1 | #!/usr/bin/env python |
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2 | """File function |
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3 | Takes a file as input, and returns it as a mathematical function. |
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4 | For example, you can load an arbitrary 2D heightfield mesh, and treat it as a |
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5 | function like so: |
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6 | |
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7 | F = file_function('my_mesh.sww', ...) |
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8 | evaluated_point = F(x, y) |
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9 | |
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10 | Values will be interpolated across the surface of the mesh. Holes in the mesh |
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11 | have an undefined value. |
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12 | |
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13 | """ |
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14 | |
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15 | import numpy as num |
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16 | |
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17 | from anuga.geospatial_data.geospatial_data import ensure_absolute |
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18 | from anuga.file.netcdf import NetCDFFile |
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19 | from anuga.config import netcdf_mode_r, netcdf_mode_w, netcdf_mode_a |
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20 | from anuga.utilities.numerical_tools import ensure_numeric |
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21 | |
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22 | import anuga.utilities.log as log |
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23 | |
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24 | |
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25 | def file_function(filename, |
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26 | domain=None, |
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27 | quantities=None, |
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28 | interpolation_points=None, |
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29 | time_thinning=1, |
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30 | time_limit=None, |
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31 | verbose=False, |
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32 | use_cache=False, |
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33 | boundary_polygon=None, |
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34 | output_centroids=False): |
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35 | """Read time history of spatial data from NetCDF file and return |
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36 | a callable object. |
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37 | |
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38 | Input variables: |
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39 | |
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40 | filename - Name of sww, tms or sts file |
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41 | |
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42 | If the file has extension 'sww' then it is assumed to be spatio-temporal |
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43 | or temporal and the callable object will have the form f(t,x,y) or f(t) |
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44 | depending on whether the file contains spatial data |
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45 | |
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46 | If the file has extension 'tms' then it is assumed to be temporal only |
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47 | and the callable object will have the form f(t) |
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48 | |
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49 | Either form will return interpolated values based on the input file |
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50 | using the underlying interpolation_function. |
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51 | |
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52 | domain - Associated domain object |
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53 | If domain is specified, model time (domain.starttime) |
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54 | will be checked and possibly modified. |
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55 | |
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56 | All times are assumed to be in UTC |
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57 | |
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58 | All spatial information is assumed to be in absolute UTM coordinates. |
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59 | |
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60 | quantities - the name of the quantity to be interpolated or a |
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61 | list of quantity names. The resulting function will return |
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62 | a tuple of values - one for each quantity |
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63 | If quantities are None, the default quantities are |
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64 | ['stage', 'xmomentum', 'ymomentum'] |
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65 | |
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66 | |
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67 | interpolation_points - list of absolute UTM coordinates for points (N x 2) |
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68 | or geospatial object or points file name at which values are sought |
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69 | |
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70 | time_thinning - |
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71 | |
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72 | verbose - |
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73 | |
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74 | use_cache: True means that caching of intermediate result of |
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75 | Interpolation_function is attempted |
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76 | |
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77 | boundary_polygon - |
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78 | |
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79 | |
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80 | See Interpolation function in anuga.fit_interpolate.interpolation for |
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81 | further documentation |
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82 | """ |
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83 | |
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84 | # FIXME (OLE): Should check origin of domain against that of file |
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85 | # In fact, this is where origin should be converted to that of domain |
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86 | # Also, check that file covers domain fully. |
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87 | |
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88 | # Take into account: |
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89 | # - domain's georef |
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90 | # - sww file's georef |
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91 | # - interpolation points as absolute UTM coordinates |
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92 | |
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93 | if quantities is None: |
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94 | if verbose: |
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95 | msg = 'Quantities specified in file_function are None,' |
