| 1 | #!/usr/bin/env python3 |
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| 2 | # -*- coding: utf-8 -*- |
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| 3 | #--------------------------------------------------------------------------------# |
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| 4 | # This file is part of the PALM model system. |
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| 5 | # |
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| 6 | # PALM is free software: you can redistribute it and/or modify it under the terms |
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| 7 | # of the GNU General Public License as published by the Free Software Foundation, |
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| 8 | # either version 3 of the License, or (at your option) any later version. |
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| 9 | # |
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| 10 | # PALM is distributed in the hope that it will be useful, but WITHOUT ANY |
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| 11 | # WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR |
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| 12 | # A PARTICULAR PURPOSE. See the GNU General Public License for more details. |
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| 13 | # |
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| 14 | # You should have received a copy of the GNU General Public License along with |
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| 15 | # PALM. If not, see <http://www.gnu.org/licenses/>. |
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| 16 | # |
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| 17 | # Copyright 1997-2018 Leibniz Universitaet Hannover |
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| 18 | #--------------------------------------------------------------------------------# |
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| 19 | # |
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| 20 | # Current revisions: |
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| 21 | # ----------------- |
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| 22 | # |
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| 23 | # |
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| 24 | # Former revisions: |
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| 25 | # ----------------- |
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| 26 | # $Id: palm_csd 3567 2018-11-27 13:59:21Z maronga $ |
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| 27 | # Initial revisions |
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| 28 | # |
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| 29 | # |
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| 30 | # |
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| 31 | # |
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| 32 | # |
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| 33 | # Description: |
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| 34 | # ------------ |
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| 35 | # Processing tool for creating PIDS conform static drivers from rastered NetCDF |
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| 36 | # input |
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| 37 | # |
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| 38 | # @Author Bjoern Maronga (maronga@muk.uni-hannover.de) |
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| 39 | # |
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| 40 | # @todo Remove high vegetation on demand |
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| 41 | # @todo Add vegetation_pars (LAI) |
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| 42 | # @todo Add building_pars (green roofs) |
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| 43 | # @todo Add LAD and BAD arrays (canopy generator) |
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| 44 | # @todo Make input files optional |
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| 45 | # @todo Allow for ASCII input of terrain height and building height |
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| 46 | # @todo Modularize reading config file |
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| 47 | #------------------------------------------------------------------------------# |
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| 48 | |
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| 49 | from palm_csd_files.palm_csd_netcdf_interface import * |
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| 50 | from palm_csd_files.palm_csd_tools import * |
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| 51 | import numpy as np |
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| 52 | |
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| 53 | |
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| 54 | def read_config_file(): |
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| 55 | |
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| 56 | import configparser |
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| 57 | from math import floor |
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| 58 | import numpy as np |
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| 59 | import os |
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| 60 | import subprocess as sub |
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| 61 | import sys |
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| 62 | |
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| 63 | # Check if configuration files exists and quit otherwise |
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| 64 | input_config = ".csd.config" |
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| 65 | for i in range(1,len(sys.argv)): |
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| 66 | input_config = str(sys.argv[i]) |
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| 67 | |
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| 68 | config = configparser.RawConfigParser(allow_no_value=True) |
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| 69 | |
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| 70 | if ( os.path.isfile(input_config) == False ): |
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| 71 | print ("Error. No configuration file " + input_config + " found.") |
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| 72 | raise SystemExit |
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| 73 | else: |
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| 74 | print(os.path.isfile(input_config)) |
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| 75 | |
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| 76 | config.read(input_config) |
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| 77 | |
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| 78 | |
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| 79 | # Definition of settings |
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| 80 | global settings_filename_out |
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| 81 | global settings_lai_season |
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| 82 | global settings_bridge_width |
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| 83 | global ndomains |
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| 84 | |
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| 85 | # Definition of global configuration parameters |
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| 86 | global global_acronym |
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| 87 | global global_angle |
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| 88 | global global_author |
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| 89 | global global_campaign |
