source: anuga_core/source/anuga/shallow_water/benchmark_sww2dem.py @ 5224

"""Least squares smoothing and interpolation.

   measure the speed of least squares.

   ________________________
   General comments
   
   The max_points_per_cell does effect the time spent solving a
   problem.  The best value to use is probably dependent on the number
   of triangles.  Maybe develop a simple imperical algorithm, based on
   test results.
   
   Duncan Gray
   Geoscience Australia, 2004.
"""


import os
import sys
import time
from random import seed, random
import profile , pstats
import tempfile
import gc

from Scientific.IO.NetCDF import NetCDFFile
from Numeric import array, Float

from anuga.fit_interpolate.interpolate import Interpolate
from anuga.fit_interpolate.fit import Fit
from anuga.geospatial_data.geospatial_data import Geospatial_data
from anuga.shallow_water import Domain
from anuga.fit_interpolate.fit import Fit, fit_to_mesh
from anuga.fit_interpolate.interpolate import benchmark_interpolate
from anuga.shallow_water.data_manager import Write_sww, export_grid

def mem_usage():
    '''
    returns the rss.

  RSS  The total amount of physical memory used by  the  task,  in  kilo-
            bytes,  is  shown  here.  For ELF processes used library pages are
            counted here, for a.out processes not.
            
    Only works on nix systems.
    '''
    import string
    p=os.popen('ps uwp %s'%os.getpid()) 
    lines=p.readlines()
    #print "lines", lines
    status=p.close() 
    if status or len(lines)!=2 or sys.platform == 'win32': 
        return None 
    return int(string.split(lines[1])[4]) 





def trial(vert_rows,
          vert_columns,
          output_quantities=['elevation'],
          save=False,
          verbose=False,
          run_profile=False):
    import time
  
    sww_file_name = build_sww(vert_rows, vert_columns, save=save)
        
    #Initial time and memory
    t0 = time.time()
    #m0 = None on windows
    m0 = mem_usage()
    #print "m0", m0

    fileout = export_grid(sww_file_name, quantities=output_quantities)
        
    time_taken_sec = (time.time()-t0)
    m1 = mem_usage()
    #print "m1", m1
    if m0 is None or m1 is None:
        memory_used = None
    else:
        memory_used = (m1 - m0)
    return time_taken_sec, memory_used, m0, m1

def build_sww(vert_rows, vert_columns, save):
    """
    Build an sww file we can read. 
    verts_rows and vert_columns have to be greater that 1
    """
    from anuga.pmesh.mesh import Mesh
    m = Mesh()
    m.build_grid(vert_rows, vert_columns)
    if save is True:
            m.export_mesh_file("aaaa.tsh")
    mesh_dict =  m.Mesh2IOTriangulationDict()
    
    sww_fileName = tempfile.mktemp(".sww" )
    # sww_fileName = "aa.sww" 
    elevation = array(range(len(mesh_dict["vertices"])))
    stage = elevation
    ymomentum = elevation
    xmomentum = elevation
        
    # NetCDF file definition
    fid = NetCDFFile(sww_fileName, 'w')
    sww = Write_sww()
    sww.store_header(fid, 0,
               len(mesh_dict['triangles']),
               len(mesh_dict["vertices"]),sww_precision=Float)
    sww.store_triangulation(fid,
                      mesh_dict["vertices"], mesh_dict['triangles'],
                      elevation)
        
    for time_step in range(10):
        sww.store_quantities(fid, 
                       time=time_step,
                       stage=stage,
                       xmomentum=xmomentum,
                       ymomentum=ymomentum)     
    #Close
    fid.close()
    del mesh_dict
    del Mesh
    return sww_fileName
    
#-------------------------------------------------------------
if __name__ == "__main__":
    delimiter = ','

    ofile = 'lbm_resultsII.csv'
    run_profile = False #True
    size_list = [[4,5],[50,40]]
    #size_list = [[5,4]]

    quantitiy_list = [['elevation'],
                      ['elevation','xmomentum'],
                      ['elevation','xmomentum','ymomentum']]
    
    fd = open(ofile,'a')
    # write the title line
    fd.write("size" + delimiter +
             "num_of_quantities" + delimiter +
             "is_profiling" + delimiter +
             "mem - diff"  + delimiter +
             "mem - initial"  + delimiter +
             "mem - final"  + delimiter +
             "time"  "\n")



    for size in size_list:
        for quantitiy in quantitiy_list:
            #sys.gettotalrefcount()
            #sys.getobjects() 
            gc.collect()
            #print " gc.get_objects() ", gc.get_objects() 
            time, mem, m0, m1 = trial(size[0]
                                        ,size[1]
                                        ,output_quantities=quantitiy
                                        ,run_profile=run_profile
                                        )
            print "time",time
            print "mem", mem
            gc.collect()
            print "mem", mem
            #print "@@@@@@@@@@@@@@@@@@@@@@@@@@@@@",
            #print "gc.get_referrers()", gc.get_referrers()
            #sys.gettotalrefcount() 
            fd.write(str(size[0]*size[1]) + delimiter +
                     str(len(quantitiy)) + delimiter +
                     str(run_profile) + delimiter +
                     str(mem)  + delimiter +
                     str(m0)  + delimiter +
                     str(m1)  + delimiter +
                     str(time) + delimiter + "\n")
    print " gc.get_objects() ", gc.get_objects()
    fd.close()