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Copy pathdiff_stats_and_histograms_v4.py
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diff_stats_and_histograms_v4.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 19 18:21:33 2024
@author: ubuntu
"""
import numpy as np
from itertools import chain
import matplotlib.pyplot as plt
from matplotlib.ticker import PercentFormatter
import sys
import seaborn as sns
import pandas as pd
from scipy import stats
file_list=["nodup_0582_9p5_chm.tif",
"nodup_0582_9p5_cover.tif",
"nodup_0582_9p5_density.tif",
"nodup_0582_9p5_density_lt1.tif",
"nodup_0582_9p5_pdsm.tif",
"nodup_0582_9p5_pdtm.tif",
"nodup_100_22_chm.tif",
"nodup_100_22_cover.tif",
"nodup_100_22_density.tif",
"nodup_100_22_density_lt1.tif",
"nodup_100_22_pdsm.tif",
"nodup_100_22_pdtm.tif",
"nodup_512_11_chm.tif",
"nodup_512_11_cover.tif",
"nodup_512_11_density.tif",
"nodup_512_11_density_lt1.tif",
"nodup_512_11_pdsm.tif",
"nodup_512_11_pdtm.tif",
"nodup_669_8_chm.tif",
"nodup_669_8_cover.tif",
"nodup_669_8_density.tif",
"nodup_669_8_density_lt1.tif",
"nodup_669_8_pdsm.tif",
"nodup_669_8_pdtm.tif",
"nodup_800_6_chm.tif",
"nodup_800_6_cover.tif",
"nodup_800_6_density.tif",
"nodup_800_6_density_lt1.tif",
"nodup_800_6_pdsm.tif",
"nodup_800_6_pdtm.tif",
"nodup_985_4_chm.tif",
"nodup_985_4_cover.tif",
"nodup_985_4_density.tif",
"nodup_985_4_density_lt1.tif",
"nodup_985_4_pdsm.tif",
"nodup_985_4_pdtm.tif"]
band_names=['chm',
'cover',
'density',
'density_lt1',
'pdsm',
'pdtm',
'chm',
'cover',
'density',
'density_lt1',
'pdsm',
'pdtm',
'chm',
'cover',
'density',
'density_lt1',
'pdsm',
'pdtm',
'chm',
'cover',
'density',
'density_lt1',
'pdsm',
'pdtm',
'chm',
'cover',
'density',
'density_lt1',
'pdsm',
'pdtm',
'chm',
'cover',
'density',
'density_lt1',
'pdsm',
'pdtm']
title_lut= {"density_lt1":'Density_lt1',
"density":'Density',
"cover":'Cover (%)',
"pdtm":'Terrain Elevation (ft)',
"pdsm":'Maximum Canopy Elevation (ft)',
"chm":'Canopy Height (ft)'}
titles=[]
for t in band_names:
titles.append(title_lut[t])
for ix,b in enumerate(band_names):
#print(file_list[ix],b,titles[ix])
#sys.exit()
# # Create list of images
# file_list=['nodup_100_22_density_lt1','nodup_100_22_density','nodup_100_22_cover',
# 'nodup_100_22_pdtm','nodup_100_22_pdsm','nodup_100_22_chm','nodup_512_11_density_lt1',
# 'nodup_512_11_density','nodup_512_11_cover','nodup_512_11_pdtm','nodup_512_11_pdsm','nodup_512_11_chm',
# 'nodup_669_8_density_lt1','nodup_669_8_density','nodup_669_8_cover','nodup_669_8_pdtm','nodup_669_8_pdsm','nodup_669_8_chm',
# 'nodup_800_6_density_lt1','nodup_800_6_density','nodup_800_6_cover','nodup_800_6_pdtm','nodup_800_6_pdsm','nodup_800_6_chm',
# 'nodup_985_4_density_lt1','nodup_985_4_density','nodup_985_4_cover','nodup_985_4_pdtm','nodup_985_4_pdsm','nodup_985_4_chm',
# 'nodup_0582_9p5_density_lt1','nodup_0582_9p5_density','nodup_0582_9p5_cover','nodup_0582_9p5_pdtm','nodup_0582_9p5_pdsm','nodup_0582_9p5_chm']
# # 'sub_01_chm','sub_01_cover','sub_01_density_lt1','sub_01_density','sub_01_pdsm','sub_01_pdtm']
# title=['Density_lt1','Density','Cover (%)','Terrain Elevation (ft)','Maximum