| 1 | """ |
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| 2 | Convert a ferret file to an SWW file. |
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| 3 | """ |
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| 4 | # external modules |
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| 5 | import numpy as num |
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| 6 | |
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| 7 | |
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| 8 | # ANUGA modules |
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| 9 | from anuga.config import netcdf_mode_r, netcdf_mode_w, netcdf_float |
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| 10 | from anuga.file.sww import Write_sww |
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| 11 | from anuga.coordinate_transforms.geo_reference import Geo_reference, \ |
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| 12 | write_NetCDF_georeference |
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| 13 | import anuga.utilities.log as log |
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| 14 | |
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| 15 | #local modules |
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| 16 | from anuga.file_conversion.file_conversion import get_min_max_indices |
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| 17 | |
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| 18 | |
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| 19 | def ferret2sww(basename_in, basename_out=None, |
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| 20 | verbose=False, |
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| 21 | minlat=None, maxlat=None, |
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| 22 | minlon=None, maxlon=None, |
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| 23 | mint=None, maxt=None, mean_stage=0, |
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| 24 | origin=None, zscale=1, |
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| 25 | fail_on_NaN=True, |
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| 26 | NaN_filler=0, |
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| 27 | elevation=None, |
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| 28 | inverted_bathymetry=True |
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| 29 | ): #FIXME: Bathymetry should be obtained |
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| 30 | #from MOST somehow. |
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| 31 | #Alternatively from elsewhere |
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| 32 | #or, as a last resort, |
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| 33 | #specified here. |
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| 34 | #The value of -100 will work |
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| 35 | #for the Wollongong tsunami |
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| 36 | #scenario but is very hacky |
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| 37 | """Convert MOST and 'Ferret' NetCDF format for wave propagation to |
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| 38 | sww format native to abstract_2d_finite_volumes. |
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| 39 | |
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| 40 | Specify only basename_in and read files of the form |
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| 41 | basefilename_ha.nc, basefilename_ua.nc, basefilename_va.nc containing |
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| 42 | relative height, x-velocity and y-velocity, respectively. |
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| 43 | |
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| 44 | Also convert latitude and longitude to UTM. All coordinates are |
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| 45 | assumed to be given in the GDA94 datum. |
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| 46 | |
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| 47 | min's and max's: If omitted - full extend is used. |
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| 48 | To include a value min may equal it, while max must exceed it. |
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| 49 | Lat and lon are assuemd to be in decimal degrees |
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| 50 | |
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| 51 | origin is a 3-tuple with geo referenced |
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| 52 | UTM coordinates (zone, easting, northing) |
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| 53 | |
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| 54 | nc format has values organised as HA[TIME, LATITUDE, LONGITUDE] |
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| 55 | which means that longitude is the fastest |
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| 56 | varying dimension (row major order, so to speak) |
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| 57 | |
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| 58 | ferret2sww uses grid points as vertices in a triangular grid |
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| 59 | counting vertices from lower left corner upwards, then right |
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| 60 | """ |
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| 61 | |
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| 62 | from Scientific.IO.NetCDF import NetCDFFile |
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| 63 | |
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| 64 | _assert_lat_long(minlat, maxlat, minlon, maxlon) |
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| 65 | |
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| 66 | # Get NetCDF data |
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| 67 | if verbose: log.critical('Reading files %s_*.nc' % basename_in) |
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| 68 | |
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| 69 | # Wave amplitude (cm) |
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| 70 | file_h = NetCDFFile(basename_in + '_ha.nc', netcdf_mode_r) |
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| 71 | |
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| 72 | # Velocity (x) (cm/s) |
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| 73 | file_u = NetCDFFile(basename_in + '_ua.nc', netcdf_mode_r) |
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| 74 | |
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| 75 | # Velocity (y) (cm/s) |
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| 76 | file_v = NetCDFFile(basename_in + '_va.nc', netcdf_mode_r) |
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| 77 | |
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| 78 | # Elevation (z) (m) |
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| 79 | file_e = NetCDFFile(basename_in + '_e.nc', netcdf_mode_r) |
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| 80 | |
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| 81 | if basename_out is None: |
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| 82 | swwname = basename_in + '.sww' |
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| 83 | else: |
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| 84 | swwname = basename_out + '.sww' |
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| 85 | |
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| 86 | # Get dimensions of file_h |
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| 87 | for dimension in file_h.dimensions.keys(): |
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| 88 | if dimension[:3] == 'LON': |
