1 | function data = nc_varget(ncfile, varname, varargin ) |
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2 | % NC_VARGET: Retrieve data from a netCDF variable. |
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3 | % |
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4 | % DATA = NC_VARGET(NCFILE,VARNAME) retrieves all the data from the |
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5 | % variable VARNAME in the netCDF file NCFILE. |
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6 | % |
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7 | % DATA = NC_VARGET(NCFILE,VARNAME,START,COUNT) retrieves the contiguous |
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8 | % portion of the variable specified by the index vectors START and |
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9 | % COUNT. Remember that SNCTOOLS indexing is zero-based, not |
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10 | % one-based. Specifying a -1 in COUNT means to retrieve everything |
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11 | % along that dimension from the START coordinate. |
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12 | % |
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13 | % DATA = NC_VARGET(NCFILE,VARNAME,START,COUNT,STRIDE) retrieves |
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14 | % a non-contiguous portion of the dataset. The amount of |
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15 | % skipping along each dimension is given through the STRIDE vector. |
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16 | % |
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17 | % NCFILE can also be an OPeNDAP URL if the proper java SNCTOOLS |
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18 | % backend is installed. See the README for details. |
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19 | % |
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20 | % NC_VARGET tries to be intelligent about retrieving the data. |
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21 | % Since most general matlab operations are done in double precision, |
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22 | % retrieved numeric data will be cast to double precision, while |
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23 | % character data remains just character data. |
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24 | % |
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25 | % Singleton dimensions are removed from the output data. |
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26 | % |
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27 | % A '_FillValue' attribute is honored by flagging those datums as NaN. |
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28 | % A 'missing_value' attribute is honored by flagging those datums as |
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29 | % NaN. The exception to this is for NC_CHAR variables, as mixing |
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30 | % character data and NaN doesn't really seem to work in matlab. |
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31 | % |
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32 | % If the named NetCDF variable has valid scale_factor and add_offset |
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33 | % attributes, then the data is scaled accordingly. |
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34 | % |
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35 | % Setting the preference 'PRESERVE_FVD' to true will compel NC_VARGET |
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36 | % to preserve the fastest varying dimension. This basically means |
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37 | % that NC_VARGET will not transpose the data. This basically flips |
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38 | % the order of the dimension IDs from what one would see by using |
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39 | % the ncdump C utility. You may get a substantial performance boost from |
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40 | % this. |
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41 | % |
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42 | % EXAMPLE: |
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43 | % #1. In this case, the variable in question has rank 2, and has size |
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44 | % 500x700. We want to retrieve starting at row 300, column 250. |
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45 | % We want 100 contiguous rows, 200 contiguous columns. |
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46 | % |
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47 | % vardata = nc_varget ( file, variable_name, [300 250], [100 200] ); |
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48 | % |
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49 | |
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50 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
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51 | % |
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52 | % $Id: nc_varget.m 2681 2009-04-28 14:55:17Z johnevans007 $ |
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53 | % $LastChangedDate: 2009-04-28 10:55:17 -0400 (Tue, 28 Apr 2009) $ |
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54 | % $LastChangedRevision: 2681 $ |
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55 | % $LastChangedBy: johnevans007 $ |
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56 | % |
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57 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
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58 | |
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59 | |
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60 | |
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61 | error(nargchk(2,5,nargin,'struct')); |
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62 | error(nargoutchk(0,1,nargout,'struct')); |
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63 | |
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64 | [start, count, stride] = parse_and_validate_args(ncfile,varname,varargin{:}); |
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65 | |
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66 | retrieval_method = snc_read_backend(ncfile); |
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67 | switch(retrieval_method) |
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68 | case 'tmw' |
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69 | data = nc_varget_tmw(ncfile,varname,start,count,stride); |
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70 | case 'java' |
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71 | data = nc_varget_java(ncfile,varname,start,count,stride); |
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72 | case 'mexnc' |
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73 | data = nc_varget_mexnc(ncfile,varname,start,count,stride); |
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74 | end |
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75 | |
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76 | return |
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77 | |
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78 | |
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79 | |
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80 | |
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81 | |
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82 | |
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83 | |
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84 | |
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85 | |
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86 | |
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87 | |
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88 | %---------------------------------------------------------------------- |
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89 | function values = nc_varget_mexnc(ncfile,varname,start,count,stride) |
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90 | |
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91 | |
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92 | |