Canopy Elevation (ft)','Canopy Height (ft)',
# 'Density_lt1','Density','Cover (%)','Terrain Elevation (ft)','Maximum Canopy Elevation (ft)','Canopy Height (ft)',
# 'Density_lt1','Density','Cover (%)','Terrain Elevation (ft)','Maximum Canopy Elevation (ft)','Canopy Height (ft)',
# 'Density_lt1','Density','Cover (%)','Terrain Elevation (ft)','Maximum Canopy Elevation (ft)','Canopy Height (ft)',
# 'Density_lt1','Density','Cover (%)','Terrain Elevation (ft)','Maximum Canopy Elevation (ft)','Canopy Height (ft)',
# 'Density_lt1','Density','Cover (%)','Terrain Elevation (ft)','Maximum Canopy Elevation (ft)','Canopy Height (ft)']
# # # 'Density_lt1','Density','Cover (%)','Terrain Elevation (ft)','Terrain Elevation (ft)','Canopy Height (ft)']
for ix,fl in enumerate(file_list):
#print(file_list[ix],titles[ix])
##print(len(file_list))
##print(len(title))
reference_bands=['sub_01_chm','sub_01_cover','sub_01_density_lt1','sub_01_density','sub_01_pdsm','sub_01_pdtm']
import rasterio
from collections.abc import Iterable
def flatten(coll):
for i in coll:
if isinstance(i, Iterable) and not isinstance(i, str):
for subc in flatten(i):
yield subc
else:
yield i
def unpack_dict_var(dict_array,varname):
# #print(type(dict_array),varname)
all=[]
# #print(type(dict_array[0]))
for x in dict_array:
# #print(x)
all.append(x[varname])
# all=[#print(x) for x in dict_array]
# #print("upd_sub",all,np.array(all))
return(all)
def extract_fileinfo(filenames):
out=[]
for ix,f in enumerate(filenames):
fs=f.split("_")
if fs[-1] == "lt1":
fs=[fs[0:len(fs)-2],fs[-2]+"_lt1"]
fs=list(flatten(fs))
if len(fs)==3:
fs=[fs[0],fs[1],str(100),fs[2]]
# #print(fs)
fs=list(flatten(fs))
tmp={"filename":f,f"ilename_id":'_'.join(fs),"shot_density":fs[2],"var":(fs[3].replace(".tif","")),"ix":ix}
out.append(tmp)
return(out)
#############################################################################################################################
def return_struct_list_wcriteria(instruct,variable,desired_shotdens):
# for i in instruct:
# #print(i['shot_density'])
shot_density=np.array(unpack_dict_var(instruct,'shot_density'))
#print("SDSDSD",shot_density)
# #print(variable)
# #print(desired_shotdens)
if desired_shotdens == None:
good_ix=list(range(0,len(shot_density)))
#print("GOOD_IDX1",good_ix)
else:
good_ix=list(np.where(shot_density == desired_shotdens))
#print(shot_density)
#print("GOOD_IDX2",good_ix)
out=[]
# #print(">>>3",good_ix[0])
# #print(">>>2",len(good_ix[0]))
# #print(">>>1",len(instruct))
# #print(good_ix,len(good_ix))
for x in good_ix[0]:
# #print(">>>",x,variable,instruct[x])
out.append(instruct[x][variable])
return(out)
#############################################################################################################################
def match_and_subtract(efinfo,in_image,titles,verbose=False):#efinfo
# #print(efinfo[0].keys())
## comparison_shot_density="8"
# all_shot_density=return_struct_list_wcriteria(efinfo,"shot_density",comparison_shot_density)
# all_filenames=return_struct_list_wcriteria(efinfo,'filename',comparison_shot_density)
# all_vars=return_struct_list_wcriteria(efinfo,'var',comparison_shot_density)
# all_index=list(range(0,len(all_vars)))
# all_index2=return_struct_list_wcriteria(efinfo,'ix',comparison_shot_density)#
all_shot_density=unpack_dict_var(efinfo,'shot_density')