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| 90 | global global_comment |
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| 91 | global global_contact |
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| 92 | global global_data_content |
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| 93 | global global_dependencies |
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| 94 | global global_institution |
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| 95 | global global_keywords |
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| 96 | global global_location |
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| 97 | global global_palm_version |
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| 98 | global global_references |
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| 99 | global global_site |
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| 100 | global global_source |
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| 101 | global global_version |
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| 102 | |
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| 103 | |
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| 104 | # Definition of domain parameters |
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| 105 | global domain_names |
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| 106 | global domain_px |
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| 107 | global domain_x0 |
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| 108 | global domain_y0 |
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| 109 | global domain_x1 |
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| 110 | global domain_y1 |
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| 111 | global domain_nx |
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| 112 | global domain_ny |
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| 113 | global domain_dz |
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| 114 | global domain_3d |
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| 115 | global domain_hv |
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| 116 | global domain_cg |
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| 117 | global domain_ip |
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| 118 | global domain_za |
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| 119 | global domain_parent |
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| 120 | |
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| 121 | # Definition of input data parameters |
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| 122 | global input_names |
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| 123 | global input_px |
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| 124 | |
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| 125 | |
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| 126 | global input_file_x |
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| 127 | global input_file_y |
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| 128 | global input_file_x_UTM |
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| 129 | global input_file_y_UTM |
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| 130 | global input_file_lat |
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| 131 | global input_file_lon |
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| 132 | global input_file_zt |
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| 133 | global input_file_buildings_2d |
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| 134 | global input_file_bridges_2d |
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| 135 | global input_file_building_id |
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| 136 | global input_file_bridges_id |
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| 137 | global input_file_building_type |
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| 138 | global input_file_building_type |
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| 139 | global input_file_vegetation_type |
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| 140 | global input_file_vegetation_height |
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| 141 | global input_file_pavement_type |
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| 142 | global input_file_water_type |
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| 143 | global input_file_street_type |
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| 144 | global input_file_street_crossings |
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| 145 | global input_file_soil_type |
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| 146 | |
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| 147 | |
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| 148 | global zt_all |
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| 149 | global zt_min |
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| 150 | |
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| 151 | settings_filename_out = "default" |
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| 152 | settings_lai_season = "summer" |
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| 153 | settings_bridge_width = 3.0 |
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| 154 | ndomains = 0 |
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| 155 | |
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| 156 | global_acronym = "" |
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| 157 | global_angle = "" |
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| 158 | global_author = "" |
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| 159 | global_campaign = "" |
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| 160 | global_comment = "" |
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| 161 | global_contact = "" |
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| 162 | global_data_content = "" |
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| 163 | global_dependencies = "" |
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| 164 | global_institution = "" |
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| 165 | global_keywords = "" |
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| 166 | global_location = "" |
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| 167 | global_palm_version = 6.0 |
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| 168 | global_references = "" |
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| 169 | global_site = "" |
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| 170 | global_source = "" |
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| 171 | global_version = 1 |
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| 172 | |
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| 173 | domain_names = [] |
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| 174 | domain_px = [] |
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| 175 | domain_x0 = [] |
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| 176 | domain_y0 = [] |
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| 177 | domain_x1 = [] |
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| 178 | domain_y1 = [] |
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| 179 | domain_nx = [] |
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| 180 | domain_ny = [] |
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| 181 | domain_dz = [] |
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| 182 | domain_3d = [] |
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| 183 | domain_hv = [] |
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| 184 | domain_cg = [] |
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| 185 | domain_ip = [] |
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| 186 | domain_za = [] |