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| 89 | dim_h_longitude = dimension |
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| 90 | if dimension[:3] == 'LAT': |
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| 91 | dim_h_latitude = dimension |
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| 92 | if dimension[:4] == 'TIME': |
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| 93 | dim_h_time = dimension |
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| 94 | |
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| 95 | times = file_h.variables[dim_h_time] |
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| 96 | latitudes = file_h.variables[dim_h_latitude] |
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| 97 | longitudes = file_h.variables[dim_h_longitude] |
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| 98 | |
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| 99 | kmin, kmax, lmin, lmax = get_min_max_indices(latitudes[:], |
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| 100 | longitudes[:], |
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| 101 | minlat, maxlat, |
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| 102 | minlon, maxlon) |
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| 103 | # get dimensions for file_e |
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| 104 | for dimension in file_e.dimensions.keys(): |
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| 105 | if dimension[:3] == 'LON': |
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| 106 | dim_e_longitude = dimension |
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| 107 | if dimension[:3] == 'LAT': |
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| 108 | dim_e_latitude = dimension |
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| 109 | |
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| 110 | # get dimensions for file_u |
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| 111 | for dimension in file_u.dimensions.keys(): |
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| 112 | if dimension[:3] == 'LON': |
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| 113 | dim_u_longitude = dimension |
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| 114 | if dimension[:3] == 'LAT': |
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| 115 | dim_u_latitude = dimension |
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| 116 | |
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| 117 | # get dimensions for file_v |
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| 118 | for dimension in file_v.dimensions.keys(): |
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| 119 | if dimension[:3] == 'LON': |
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| 120 | dim_v_longitude = dimension |
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| 121 | if dimension[:3] == 'LAT': |
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| 122 | dim_v_latitude = dimension |
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| 123 | |
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| 124 | # Precision used by most for lat/lon is 4 or 5 decimals |
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| 125 | e_lat = num.around(file_e.variables[dim_e_latitude][:], 5) |
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| 126 | e_lon = num.around(file_e.variables[dim_e_longitude][:], 5) |
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| 127 | |
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| 128 | # Check that files are compatible |
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| 129 | assert num.allclose(latitudes, file_u.variables[dim_u_latitude]) |
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| 130 | assert num.allclose(latitudes, file_v.variables[dim_v_latitude]) |
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| 131 | assert num.allclose(latitudes, e_lat) |
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| 132 | |
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| 133 | assert num.allclose(longitudes, file_u.variables[dim_u_longitude]) |
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| 134 | assert num.allclose(longitudes, file_v.variables[dim_v_longitude]) |
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| 135 | assert num.allclose(longitudes, e_lon) |
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| 136 | |
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| 137 | if mint is None: |
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| 138 | jmin = 0 |
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| 139 | mint = times[0] |
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| 140 | else: |
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| 141 | jmin = num.searchsorted(times, mint) |
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| 142 | |
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| 143 | # numpy.int32 didn't work in slicing of amplitude below |
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| 144 | jmin = int(jmin) |
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| 145 | |
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| 146 | if maxt is None: |
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| 147 | jmax = len(times) |
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| 148 | maxt = times[-1] |
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| 149 | else: |
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| 150 | jmax = num.searchsorted(times, maxt) |
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| 151 | |
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| 152 | # numpy.int32 didn't work in slicing of amplitude below |
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| 153 | jmax = int(jmax) |
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| 154 | |
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| 155 | kmin, kmax, lmin, lmax = get_min_max_indices(latitudes[:], |
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| 156 | longitudes[:], |
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| 157 | minlat, maxlat, |
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| 158 | minlon, maxlon) |
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| 159 | |
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| 160 | |
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| 161 | times = times[jmin:jmax] |
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| 162 | latitudes = latitudes[kmin:kmax] |
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| 163 | longitudes = longitudes[lmin:lmax] |
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| 164 | |
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| 165 | if verbose: log.critical('cropping') |
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| 166 | |
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| 167 | zname = 'ELEVATION' |
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| 168 | |
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| 169 | amplitudes = file_h.variables['HA'][jmin:jmax, kmin:kmax, lmin:lmax] |
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| 170 | uspeed = file_u.variables['UA'][jmin:jmax, kmin:kmax, lmin:lmax] #Lon |
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| 171 | vspeed = file_v.variables['VA'][jmin:jmax, kmin:kmax, lmin:lmax] #Lat |
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| 172 | elevations = file_e.variables[zname][kmin:kmax, lmin:lmax] |
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| 173 | |
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| 174 | # Get missing values |
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| 175 | nan_ha = file_h.variables['HA'].missing_value[0] |
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| 176 | nan_ua = file_u.variables['UA'].missing_value[0] |