all_filenames=unpack_dict_var(efinfo,'filename')
all_vars=unpack_dict_var(efinfo,'var')
all_index=list(range(0,len(all_vars)))
all_index2=unpack_dict_var(efinfo,'ix')
##print("alix",all_index)
##print(all_index2)
#print("LBA: ",len(all_index),len(all_index),len(all_vars),len(all_filenames),len(all_shot_density))
# #print(all_shot_density == str(22))
# #print(type(all_shot_density == str(22)),type(baseline_filenames))
baseline_target_density="22"
baseline_filenames=return_struct_list_wcriteria(efinfo,'filename',baseline_target_density)
baseline_vars=return_struct_list_wcriteria(efinfo,'var',baseline_target_density)#
baseline_shot_density=return_struct_list_wcriteria(efinfo,'shot_density',baseline_target_density)
baseline_index=list(range(0,len(baseline_vars)))
baseline_index2=return_struct_list_wcriteria(efinfo,'ix',baseline_target_density)
##print("LBA: ",len(baseline_index),len(all_index),len(baseline_vars),len(baseline_filenames),len(baseline_shot_density))
infile_raster = rasterio.open(in_image)
mask=infile_raster.read_masks()
mask=mask[0,:,:].squeeze()
mask[:]=1
# #print(mask.shape)
meta = infile_raster.meta.copy()
out_meta=infile_raster.meta.copy()
#print("LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLsLOM")
#print(meta['count'],in_image)
out_meta.update({"count":out_meta["count"]*2})
#print("LOM",out_meta['count'])
if verbose:
#print("ai",all_index)
#print("bi",baseline_index)
with open("/home/ubuntu/density_comparison_v2/difference_output_xx.tif.csv", 'w') as f:
header="shot_density,variable,all_filenames,all_mean,all_std,all_min,all_max,base_filenames,base_mean,base_std,base_min,base_max,diff_mean,diff_std,diff_min,diff_max"
f.write(header+"\n")
with rasterio.open(in_image.replace(".tif","_wdiff.tif"), 'w', **out_meta) as dest:
#print("all_index",all_index)
for ix in all_index:
# input()
#print("next")
# ix=ix+1match_ixz
if verbose:
#print("==========================================================================")
#print("==========================================================================")
#print("==========================================================================")
#print("IX",ix)
# #print(out_meta)
r=infile_raster.read(ix+1)
dest.write(r, ix+1)
af=efinfo[ix]
# #print("aff",af)
# #print(baseline_var)
# #print("afb",af.shape,baseline.shape)
#match=baseline_vars[af['var'] == baseline_vars]
if verbose:
#print('len',len(baseline_vars),len(baseline_index),len(af))
#print('type',type(baseline_vars),type(baseline_index),type(af))
# #print("-----------------------------------------------------",baseline_index)
# #print(af['var'],np.array(baseline_vars))
# for mix in range(baseline_index):
##print("compare var",af['var'])
##print("bv",baseline_vars,len(baseline_vars),len(baseline_index))
##print("av",all_vars,len(all_vars),len(all_index))
##print()
ew=af
match_ix=[]
match=[]
ewout=[]
for b in range(len(baseline_index)):