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| 187 | domain_parent = [] |
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| 188 | |
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| 189 | zt_min = 0.0 |
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| 190 | zt_all = [] |
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| 191 | |
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| 192 | input_names = [] |
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| 193 | input_px = [] |
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| 194 | |
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| 195 | input_file_x = [] |
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| 196 | input_file_y = [] |
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| 197 | input_file_x_UTM = [] |
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| 198 | input_file_y_UTM = [] |
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| 199 | input_file_lat = [] |
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| 200 | input_file_lon = [] |
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| 201 | |
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| 202 | input_file_zt = [] |
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| 203 | input_file_buildings_2d = [] |
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| 204 | input_file_bridges_2d = [] |
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| 205 | input_file_building_id = [] |
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| 206 | input_file_bridges_id = [] |
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| 207 | input_file_building_type = [] |
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| 208 | input_file_vegetation_type = [] |
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| 209 | input_file_vegetation_height = [] |
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| 210 | input_file_pavement_type = [] |
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| 211 | input_file_water_type = [] |
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| 212 | input_file_street_type = [] |
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| 213 | input_file_street_crossings = [] |
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| 214 | input_file_soil_type = [] |
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| 215 | |
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| 216 | |
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| 217 | # Load all user parameters from config file |
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| 218 | for i in range(0,len(config.sections())): |
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| 219 | |
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| 220 | read_tmp = config.sections()[i] |
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| 221 | |
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| 222 | if ( read_tmp == 'global' ): |
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| 223 | global_acronym = config.get(read_tmp, 'acronym') |
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| 224 | global_angle = float(config.get(read_tmp, 'rotation_angle')) |
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| 225 | global_author = config.get(read_tmp, 'author') |
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| 226 | global_campaign = config.get(read_tmp, 'campaign') |
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| 227 | global_comment = config.get(read_tmp, 'comment') |
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| 228 | global_contact = config.get(read_tmp, 'contact_person') |
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| 229 | global_data_content = config.get(read_tmp, 'data_content') |
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| 230 | global_dependencies = config.get(read_tmp, 'dependencies') |
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| 231 | global_institution = config.get(read_tmp, 'institution') |
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| 232 | global_keywords = config.get(read_tmp, 'keywords') |
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| 233 | global_location = config.get(read_tmp, 'location') |
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| 234 | global_palm_version = float(config.get(read_tmp, 'palm_version')) |
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| 235 | global_references = config.get(read_tmp, 'references') |
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| 236 | global_site = config.get(read_tmp, 'site') |
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| 237 | global_source = config.get(read_tmp, 'source') |
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| 238 | global_version = float(config.get(read_tmp, 'version')) |
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| 239 | |
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| 240 | if ( read_tmp == 'settings' ): |
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| 241 | settings_filename_out = config.get(read_tmp, 'filename_out') |
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| 242 | settings_lai_season = config.get(read_tmp, 'lai_season') |
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| 243 | settings_bridge_width = float(config.get(read_tmp, 'bridge_width')) |
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| 244 | |
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| 245 | if ( read_tmp.split("_")[0] == 'domain' ): |
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| 246 | ndomains = ndomains + 1 |
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| 247 | domain_names.append(read_tmp.split("_")[1]) |
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| 248 | domain_px.append(float(config.get(read_tmp, 'pixel_size'))) |
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| 249 | domain_nx.append(int(config.get(read_tmp, 'nx'))) |
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| 250 | domain_ny.append(int(config.get(read_tmp, 'ny'))) |
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| 251 | domain_dz.append(float(config.get(read_tmp, 'dz'))) |
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| 252 | domain_3d.append(config.getboolean(read_tmp, 'buildings_3d')) |
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| 253 | domain_hv.append(config.getboolean(read_tmp, 'allow_high_vegetation')) |
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| 254 | domain_cg.append(config.getboolean(read_tmp, 'generate_vegetation_patches')) |
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| 255 | domain_ip.append(config.getboolean(read_tmp, 'interpolate_terrain')) |
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| 256 | domain_za.append(config.getboolean(read_tmp, 'use_palm_z_axis')) |
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| 257 | if domain_ip[ndomains-1] and not domain_za[ndomains-1]: |
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| 258 | domain_za[ndomains-1] = True |
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| 259 | print("+++ Overwrite user setting for use_palm_z_axis") |
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| 260 | |
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| 261 | domain_parent.append(config.get(read_tmp, 'domain_parent')) |
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| 262 | |
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| 263 | domain_x0.append(int(floor(float(config.get(read_tmp, 'origin_x'))/float(config.get(read_tmp, 'pixel_size'))))) |
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| 264 | domain_y0.append(int(floor(float(config.get(read_tmp, 'origin_y'))/float(config.get(read_tmp, 'pixel_size'))))) |
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| 265 | domain_x1.append(int(floor(float(config.get(read_tmp, 'origin_x'))/float(config.get(read_tmp, 'pixel_size'))) + int(config.get(read_tmp, 'nx')))) |