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| 177 | nan_va = file_v.variables['VA'].missing_value[0] |
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| 178 | if hasattr(file_e.variables[zname],'missing_value'): |
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| 179 | nan_e = file_e.variables[zname].missing_value[0] |
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| 180 | else: |
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| 181 | nan_e = None |
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| 182 | |
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| 183 | # Cleanup |
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| 184 | missing = (amplitudes == nan_ha) |
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| 185 | if num.sometrue (missing): |
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| 186 | if fail_on_NaN: |
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| 187 | msg = 'NetCDFFile %s contains missing values' \ |
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| 188 | % basename_in + '_ha.nc' |
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| 189 | raise DataMissingValuesError, msg |
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| 190 | else: |
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| 191 | amplitudes = amplitudes*(missing==0) + missing*NaN_filler |
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| 192 | |
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| 193 | missing = (uspeed == nan_ua) |
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| 194 | if num.sometrue (missing): |
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| 195 | if fail_on_NaN: |
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| 196 | msg = 'NetCDFFile %s contains missing values' \ |
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| 197 | % basename_in + '_ua.nc' |
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| 198 | raise DataMissingValuesError, msg |
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| 199 | else: |
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| 200 | uspeed = uspeed*(missing==0) + missing*NaN_filler |
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| 201 | |
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| 202 | missing = (vspeed == nan_va) |
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| 203 | if num.sometrue (missing): |
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| 204 | if fail_on_NaN: |
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| 205 | msg = 'NetCDFFile %s contains missing values' \ |
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| 206 | % basename_in + '_va.nc' |
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| 207 | raise DataMissingValuesError, msg |
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| 208 | else: |
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| 209 | vspeed = vspeed*(missing==0) + missing*NaN_filler |
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| 210 | |
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| 211 | missing = (elevations == nan_e) |
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| 212 | if num.sometrue (missing): |
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| 213 | if fail_on_NaN: |
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| 214 | msg = 'NetCDFFile %s contains missing values' \ |
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| 215 | % basename_in + '_e.nc' |
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| 216 | raise DataMissingValuesError, msg |
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| 217 | else: |
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| 218 | elevations = elevations*(missing==0) + missing*NaN_filler |
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| 219 | |
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| 220 | number_of_times = times.shape[0] |
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| 221 | number_of_latitudes = latitudes.shape[0] |
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| 222 | number_of_longitudes = longitudes.shape[0] |
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| 223 | |
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| 224 | assert amplitudes.shape[0] == number_of_times |
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| 225 | assert amplitudes.shape[1] == number_of_latitudes |
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| 226 | assert amplitudes.shape[2] == number_of_longitudes |
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| 227 | |
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| 228 | if verbose: |
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| 229 | _show_stats((latitudes, longitudes), times, amplitudes, \ |
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| 230 | (uspeed, vspeed), elevations) |
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| 231 | |
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| 232 | # print number_of_latitudes, number_of_longitudes |
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| 233 | number_of_points = number_of_latitudes * number_of_longitudes |
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| 234 | number_of_volumes = (number_of_latitudes-1) * (number_of_longitudes-1) * 2 |
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| 235 | |
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| 236 | file_h.close() |
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| 237 | file_u.close() |
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| 238 | file_v.close() |
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| 239 | file_e.close() |
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| 240 | |
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| 241 | # NetCDF file definition |
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| 242 | outfile = NetCDFFile(swwname, netcdf_mode_w) |
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| 243 | |
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| 244 | description = 'Converted from Ferret files: %s, %s, %s, %s' \ |
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| 245 | % (basename_in + '_ha.nc', |
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| 246 | basename_in + '_ua.nc', |
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| 247 | basename_in + '_va.nc', |
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| 248 | basename_in + '_e.nc') |
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| 249 | |
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| 250 | # Create new file |
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| 251 | starttime = times[0] |
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| 252 | |
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| 253 | sww = Write_sww(['elevation'], ['stage', 'xmomentum', 'ymomentum']) |
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| 254 | sww.store_header(outfile, times, number_of_volumes, |
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| 255 | number_of_points, description=description, |
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| 256 | verbose=verbose, sww_precision=netcdf_float) |
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| 257 | |
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| 258 | # Store |
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| 259 | from anuga.coordinate_transforms.redfearn import redfearn |
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| 260 | x = num.zeros(number_of_points, num.float) #Easting |
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| 261 | y = num.zeros(number_of_points, num.float) #Northing |
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| 262 | |