##print("CHECK",baseline_vars[b],af['var'],baseline_vars[b]==af['var'])
if (baseline_vars[b]==af['var']):
match_ix.append(b)
match.append(baseline_filenames[b])
#print(baseline_filenames[b])
ew['baseline_match']=str(baseline_filenames[b])
#print(b,af['var'])
ewout.append(ew)
##print("MATCH",match)c
try:
tmp=len(match_ix)
except:
#print("MATCH_ISNT_LISt")
else:
##print(tmp,len(match_ix))
match_ix=match_ix[0]
#print("match_ix",match_ix)
#print('match',match)
if verbose:
#print("111111111111111111111111111111111111111111111111111111111111111111111111111")
#print("TRYTRI",match_ix,baseline_vars[match_ix],af['var'])
#print(len(all_filenames),len(baseline_filenames))
#print("--------------------")
#print("MATCHIX",match_ix)
#print("KATCH",match)
#print(af['var'])
#print("IX_MATCH",ix,match_ix)
#print("22222222222222222222222222222222222222222222222222222222222222222222222222222")
#print("<<<<<",ix,match_ix)
#print(baseline_filenames[match_ix],all_filenames[ix])
#print(">>>>>",ix,match_ix,baseline_vars[match_ix],all_vars[ix])
#print([af['var']])
#print('MATCH:2',match,match_ix,ix,baseline_filenames[match_ix],all_filenames[ix])
#print(baseline_index[match_ix],all_index[ix])
all_index2=list(all_index2)
##print("$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$")
##print(all_index2[ix]+1,all_index2)
##print(len(all_index2))
##print(type(all_index2))
##print(type(ix))
##print("$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$")
##print(baseline_index2[ix]+1,baseline_index2)
##print(len(baseline_index2))
##print(type(baseline_index2))
##print(type(ix))
##print(ix)
# [ix]+1),type(all_index2),type(ix)) ###print(len(all_index2[ix]+1))#,
# #print(">>>>>", all_index2[int(match_ix)+1],
# #print(ix,len(all_index2),match_ix,len(baseline_index2))
# tmp1=infile_raster.read(all_index2[int(ix)]+1).squeeze()
# tmp2=infile_raster.read(baseline_index2[int(match_ix)]+1).squeeze()
with rasterio.open("/home/ubuntu/density_comparison_v2/"+af['filename']) as tmp1_raster:
tmp1=tmp1_raster.read(1).squeeze()
#print(match)
with rasterio.open("/home/ubuntu/density_comparison_v2/"+match[0]) as tmp2_raster:
tmp2=tmp2_raster.read(1).squeeze()
tmp1=np.nan_to_num(tmp1, nan=-9999.0, posinf=-9999, neginf=-9999)
tmp2=np.nan_to_num(tmp2, nan=-9999.0, posinf=-9999, neginf=-9999)
tmp1[tmp1>3e+38]=0
tmp2[tmp2>3e+38]=0
#print(np.mean(tmp1),np.min(tmp1),np.max(tmp1))
#print(np.mean(tmp2),np.min(tmp1),np.max(tmp1))
# tmp2=infile_raster.read(match).squeeze()
#print(tmp1.shape)
#print(tmp2.shape)
tmp1=tmp1[0:1199,0:1199]
tmp2=tmp2[0:1199,0:1199]
tmp1_back=tmp1
tmp2_back=tmp2
#print(np.mean(tmp1_back))
#print(np.mean(tmp2_back))
#print(np.mean(tmp1))
#print(np.mean(tmp2))
# input()
#print(tmp1.shape)
#print(tmp2.shape)
#print(np.min(tmp1))
#print(np.min(tmp2))
#print(tmp1.shape)
#print(tmp2.shape)
out_calc=tmp2-tmp1
if verbose:
#print("33333333333333333333333333333333333333333333333333333333333333333333333333333")
#print("band_stats",np.mean(tmp1),np.mean(tmp2))
# mask=mask*(tmp1>-9999)*(tmp2>-9999)
#print("EFINFO",len(efinfo))
dest.write(out_calc, ix+len(efinfo))
#print(ix,len(file_list),ix+len(file_list))
dest.set_band_description(ix+len(efinfo), 'diff_'+file_list[ix-1])