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93 | [ncid,status]=mexnc('open',ncfile,'NOWRITE'); |
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94 | if status ~= 0 |
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95 | ncerr = mexnc('strerror', status); |
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96 | error ( 'SNCTOOLS:NC_VARGET:MEXNC:OPEN', ncerr ); |
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97 | end |
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98 | |
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99 | |
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100 | [varid, status]=mexnc('inq_varid',ncid,varname); |
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101 | if status ~= 0 |
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102 | ncerr = mexnc('strerror', status); |
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103 | mexnc('close',ncid); |
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104 | error ( 'SNCTOOLS:NC_VARGET:MEXNC:INQ_VARID', ncerr ); |
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105 | end |
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106 | |
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107 | [dud,var_type,nvdims,dimids,dud,status]=mexnc('inq_var',ncid,varid); |
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108 | if status ~= 0 |
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109 | mexnc('close',ncid); |
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110 | error ( 'SNCTOOLS:NC_VARGET:MEXNC:INQ_VAR', mexnc('strerror',status) ); |
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111 | end |
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112 | |
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113 | |
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114 | % mexnc does not preserve the fastest varying dimension. If we want this, |
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115 | % then we flip the indices. |
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116 | preserve_fvd = getpref('SNCTOOLS','PRESERVE_FVD',false); |
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117 | if preserve_fvd |
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118 | start = fliplr(start); |
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119 | count = fliplr(count); |
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120 | stride = fliplr(stride); |
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121 | end |
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122 | |
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123 | |
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124 | % |
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125 | % Check that the start, count, stride parameters have appropriate lengths. |
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126 | % Otherwise we get confusing error messages later on. |
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127 | validate_index_vectors(start,count,stride,nvdims); |
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128 | |
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129 | % |
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130 | % What mexnc operation will we use? |
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131 | [funcstr_family, funcstr] = determine_funcstr ( var_type, nvdims, start, count, stride ); |
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132 | |
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133 | |
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134 | the_var_size = determine_varsize_mex ( ncid, dimids, nvdims ); |
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135 | |
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136 | % |
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137 | % If the user had set non-positive numbers in "count", then we replace them |
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138 | % with what we need to get the rest of the variable. |
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139 | negs = find(count<0); |
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140 | count(negs) = the_var_size(negs) - start(negs); |
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141 | |
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142 | |
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143 | |
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144 | % |
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145 | % At long last, retrieve the data. |
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146 | switch funcstr_family |
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147 | case 'get_var' |
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148 | [values, status] = mexnc ( funcstr, ncid, varid ); |
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149 | |
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150 | case 'get_var1' |
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151 | [values, status] = mexnc ( funcstr, ncid, varid, 0 ); |
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152 | |
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153 | case 'get_vara' |
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154 | [values, status] = mexnc ( funcstr, ncid, varid, start, count ); |
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155 | |
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156 | |
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157 | case 'get_vars' |
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158 | [values, status] = mexnc ( funcstr, ncid, varid, start, count, stride ); |
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159 | |
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160 | otherwise |
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161 | error ( 'SNCTOOLS:NC_VARGET:unhandledType', ... |
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162 | 'Unhandled function string type ''%s''\n', funcstr_family ); |
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163 | |
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164 | end |
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165 | |
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166 | if ( status ~= 0 ) |
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167 | mexnc('close',ncid); |
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168 | ncerr = mexnc('strerror', status); |
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169 | eid = sprintf ( 'SNCTOOLS:nc_varget:%s', funcstr ); |
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170 | error ( eid, ncerr ); |
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171 | end |
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172 | |
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173 | |
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174 | |
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175 | |
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176 | % |
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177 | % If it's a 1D vector, make it a column vector. |
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178 | % Otherwise permute the data |
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179 | % to make up for the row-major-order-vs-column-major-order issue. |
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180 | if length(the_var_size) == 1 |
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181 | values = values(:); |
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182 | else |
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183 | % Ok it's not a 1D vector. If we are not preserving the fastest |
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184 | % varying dimension, we should permute the data. |
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185 | if ~getpref('SNCTOOLS','PRESERVE_FVD',false) |
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186 | pv = fliplr ( 1:length(the_var_size) ); |
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187 | values = permute(values,pv); |
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188 | end |
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189 | end |
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190 | |
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191 | |
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192 | values = handle_fill_value_mex ( ncid, varid, var_type, values ); |