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| 263 | if verbose: |
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| 264 | log.critical('Making triangular grid') |
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| 265 | |
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| 266 | # Check zone boundaries |
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| 267 | refzone, _, _ = redfearn(latitudes[0], longitudes[0]) |
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| 268 | |
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| 269 | vertices = {} |
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| 270 | i = 0 |
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| 271 | for k, lat in enumerate(latitudes): # Y direction |
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| 272 | for l, lon in enumerate(longitudes): # X direction |
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| 273 | vertices[l, k] = i |
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| 274 | |
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| 275 | _, easting, northing = redfearn(lat, lon) |
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| 276 | |
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| 277 | #msg = 'Zone boundary crossed at longitude =', lon |
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| 278 | #assert zone == refzone, msg |
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| 279 | #print '%7.2f %7.2f %8.2f %8.2f' %(lon, lat, easting, northing) |
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| 280 | x[i] = easting |
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| 281 | y[i] = northing |
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| 282 | i += 1 |
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| 283 | |
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| 284 | #Construct 2 triangles per 'rectangular' element |
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| 285 | volumes = [] |
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| 286 | for l in range(number_of_longitudes-1): # X direction |
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| 287 | for k in range(number_of_latitudes-1): # Y direction |
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| 288 | v1 = vertices[l, k+1] |
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| 289 | v2 = vertices[l, k] |
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| 290 | v3 = vertices[l+1, k+1] |
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| 291 | v4 = vertices[l+1, k] |
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| 292 | |
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| 293 | volumes.append([v1, v2, v3]) #Upper element |
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| 294 | volumes.append([v4, v3, v2]) #Lower element |
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| 295 | |
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| 296 | volumes = num.array(volumes, num.int) #array default# |
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| 297 | |
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| 298 | if origin is None: |
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| 299 | origin = Geo_reference(refzone, min(x), min(y)) |
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| 300 | geo_ref = write_NetCDF_georeference(origin, outfile) |
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| 301 | |
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| 302 | if elevation is not None: |
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| 303 | z = elevation |
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| 304 | else: |
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| 305 | if inverted_bathymetry: |
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| 306 | z = -1 * elevations |
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| 307 | else: |
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| 308 | z = elevations |
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| 309 | #FIXME: z should be obtained from MOST and passed in here |
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| 310 | |
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| 311 | #FIXME use the Write_sww instance(sww) to write this info |
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| 312 | z = num.resize(z, outfile.variables['elevation'][:].shape) |
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| 313 | outfile.variables['x'][:] = x - geo_ref.get_xllcorner() |
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| 314 | outfile.variables['y'][:] = y - geo_ref.get_yllcorner() |
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| 315 | #outfile.variables['z'][:] = z #FIXME HACK for bacwards compat. |
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| 316 | outfile.variables['elevation'][:] = z |
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| 317 | outfile.variables['volumes'][:] = volumes.astype(num.int32) #For Opteron 64 |
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| 318 | |
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| 319 | #Time stepping |
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| 320 | stage = outfile.variables['stage'] |
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| 321 | xmomentum = outfile.variables['xmomentum'] |
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| 322 | ymomentum = outfile.variables['ymomentum'] |
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| 323 | |
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| 324 | if verbose: |
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| 325 | log.critical('Converting quantities') |
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| 326 | |
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| 327 | n = len(times) |
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| 328 | for j in range(n): |
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| 329 | if verbose and j % ((n+10)/10) == 0: |
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| 330 | log.critical(' Doing %d of %d' % (j, n)) |
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| 331 | |
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| 332 | i = 0 |
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| 333 | for k in range(number_of_latitudes): # Y direction |
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| 334 | for l in range(number_of_longitudes): # X direction |
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| 335 | w = zscale * amplitudes[j, k, l] / 100 + mean_stage |
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| 336 | stage[j, i] = w |
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| 337 | h = w - z[i] |
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| 338 | xmomentum[j, i] = uspeed[j, k, l]/100*h |
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| 339 | ymomentum[j, i] = vspeed[j, k, l]/100*h |
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| 340 | i += 1 |
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| 341 | |
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| 342 | #outfile.close() |
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| 343 | |
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| 344 | #FIXME: Refactor using code from file_function.statistics |
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| 345 | #Something like print swwstats(swwname) |
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| 346 | if verbose: |
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| 347 | time_info = times, starttime, mint, maxt |
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| 348 | _show_sww_stats(outfile, swwname, geo_ref, time_info) |
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| 349 | |
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| 350 | outfile.close() |