if (af['var'] !='cover'):
rtmp=r[r >1]
else:
rtmp=r[r>0]
if verbose:
#print("444444444444444444444444444444444444444444444444444444444444444444444444444444")
#print("SHAPE",tmp1.shape)
#print("444444444444444444444444444444444444444444444444444444444444444444444444444444")
#print("444444444444444444444444444444444444444444444444444444444444444444444444444444")
#print("444444444444444444444444444444444444444444444444444444444444444444444444444444")
#print("444444444444444444444444444444444444444444444444444444444444444444444444444444")
#print("444444444444444444444444444444444444444444444444444444444444444444444444444444")
#print(baseline_filenames[match_ix])
#print(all_filenames[ix])
#
# #print(">>>",np.min(is_good),np.max(is_good),sum(is_good))
#print(">>>",np.min(tmp1),np.max(tmp1),sum(tmp1))
#print(">>>",np.min(tmp2),np.max(tmp2)),sum(tmp2)
if (np.min(tmp1) != -9999) or (np.min(tmp1) != -9999):
#print("////////////////////////////////////////////////////////////")
is_good=np.logical_and(tmp1 > -9999,tmp2 > -9999)
tmp1=tmp1[is_good]
tmp2=tmp2[is_good]
out_calc=tmp2-tmp1
rtmp2=out_calc
#print("--------------------------------------------------------------------------------------------------")
#print("--------------------------------------------------------------------------------------------------")
#print(max(tmp1),max(tmp2))
#print("--------------------------------------------------------------------------------------------------")
if(max(tmp1)<1) or (max(tmp1)<1):
#print("THEEND")
#print(max(tmp1_back[is_good]))
#print(max(tmp2_back[is_good]))
# sys.exit()
#print(baseline_filenames[match_ix])
#print(all_filenames[ix])
#print(">>>",np.min(is_good),np.max(is_good),sum(is_good))
#print(">>>",np.min(tmp1),np.max(tmp1),sum(tmp1))
#print(">>>",np.min(tmp2),np.max(tmp2)),sum(tmp2)
if (np.min(tmp1) != -9999) or (np.min(tmp1) != -9999):
#print("////////////////////////////////////////////////////////////")
# #print(is_good[0:399])
# #print(tmp1[0:399])
# #print(meantmp_))
# #print(is_good[0:399])
# #print(tmp1[0:399])
# #print(is_good[(0:399]))
## #print(tmp1[0:399])
# #print(tmp2[0:399])
# #print(len(tmp1),len(tmp2),len(rtmp2))
np.set_#printoptions(linewidth=200)
tmp=all_filenames[ix].split("_")
# #print(tmp)
if len(tmp) == 5:
var_out=tmp[3]+"_"+tmp[4]
dns_out=tmp[2]
if len(tmp)==4:
var_out=tmp[3]
dns_out=tmp[2]
if len(tmp)==3:
var_out=tmp[2]
dns_out="100"
# #print(var_out)
# #print(dns_out)
# #print(len(var_out,len(dns_out),len(all_filenames))
# #print(lvar_out),len(dns_out),len(all_filenames))
output1=[all_filenames[ix],var_out,dns_out,np.mean(tmp2),np.std(tmp2),min(tmp2),max(tmp2),
baseline_filenames[match_ix],np.mean(tmp1),np.std(tmp1),min(tmp1),max(tmp1),
np.mean(rtmp2),np.std(rtmp2),min(rtmp2),max(rtmp2)]
if np.std(tmp1) == 0:
#print("outpu1",output1)
#print(np.mean(tmp2),ix,len(tmp1),len(tmp2))
# #print(tmp1[:399])
# #print(tmp2[:399])
#print(baseline_index[match_ix])
# sys.exit()
output=[]
for o in output1:
output.append(str(o))
# output=','.join(str(v) for v in output)
# #print(str(",").join(output))
f.write(",".join(output)+"\n")