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| 266 | domain_y1.append(int(floor(float(config.get(read_tmp, 'origin_y'))/float(config.get(read_tmp, 'pixel_size'))) + int(config.get(read_tmp, 'ny')))) |
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| 267 | |
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| 268 | if ( read_tmp.split("_")[0] == 'input' ): |
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| 269 | input_names.append(read_tmp.split("_")[1]) |
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| 270 | input_px.append(float(config.get(read_tmp, 'pixel_size'))) |
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| 271 | input_file_x.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_x')) |
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| 272 | input_file_y.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_y')) |
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| 273 | input_file_lat.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_lat')) |
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| 274 | input_file_lon.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_lon')) |
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| 275 | input_file_x_UTM.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_x_UTM')) |
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| 276 | input_file_y_UTM.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_y_UTM')) |
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| 277 | input_file_zt.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_zt')) |
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| 278 | input_file_buildings_2d.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_buildings_2d')) |
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| 279 | input_file_bridges_2d.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_bridges_2d')) |
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| 280 | input_file_building_id.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_building_id')) |
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| 281 | input_file_bridges_id.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_bridges_id')) |
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| 282 | input_file_building_type.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_building_type')) |
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| 283 | input_file_vegetation_type.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_vegetation_type')) |
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| 284 | input_file_vegetation_height.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_vegetation_height')) |
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| 285 | input_file_pavement_type.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_pavement_type')) |
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| 286 | input_file_water_type.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_water_type')) |
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| 287 | input_file_street_type.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_street_type')) |
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| 288 | input_file_street_crossings.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_street_crossings')) |
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| 289 | #input_file_soil_type.append(config.get(read_tmp, 'path') + "/" + config.get(read_tmp, 'file_soil_type')) |
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| 290 | return 0 |
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| 291 | |
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| 292 | |
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| 293 | ############################################################ |
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| 294 | |
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| 295 | # Start of main program |
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| 296 | datatypes = { |
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| 297 | "x": "f4", |
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| 298 | "y": "f4", |
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| 299 | "z": "f4", |
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| 300 | "lat": "f4", |
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| 301 | "lon": "f4", |
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| 302 | "E_UTM": "f4", |
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| 303 | "N_UTM": "f4", |
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| 304 | "zt": "f4", |
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| 305 | "buildings_2d": "f4", |
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| 306 | "buildings_3d": "b", |
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| 307 | "bridges_2d": "f4", |
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| 308 | "building_id": "i", |
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| 309 | "bridges_id": "i", |
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| 310 | "building_type": "b", |
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| 311 | "nsurface_fraction": "i", |
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| 312 | "vegetation_type": "b", |
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| 313 | "vegetation_height": "f4", |
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| 314 | "pavement_type": "b", |
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| 315 | "water_type": "b", |
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| 316 | "street_type": "b", |
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| 317 | "street_crossings": "b", |
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| 318 | "soil_type": "b", |
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| 319 | "surface_fraction": "f4" |
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| 320 | } |
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| 321 | |
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| 322 | fillvalues = { |
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| 323 | "lat": float(-9999.0), |
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| 324 | "lon": float(-9999.0), |
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| 325 | "E_UTM": float(-9999.0), |
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| 326 | "N_UTM": float(-9999.0), |
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| 327 | "zt": float(-9999.0), |
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| 328 | "buildings_2d": float(-9999.0), |
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| 329 | "buildings_3d": np.byte(-127), |
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| 330 | "bridges_2d": float(-9999.0), |
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| 331 | "building_id": int(-9999), |
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| 332 | "bridges_id": int(-9999), |
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| 333 | "building_type": np.byte(-127), |
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| 334 | "nsurface_fraction": int(-9999), |
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| 335 | "vegetation_type": np.byte(-127), |
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| 336 | "vegetation_height": float(-9999.0), |
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| 337 | "pavement_type": np.byte(-127), |
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| 338 | "water_type": np.byte(-127), |
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| 339 | "street_type": np.byte(-127), |
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| 340 | "street_crossings": np.byte(-127), |
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| 341 | "soil_type": np.byte(-127), |
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| 342 | "surface_fraction": float(-9999.0) |
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| 343 | } |
