1 | # external modules |
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2 | import numpy as num |
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3 | import anuga.utilities.log as log |
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4 | |
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5 | # ANUGA modules |
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6 | from anuga.config import netcdf_mode_r, netcdf_mode_w, netcdf_mode_a, \ |
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7 | netcdf_float |
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8 | |
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9 | def asc2dem(name_in, name_out=None, |
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10 | use_cache=False, |
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11 | verbose=False): |
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12 | """Read Digital Elevation model from the following ASCII format (.asc) |
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13 | |
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14 | Example: |
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15 | ncols 3121 |
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16 | nrows 1800 |
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17 | xllcorner 722000 |
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18 | yllcorner 5893000 |
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19 | cellsize 25 |
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20 | NODATA_value -9999 |
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21 | 138.3698 137.4194 136.5062 135.5558 .......... |
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22 | |
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23 | Convert name_in (.asc) to NetCDF format (.dem) |
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24 | mimicking the ASCII format closely. |
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25 | |
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26 | An accompanying file with same basename but extension .prj must exist |
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27 | and is used to fix the UTM zone, datum, false northings and eastings. |
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28 | |
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29 | The prj format is assumed to be as |
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30 | |
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31 | Projection UTM |
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32 | Zone 56 |
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33 | Datum WGS84 |
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34 | Zunits NO |
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35 | Units METERS |
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36 | Spheroid WGS84 |
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37 | Xshift 0.0000000000 |
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38 | Yshift 10000000.0000000000 |
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39 | Parameters |
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40 | """ |
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41 | |
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42 | kwargs = {'name_out': name_out, 'verbose': verbose} |
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43 | |
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44 | if use_cache is True: |
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45 | from caching import cache |
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46 | result = cache(_convert_dem_from_ascii2netcdf, name_in, kwargs, |
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47 | dependencies=[name_in, |
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48 | name_in[:-4] + '.prj'], |
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49 | verbose=verbose) |
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50 | |
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51 | else: |
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52 | result = apply(_convert_dem_from_ascii2netcdf, [name_in], kwargs) |
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53 | |
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54 | return result |
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55 | |
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56 | |
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57 | ## |
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58 | # @brief Convert an ASC file to a DEM file. |
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59 | # @param basename_in Stem of input filename. |
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60 | # @param basename_out Stem of output filename. |
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61 | # @param verbose True if this function is to be verbose. |
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62 | def _convert_dem_from_ascii2netcdf(name_in, name_out = None, |
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63 | verbose = False): |
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64 | """Read Digital Elevation model from the following ASCII format (.asc) |
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65 | |
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66 | Internal function. See public function convert_dem_from_ascii2netcdf |
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67 | for details. |
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68 | """ |
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69 | |
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70 | import os |
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71 | from Scientific.IO.NetCDF import NetCDFFile |
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72 | |
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73 | root = name_in[:-4] |
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74 | |
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75 | # Read Meta data |
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76 | if verbose: log.critical('Reading METADATA from %s' % (root + '.prj')) |
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77 | |
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78 | metadatafile = open(root + '.prj') |
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79 | metalines = metadatafile.readlines() |
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80 | metadatafile.close() |
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81 | |
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82 | L = metalines[0].strip().split() |
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83 | assert L[0].strip().lower() == 'projection' |
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84 | projection = L[1].strip() #TEXT |
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85 | |
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86 | L = metalines[1].strip().split() |
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87 | assert L[0].strip().lower() == 'zone' |
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88 | zone = int(L[1].strip()) |
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89 | |
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90 | L = metalines[2].strip().split() |
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91 | assert L[0].strip().lower() == 'datum' |
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92 | datum = L[1].strip() #TEXT |
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93 | |
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94 | L = metalines[3].strip().split() |
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95 | assert L[0].strip().lower() == 'zunits' #IGNORE |
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96 | zunits = L[1].strip() #TEXT |
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97 | |
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98 | L = metalines[4].strip().split() |
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99 | assert L[0].strip().lower() == 'units' |
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100 | units = L[1].strip() #TEXT |
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101 | |
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102 | L = metalines[5].strip().split() |
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103 | assert L[0].strip().lower() == 'spheroid' #IGNORE |
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104 | spheroid = L[1].strip() #TEXT |
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105 | |
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106 | L = metalines[6].strip().split() |
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107 | assert L[0].strip().lower() == 'xshift' |
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108 | false_easting = float(L[1].strip()) |
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109 | |