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| 351 | |
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| 352 | |
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| 353 | def _show_stats(latlong, times, amplitudes, speeds, elevations): |
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| 354 | """ Print the statistics nicely to the log file """ |
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| 355 | |
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| 356 | latitudes, longitudes = latlong |
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| 357 | uspeed, vspeed = speeds |
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| 358 | |
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| 359 | log.critical('------------------------------------------------') |
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| 360 | log.critical('Statistics:') |
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| 361 | log.critical(' Extent (lat/lon):') |
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| 362 | log.critical(' lat in [%f, %f], len(lat) == %d' |
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| 363 | % (num.min(latitudes), num.max(latitudes), |
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| 364 | len(latitudes.flat))) |
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| 365 | log.critical(' lon in [%f, %f], len(lon) == %d' |
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| 366 | % (num.min(longitudes), num.max(longitudes), |
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| 367 | len(longitudes.flat))) |
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| 368 | log.critical(' t in [%f, %f], len(t) == %d' |
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| 369 | % (num.min(times), num.max(times), len(times.flat))) |
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| 370 | |
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| 371 | name = 'Amplitudes (ha) [cm]' |
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| 372 | log.critical(' %s in [%f, %f]' |
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| 373 | % (name, num.min(amplitudes), num.max(amplitudes))) |
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| 374 | |
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| 375 | name = 'Speeds (ua) [cm/s]' |
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| 376 | log.critical(' %s in [%f, %f]' |
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| 377 | % (name, num.min(uspeed), num.max(uspeed))) |
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| 378 | |
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| 379 | name = 'Speeds (va) [cm/s]' |
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| 380 | log.critical(' %s in [%f, %f]' |
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| 381 | % (name, num.min(vspeed), num.max(vspeed))) |
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| 382 | |
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| 383 | name = 'Elevations (e) [m]' |
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| 384 | log.critical(' %s in [%f, %f]' |
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| 385 | % (name, num.min(elevations), num.max(elevations))) |
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| 386 | |
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| 387 | |
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| 388 | |
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| 389 | def _show_sww_stats(outfile, swwname, geo_ref, time_info): |
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| 390 | """ Log SWW output stats. """ |
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| 391 | times, starttime, mint, maxt = time_info |
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| 392 | x = outfile.variables['x'][:] |
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| 393 | y = outfile.variables['y'][:] |
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| 394 | log.critical('------------------------------------------------') |
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| 395 | log.critical('Statistics of output file:') |
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| 396 | log.critical(' Name: %s' %swwname) |
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| 397 | log.critical(' Reference:') |
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| 398 | log.critical(' Lower left corner: [%f, %f]' |
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| 399 | % (geo_ref.get_xllcorner(), geo_ref.get_yllcorner())) |
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| 400 | log.critical(' Start time: %f' %starttime) |
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| 401 | log.critical(' Min time: %f' %mint) |
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| 402 | log.critical(' Max time: %f' %maxt) |
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| 403 | log.critical(' Extent:') |
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| 404 | log.critical(' x [m] in [%f, %f], len(x) == %d' |
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| 405 | % (num.min(x), num.max(x), len(x.flat))) |
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| 406 | log.critical(' y [m] in [%f, %f], len(y) == %d' |
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| 407 | % (num.min(y), num.max(y), len(y.flat))) |
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| 408 | log.critical(' t [s] in [%f, %f], len(t) == %d' |
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| 409 | % (min(times), max(times), len(times))) |
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| 410 | log.critical(' Quantities [SI units]:') |
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| 411 | for name in ['stage', 'xmomentum', 'ymomentum', 'elevation']: |
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| 412 | q = outfile.variables[name][:] # .flatten() |
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| 413 | log.critical(' %s in [%f, %f]' % \ |
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| 414 | (name, num.min(q), num.max(q))) |
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| 415 | |
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| 416 | |
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| 417 | def _assert_lat_long(minlat, maxlat, minlon, maxlon): |
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| 418 | """Check latitudes and longitudes for validity.""" |
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| 419 | |
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| 420 | msg = 'Must use latitudes and longitudes for minlat, maxlon etc' |
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| 421 | |
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| 422 | if minlat != None: |
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| 423 | assert -90 < minlat < 90 , msg |
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| 424 | if maxlat != None: |
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| 425 | assert -90 < maxlat < 90 , msg |
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| 426 | if minlat != None: |
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| 427 | assert maxlat > minlat |
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| 428 | if minlon != None: |
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| 429 | assert -180 < minlon < 180 , msg |
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| 430 | if maxlon != None: |
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| 431 | assert -180 < maxlon < 180 , msg |
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| 432 | if minlon != None: |
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| 433 | assert maxlon > minlon |
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