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| 344 | |
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| 345 | defaultvalues = { |
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| 346 | "lat": float(-9999.0), |
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| 347 | "lon": float(-9999.0), |
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| 348 | "E_UTM": float(-9999.0), |
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| 349 | "N_UTM": float(-9999.0), |
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| 350 | "zt": float(0.0), |
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| 351 | "buildings_2d": float(0.0), |
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| 352 | "buildings_3d": 0, |
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| 353 | "bridges_2d": float(0.0), |
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| 354 | "building_id": int(0), |
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| 355 | "bridges_id": int(0), |
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| 356 | "building_type": 1, |
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| 357 | "nsurface_fraction": int(-9999), |
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| 358 | "vegetation_type": 3, |
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| 359 | "vegetation_height": float(-9999.0), |
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| 360 | "pavement_type": 1, |
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| 361 | "water_type": 1, |
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| 362 | "street_type": 1, |
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| 363 | "street_crossings": 0, |
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| 364 | "soil_type": 1, |
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| 365 | "surface_fraction": float(0.0) |
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| 366 | } |
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| 367 | |
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| 368 | # Read configuration file and set parameters accordingly |
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| 369 | read_config_file() |
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| 370 | |
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| 371 | |
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| 372 | filename = [] |
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| 373 | ii = [] |
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| 374 | ii_parent = [] |
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| 375 | # Define indices and filenames for all domains and create netCDF files |
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| 376 | for i in range(0,ndomains): |
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| 377 | |
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| 378 | # Calculate indices and input files |
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| 379 | ii.append(input_px.index(domain_px[i])) |
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| 380 | filename.append(settings_filename_out + "_" + domain_names[i]) |
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| 381 | if domain_parent[i] is not None: |
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| 382 | ii_parent.append(domain_names.index(domain_parent[i])) |
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| 383 | else: |
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| 384 | ii_parent.append(None) |
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| 385 | |
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| 386 | |
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| 387 | x_UTM = nc_read_from_file_2d(input_file_x[ii[i]], "Band1", domain_x0[i], domain_x0[i], domain_y0[i], domain_y0[i]) |
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| 388 | y_UTM = nc_read_from_file_2d(input_file_y[ii[i]], "Band1", domain_x0[i], domain_x0[i], domain_y0[i], domain_y0[i]) |
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| 389 | lat = nc_read_from_file_2d(input_file_lat[ii[i]], "Band1", domain_x0[i], domain_x0[i], domain_y0[i], domain_y0[i]) |
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| 390 | lon = nc_read_from_file_2d(input_file_lon[ii[i]], "Band1", domain_x0[i], domain_x0[i], domain_y0[i], domain_y0[i]) |
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| 391 | |
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| 392 | # Create NetCDF output file and set global attributes |
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| 393 | nc_create_file(filename[i]) |
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| 394 | nc_write_global_attributes(filename[i],float(x_UTM[0,0]),float(y_UTM[0,0]),float(lat[0,0]),float(lon[0,0]),"",global_acronym,global_angle,global_author,global_campaign,global_comment,global_contact,global_data_content,global_dependencies,global_institution,global_keywords,global_location,global_palm_version,global_references,global_site,global_source,global_version) |
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| 395 | |
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| 396 | |
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| 397 | # Process terrain height |
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| 398 | for i in range(0,ndomains): |
|---|
| 399 | |
|---|
| 400 | # Read and write terrain height (zt) |
|---|
| 401 | zt = nc_read_from_file_2d(input_file_zt[ii[i]], 'Band1', domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 402 | |
|---|
| 403 | # Final step: add zt array to the global array |
|---|
| 404 | zt_all.append(zt) |
|---|
| 405 | del zt |
|---|
| 406 | |
|---|
| 407 | # Calculate the global (all domains) minimum of the terrain height. This value will be substracted for all |
|---|
| 408 | # data sets |
|---|
| 409 | zt_min = min(zt_all[0].flatten()) |
|---|
| 410 | for i in range(0,ndomains): |
|---|
| 411 | zt_min = min(zt_min,min(zt_all[i].flatten())) |
|---|
| 412 | |
|---|
| 413 | del zt_all[:] |
|---|
| 414 | |
|---|
| 415 | for i in range(0,ndomains): |
|---|
| 416 | |
|---|
| 417 | # Read and write terrain height (zt) |
|---|
| 418 | zt = nc_read_from_file_2d(input_file_zt[ii[i]], 'Band1', domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 419 | x = nc_read_from_file_1d(input_file_x[ii[i]], "x", domain_x0[i], domain_x1[i]) |
|---|
| 420 | y = nc_read_from_file_1d(input_file_y[ii[i]], "y", domain_y0[i], domain_y1[i]) |
|---|
| 421 | |
|---|
| 422 | print( "Shift terrain height by -" + str(zt_min)) |
|---|
| 423 | zt = zt - zt_min |
|---|
| 424 | |
|---|
| 425 | # If necessary, interpolate parent domain terrain height on child domain grid and blend the two |
|---|
| 426 | if domain_ip[i]: |
|---|
| 427 | tmp_x0 = int( domain_x0[i] * domain_px[i] / domain_px[ii_parent[i]] ) - 1 |
|---|
| 428 | tmp_y0 = int( domain_y0[i] * domain_px[i] / domain_px[ii_parent[i]] ) - 1 |
|---|
| 429 | tmp_x1 = int( domain_x1[i] * domain_px[i] / domain_px[ii_parent[i]] ) + 1 |
|---|
| 430 | tmp_y1 = int( domain_y1[i] * domain_px[i] / domain_px[ii_parent[i]] ) + 1 |
|---|
| 431 | |
|---|
| 432 | tmp_x = nc_read_from_file_1d(input_file_x[ii_parent[i]], "x", tmp_x0, tmp_x1) |
|---|
| 433 | tmp_y = nc_read_from_file_1d(input_file_y[ii_parent[i]], "y", tmp_y0, tmp_y1) |
|---|
| 434 | |
|---|
| 435 | zt_parent = nc_read_from_file_2d(input_file_zt[ii_parent[i]], 'Band1', tmp_x0, tmp_x1, tmp_y0, tmp_y1) |
|---|
| 436 | |
|---|
| 437 | print( "Shift terrain height by -" + str(zt_min)) |
|---|
| 438 | zt_parent = zt_parent - zt_min |
|---|
| 439 | |
|---|
| 440 | # Interpolate array and bring to PALM grid of child domain |
|---|
| 441 | zt_ip = interpolate_2d(zt_parent,tmp_x,tmp_y,x,y) |
|---|
| 442 | zt_ip = bring_to_palm_grid(zt_ip,x,y,domain_dz[ii_parent[i]]) |
|---|
| 443 | |
|---|
| 444 | # Shift the child terrain height according to the parent mean terrain height |
|---|
| 445 | zt = zt - np.mean(zt) + np.mean(zt_ip) |
