP,
#Shr_NPG, Shr_LCP, Shr_FCP, Shr_HCP):#, Ponds,
# Lakes):
#=======================================
# OUTPUT FIGURES
#----------------------------------------
# Wetland Non-Polygonal Ground (meadow)
# ---------------------------------------
if self.WetNPG['Figures'].lower() == 'yes':
# Change to Output Directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/Wet_NPG/Year_Cohorts')
Wet_NPG_plot = np.reshape(self.ATTM_Wet_NPG, [int(self.ATTM_nrows), int(self.ATTM_ncols)])
# --------------------------------------
# Output figures placed into directory
# --------------------------------------
year = str(int(time + self.Year[0]))
# ---------------------------------------
# Create figures and corresponding data
#----------------------------------------
fig = pl.figure()
pl.imshow(Wet_NPG_plot, interpolation = 'nearest', cmap = 'spectral', vmin = 0.0, vmax = 1.0)
pl.title('Wetland Non-Polygonal Ground Fractional Area - '+str(year))
pl.colorbar(extend = 'neither', shrink = 0.92)
pl.savefig('Wet_NPG_Fractional_Area_'+str(year)+'.jpg', format = 'jpg')
Wet_NPG_plot.tofile('Wet_NPG_Fractional_Area_'+str(year)+'.bin')
pl.close()
# ---------------------------------------
# Wetland Low Center Polygons
# ---------------------------------------
if self.WetLCP['Figures'].lower() == 'yes':
# Change to Output Directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/Wet_LCP/Year_Cohorts')
Wet_LCP_plot = np.reshape(self.ATTM_Wet_LCP, [int(self.ATTM_nrows), int(self.ATTM_ncols)])
# --------------------------------------
# Output figures placed into directory
# --------------------------------------
year = str(int(time + self.Year[0]))
# ---------------------------------------
# Create figures and corresponding data
#----------------------------------------
fig = pl.figure()
pl.imshow(Wet_LCP_plot, interpolation = 'nearest', cmap = 'spectral', vmin = 0.0, vmax = 1.0)
pl.title('Wetland Low Center Polygons Fractional Area - '+str(year))
pl.colorbar(extend = 'neither', shrink = 0.92)
pl.savefig('Wet_LCP_Fractional_Area_'+str(year)+'.jpg', format = 'jpg')
Wet_LCP_plot.tofile('Wet_LCP_Fractional_Area_'+str(year)+'.bin')
pl.close()
# ---------------------------------------
# Wetland Coalescent Low Center Polygons
# ---------------------------------------
if self.WetCLC['Figures'].lower() == 'yes' :
# Change to Output Directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/Wet_CLC/Year_Cohorts')
Wet_CLC_plot = np.reshape(self.ATTM_Wet_CLC, [int(self.ATTM_nrows), int(self.ATTM_ncols)])
# --------------------------------------
# Output figures placed into directory
# --------------------------------------
year = str(int(time + self.Year[0]))
# ---------------------------------------
# Create figures and corresponding data
#----------------------------------------
fig = pl.figure()
pl.imshow(Wet_CLC_plot, interpolation = 'nearest', cmap = 'spectral', vmin = 0.0, vmax = 1.0)
pl.title('Wetland Coalescent Low Center Polygons Fractional Area - '+str(year))
pl.colorbar(extend = 'neither', shrink = 0.92)
pl.savefig('Wet_CLC_Fractional_Area_'+str(year)+'.jpg', format = 'jpg')
Wet_CLC_plot.tofile('Wet_CLC_Fractional_Area_'+str(year)+'.bin')
pl.close()
# ---------------------------------------
# Wetland Flat Center Polygons
# ---------------------------------------
if self.WetFCP['Figures'].lower() == 'yes' :
# Change to Output Directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/Wet_FCP/Year_Cohorts')
Wet_FCP_plot = np.reshape(self.ATTM_Wet_FCP, [int(self.ATTM_nrows), int(self.ATTM_ncols)])
