| 1 | """ |
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| 2 | Merge a list of .sww files together into a single file. |
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| 3 | """ |
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| 4 | |
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| 5 | import numpy as num |
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| 6 | from anuga.utilities.numerical_tools import ensure_numeric |
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| 7 | |
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| 8 | from Scientific.IO.NetCDF import NetCDFFile |
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| 9 | from anuga.config import netcdf_mode_r, netcdf_mode_w, \ |
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| 10 | netcdf_mode_a, netcdf_float |
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| 11 | from anuga.file.sww import SWW_file, Write_sww |
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| 12 | |
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| 13 | |
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| 14 | def sww_merge(swwfiles, output, verbose = False): |
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| 15 | """ |
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| 16 | Merge a list of sww files into a single file. |
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| 17 | |
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| 18 | May be useful for parallel runs. Note that colinear points and |
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| 19 | edges are not merged: there will essentially be multiple meshes within |
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| 20 | the one sww file. |
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| 21 | |
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| 22 | The sww files to be merged must have exactly the same timesteps. Note |
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| 23 | that some advanced information and custom quantities may not be |
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| 24 | exported. |
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| 25 | |
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| 26 | swwfiles is a list of .sww files to merge. |
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| 27 | output is the output filename, including .sww extension. |
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| 28 | verbose True to log output information |
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| 29 | """ |
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| 30 | |
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| 31 | static_quantities = ['elevation'] |
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| 32 | dynamic_quantities = ['stage', 'xmomentum', 'ymomentum'] |
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| 33 | |
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| 34 | first_file = True |
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| 35 | tri_offset = 0 |
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| 36 | for filename in swwfiles: |
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| 37 | if verbose: |
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| 38 | print 'Reading file ', filename, ':' |
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| 39 | |
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| 40 | fid = NetCDFFile(filename, netcdf_mode_r) |
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| 41 | tris = fid.variables['volumes'][:] |
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| 42 | |
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| 43 | if first_file: |
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| 44 | times = fid.variables['time'][:] |
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| 45 | x = [] |
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| 46 | y = [] |
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| 47 | out_tris = list(tris) |
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| 48 | out_s_quantities = {} |
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| 49 | out_d_quantities = {} |
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| 50 | |
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| 51 | for quantity in static_quantities: |
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| 52 | out_s_quantities[quantity] = [] |
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| 53 | |
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| 54 | # Quantities are stored as a 2D array of timesteps x data. |
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| 55 | for quantity in dynamic_quantities: |
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| 56 | out_d_quantities[quantity] = [ [] for _ in range(len(times))] |
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| 57 | |
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| 58 | description = 'merged:' + getattr(fid, 'description') |
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| 59 | first_file = False |
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| 60 | else: |
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| 61 | for tri in tris: |
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| 62 | # Advance new tri indices to point at newly appended points. |
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| 63 | verts = [vertex+tri_offset for vertex in tri] |
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| 64 | out_tris.append(verts) |
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| 65 | |
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| 66 | num_pts = fid.dimensions['number_of_points'] |
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| 67 | tri_offset += num_pts |
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| 68 | |
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| 69 | if verbose: |
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| 70 | print ' new triangle index offset is ', tri_offset |
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| 71 | |
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| 72 | x.extend(list(fid.variables['x'][:])) |
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| 73 | y.extend(list(fid.variables['y'][:])) |
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| 74 | |
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| 75 | # Grow the list of static quantities associated with the x,y points |
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| 76 | for quantity in static_quantities: |
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| 77 | out_s_quantities[quantity].extend(fid.variables[quantity][:]) |
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| 78 | |
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| 79 | #Collate all dynamic quantities according to their timestep |
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| 80 | for quantity in dynamic_quantities: |
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| 81 | time_chunks = fid.variables[quantity][:] |
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| 82 | for i, time_chunk in enumerate(time_chunks): |
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| 83 | out_d_quantities[quantity][i].extend(time_chunk) |
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| 84 | |
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| 85 | # Mash all points into a single big list |
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| 86 | points = [[xx, yy] for xx, yy in zip(x, y)] |
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| 87 | fid.close() |
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| 88 | |
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| 89 | # Write out the SWW file |
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| 90 | fido = NetCDFFile(output, netcdf_mode_w) |
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| 91 | sww = Write_sww(static_quantities, dynamic_quantities) |
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| 92 | sww.store_header(fido, times, |
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| 93 | len(out_tris), |
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| 94 | len(points), |
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| 95 | description=description, |
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| 96 | sww_precision=netcdf_float) |
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| 97 | |
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| 98 | |
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| 99 | sww.store_triangulation(fido, points, out_tris) |
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| 100 | |
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| 101 | sww.store_static_quantities(fido, verbose=verbose, **out_s_quantities) |
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| 102 | |
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| 103 | # Write out all the dynamic quantities for each timestep |
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| 104 | for q in dynamic_quantities: |
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| 105 | q_values = out_d_quantities[q] |
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| 106 | for i, time_slice in enumerate(q_values): |
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| 107 | fido.variables[q][i] = num.array(time_slice, netcdf_float) |
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| 108 | |
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| 109 | # This updates the _range values |
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| 110 | q_range = fido.variables[q + Write_sww.RANGE][:] |
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| 111 | q_values_min = num.min(q_values) |
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| 112 | if q_values_min < q_range[0]: |
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| 113 | fido.variables[q + Write_sww.RANGE][0] = q_values_min |
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| 114 | q_values_max = num.max(q_values) |
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| 115 | if q_values_max > q_range[1]: |
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| 116 | fido.variables[q + Write_sww.RANGE][1] = q_values_max |
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| 117 | |
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| 118 | |
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| 119 | fido.close() |
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| 120 | |
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| 121 | |
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