|---|
| 446 | |
|---|
| 447 | |
|---|
| 448 | # Blend over the parent and child terrain height within a radius of 50 px |
|---|
| 449 | zt = blend_array_2d(zt,zt_ip,50) |
|---|
| 450 | |
|---|
| 451 | # Final step: add zt array to the global array |
|---|
| 452 | zt_all.append(zt) |
|---|
| 453 | del zt |
|---|
| 454 | |
|---|
| 455 | |
|---|
| 456 | # Read and shift x and y coordinates, shift terrain height according to its minimum value and write all data |
|---|
| 457 | # to file |
|---|
| 458 | for i in range(0,ndomains): |
|---|
| 459 | # Read horizontal grid variables from zt file and write them to output file |
|---|
| 460 | x = nc_read_from_file_1d(input_file_x[ii[i]], "x", domain_x0[i], domain_x1[i]) |
|---|
| 461 | y = nc_read_from_file_1d(input_file_y[ii[i]], "y", domain_y0[i], domain_y1[i]) |
|---|
| 462 | x = x - min(x.flatten()) + domain_px[i]/2.0 |
|---|
| 463 | y = y - min(y.flatten()) + domain_px[i]/2.0 |
|---|
| 464 | nc_write_dimension(filename[i], 'x', x, datatypes["x"]) |
|---|
| 465 | nc_write_dimension(filename[i], 'y', y, datatypes["y"]) |
|---|
| 466 | nc_write_attribute(filename[i], 'x', 'long_name', 'x') |
|---|
| 467 | nc_write_attribute(filename[i], 'x', 'standard_name','projection_x_coordinate') |
|---|
| 468 | nc_write_attribute(filename[i], 'x', 'units', 'm') |
|---|
| 469 | nc_write_attribute(filename[i], 'y', 'long_name', 'x') |
|---|
| 470 | nc_write_attribute(filename[i], 'y', 'standard_name', 'projection_y_coordinate') |
|---|
| 471 | nc_write_attribute(filename[i], 'y', 'units', 'm') |
|---|
| 472 | |
|---|
| 473 | lat = nc_read_from_file_2d(input_file_lat[ii[i]], "Band1", domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 474 | lon = nc_read_from_file_2d(input_file_lon[ii[i]], "Band1", domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 475 | |
|---|
| 476 | nc_write_to_file_2d(filename[i], 'lat', lat, datatypes["lat"],'y','x',fillvalues["lat"]) |
|---|
| 477 | nc_write_to_file_2d(filename[i], 'lon', lon, datatypes["lon"],'y','x',fillvalues["lon"]) |
|---|
| 478 | |
|---|
| 479 | nc_write_attribute(filename[i], 'lat', 'long_name', 'latitude') |
|---|
| 480 | nc_write_attribute(filename[i], 'lat', 'standard_name','latitude') |
|---|
| 481 | nc_write_attribute(filename[i], 'lat', 'units', 'degrees_north') |
|---|
| 482 | |
|---|
| 483 | nc_write_attribute(filename[i], 'lon', 'long_name', 'longitude') |
|---|
| 484 | nc_write_attribute(filename[i], 'lon', 'standard_name','longitude') |
|---|
| 485 | nc_write_attribute(filename[i], 'lon', 'units', 'degrees_east') |
|---|
| 486 | |
|---|
| 487 | x_UTM = nc_read_from_file_2d(input_file_x_UTM[ii[i]], "Band1", domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 488 | y_UTM = nc_read_from_file_2d(input_file_y_UTM[ii[i]], "Band1", domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 489 | |
|---|
| 490 | nc_write_to_file_2d(filename[i], 'E_UTM', x_UTM, datatypes["E_UTM"],'y','x',fillvalues["E_UTM"]) |
|---|
| 491 | nc_write_to_file_2d(filename[i], 'N_UTM', y_UTM, datatypes["N_UTM"],'y','x',fillvalues["N_UTM"]) |
|---|
| 492 | |
|---|
| 493 | nc_write_attribute(filename[i], 'E_UTM', 'long_name', 'easting') |
|---|
| 494 | nc_write_attribute(filename[i], 'E_UTM', 'standard_name','projection_x_coorindate') |
|---|
| 495 | nc_write_attribute(filename[i], 'E_UTM', 'units', 'm') |
|---|
| 496 | |
|---|
| 497 | nc_write_attribute(filename[i], 'N_UTM', 'long_name', 'northing') |
|---|
| 498 | nc_write_attribute(filename[i], 'N_UTM', 'standard_name','projection_y_coorindate') |
|---|
| 499 | nc_write_attribute(filename[i], 'N_UTM', 'units', 'm') |
|---|
| 500 | |
|---|
| 501 | nc_write_crs(filename[i]) |
|---|
| 502 | |
|---|
| 503 | |
|---|
| 504 | |
|---|
| 505 | # If necessary, bring terrain height to PALM's vertical grid. This is either forced by the user or implicitly |
|---|
| 506 | # by using interpolation for a child domain |
|---|
| 507 | if domain_za[i]: |
|---|
| 508 | zt_all[i] = bring_to_palm_grid(zt_all[i],x,y,domain_dz[i]) |
|---|
| 509 | |
|---|
| 510 | nc_write_to_file_2d(filename[i], 'zt', zt_all[i], datatypes["zt"],'y','x',fillvalues["zt"]) |
|---|
| 511 | nc_write_attribute(filename[i], 'zt', 'long_name', 'orography') |
|---|
| 512 | nc_write_attribute(filename[i], 'zt', 'units', 'm') |
|---|
| 513 | nc_write_attribute(filename[i], 'zt', 'res_orig', domain_px[i]) |
|---|
| 514 | nc_write_attribute(filename[i], 'zt', 'coordinates', 'E_UTM N_UTM lon lat') |
|---|
| 515 | nc_write_attribute(filename[i], 'zt', 'grid_mapping', 'E_UTM N_UTM lon lat') |
|---|
| 516 | |
|---|
| 517 | del zt_all |
|---|
| 518 | |
|---|
| 519 | |
|---|
| 520 | # Process building height, id, and type |
|---|
| 521 | for i in range(0,ndomains): |
|---|
| 522 | buildings_2d = nc_read_from_file_2d(input_file_buildings_2d[ii[i]], 'Band1', domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 523 | |
|---|
| 524 | building_id = nc_read_from_file_2d(input_file_building_id[ii[i]], 'Band1', domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 525 | |
|---|
| 526 | building_type = nc_read_from_file_2d(input_file_building_type[ii[i]], 'Band1', domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 527 | building_type[building_type == 255] = fillvalues["building_type"] |
|---|
| 528 | building_type = np.where(building_type < 1,defaultvalues["building_type"],building_type) |
|---|
| 529 | |
|---|
| 530 | check = check_arrays_2(buildings_2d,building_id,fillvalues["buildings_2d"],fillvalues["building_id"]) |
|---|
| 531 | if not check: |
|---|
| 532 | buildings_2d = np.where(building_id != fillvalues["building_id"],buildings_2d,fillvalues["buildings_2d"]) |
|---|
| 533 | building_id = np.where(buildings_2d == fillvalues["buildings_2d"],fillvalues["building_id"],building_id) |
|---|
| 534 | print("Data check #1 " + str(check_arrays_2(buildings_2d,building_id,fillvalues["buildings_2d"],fillvalues["building_id"]))) |
|---|
| 535 | |
|---|
| 536 | check = check_arrays_2(buildings_2d,building_type,fillvalues["buildings_2d"],fillvalues["building_type"]) |
|---|
| 537 | if not check: |
|---|
| 538 | building_type = np.where(buildings_2d == fillvalues["buildings_2d"],fillvalues["building_type"],building_type) |
|---|
| 539 | building_type = np.where((building_type == fillvalues["building_type"]) & (buildings_2d != fillvalues["buildings_2d"]),defaultvalues["building_type"],building_type) |
|---|
| 540 | print("Data check #2 " + str(check_arrays_2(buildings_2d,building_type,fillvalues["buildings_2d"],fillvalues["building_type"]))) |
|---|
| 541 | |
|---|
| 542 | nc_write_to_file_2d(filename[i], 'buildings_2d', buildings_2d, datatypes["buildings_2d"],'y','x',fillvalues["buildings_2d"]) |
|---|
| 543 | nc_write_attribute(filename[i], 'buildings_2d', 'long_name', 'buildings') |
|---|
| 544 | nc_write_attribute(filename[i], 'buildings_2d', 'units', 'm') |
|---|
| 545 | nc_write_attribute(filename[i], 'buildings_2d', 'res_orig', domain_px[i]) |
|---|
| 546 | nc_write_attribute(filename[i], 'buildings_2d', 'lod', 1) |
|---|
| 547 | nc_write_attribute(filename[i], 'buildings_2d', 'coordinates', 'E_UTM N_UTM lon lat') |
|---|
| 548 | nc_write_attribute(filename[i], 'buildings_2d', 'grid_mapping', 'E_UTM N_UTM lon lat') |
|---|
| 549 | |
|---|
| 550 | nc_write_to_file_2d(filename[i], 'building_id', building_id, datatypes["building_id"],'y','x',fillvalues["building_id"]) |
|---|
| 551 | nc_write_attribute(filename[i], 'building_id', 'long_name', 'building id') |
|---|
| 552 | nc_write_attribute(filename[i], 'building_id', 'units', '') |
|---|
| 553 | nc_write_attribute(filename[i], 'building_id', 'res_orig', domain_px[i]) |
|---|
| 554 | nc_write_attribute(filename[i], 'building_id', 'coordinates', 'E_UTM N_UTM lon lat') |
|---|
| 555 | nc_write_attribute(filename[i], 'building_id', 'grid_mapping', 'E_UTM N_UTM lon lat') |
|---|
| 556 | |
|---|
| 557 | nc_write_to_file_2d(filename[i], 'building_type', building_type, datatypes["building_type"],'y','x',fillvalues["building_type"]) |