# --------------------------------------
# Output figures placed into directory
# --------------------------------------
year = str(int(time + self.Year[0]))
# ---------------------------------------
# Create figures and corresponding data
#----------------------------------------
fig = pl.figure()
pl.imshow(Wet_FCP_plot, interpolation = 'nearest', cmap = 'spectral', vmin = 0.0, vmax = 1.0)
pl.title('Wetland Flat Center Polygons Fractional Area - '+str(year))
pl.colorbar(extend = 'neither', shrink = 0.92)
pl.savefig('Wet_FCP_Fractional_Area_'+str(year)+'.jpg', format = 'jpg')
Wet_FCP_plot.tofile('Wet_FCP_Fractional_Area_'+str(year)+'.bin')
pl.close()
# ---------------------------------------
# Wetland High Center Polygons
# ---------------------------------------
if self.WetHCP['Figures'].lower() == 'yes':
# Change to Output Directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/Wet_HCP/Year_Cohorts')
Wet_HCP_plot = np.reshape(self.ATTM_Wet_HCP, [int(self.ATTM_nrows), int(self.ATTM_ncols)])
# --------------------------------------
# Output figures placed into directory
# --------------------------------------
year = str(int(time + self.Year[0]))
# ---------------------------------------
# Create figures and corresponding data
#----------------------------------------
fig = pl.figure()
pl.imshow(Wet_HCP_plot, interpolation = 'nearest', cmap = 'spectral', vmin = 0.0, vmax = 1.0)
pl.title('Wetland High Center Polygons Fractional Area - '+str(year))
pl.colorbar(extend = 'neither', shrink = 0.92)
pl.savefig('Wet_HCP_Fractional_Area_'+str(year)+'.jpg', format = 'jpg')
Wet_HCP_plot.tofile('Wet_HCP_Fractional_Area_'+str(year)+'.bin')
pl.close()
# ---------------------------------------
# Ponds
# ---------------------------------------
if self.LakePond['Pond_Figures'].lower() == 'yes':
# Change to Output Directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/Ponds/Year_Cohorts')
Ponds_plot = np.reshape(self.ATTM_Ponds, [int(self.ATTM_nrows), int(self.ATTM_ncols)])
# --------------------------------------
# Output figures placed into directory
# --------------------------------------
year = str(int(time + self.Year[0]))
# ---------------------------------------
# Create figures and corresponding data
#----------------------------------------
fig = pl.figure()
pl.imshow(Ponds_plot, interpolation = 'nearest', cmap = 'spectral', vmin = 0.0, vmax = 1.0)
pl.title('Ponds Fractional Area - '+str(year))
pl.colorbar(extend = 'neither', shrink = 0.92)
pl.savefig('Ponds_Fractional_Area_'+str(year)+'.jpg', format = 'jpg')
Ponds_plot.tofile('Ponds_Fractional_Area_'+str(year)+'.bin')
pl.close()
# ---------------------------------------
# Lakes
# ---------------------------------------
if self.LakePond['Lake_Figures'].lower() == 'yes':
# Change to Output Directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/Lakes/Year_Cohorts')
Lakes_plot = np.reshape(self.ATTM_Lakes, [int(self.ATTM_nrows), int(self.ATTM_ncols)])
# --------------------------------------
# Output figures placed into directory
# --------------------------------------
year = str(int(time + self.Year[0]))
# ---------------------------------------
# Create figures and corresponding data
#----------------------------------------
fig = pl.figure()
pl.imshow(Lakes_plot, interpolation = 'nearest', cmap = 'spectral', vmin = 0.0, vmax = 1.0)
pl.title('Lakes Fractional Area - '+str(year))
