source: palm/trunk/SCRIPTS/palm_csd_files/palm_csd_tools.py @ 3746

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#--------------------------------------------------------------------------------#
# This file is part of the PALM model system.
#
# PALM is free software: you can redistribute it and/or modify it under the terms
# of the GNU General Public License as published by the Free Software Foundation,
# either version 3 of the License, or (at your option) any later version.
#
# PALM is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
# A PARTICULAR PURPOSE.  See the GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License along with
# PALM. If not, see <http://www.gnu.org/licenses/>.
#
# Copyright 1997-2018  Leibniz Universitaet Hannover
#--------------------------------------------------------------------------------#
#
# Current revisions:
# -----------------
# 
# 
# Former revisions:
# -----------------
# $Id: palm_csd_tools.py 3726 2019-02-07 18:22:49Z gronemeier $
# Index bound bugfix
# 
# 3668 2019-01-14 12:49:24Z maronga
# Minor changes
# 
# 3567 2018-11-27 13:59:21Z maronga
# Initial revisions
#
#
# Description:
# ------------
# Support routines for palm_csd
#
# @Author Bjoern Maronga (maronga@muk.uni-hannover.de)
#
#------------------------------------------------------------------------------#
import numpy as np
from scipy.interpolate import interp2d

def blend_array_2d(array1,array2,radius):
#  Blend over the parent and child terrain height within a radius of 50 px
   
   gradient_matrix = np.copy(array1)
   gradient_matrix[:,:] = 1.0
   gradient_px     = 50

   for i in range(0,gradient_px):
      gradient_matrix[:,i] = float(i)/float(gradient_px)


   for i in range(len(gradient_matrix[0,:])-gradient_px,len(gradient_matrix[0,:])):
      gradient_matrix[:,i] = float(len(gradient_matrix[0,:])-i)/float(gradient_px)  
     

   for j in range(0,gradient_px):
      for i in range(0,len(gradient_matrix[0,:])):
         if  gradient_matrix[j,i] == 1.0:
            gradient_matrix[j,i] = float(j)/float(gradient_px) 
         else:
            gradient_matrix[j,i] = (gradient_matrix[j,i] + float(j)/float(gradient_px))/2.0


   for j in range(len(gradient_matrix[:,0])-gradient_px,len(gradient_matrix[:,0])):
      for i in range(0,len(gradient_matrix[0,:])):        
         if  gradient_matrix[j,i] == 1.0:
            gradient_matrix[j,i] = (len(gradient_matrix[:,0])-j)/float(gradient_px)
         else:
            gradient_matrix[j,i] = (gradient_matrix[j,i] + (len(gradient_matrix[:,0])-j)/float(gradient_px))/2.0

   array_blended = array1 * gradient_matrix + (1.0 - gradient_matrix ) * array2 
       
   return array_blended


def interpolate_2d(array,x1,y1,x2,y2):
   tmp_int2d = interp2d(x1,y1,array,kind='linear')
   array_ip = tmp_int2d(x2.astype(float), y2.astype(float)) 

   return array_ip 
   
   
def bring_to_palm_grid(array,x,y,dz):
    
#     Bring the parent terrain height to the child grid  
      k_tmp = np.arange(0,max(array.flatten())+dz*2,dz)
      k_tmp[1:] = k_tmp[1:] - dz * 0.5
      for l in range(0,len(x)):
         for m in range(0,len(y)):
            for k in range(1,len(k_tmp+1)):
               if k_tmp[k] > array[m,l]:
                  array[m,l] = k_tmp[k-1]
                  break

      return array  


def make_3d_from_2d(array_2d,x,y,dz):
    
      k_tmp = np.arange(0,max(array_2d.flatten())+dz*2,dz)
 
      k_tmp[1:] = k_tmp[1:] - dz * 0.5
      array_3d = np.ones((len(k_tmp),len(y),len(x)))
      
      for l in range(0,len(x)):
         for m in range(0,len(y)):
            for k in range(0,len(k_tmp)):
               if k_tmp[k] > array_2d[m,l]:
                  array_3d[k,m,l] = 0

      return array_3d.astype(np.byte), k_tmp


def make_3d_from_bridges_2d(array_3d,array_2d,x,y,dz,width,fill):
      
      for l in range(0,len(x)-1):
         for m in range(0,len(y)-1):
            if array_2d[m,l] != fill:
               k_min = max( int(array_2d[m,l] - width)/dz, 0 )
               k_max = int(round(array_2d[m,l]/dz))
               array_3d[k_min:k_max+1,m,l] = 1


      return array_3d.astype(np.byte)


def check_arrays_2(array1,array2,fill1,fill2):

   missing1 = np.where(array1 == fill1,1,0)
   missing2 = np.where(array2 == fill2,1,0)
   result = np.array_equal(missing1,missing2)
    
   return result

def check_consistency_3(array1,array2,array3,fill1,fill2,fill3):

   tmp_array = np.where(array1 != fill1,1,0) + np.where(array2 != fill2,1,0) + np.where(array3 != fill3,-1,0)
   
   test = np.any(tmp_array.flatten() != 0)
   if test:
      print("soil_type array is not consistent!")
      print("max: " + str(max(tmp_array.flatten())) + ", min: " + str(min(tmp_array.flatten())))
   else:
      print("soil_type array is consistent!")     
   return tmp_array, test




def check_consistency_4(array1,array2,array3,array4,fill1,fill2,fill3,fill4):

   tmp_array = np.where(array1 != fill1,1,0) + np.where(array2 != fill2,1,0) + np.where(array3 != fill3,1,0) + np.where(array4 != fill4,1,0)
   
   test = np.any(tmp_array.flatten() != 1)
   if test:
      print("*_type arrays are not consistent!")
      print("max: " + str(max(tmp_array.flatten())) + ", min: " + str(min(tmp_array.flatten())))
   else:
      print("*_type arrays are consistent!")     
   return tmp_array, test