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193 | values = handle_mex_missing_value ( ncid, varid, var_type, values ); |
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194 | values = handle_scaling_mex ( ncid, varid, values ); |
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195 | |
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196 | |
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197 | % |
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198 | % remove any singleton dimensions. |
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199 | values = squeeze ( values ); |
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200 | |
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201 | |
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202 | mexnc('close',ncid); |
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203 | |
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204 | |
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205 | return |
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206 | |
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207 | |
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208 | |
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209 | |
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210 | |
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211 | |
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212 | |
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213 | |
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214 | |
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215 | |
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216 | |
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217 | |
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218 | |
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219 | |
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220 | |
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221 | |
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222 | |
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223 | %-------------------------------------------------------------------------- |
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224 | function [start, count, stride] = parse_and_validate_args(ncfile,varname,varargin) |
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225 | |
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226 | % |
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227 | % Set up default outputs. |
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228 | start = []; |
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229 | count = []; |
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230 | stride = []; |
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231 | |
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232 | |
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233 | switch nargin |
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234 | case 4 |
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235 | start = varargin{1}; |
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236 | count = varargin{2}; |
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237 | |
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238 | case 5 |
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239 | start = varargin{1}; |
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240 | count = varargin{2}; |
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241 | stride = varargin{3}; |
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242 | |
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243 | end |
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244 | |
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245 | |
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246 | |
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247 | % |
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248 | % Error checking on the inputs. |
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249 | if ~ischar(ncfile) |
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250 | error ( 'SNCTOOLS:NC_VARGET:badInput', 'the filename must be character.' ); |
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251 | end |
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252 | if ~ischar(varname) |
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253 | error ( 'SNCTOOLS:NC_VARGET:badInput', 'the variable name must be character.' ); |
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254 | end |
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255 | |
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256 | if ~isnumeric ( start ) |
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257 | error ( 'SNCTOOLS:NC_VARGET:badInput', 'the ''start'' argument must be numeric.' ); |
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258 | end |
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259 | if ~isnumeric ( count ) |
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260 | error ( 'SNCTOOLS:NC_VARGET:badInput', 'the ''count'' argument must be numeric.' ); |
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261 | end |
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262 | if ~isnumeric ( stride ) |
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263 | error ( 'SNCTOOLS:NC_VARGET:badInput', 'the ''stride'' argument must be numeric.' ); |
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264 | end |
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265 | |
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266 | |
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267 | return |
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268 | |
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269 | |
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270 | |
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271 | |
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272 | |
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273 | |
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274 | |
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275 | |
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276 | |
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277 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
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278 | % |
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279 | % DETERMINE_FUNCSTR |
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280 | % Determines if we are to use, say, 'get_var1_text', or 'get_vars_double', |
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281 | % or whatever. |
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282 | % |
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283 | function [prefix,funcstr] = determine_funcstr ( var_type, nvdims, start, count, stride ) |
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284 | |
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285 | % |
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286 | % Determine if we are retriving a single value, the whole variable, a |
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287 | % contiguous portion, or a strided portion. |
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288 | if nvdims == 0 |
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289 | |
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290 | % |
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291 | % It is a singleton variable. |
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292 | prefix = 'get_var1'; |
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293 | |
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294 | elseif isempty(start) |
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295 | |
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296 | % |
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297 | % retrieving the entire variable. |
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298 | prefix = 'get_var'; |
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299 | |
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300 | elseif ~isempty(start) && ~isempty(count) && isempty(stride) |
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301 | |
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302 | % |
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303 | % retrieving a contiguous portion |
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304 | prefix = 'get_vara'; |