# #print("aff",match,af['filename'])
##print("1 ","Diff ","mean(rtmp2),np.std(rtmp2),min(rtmp2),max(rtmp2))
##print("2 ",baseline_filenames[match_ix],np.mean(tmp1),np.std(tmp1),min(tmp1),max(tmp2))
##print("3 ",all_filenames[ix ],np.mean(tmp2),np.std(tmp2),min(tmp2),max(tmp2))
# ##print ("diff_"+file_list[ix-1],np.mean(rtmp2),min(rtmp2),max(rtmp2),np.std(rtmp2))
p=1
# xrange=()
#print(af['var'])
# if titles[ix-1]== "cover":
# sys.exit
rtmp2=tmp2-tmp1
if af['var']=="cover":
rtmp2=(100*tmp2)-(100*tmp1)
xrange=(np.percentile(rtmp2,p),np.percentile(rtmp2,100-(1*p)))
title_lut= {"density_lt1":'Density_lt1',
"density":'Density',
"cover":'Cover (%)',
"pdtm":'Terrain Elevation (ft)',
"pdsm":'Maximum Canopy Elevation (ft)',
"chm":'Canopy Height (ft)'}
#print(xrange,np.std(rtmp2))
#print("7777777777777777777777777777777777777777777777777777777777777777")
#print("77777777777777777777777777777777777777777777777777777777777",af['shot_density'],baseline_shot_density[[match_ix][0]])
#print("7777777777777777777777777777777777777777777777777777777777777777")
#print(af['shot_density']=="8",baseline_shot_density[[match_ix][0]]=="22")
if (af['shot_density'] == "8") and (baseline_shot_density[[match_ix][0]])=="22":
#print("STATS1",np.mean(rtmp2),np.std(rtmp2),np.min(rtmp2),np.max(rtmp2))
# if (af['var']=="cover"):
# sys.exit()
# rtmp2=(100*tmp2)-(100*tmp1)
#good_ix=list(np.where(np.array(tmp1) != 0 and np.array(tmp2) !=0) != 0)
# good_ix=(np.array(tmp1) != 0 and np.array(tmp2) !=0)
# mmd=stats.mode(rtmp2)
# mmd=mmd[0]
# #print("MMD",mmd)
# (fig,ax)=sns.displot(data=pd.DataFrame(np.round(rtmp2[rtmp2 != mmd]), columns=['Difference']), x="Difference",bins=50,)
# ax.set(rc={'figure.figsize':(4,3)})
# ax.set_xlim(xrange[0],xrange[1])
# ax.set_xticks(range(xrange[0],xrange[1]))
#
#print("stats",np.mean(rtmp2),np.std(rtmp2),np.min(rtmp2),np.max(rtmp2))
plt.hist(rtmp2,bins=40,density=False,range=xrange)#,weights=np.ones(len(rtmp2)) / len(rtmp2))
# plt.title(str(np.mean(rtmp2))+" "+str(np.std(rtmp2))+" "+str(np.min(rtmp2))+" "+str(np.max(rtmp2))+" "+str(xrange)+str(titles[ix-1]),fontsize=10)
title=title_lut[af['var']]
plt.title(title,fontsize=14)
plt.xlabel('Difference',fontsize=10)
plt.ylabel('Number of observations',fontsize=10)
# plt.gca().yaxis.set_major_formatter(PercentFormatter(1))
plt.savefig('/home/ubuntu/density_comparison_v2/diffig_'+af['var']+".png",bbox_inches='tight')
plt.show()
#print("savefig")
#print("XXXXXXXXXXXXXXXXXXXXXXXXXXXXX")
plt.clf()
# sys.exit()
dest.write_mask(mask*255)
return(ewout)
# for ix,af in enumerate(efinfo):
# #print(mask.shape)
# #print(ef[0].keys())
# for e in ef:
# #print(ef[e],"\n")
# #print(ef[0],"\n")
# return(baseline_filenames,baseline_vars,f)
#
##print(ef[0])
#titles=[]
#for t in band_names:
# titles.append(title_lut[t])
filename="multistack_v2.tif"
ef=extract_fileinfo(file_list)
#print(len(ef))
#print(ef[0])
#{'filename': 'nodup_0582_9p5_chm.tif', 'ilename_id': 'nodup_0582_9p5_chm.tif', 'shot_density': '9p5', 'var': 'chm', 'ix': 0}
#print("here")
s=match_and_subtract(ef,"/home/ubuntu/density_comparison_v2/multistack_v2.tif",band_names)
#for t in s:
# #print(t['{}