source: inundation/pyvolution/util.py @ 2908

"""This module contains various auxiliary function used by pyvolution.

It is also a clearing house for functions that may later earn a module
of their own.
"""


import utilities.polygon
from warnings import warn



def file_function(filename,
                  domain = None,
                  quantities = None,
                  interpolation_points = None,
                  verbose = False,
                  use_cache = False):
    """Read time history of spatial data from NetCDF file and return
    a callable object.

    Input variables:
    
    filename - Name of sww or tms file
       
       If the file has extension 'sww' then it is assumed to be spatio-temporal
       or temporal and the callable object will have the form f(t,x,y) or f(t)
       depending on whether the file contains spatial data

       If the file has extension 'tms' then it is assumed to be temporal only
       and the callable object will have the form f(t)

       Either form will return interpolated values based on the input file
       using the underlying interpolation_function.

    domain - Associated domain object   
       If domain is specified, model time (domain.starttime)
       will be checked and possibly modified.
    
       All times are assumed to be in UTC
       
       All spatial information is assumed to be in absolute UTM coordinates.

    quantities - the name of the quantity to be interpolated or a
                 list of quantity names. The resulting function will return
                 a tuple of values - one for each quantity  

    interpolation_points - list of absolute UTM coordinates for points at
    which values are sought
    
    use_cache: True means that caching of intermediate result of
               Interpolation_function is attempted

    
    See Interpolation function for further documentation
    """


    if use_cache is True:
        try:
            from caching import cache
        except:
            msg = 'Caching was requested, but caching module'+\
                  'could not be imported'
            raise msg


        f = cache(_file_function,
                  filename,
                  {'domain': domain,
                   'quantities': quantities,
                   'interpolation_points': interpolation_points,
                   'verbose': verbose},
                  dependencies = [filename],
                  compression = False,
                  verbose = verbose)
        #FIXME (Ole): Pass cache arguments, such as compression, in some sort of
        #structure
        
    else:
        f = _file_function(filename,
                           domain,
                           quantities,
                           interpolation_points,
                           verbose)            

    return f



def _file_function(filename,
                   domain = None,
                   quantities = None,
                   interpolation_points = None,
                   verbose = False):
    """Internal function
    
    See file_function for documentatiton
    """
    

    #FIXME (OLE): Should check origin of domain against that of file
    #In fact, this is where origin should be converted to that of domain
    #Also, check that file covers domain fully.
    #If we use the suggested Point_set class for interpolation points
    #here it would be easier

    #Take into account:
    #- domain's georef
    #- sww file's georef
    #- interpolation points as absolute UTM coordinates


    assert type(filename) == type(''),\
               'First argument to File_function must be a string'

    try:
        fid = open(filename)
    except Exception, e:
        msg = 'File "%s" could not be opened: Error="%s"'\
                  %(filename, e)
        raise msg

    line = fid.readline()
    fid.close()

    if quantities is None: 
        if domain is not None:
            quantities = domain.conserved_quantities



    if line[:3] == 'CDF':
        return get_netcdf_file_function(filename, domain, quantities,
                                        interpolation_points,
                                        verbose = verbose)
    else:
        raise 'Must be a NetCDF File'



def get_netcdf_file_function(filename,
                             domain=None,
                             quantity_names=None,
                             interpolation_points=None,
                             verbose = False):
    """Read time history of spatial data from NetCDF sww file and
    return a callable object f(t,x,y)
    which will return interpolated values based on the input file.

    If domain is specified, model time (domain.starttime)
    will be checked and possibly modified
    
    All times are assumed to be in UTC

    See Interpolation function for further documetation
    
    """
    
    
    #FIXME: Check that model origin is the same as file's origin
    #(both in UTM coordinates)
    #If not - modify those from file to match domain
    #Take this code from e.g. dem2pts in data_manager.py
    #FIXME: Use geo_reference to read and write xllcorner...
        