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305 | |
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306 | elseif ~isempty(start) && ~isempty(count) && ~isempty(stride) |
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307 | |
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308 | % |
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309 | % retrieving a contiguous portion |
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310 | prefix = 'get_vars'; |
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311 | |
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312 | else |
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313 | error ( 'SNCTOOLS:NC_VARGET:FUNCSTR', 'Could not determine funcstr prefix.' ); |
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314 | end |
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315 | |
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316 | |
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317 | |
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318 | switch ( var_type ) |
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319 | case nc_char |
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320 | funcstr = [prefix '_text']; |
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321 | |
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322 | case { nc_double, nc_float, nc_int, nc_short, nc_byte } |
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323 | funcstr = [prefix '_double']; |
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324 | |
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325 | otherwise |
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326 | error ( 'SNCTOOLS:NC_VARGET:badDatatype', ... |
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327 | 'Unhandled datatype %d.', var_type ); |
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328 | |
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329 | end |
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330 | return |
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331 | |
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332 | |
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333 | |
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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 | % HANDLE_MEX_FILL_VALUE |
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339 | % If there is a fill value, then replace such values with NaN. |
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340 | % |
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341 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
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342 | function values = handle_fill_value_mex ( ncid, varid, var_type, values ) |
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343 | |
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344 | % |
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345 | % Handle the fill value, if any. Change those values into NaN. |
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346 | [dud, dud, status] = mexnc('INQ_ATT', ncid, varid, '_FillValue' ); |
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347 | if ( status == 0 ) |
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348 | |
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349 | switch ( var_type ) |
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350 | case nc_char |
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351 | % |
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352 | % For now, do nothing. Does a fill value even make sense with char data? |
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353 | % If it does, please tell me so. |
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354 | |
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355 | case { nc_double, nc_float, nc_int, nc_short, nc_byte } |
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356 | [fill_value, status] = mexnc ( 'get_att_double', ncid, varid, '_FillValue' ); |
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357 | values(values==fill_value) = NaN; |
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358 | |
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359 | otherwise |
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360 | mexnc('close',ncid); |
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361 | error ( 'SNCTOOLS:nc_varget:mexnc:unhandledFillValueDatatype', ... |
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362 | 'Unhandled datatype %d.', var_type ); |
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363 | end |
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364 | |
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365 | if ( status ~= 0 ) |
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366 | mexnc('close',ncid); |
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367 | ncerr = mexnc ( 'strerror', status ); |
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368 | error ( 'SNCTOOLS:NC_VARGET:MEXNC:GET_ATT', ncerr ); |
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369 | end |
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370 | |
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371 | |
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372 | |
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373 | end |
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374 | |
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375 | return |
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376 | |
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377 | |
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378 | |
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379 | |
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380 | %-------------------------------------------------------------------------- |
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381 | function values = handle_mex_missing_value ( ncid, varid, var_type, values ) |
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382 | % HANDLE_MEX_MISSING_VALUE |
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383 | % If there is a missing value, then replace such values with NaN. |
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384 | |
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385 | % |
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386 | % If there is a fill value attribute, then that had precedence. Do nothing. |
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387 | [dud, dud, status] = mexnc('INQ_ATT', ncid, varid, '_FillValue' ); |
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388 | if status == 0 |
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389 | return |
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390 | end |
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391 | |
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392 | % |
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393 | % Handle the missing value, if any. Change those values into NaN. |
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394 | [dud, dud, status] = mexnc('INQ_ATT', ncid, varid, 'missing_value' ); |
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395 | if ( status == 0 ) |
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396 | |
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397 | switch ( var_type ) |
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398 | case nc_char |
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399 | % |
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400 | % For now, do nothing. Does a fill value even make sense with char data? |
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401 | % If it does, please tell me so. |
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402 | |
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403 | case { nc_double, nc_float, nc_int, nc_short, nc_byte } |
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404 | [fill_value, status] = mexnc ( 'get_att_double', ncid, varid, 'missing_value' ); |
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405 | values(values==fill_value) = NaN; |
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406 | |
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407 | otherwise |
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408 | mexnc('close',ncid); |