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96 | msg += ' so using stage, xmomentum, and ymomentum in that order' |
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97 | log.critical(msg) |
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98 | quantities = ['stage', 'xmomentum', 'ymomentum'] |
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99 | |
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100 | # Use domain's startime if available |
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101 | if domain is not None: |
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102 | domain_starttime = domain.get_starttime() |
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103 | else: |
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104 | domain_starttime = None |
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105 | |
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106 | # Build arguments and keyword arguments for use with caching or apply. |
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107 | args = (filename,) |
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108 | |
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109 | # FIXME (Ole): Caching this function will not work well |
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110 | # if domain is passed in as instances change hash code. |
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111 | # Instead we pass in those attributes that are needed (and return them |
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112 | # if modified) |
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113 | kwargs = {'quantities': quantities, |
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114 | 'interpolation_points': interpolation_points, |
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115 | 'domain_starttime': domain_starttime, |
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116 | 'time_thinning': time_thinning, |
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117 | 'time_limit': time_limit, |
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118 | 'verbose': verbose, |
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119 | 'boundary_polygon': boundary_polygon, |
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120 | 'output_centroids': output_centroids} |
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121 | |
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122 | # Call underlying engine with or without caching |
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123 | if use_cache is True: |
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124 | try: |
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125 | from caching import cache |
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126 | except: |
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127 | msg = 'Caching was requested, but caching module'+\ |
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128 | 'could not be imported' |
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129 | raise Exception(msg) |
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130 | |
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131 | f, starttime = cache(_file_function, |
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132 | args, kwargs, |
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133 | dependencies=[filename], |
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134 | compression=False, |
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135 | verbose=verbose) |
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136 | else: |
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137 | f, starttime = apply(_file_function, |
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138 | args, kwargs) |
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139 | |
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140 | #FIXME (Ole): Pass cache arguments, such as compression, in some sort of |
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141 | #structure |
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142 | |
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143 | f.starttime = starttime |
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144 | f.filename = filename |
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145 | |
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146 | if domain is not None: |
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147 | #Update domain.startime if it is *earlier* than starttime from file |
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148 | if starttime > domain.starttime: |
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149 | msg = 'WARNING: Start time as specified in domain (%f)' \ |
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150 | % domain.starttime |
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151 | msg += ' is earlier than the starttime of file %s (%f).' \ |
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152 | % (filename, starttime) |
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153 | msg += ' Modifying domain starttime accordingly.' |
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154 | |
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155 | if verbose: log.critical(msg) |
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156 | |
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157 | domain.set_starttime(starttime) #Modifying model time |
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158 | |
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159 | if verbose: log.critical('Domain starttime is now set to %f' |
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160 | % domain.starttime) |
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161 | return f |
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162 | |
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163 | |
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164 | def _file_function(filename, |
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165 | quantities=None, |
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166 | interpolation_points=None, |
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167 | domain_starttime=None, |
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168 | time_thinning=1, |
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169 | time_limit=None, |
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170 | verbose=False, |
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171 | boundary_polygon=None, |
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172 | output_centroids=False): |
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173 | """Internal function |
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174 | |
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175 | See file_function for documentatiton |
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176 | """ |
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177 | |
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178 | assert type(filename) == type(''),\ |
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179 | 'First argument to File_function must be a string' |
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180 | |
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181 | try: |
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182 | fid = open(filename) |
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183 | except IOError, e: |
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184 | msg = 'File "%s" could not be opened: Error="%s"' % (filename, e) |
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185 | raise IOError(msg) |
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186 | |
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187 | # read first line of file, guess file type |
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188 | line = fid.readline() |
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189 | fid.close() |
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190 | |
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191 | # FIXME SR: This test doesn't seem to work with netcdf4 |
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192 | if line[:3] == 'CDF': |
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193 | return get_netcdf_file_function(filename, |
