pythonarraysnumpyfortranflopy

How to convert a unformatted fortran file(modflow output ) to numpy array


I have a modflow output file with extension hds. Google drive link fora file. Its a unformatted fortran file. I need to convert it to numpy array, I have tried :

floattype = 'f4'
a = np.fromfile("lake_example.hds", np.dtype([('kstp','i4'),('kper','i4'),('pertim',floattype),('totim',floattype),('text','a16'),('ncol','i4'),('nrow','i4'),('ilay','i4')]))
print a
print a.shape

github link for code: https://github.com/Kirubaharan/hydrology/blob/master/gw_tut.py

I am a trying a tutorial from this link. Since I am on linux I cannot use flopy's method to get the output array from the file. So I am trying to use np.fromfile, But I am having problem in getting the output.

My output is like this now:

[ (44, 1, 1.401298464324817e-45, 1.0, '\x00\x00\x80?            ', 1145128264, 11, 11)
 (1, 44, 6.782284567332115e-43, 100.0, '\x00\x00\xc8B\x00\x00\xc8B\x00\x00\xc8B\x00\x00\xc8B', 1120403456, 1120403456, 1120403456)
 (1120403456, 1120403456, 100.0, 100.0, '\x0c\xbf\xc7B\x18~\xc7B=@\xc7B\xce\x0e\xc7B', 1120336356, 1120341710, 1120354365)
 (1120370200, 1120386828, 100.0, 100.0, '\x18~\xc7B\x0e\xf9\xc6B\xf0s\xc6B\xaa\x00\xc6B', 1120258308, 1120272554, 1120302064)
 (1120336142, 1120370200, 100.0, 100.0, '=@\xc7B\xf0s\xc6B\xf8\x94\xc5B\x91\xb3\xc4B', 1120149448, 1120187281, 1120244984)
 (1120302064, 1120354365, 100.0, 100.0, '\xce\x0e\xc7B\xaa\x00\xc6B\x91\xb3\xc4B\xac\xff\xc2B', 1119940155, 1120075692, 1120187281)
 (1120272554, 1120341710, 100.0, 100.0, '\xe4\xf9\xc6B\x04\xc9\xc5B\xc8\x1f\xc4B;\xee\xc0B', 1119092736, 1119940155, 1120149448)
 (1120258308, 1120336356, 100.0, 100.0, '\xce\x0e\xc7B\xaa\x00\xc6B\x91\xb3\xc4B\xac\xff\xc2B', 1119940155, 1120075692, 1120187281)
 (1120272554, 1120341710, 100.0, 100.0, '=@\xc7B\xf0s\xc6B\xf8\x94\xc5B\x91\xb3\xc4B', 1120149448, 1120187281, 1120244984)
 (1120302064, 1120354365, 100.0, 100.0, '\x18~\xc7B\x0e\xf9\xc6B\xf0s\xc6B\xaa\x00\xc6B', 1120258308, 1120272554, 1120302064)
 (1120336142, 1120370200, 100.0, 100.0, '\x0c\xbf\xc7B\x18~\xc7B=@\xc7B\xce\x0e\xc7B', 1120336356, 1120341710, 1120354365)

I have included only few lines of output.

For header information you can refer their source code:https://github.com/modflowpy/flopy/blob/master/flopy/utils/binaryfile.py#L30g


Solution

  • Your code doesn't match the structure of your data file:

    00000000  2c 00 00 00 01 00 00 00  01 00 00 00 00 00 80 3f  |,..............?|
    00000010  00 00 80 3f 20 20 20 20  20 20 20 20 20 20 20 20  |...?            |
    00000020  48 45 41 44 0b 00 00 00  0b 00 00 00 01 00 00 00  |HEAD............|
    00000030  2c 00 00 00 e4 01 00 00  00 00 c8 42 00 00 c8 42  |,..........B...B|
    00000040  00 00 c8 42 00 00 c8 42  00 00 c8 42 00 00 c8 42  |...B...B...B...B|
    00000050  00 00 c8 42 00 00 c8 42  00 00 c8 42 00 00 c8 42  |...B...B...B...B|
    

    Each data block has it's own 56 bytes header consisting of: 3 integers (i4), 2 floating point values (f4), 16 characters, and again 5 integers (i4):

    44 1 1
    1.0 1.0
                HEAD
    11 11 1 44 484
    

    Then the data block follows (11x11 floating point values):

    100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
    100.0 99.87313842773438 99.74627685546875 99.6254653930664 ...
    

    I'm not sure whether this could be imported directly into a numpy array.

    The following sample code will loop over the whole file and extracts header and data for each block:

    #!/usr/bin/python
    
    import struct
    import numpy as np
    
    infile = open("lake_example.hds","rb")
    
    blockdata = []
    
    while infile.read(1):
        infile.seek(-1,1)
        data = infile.read(56)
        n = struct.unpack('<3i4', data[0:12])
    #    print n[0], n[1], n[2]
        n = struct.unpack('<2f4', data[12:20])
    #    print n[0], n[1]
    #    print data[20:36]
        n = struct.unpack('<5i4', data[36:56])
    #    print n[0], n[1], n[2], n[3], n[4]
        ncol = n[0]
        nrow = n[1]
        a = np.fromfile(infile,dtype='f4',count=ncol*nrow).reshape((ncol,nrow))
        blockdata.append(a)
        data = infile.read(4)
        n = struct.unpack('<i4', data)
    #    print n[0]
    
    for block in blockdata:
        print block
    

    Most likely you also will need some of the information from the block headers (see print statements).