|---|
| 558 | nc_write_attribute(filename[i], 'building_type', 'long_name', 'building type') |
|---|
| 559 | nc_write_attribute(filename[i], 'building_type', 'units', '') |
|---|
| 560 | nc_write_attribute(filename[i], 'building_type', 'res_orig', domain_px[i]) |
|---|
| 561 | nc_write_attribute(filename[i], 'building_type', 'coordinates', 'E_UTM N_UTM lon lat') |
|---|
| 562 | nc_write_attribute(filename[i], 'building_type', 'grid_mapping', 'E_UTM N_UTM lon lat') |
|---|
| 563 | |
|---|
| 564 | del buildings_2d |
|---|
| 565 | del building_id |
|---|
| 566 | del building_type |
|---|
| 567 | |
|---|
| 568 | # Create 3d buildings if necessary. In that course, read bridge objects and add them to building layer |
|---|
| 569 | for i in range(0,ndomains): |
|---|
| 570 | |
|---|
| 571 | if domain_3d[i]: |
|---|
| 572 | x = nc_read_from_file_2d_all(filename[i], 'x') |
|---|
| 573 | y = nc_read_from_file_2d_all(filename[i], 'y') |
|---|
| 574 | buildings_2d = nc_read_from_file_2d_all(filename[i], 'buildings_2d') |
|---|
| 575 | building_id = nc_read_from_file_2d_all(filename[i], 'building_id') |
|---|
| 576 | |
|---|
| 577 | bridges_2d = nc_read_from_file_2d(input_file_bridges_2d[ii[i]], 'Band1', domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 578 | bridges_id = nc_read_from_file_2d(input_file_bridges_id[ii[i]], 'Band1', domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 579 | |
|---|
| 580 | bridges_2d = np.where(bridges_2d == 0.0,fillvalues["bridges_2d"],bridges_2d) |
|---|
| 581 | building_id = np.where(bridges_2d == fillvalues["bridges_2d"],building_id,bridges_id) |
|---|
| 582 | |
|---|
| 583 | |
|---|
| 584 | if np.any(buildings_2d != fillvalues["buildings_2d"]): |
|---|
| 585 | buildings_3d, z = make_3d_from_2d(buildings_2d,x,y,domain_dz[i]) |
|---|
| 586 | if np.any(bridges_2d != fillvalues["bridges_2d"]): |
|---|
| 587 | buildings_3d = make_3d_from_bridges_2d(buildings_3d,bridges_2d,x,y,domain_dz[i],settings_bridge_width,fillvalues["bridges_2d"]) |
|---|
| 588 | else: |
|---|
| 589 | print("Skipping creation of 3D bridges (no bridges in domain)") |
|---|
| 590 | |
|---|
| 591 | |
|---|
| 592 | nc_write_dimension(filename[i], 'z', z, datatypes["z"]) |
|---|
| 593 | nc_write_attribute(filename[i], 'z', 'long_name', 'z') |
|---|
| 594 | nc_write_attribute(filename[i], 'z', 'units', 'm') |
|---|
| 595 | |
|---|
| 596 | nc_write_to_file_3d(filename[i], 'buildings_3d', buildings_3d, datatypes["buildings_3d"],'z','y','x',fillvalues["buildings_3d"]) |
|---|
| 597 | nc_write_attribute(filename[i], 'buildings_3d', 'long_name', 'buildings 3d') |
|---|
| 598 | nc_write_attribute(filename[i], 'buildings_3d', 'units', '') |
|---|
| 599 | nc_write_attribute(filename[i], 'buildings_3d', 'res_orig', domain_px[i]) |
|---|
| 600 | nc_write_attribute(filename[i], 'buildings_3d', 'lod', 2) |
|---|
| 601 | |
|---|
| 602 | del buildings_3d |
|---|
| 603 | |
|---|
| 604 | else: |
|---|
| 605 | print("Skipping creation of 3D buildings (no buildings in domain)") |
|---|
| 606 | |
|---|
| 607 | |
|---|
| 608 | del bridges_2d, bridges_id, building_id |
|---|
| 609 | |
|---|
| 610 | |
|---|
| 611 | |
|---|
| 612 | # Read vegetation type, water_type, pavement_type, soil_type and make fields consistent |
|---|
| 613 | for i in range(0,ndomains): |
|---|
| 614 | |
|---|
| 615 | building_type = nc_read_from_file_2d_all(filename[i], 'building_type') |
|---|
| 616 | |
|---|
| 617 | vegetation_type = nc_read_from_file_2d(input_file_vegetation_type[ii[i]], 'Band1', domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 618 | vegetation_type[vegetation_type == 255] = fillvalues["vegetation_type"] |
|---|
| 619 | vegetation_type = np.where((vegetation_type < 1) & (vegetation_type != fillvalues["vegetation_type"]),defaultvalues["vegetation_type"],vegetation_type) |
|---|
| 620 | |
|---|
| 621 | pavement_type = nc_read_from_file_2d(input_file_pavement_type[ii[i]], 'Band1', domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 622 | pavement_type[pavement_type == 255] = fillvalues["pavement_type"] |
|---|
| 623 | pavement_type = np.where((pavement_type < 1) & (pavement_type != fillvalues["pavement_type"]),defaultvalues["pavement_type"],pavement_type) |
|---|
| 624 | |
|---|
| 625 | water_type = nc_read_from_file_2d(input_file_water_type[ii[i]], 'Band1', domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 626 | water_type[water_type == 255] = fillvalues["water_type"] |
|---|
| 627 | water_type = np.where((water_type < 1) & (water_type != fillvalues["water_type"]),defaultvalues["water_type"],water_type) |
|---|
| 628 | |
|---|
| 629 | # to do: replace by real soil input data |
|---|
| 630 | soil_type = nc_read_from_file_2d(input_file_vegetation_type[ii[i]], 'Band1', domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 631 | soil_type[soil_type == 255] = fillvalues["soil_type"] |
|---|
| 632 | soil_type = np.where((soil_type < 1) & (soil_type != fillvalues["soil_type"]),defaultvalues["soil_type"],soil_type) |
|---|
| 633 | |
|---|
| 634 | # Make arrays consistent |
|---|
| 635 | # #1 Set vegetation type to missing for pixel where a pavement type is set |
|---|
| 636 | vegetation_type = np.where((vegetation_type != fillvalues["vegetation_type"]) & (pavement_type != fillvalues["pavement_type"]),fillvalues["vegetation_type"],vegetation_type) |
|---|
| 637 | |
|---|
| 638 | # #2 Set vegetation type to missing for pixel where a building type is set |
|---|
| 639 | vegetation_type = np.where((vegetation_type != fillvalues["vegetation_type"]) & (building_type != fillvalues["building_type"]) ,fillvalues["vegetation_type"],vegetation_type) |
|---|
| 640 | |
|---|
| 641 | # #3 Set vegetation type to missing for pixel where a building type is set |
|---|
| 642 | vegetation_type = np.where((vegetation_type != fillvalues["vegetation_type"]) & (water_type != fillvalues["water_type"]),fillvalues["vegetation_type"],vegetation_type) |
|---|
| 643 | |
|---|
| 644 | # #4 Remove pavement for pixels with buildings |
|---|
| 645 | pavement_type = np.where((pavement_type != fillvalues["pavement_type"]) & (building_type != fillvalues["building_type"]),fillvalues["pavement_type"],pavement_type) |
|---|
| 646 | |
|---|
| 647 | # #5 Remove pavement for pixels with water |
|---|
| 648 | pavement_type = np.where((pavement_type != fillvalues["pavement_type"]) & (water_type != fillvalues["water_type"]),fillvalues["pavement_type"],pavement_type) |
|---|
| 649 | |
|---|
| 650 | # #6 Remove water for pixels with buildings |
|---|
| 651 | water_type = np.where((water_type != fillvalues["water_type"]) & (building_type != fillvalues["building_type"]),fillvalues["water_type"],water_type) |
|---|
| 652 | |
|---|
| 653 | |
|---|
| 654 | # #7 to be removed: set default soil type everywhere |
|---|
| 655 | soil_type = np.where((vegetation_type != fillvalues["vegetation_type"]) | (pavement_type != fillvalues["pavement_type"]),defaultvalues["soil_type"],fillvalues["soil_type"]) |
|---|
| 656 | |
|---|
| 657 | |
|---|
| 658 | # Check for consistency and fill empty fields with default vegetation type |
|---|
| 659 | consistency_array, test = check_consistency_4(vegetation_type,building_type,pavement_type,water_type,fillvalues["vegetation_type"],fillvalues["building_type"],fillvalues["pavement_type"],fillvalues["water_type"]) |
|---|
| 660 | |
|---|
| 661 | if test: |
|---|
| 662 | vegetation_type = np.where(consistency_array == 0,defaultvalues["vegetation_type"],vegetation_type) |
|---|
| 663 | consistency_array, test = check_consistency_4(vegetation_type,building_type,pavement_type,water_type,fillvalues["vegetation_type"],fillvalues["building_type"],fillvalues["pavement_type"],fillvalues["water_type"]) |
|---|
| 664 | |
|---|
| 665 | # Create surface_fraction array |
|---|
| 666 | x = nc_read_from_file_2d_all(filename[i], 'x') |
|---|
| 667 | y = nc_read_from_file_2d_all(filename[i], 'y') |
|---|
| 668 | nsurface_fraction = np.arange(0,3) |
|---|
| 669 | surface_fraction = np.ones((len(nsurface_fraction),len(y),len(x))) |