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194 | quantities, |
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195 | interpolation_points, |
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196 | domain_starttime, |
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197 | time_thinning=time_thinning, |
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198 | time_limit=time_limit, |
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199 | verbose=verbose, |
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200 | boundary_polygon=boundary_polygon, |
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201 | output_centroids=output_centroids) |
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202 | else: |
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203 | # FIXME (Ole): Could add csv file here to address Ted Rigby's |
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204 | # suggestion about reading hydrographs. |
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205 | # This may also deal with the gist of ticket:289 |
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206 | raise Exception('Must be a NetCDF File') |
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207 | |
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208 | |
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209 | def get_netcdf_file_function(filename, |
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210 | quantity_names=None, |
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211 | interpolation_points=None, |
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212 | domain_starttime=None, |
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213 | time_thinning=1, |
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214 | time_limit=None, |
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215 | verbose=False, |
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216 | boundary_polygon=None, |
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217 | output_centroids=False): |
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218 | """Read time history of spatial data from NetCDF sww file and |
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219 | return a callable object f(t,x,y) |
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220 | which will return interpolated values based on the input file. |
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221 | |
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222 | Model time (domain_starttime) |
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223 | will be checked, possibly modified and returned |
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224 | |
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225 | All times are assumed to be in UTC |
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226 | |
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227 | See Interpolation function for further documetation |
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228 | """ |
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229 | |
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230 | # FIXME: Check that model origin is the same as file's origin |
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231 | # (both in UTM coordinates) |
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232 | # If not - modify those from file to match domain |
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233 | # (origin should be passed in) |
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234 | # Take this code from e.g. dem2pts in data_manager.py |
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235 | # FIXME: Use geo_reference to read and write xllcorner... |
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236 | |
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237 | import time, calendar |
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238 | from anuga.config import time_format |
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239 | |
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240 | # Open NetCDF file |
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241 | if verbose: log.critical('Reading %s' % filename) |
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242 | |
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243 | fid = NetCDFFile(filename, netcdf_mode_r) |
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244 | |
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245 | if isinstance(quantity_names, basestring): |
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246 | quantity_names = [quantity_names] |
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247 | |
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248 | if quantity_names is None or len(quantity_names) < 1: |
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249 | msg = 'No quantities are specified in file_function' |
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250 | raise Exception(msg) |
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251 | |
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252 | if interpolation_points is not None: |
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253 | |
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254 | #interpolation_points = num.array(interpolation_points, num.float) |
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255 | interpolation_points = ensure_absolute(interpolation_points) |
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256 | msg = 'Points must by N x 2. I got %d' % interpolation_points.shape[1] |
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257 | assert interpolation_points.shape[1] == 2, msg |
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258 | |
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259 | # Now assert that requested quantitites (and the independent ones) |
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260 | # are present in file |
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261 | missing = [] |
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262 | for quantity in ['time'] + quantity_names: |
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263 | if not fid.variables.has_key(quantity): |
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264 | missing.append(quantity) |
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265 | |
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266 | if len(missing) > 0: |
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267 | msg = 'Quantities %s could not be found in file %s'\ |
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268 | % (str(missing), filename) |
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269 | fid.close() |
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270 | raise Exception(msg) |
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271 | |
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272 | # Decide whether this data has a spatial dimension |
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273 | spatial = True |
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274 | for quantity in ['x', 'y']: |
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275 | if not fid.variables.has_key(quantity): |
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276 | spatial = False |
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277 | |
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278 | if filename[-3:] == 'tms' and spatial is True: |
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279 | msg = 'Files of type TMS must not contain spatial information' |
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280 | raise Exception(msg) |
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281 | |
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282 | if filename[-3:] == 'sww' and spatial is False: |
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283 | msg = 'Files of type SWW must contain spatial information' |
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284 | raise Exception(msg) |
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285 | |
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286 | if filename[-3:] == 'sts' and spatial is False: |