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409 | error ( 'SNCTOOLS:nc_varget:mexnc:unhandledDatatype', ... |
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410 | 'Unhandled datatype %d.', var_type ); |
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411 | |
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412 | end |
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413 | |
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414 | if ( status ~= 0 ) |
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415 | mexnc('close',ncid); |
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416 | ncerr = mexnc ( 'strerror', status ); |
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417 | error ( 'SNCTOOLS:NC_VARGET:MEXNC:GET_ATT', ncerr ); |
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418 | end |
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419 | |
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420 | |
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421 | end |
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422 | |
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423 | return |
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424 | |
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425 | |
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426 | |
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427 | |
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428 | |
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429 | |
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430 | %-------------------------------------------------------------------------- |
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431 | function values = handle_scaling_mex ( ncid, varid, values ) |
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432 | % HANDLE_MEX_SCALING |
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433 | % If there is a scale factor and/or add_offset attribute, convert the data |
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434 | % to double precision and apply the scaling. |
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435 | |
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436 | have_scale = false; |
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437 | have_addoffset = false; |
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438 | [dud, dud, status] = mexnc('INQ_ATT', ncid, varid, 'scale_factor' ); |
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439 | if ( status == 0 ) |
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440 | have_scale = true; |
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441 | end |
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442 | [dud, dud, status] = mexnc('INQ_ATT', ncid, varid, 'add_offset' ); |
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443 | if ( status == 0 ) |
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444 | have_addoffset = true; |
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445 | end |
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446 | |
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447 | % |
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448 | % Return early if we don't have either one. |
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449 | if ~(have_scale || have_addoffset) |
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450 | return; |
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451 | end |
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452 | |
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453 | scale_factor = 1.0; |
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454 | add_offset = 0.0; |
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455 | |
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456 | if have_scale |
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457 | [scale_factor, status] = mexnc ( 'get_att_double', ncid, varid, 'scale_factor' ); |
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458 | if ( status ~= 0 ) |
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459 | mexnc('close',ncid); |
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460 | ncerr = mexnc('strerror', status); |
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461 | error ( 'SNCTOOLS:NC_VARGET:MEXNC:GET_ATT_DOUBLE', ncerr ); |
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462 | end |
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463 | end |
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464 | |
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465 | if have_addoffset |
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466 | [add_offset, status] = mexnc ( 'get_att_double', ncid, varid, 'add_offset' ); |
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467 | if ( status ~= 0 ) |
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468 | mexnc('close',ncid); |
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469 | ncerr = mexnc('strerror', status); |
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470 | error ( 'SNCTOOLS:NC_VARGET:MEXNC:GET_ATT_DOUBLE', ncerr ); |
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471 | end |
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472 | end |
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473 | |
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474 | values = double(values) * scale_factor + add_offset; |
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475 | |
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476 | return |
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477 | |
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478 | |
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479 | |
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480 | |
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481 | |
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482 | |
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483 | |
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484 | |
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485 | %----------------------------------------------------------------------- |
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486 | function the_var_size = determine_varsize_mex ( ncid, dimids, nvdims ) |
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487 | % DETERMINE_VARSIZE_MEX: Need to figure out just how big the variable is. |
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488 | % |
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489 | % VAR_SIZE = DETERMINE_VARSIZE_MEX(NCID,DIMIDS,NVDIMS); |
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490 | |
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491 | % |
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492 | % If not a singleton, we need to figure out how big the variable is. |
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493 | if nvdims == 0 |
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494 | the_var_size = 1; |
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495 | else |
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496 | the_var_size = zeros(1,nvdims); |
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497 | for j=1:nvdims, |
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498 | dimid = dimids(j); |
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499 | [dim_size,status]=mexnc('inq_dimlen', ncid, dimid); |
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500 | if ( status ~= 0 ) |
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501 | ncerr = mexnc ( 'strerror', status ); |
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502 | mexnc('close',ncid); |
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503 | error ( 'SNCTOOLS:NC_VARGET:MEXNC:INQ_DIM_LEN', ncerr ); |
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504 | end |
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505 | the_var_size(j)=dim_size; |
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506 | end |
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507 | end |
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508 | |
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509 | return |
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510 | |
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511 | |
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512 | |
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513 | |
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