|---|
| 670 | |
|---|
| 671 | surface_fraction[0,:,:] = np.where(vegetation_type != fillvalues["vegetation_type"], 1.0, 0.0) |
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| 672 | surface_fraction[1,:,:] = np.where(pavement_type != fillvalues["pavement_type"], 1.0, 0.0) |
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| 673 | surface_fraction[2,:,:] = np.where(water_type != fillvalues["water_type"], 1.0, 0.0) |
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| 674 | |
|---|
| 675 | nc_write_dimension(filename[i], 'nsurface_fraction', nsurface_fraction, datatypes["nsurface_fraction"]) |
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| 676 | nc_write_to_file_3d(filename[i], 'surface_fraction', surface_fraction, datatypes["surface_fraction"],'nsurface_fraction','y','x',fillvalues["surface_fraction"]) |
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| 677 | nc_write_attribute(filename[i], 'surface_fraction', 'long_name', 'surface fraction') |
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| 678 | nc_write_attribute(filename[i], 'surface_fraction', 'units', '') |
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| 679 | nc_write_attribute(filename[i], 'surface_fraction', 'res_orig', domain_px[i]) |
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| 680 | del surface_fraction |
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| 681 | |
|---|
| 682 | |
|---|
| 683 | # Correct vegetation_type when a vegetation height is available and is indicative of low vegeetation |
|---|
| 684 | vegetation_height = nc_read_from_file_2d(input_file_vegetation_height[ii[i]], 'Band1', domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
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| 685 | |
|---|
| 686 | vegetation_type = np.where((vegetation_height != fillvalues["vegetation_height"]) & (vegetation_height == 0.0) & ((vegetation_type == 4) | (vegetation_type == 7) | (vegetation_type == 17)), 3, vegetation_type) |
|---|
| 687 | vegetation_height = np.where((vegetation_height != fillvalues["vegetation_height"]) & (vegetation_height == 0.0) & ((vegetation_type == 4) | (vegetation_type == 7) | (vegetation_type == 17)), fillvalues["vegetation_height"],vegetation_height) |
|---|
| 688 | |
|---|
| 689 | |
|---|
| 690 | nc_write_to_file_2d(filename[i], 'vegetation_type', vegetation_type, datatypes["vegetation_type"],'y','x',fillvalues["vegetation_type"]) |
|---|
| 691 | nc_write_attribute(filename[i], 'vegetation_type', 'long_name', 'vegetation type') |
|---|
| 692 | nc_write_attribute(filename[i], 'vegetation_type', 'units', '') |
|---|
| 693 | nc_write_attribute(filename[i], 'vegetation_type', 'res_orig', domain_px[i]) |
|---|
| 694 | nc_write_attribute(filename[i], 'vegetation_type', 'coordinates', 'E_UTM N_UTM lon lat') |
|---|
| 695 | nc_write_attribute(filename[i], 'vegetation_type', 'grid_mapping', 'E_UTM N_UTM lon lat') |
|---|
| 696 | del vegetation_type |
|---|
| 697 | |
|---|
| 698 | nc_write_to_file_2d(filename[i], 'pavement_type', pavement_type, datatypes["pavement_type"],'y','x',fillvalues["pavement_type"]) |
|---|
| 699 | nc_write_attribute(filename[i], 'pavement_type', 'long_name', 'pavement type') |
|---|
| 700 | nc_write_attribute(filename[i], 'pavement_type', 'units', '') |
|---|
| 701 | nc_write_attribute(filename[i], 'pavement_type', 'res_orig', domain_px[i]) |
|---|
| 702 | nc_write_attribute(filename[i], 'pavement_type', 'coordinates', 'E_UTM N_UTM lon lat') |
|---|
| 703 | nc_write_attribute(filename[i], 'pavement_type', 'grid_mapping', 'E_UTM N_UTM lon lat') |
|---|
| 704 | del pavement_type |
|---|
| 705 | |
|---|
| 706 | nc_write_to_file_2d(filename[i], 'water_type', water_type, datatypes["water_type"],'y','x',fillvalues["water_type"]) |
|---|
| 707 | nc_write_attribute(filename[i], 'water_type', 'long_name', 'water type') |
|---|
| 708 | nc_write_attribute(filename[i], 'water_type', 'units', '') |
|---|
| 709 | nc_write_attribute(filename[i], 'water_type', 'res_orig', domain_px[i]) |
|---|
| 710 | nc_write_attribute(filename[i], 'water_type', 'coordinates', 'E_UTM N_UTM lon lat') |
|---|
| 711 | nc_write_attribute(filename[i], 'water_type', 'grid_mapping', 'E_UTM N_UTM lon lat') |
|---|
| 712 | del water_type |
|---|
| 713 | |
|---|
| 714 | nc_write_to_file_2d(filename[i], 'soil_type', soil_type, datatypes["soil_type"],'y','x',fillvalues["soil_type"]) |
|---|
| 715 | nc_write_attribute(filename[i], 'soil_type', 'long_name', 'soil type') |
|---|
| 716 | nc_write_attribute(filename[i], 'soil_type', 'units', '') |
|---|
| 717 | nc_write_attribute(filename[i], 'soil_type', 'res_orig', domain_px[i]) |
|---|
| 718 | nc_write_attribute(filename[i], 'soil_type', 'coordinates', 'E_UTM N_UTM lon lat') |
|---|
| 719 | nc_write_attribute(filename[i], 'soil_type', 'grid_mapping', 'E_UTM N_UTM lon lat') |
|---|
| 720 | del soil_type |
|---|
| 721 | |
|---|
| 722 | |
|---|
| 723 | |
|---|
| 724 | |
|---|
| 725 | |
|---|
| 726 | # pixels with bridges get building_type = 7 = bridge. This does not change the _type setting for the under-bridge |
|---|
| 727 | # area |
|---|
| 728 | if domain_3d[i]: |
|---|
| 729 | if np.any(building_type != fillvalues["building_type"]): |
|---|
| 730 | |
|---|
| 731 | bridges_2d = nc_read_from_file_2d(input_file_bridges_2d[ii[i]], 'Band1', domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 732 | bridges_2d = np.where(bridges_2d == 0.0,fillvalues["bridges_2d"],bridges_2d) |
|---|
| 733 | building_type = np.where(bridges_2d != fillvalues["bridges_2d"],7,building_type) |
|---|
| 734 | nc_overwrite_to_file_2d(filename[i], 'building_type', building_type) |
|---|
| 735 | |
|---|
| 736 | del building_type |
|---|
| 737 | del bridges_2d |
|---|
| 738 | |
|---|
| 739 | # Read/Write street type and street crossings |
|---|
| 740 | for i in range(0,ndomains): |
|---|
| 741 | |
|---|
| 742 | street_type = nc_read_from_file_2d(input_file_street_type[ii[i]], 'Band1', domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 743 | street_type[street_type == 255] = fillvalues["street_type"] |
|---|
| 744 | street_type = np.where((street_type < 1) & (street_type != fillvalues["street_type"]),defaultvalues["street_type"],street_type) |
|---|
| 745 | |
|---|
| 746 | nc_write_to_file_2d(filename[i], 'street_type', street_type, datatypes["street_type"],'y','x',fillvalues["street_type"]) |
|---|
| 747 | nc_write_attribute(filename[i], 'street_type', 'long_name', 'street type') |
|---|
| 748 | nc_write_attribute(filename[i], 'street_type', 'units', '') |
|---|
| 749 | nc_write_attribute(filename[i], 'street_type', 'res_orig', domain_px[i]) |
|---|
| 750 | nc_write_attribute(filename[i], 'street_type', 'coordinates', 'E_UTM N_UTM lon lat') |
|---|
| 751 | nc_write_attribute(filename[i], 'street_type', 'grid_mapping', 'E_UTM N_UTM lon lat') |
|---|
| 752 | del street_type |
|---|
| 753 | |
|---|
| 754 | street_crossings = nc_read_from_file_2d(input_file_street_crossings[ii[i]], 'Band1', domain_x0[i], domain_x1[i], domain_y0[i], domain_y1[i]) |
|---|
| 755 | street_crossings[street_crossings == 255] = fillvalues["street_crossings"] |
|---|
| 756 | street_crossings = np.where((street_crossings < 1) & (street_crossings != fillvalues["street_crossings"]),defaultvalues["street_crossings"],street_crossings) |
|---|
| 757 | |
|---|
| 758 | nc_write_to_file_2d(filename[i], 'street_crossings', street_crossings, datatypes["street_crossings"],'y','x',fillvalues["street_crossings"]) |
|---|
| 759 | nc_write_attribute(filename[i], 'street_crossings', 'long_name', 'street crossings') |
|---|
| 760 | nc_write_attribute(filename[i], 'street_crossings', 'units', '') |
|---|
| 761 | nc_write_attribute(filename[i], 'street_crossings', 'res_orig', domain_px[i]) |
|---|
| 762 | nc_write_attribute(filename[i], 'street_crossings', 'coordinates', 'E_UTM N_UTM lon lat') |
|---|
| 763 | nc_write_attribute(filename[i], 'street_crossings', 'grid_mapping', 'E_UTM N_UTM lon lat') |
|---|
| 764 | del street_crossings |
|---|