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287 | #What if mux file only contains one point |
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288 | msg = 'Files of type STS must contain spatial information' |
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289 | raise Exception(msg) |
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290 | |
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291 | # JJ REMOVED |
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292 | #if filename[-3:] == 'sts' and boundary_polygon is None: |
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293 | # #What if mux file only contains one point |
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294 | # msg = 'Files of type sts require boundary polygon' |
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295 | # raise Exception(msg) |
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296 | |
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297 | # Get first timestep |
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298 | try: |
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299 | starttime = float(fid.starttime) |
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300 | except ValueError: |
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301 | msg = 'Could not read starttime from file %s' % filename |
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302 | raise Exception(msg) |
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303 | |
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304 | |
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305 | # Get variables |
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306 | # if verbose: log.critical('Get variables' ) |
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307 | time = fid.variables['time'][:] |
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308 | # FIXME(Ole): Is time monotoneous? |
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309 | |
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310 | # Apply time limit if requested |
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311 | upper_time_index = len(time) |
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312 | msg = 'Time vector obtained from file %s has length 0' % filename |
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313 | assert upper_time_index > 0, msg |
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314 | |
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315 | if time_limit is not None: |
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316 | # Adjust given time limit to given start time |
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317 | time_limit = time_limit - starttime |
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318 | |
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319 | |
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320 | # Find limit point |
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321 | for i, t in enumerate(time): |
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322 | if t > time_limit: |
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323 | upper_time_index = i |
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324 | break |
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325 | |
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326 | msg = 'Time vector is zero. Requested time limit is %f' % time_limit |
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327 | assert upper_time_index > 0, msg |
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328 | |
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329 | if time_limit < time[-1] and verbose is True: |
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330 | log.critical('Limited time vector from %.2fs to %.2fs' |
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331 | % (time[-1], time_limit)) |
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332 | |
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333 | time = time[:upper_time_index] |
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334 | |
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335 | |
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336 | |
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337 | |
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338 | # Get time independent stuff |
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339 | if spatial: |
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340 | # Get origin |
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341 | #xllcorner = fid.xllcorner[0] |
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342 | #yllcorner = fid.yllcorner[0] |
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343 | #zone = fid.zone[0] |
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344 | |
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345 | xllcorner = fid.xllcorner |
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346 | yllcorner = fid.yllcorner |
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347 | zone = fid.zone |
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348 | |
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349 | x = fid.variables['x'][:] |
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350 | y = fid.variables['y'][:] |
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351 | if filename.endswith('sww'): |
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352 | triangles = fid.variables['volumes'][:] |
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353 | |
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354 | x = num.reshape(x, (len(x), 1)) |
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355 | y = num.reshape(y, (len(y), 1)) |
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356 | vertex_coordinates = num.concatenate((x, y), axis=1) #m x 2 array |
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357 | |
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358 | if boundary_polygon is not None: |
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359 | # Remove sts points that do not lie on boundary |
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360 | # FIXME(Ole): Why don't we just remove such points from the list of |
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361 | # points and associated data? |
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362 | # I am actually convinced we can get rid of neighbour_gauge_id |
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363 | # altogether as the sts file is produced using the ordering file. |
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364 | # All sts points are therefore always present in the boundary. |
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365 | # In fact, they *define* parts of the boundary. |
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366 | boundary_polygon=ensure_numeric(boundary_polygon) |
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367 | boundary_polygon[:, 0] -= xllcorner |
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368 | boundary_polygon[:, 1] -= yllcorner |
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369 | temp=[] |
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370 | boundary_id=[] |
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371 | gauge_id=[] |
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372 | for i in range(len(boundary_polygon)): |
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373 | for j in range(len(x)): |
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374 | if num.allclose(vertex_coordinates[j], |
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375 | boundary_polygon[i], 1e-4): |
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376 | #FIXME: |
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377 | #currently gauges lat and long is stored as float and |
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378 | #then cast to double. This cuases slight repositioning |
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379 | #of vertex_coordinates. |
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380 | temp.append(boundary_polygon[i]) |
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381 | gauge_id.append(j) |