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110 | L = metalines[7].strip().split() |
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111 | assert L[0].strip().lower() == 'yshift' |
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112 | false_northing = float(L[1].strip()) |
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113 | |
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114 | if name_in[-4:] != '.asc': |
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115 | raise IOError('Input file %s should be of type .asc.' % name_in) |
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116 | |
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117 | #Read DEM data |
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118 | datafile = open(name_in) |
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119 | |
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120 | if verbose: log.critical('Reading DEM from %s' % (name_in)) |
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121 | |
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122 | lines = datafile.readlines() |
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123 | datafile.close() |
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124 | |
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125 | if verbose: log.critical('Got %d lines' % len(lines)) |
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126 | |
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127 | ncols = int(lines[0].split()[1].strip()) |
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128 | nrows = int(lines[1].split()[1].strip()) |
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129 | |
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130 | # Do cellsize (line 4) before line 2 and 3 |
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131 | cellsize = float(lines[4].split()[1].strip()) |
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132 | |
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133 | # Checks suggested by Joaquim Luis |
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134 | # Our internal representation of xllcorner |
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135 | # and yllcorner is non-standard. |
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136 | xref = lines[2].split() |
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137 | if xref[0].strip() == 'xllcorner': |
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138 | xllcorner = float(xref[1].strip()) # + 0.5*cellsize # Correct offset |
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139 | elif xref[0].strip() == 'xllcenter': |
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140 | xllcorner = float(xref[1].strip()) |
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141 | else: |
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142 | msg = 'Unknown keyword: %s' % xref[0].strip() |
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143 | raise Exception, msg |
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144 | |
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145 | yref = lines[3].split() |
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146 | if yref[0].strip() == 'yllcorner': |
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147 | yllcorner = float(yref[1].strip()) # + 0.5*cellsize # Correct offset |
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148 | elif yref[0].strip() == 'yllcenter': |
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149 | yllcorner = float(yref[1].strip()) |
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150 | else: |
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151 | msg = 'Unknown keyword: %s' % yref[0].strip() |
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152 | raise Exception, msg |
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153 | |
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154 | NODATA_value = int(lines[5].split()[1].strip()) |
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155 | |
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156 | assert len(lines) == nrows + 6 |
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157 | |
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158 | if name_out == None: |
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159 | netcdfname = name_in[:-4]+'.dem' |
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160 | else: |
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161 | netcdfname = name_out + '.dem' |
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162 | |
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163 | if verbose: log.critical('Store to NetCDF file %s' % netcdfname) |
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164 | |
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165 | # NetCDF file definition |
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166 | fid = NetCDFFile(netcdfname, netcdf_mode_w) |
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167 | |
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168 | #Create new file |
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169 | fid.institution = 'Geoscience Australia' |
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170 | fid.description = 'NetCDF DEM format for compact and portable storage ' \ |
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171 | 'of spatial point data' |
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172 | |
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173 | fid.ncols = ncols |
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174 | fid.nrows = nrows |
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175 | fid.xllcorner = xllcorner |
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176 | fid.yllcorner = yllcorner |
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177 | fid.cellsize = cellsize |
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178 | fid.NODATA_value = NODATA_value |
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179 | |
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180 | fid.zone = zone |
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181 | fid.false_easting = false_easting |
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182 | fid.false_northing = false_northing |
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183 | fid.projection = projection |
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184 | fid.datum = datum |
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185 | fid.units = units |
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186 | |
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187 | # dimension definitions |
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188 | fid.createDimension('number_of_rows', nrows) |
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189 | fid.createDimension('number_of_columns', ncols) |
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190 | |
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191 | # variable definitions |
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192 | fid.createVariable('elevation', netcdf_float, ('number_of_rows', |
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193 | 'number_of_columns')) |
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194 | |
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195 | # Get handles to the variables |
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196 | elevation = fid.variables['elevation'] |
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197 | |
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198 | #Store data |
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199 | n = len(lines[6:]) |
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200 | for i, line in enumerate(lines[6:]): |
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201 | fields = line.split() |
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202 | if verbose and i % ((n+10)/10) == 0: |
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203 | log.critical('Processing row %d of %d' % (i, nrows)) |
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204 | |
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205 | if len(fields) != ncols: |
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206 | msg = 'Wrong number of columns in file "%s" line %d\n' % (name_in, i) |
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207 | msg += 'I got %d elements, but there should have been %d\n' % (len(fields), ncols) |
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208 | raise Exception, msg |
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209 | |
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210 | elevation[i, :] = num.array([float(x) for x in fields]) |
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211 | |
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212 | fid.close() |
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