pl.colorbar(extend = 'neither', shrink = 0.92)
pl.savefig('Lakes_Fractional_Area_'+str(year)+'.jpg', format = 'jpg')
Lakes_plot.tofile('Lakes_Fractional_Area_'+str(year)+'.bin')
pl.close()
################################
# Animation of Fractional Area #
################################
def write_Fractions_avi(self):#, Gra_NPG, Gra_LCP, Gra_FCP, Gra_HCP, Shr_NPG, Shr_LCP,
#Shr_FCP, Shr_HCP, Ponds, Lakes):
# -----------------------------
# Wetland Non-Polygonal Ground
# -----------------------------
if self.WetNPG['Movie'].lower() == 'yes' and self.WetNPG['Figures'].lower() == 'yes':
# Move to output directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/Wet_NPG/Year_Cohorts')
# Write AVI file
subprocess.call('./avi_script_Wet_NPG_Fraction', shell = True)
# Move to Run directory
os.chdir(self.control['Run_dir'])
# ---------------------------
# Wetland Low Center Polygon
# ---------------------------
if self.WetLCP['Movie'].lower() == 'yes' and self.WetLCP['Figures'].lower() == 'yes':
# Move to output directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/Wet_LCP/Year_Cohorts')
# Write AVI file
subprocess.call('./avi_script_Wet_LCP_Fraction', shell = True)
# Move to Run directory
os.chdir(self.control['Run_dir'])
# --------------------------------------
# Wetland Coalescent Low Center Polygon
# --------------------------------------
if self.WetCLC['Movie'].lower() == 'yes' and self.WetCLC['Figures'].lower() == 'yes':
# Move to output directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/Wet_CLC/Year_Cohorts')
# Write AVI file
subprocess.call('./avi_script_Wet_CLC_Fraction', shell = True)
# Move to Run directory
os.chdir(self.control['Run_dir'])
# -----------------------------
# Wetland Flat Center Polygon
# -----------------------------
if self.WetFCP['Figures'].lower() == 'yes' and self.WetFCP['Movie'].lower() == 'yes':
# Move to output directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/Wet_FCP/Year_Cohorts')
# Write AVI file
subprocess.call('./avi_script_Wet_FCP_Fraction', shell = True)
# Move to Run directory
os.chdir(self.control['Run_dir'])
# ----------------------------
# Wetland High Center Polygon
# ----------------------------
if self.WetHCP['Movie'].lower() == 'yes' and self.WetHCP['Figures'].lower() == 'yes':
# Move to output directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/Wet_HCP/Year_Cohorts')
# Write AVI file
subprocess.call('./avi_script_Wet_HCP_Fraction', shell = True)
# Move to Run directory
os.chdir(self.control['Run_dir'])
# -----------------------------
# Ponds
# -----------------------------
if self.LakePond['Pond_Figures'].lower == 'yes' and self.LakePond['Pond_Movie'].lower() == 'yes':
# Move to output directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/Ponds/Year_Cohorts')
# Write AVI file
subprocess.call('./avi_script_Ponds_Fraction', shell = True)
# Move to Run directory
os.chdir(self.control['Run_dir'])
# ----------------------------
# Lakes
# ----------------------------
if self.LakePond['Lake_Figures'].lower() == 'yes' and self.LakePond['Lake_Movie'].lower() == 'yes':
# Move to output directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/Lakes/Year_Cohorts')
# Write AVI file
subprocess.call('./avi_script_Lakes_Fraction', shell = True)
# Move to Run directory
os.chdir(self.control['Run_dir'])
#---------------------------------------------------------------------------------
def dominant_fractional_plot(self, time):