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382 | boundary_id.append(i) |
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383 | break |
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384 | gauge_neighbour_id=[] |
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385 | for i in range(len(boundary_id)-1): |
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386 | if boundary_id[i]+1==boundary_id[i+1]: |
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387 | gauge_neighbour_id.append(i+1) |
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388 | else: |
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389 | gauge_neighbour_id.append(-1) |
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390 | if boundary_id[len(boundary_id)-1]==len(boundary_polygon)-1 \ |
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391 | and boundary_id[0]==0: |
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392 | gauge_neighbour_id.append(0) |
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393 | else: |
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394 | gauge_neighbour_id.append(-1) |
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395 | gauge_neighbour_id=ensure_numeric(gauge_neighbour_id) |
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396 | |
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397 | if len(num.compress(gauge_neighbour_id>=0, gauge_neighbour_id)) \ |
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398 | != len(temp)-1: |
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399 | msg='incorrect number of segments' |
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400 | raise Exception(msg) |
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401 | vertex_coordinates=ensure_numeric(temp) |
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402 | if len(vertex_coordinates)==0: |
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403 | msg = 'None of the sts gauges fall on the boundary' |
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404 | raise Exception(msg) |
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405 | else: |
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406 | gauge_neighbour_id=None |
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407 | |
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408 | if interpolation_points is not None: |
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409 | # Adjust for georef |
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410 | interpolation_points[:, 0] -= xllcorner |
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411 | interpolation_points[:, 1] -= yllcorner |
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412 | else: |
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413 | gauge_neighbour_id=None |
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414 | |
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415 | if domain_starttime is not None: |
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416 | # If domain_startime is *later* than starttime, |
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417 | # move time back - relative to domain's time |
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418 | if domain_starttime > starttime: |
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419 | time = time - domain_starttime + starttime |
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420 | |
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421 | # FIXME Use method in geo to reconcile |
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422 | # if spatial: |
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423 | # assert domain.geo_reference.xllcorner == xllcorner |
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424 | # assert domain.geo_reference.yllcorner == yllcorner |
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425 | # assert domain.geo_reference.zone == zone |
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426 | |
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427 | if verbose: |
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428 | log.critical('File_function data obtained from: %s' % filename) |
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429 | log.critical(' References:') |
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430 | if spatial: |
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431 | log.critical(' Lower left corner: [%f, %f]' |
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432 | % (xllcorner, yllcorner)) |
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433 | log.critical(' Start time: %f' % starttime) |
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434 | |
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435 | |
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436 | # Produce values for desired data points at |
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437 | # each timestep for each quantity |
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438 | quantities = {} |
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439 | for i, name in enumerate(quantity_names): |
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440 | quantities[name] = fid.variables[name][:] |
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441 | if boundary_polygon is not None: |
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442 | #removes sts points that do not lie on boundary |
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443 | quantities[name] = num.take(quantities[name], gauge_id, axis=1) |
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444 | |
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445 | # Close sww, tms or sts netcdf file |
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446 | fid.close() |
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447 | |
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448 | from anuga.fit_interpolate.interpolate import Interpolation_function |
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449 | |
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450 | if not spatial: |
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451 | vertex_coordinates = triangles = interpolation_points = None |
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452 | if filename[-3:] == 'sts':#added |
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453 | triangles = None |
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454 | #vertex coordinates is position of urs gauges |
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455 | |
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456 | if verbose: |
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457 | log.critical('Calling interpolation function') |
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458 | |
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459 | # Return Interpolation_function instance as well as |
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460 | # starttime for use to possible modify that of domain |
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461 | return (Interpolation_function(time, |
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462 | quantities, |
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463 | quantity_names, |
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464 | vertex_coordinates, |
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465 | triangles, |
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466 | interpolation_points, |
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467 | time_thinning=time_thinning, |
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468 | verbose=verbose, |
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469 | gauge_neighbour_id=gauge_neighbour_id, |
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470 | output_centroids=output_centroids), |
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471 | starttime) |
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472 | |
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473 | # NOTE (Ole): Caching Interpolation function is too slow as |
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474 | # the very long parameters need to be hashed. |
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