if self.Terrestrial['Figure'].lower() == 'yes':
# Change to Output Directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/All_Cohorts/Year_Cohorts')
dominant_cohort_plot = np.reshape(self.dominant_cohort, [int(self.ATTM_nrows), int(self.ATTM_ncols)])
# --------------------------------------
# Output figures placed into directory
# --------------------------------------
year = str(int(time + self.Year[0]))
# ---------------------------------------
# Create figures and corresponding data
#----------------------------------------
fig = pl.figure()
cax = pl.imshow(dominant_cohort_plot, interpolation = 'nearest', cmap = 'spectral', vmin = 0, vmax = 9)
pl.title('Dominant Cohort - '+str(year))
cbar = pl.colorbar(ticks = [0,1,2,3,4,5,6,7,8,9], orientation = 'vertical')
#cbar.set_ticklabels(['', 'Urban', 'Rivers', 'Wetland NPG', 'Wetland LCP',
# 'Wetland CLC','Wetland FCP', 'Wetland HCP',
# 'Ponds', 'Lakes'])
cbar.set_ticklabels(['', 'Urban', 'River', 'Lake', 'Pond', 'Wetland HCP',
'Wetland FCP', 'Wetland CLC', 'Wetland LCP', 'Meadow'])
pl.savefig('Dominant_Cohort'+str(year)+'.jpg', format = 'jpg')
dominant_cohort_plot.tofile('Dominant_Cohort'+str(year)+'.bin')
pl.close()
# Return to Run Directory
os.chdir(self.control['Run_dir'])
#---------------------------------------------------------------------------------
def dominant_cohort(self):
if self.Terrestrial['Figure'].lower() == 'yes':
self.dominant_cohort = np.zeros([self.ATTM_nrows * self.ATTM_ncols])
## # Urban [0], Rivers [1], Wet_NPG [2], Wet_LCP [3], Wet_CLC [4], Wet_FCP [5], Wet_HCP [6],
## # Ponds [7], Lakes [8]
# Urban [0], Rivers [1], Lakes [2], Ponds [3], Wet_HCP [4], Wet_FCP [5], Wet_CLC [6],
# Wet_LCP [7], Wet_NPG [8]
cohort_compare = np.zeros(9)
for i in range(0, self.ATTM_nrows * self.ATTM_ncols):
if np.sum(self.ATTM_Urban[i] + self.ATTM_Rivers[i] + self.ATTM_Wet_NPG[i] +
self.ATTM_Wet_LCP[i] + self.ATTM_Wet_CLC[i] + self.ATTM_Wet_FCP[i] +
self.ATTM_Wet_HCP[i] + self.ATTM_Lakes[i] + self.ATTM_Ponds[i]) > 0.0 :
cohort_compare[0] = self.ATTM_Urban[i]
cohort_compare[1] = self.ATTM_Rivers[i]
cohort_compare[8] = self.ATTM_Wet_NPG[i]
cohort_compare[7] = self.ATTM_Wet_LCP[i]
cohort_compare[6] = self.ATTM_Wet_CLC[i]
cohort_compare[5] = self.ATTM_Wet_FCP[i]
cohort_compare[4] = self.ATTM_Wet_HCP[i]
cohort_compare[3] = self.ATTM_Ponds[i]
cohort_compare[2] = self.ATTM_Lakes[i]
cohort_max = np.where(cohort_compare == cohort_compare.max())
if cohort_max[0][0] == 0: self.dominant_cohort[i] = 1
if cohort_max[0][0] == 1: self.dominant_cohort[i] = 2
if cohort_max[0][0] == 2: self.dominant_cohort[i] = 3
if cohort_max[0][0] == 3: self.dominant_cohort[i] = 4
if cohort_max[0][0] == 4: self.dominant_cohort[i] = 5
if cohort_max[0][0] == 5: self.dominant_cohort[i] = 6
if cohort_max[0][0] == 6: self.dominant_cohort[i] = 7
if cohort_max[0][0] == 7: self.dominant_cohort[i] = 8
if cohort_max[0][0] == 8: self.dominant_cohort[i] = 9
else:
self.dominant_cohort[i] = 0
#########################################
# Animation of Dominant Fractional Area #
#########################################
def write_Dominant_Cohort_avi(self):
if self.Terrestrial['Movie'].lower() == 'yes' and self.Terrestrial['Figure'].lower() == 'yes':
# Move to output directory
os.chdir(self.control['Run_dir']+self.Output_directory+'/All_Cohorts/Year_Cohorts')
# Write AVI file
subprocess.call('./avi_script_Dominant_Cohort', shell = True)
# Move to Run Directory
os.chdir(self.control['Run_dir'])