    #FIXME: Maybe move caching out to this level rather than at the
    #Interpolation_function level (below)

    import time, calendar, types
    from config import time_format
    from Scientific.IO.NetCDF import NetCDFFile
    from Numeric import array, zeros, Float, alltrue, concatenate, reshape
    from utilities.numerical_tools import ensure_numeric    

    #Open NetCDF file
    if verbose: print 'Reading', filename
    fid = NetCDFFile(filename, 'r')

    if type(quantity_names) == types.StringType:
        quantity_names = [quantity_names]        
    
    if quantity_names is None or len(quantity_names) < 1:
        #If no quantities are specified get quantities from file
        #x, y, time are assumed as the independent variables so
        #they are excluded as potentiol quantities
        quantity_names = []
        for name in fid.variables.keys():
            if name not in ['x', 'y', 'time']:
                quantity_names.append(name)

    if len(quantity_names) < 1:                
        msg = 'ERROR: At least one independent value must be specified'
        raise msg


    if interpolation_points is not None:
        interpolation_points = ensure_numeric(interpolation_points, Float)



    #Now assert that requested quantitites (and the independent ones)
    #are present in file 
    missing = []
    for quantity in ['time'] + quantity_names:
        if not fid.variables.has_key(quantity):
            missing.append(quantity)

    if len(missing) > 0:
        msg = 'Quantities %s could not be found in file %s'\
              %(str(missing), filename)
        fid.close()
        raise msg

    #Decide whether this data has a spatial dimension
    spatial = True
    for quantity in ['x', 'y']:
        if not fid.variables.has_key(quantity):
            spatial = False

    if filename[-3:] == 'tms' and spatial is True:
        msg = 'Files of type tms must not contain spatial information'
        raise msg

    if filename[-3:] == 'sww' and spatial is False:
        msg = 'Files of type sww must contain spatial information'        
        raise msg        

    #Get first timestep
    try:
        starttime = fid.starttime[0]
    except ValueError:
        msg = 'Could not read starttime from file %s' %filename
        raise msg

    #Get variables
    if verbose: print 'Get variables'    
    time = fid.variables['time'][:]    

    if spatial:
        #Get origin
        xllcorner = fid.xllcorner[0]
        yllcorner = fid.yllcorner[0]
        zone = fid.zone[0]        

        x = fid.variables['x'][:]
        y = fid.variables['y'][:]
        triangles = fid.variables['volumes'][:]

        x = reshape(x, (len(x),1))
        y = reshape(y, (len(y),1))
        vertex_coordinates = concatenate((x,y), axis=1) #m x 2 array

        if interpolation_points is not None:
            #Adjust for georef
            interpolation_points[:,0] -= xllcorner
            interpolation_points[:,1] -= yllcorner        
        



    if domain is not None:
        #Update domain.startime if it is *earlier* than starttime
        if starttime > domain.starttime:
            msg = 'WARNING: Start time as specified in domain (%f)'\
                  %domain.starttime
            msg += ' is earlier than the starttime of file %s (%f).'\
                     %(filename, starttime)
            msg += ' Modifying domain starttime accordingly.'
            
            if verbose: print msg
            domain.starttime = starttime #Modifying model time
            if verbose: print 'Domain starttime is now set to %f'\
               %domain.starttime


        #If domain.startime is *later* than starttime,
        #move time back - relative to domain's time
        if domain.starttime > starttime:
            time = time - domain.starttime + starttime

        #FIXME Use method in geo to reconcile
        #if spatial:
        #assert domain.geo_reference.xllcorner == xllcorner
        #assert domain.geo_reference.yllcorner == yllcorner
        #assert domain.geo_reference.zone == zone        
        
    if verbose:
        print 'File_function data obtained from: %s' %filename
        print '  References:'
        #print '    Datum ....' #FIXME
        if spatial:
            print '    Lower left corner: [%f, %f]'\
                  %(xllcorner, yllcorner)
        print '    Start time:   %f' %starttime                
        
    
    #Produce values for desired data points at
    #each timestep

    quantities = {}
    for i, name in enumerate(quantity_names):
        quantities[name] = fid.variables[name][:]
    fid.close()
    

    #from least_squares import Interpolation_function
    from fit_interpolate.interpolate import Interpolation_function

    if not spatial:
        vertex_coordinates = triangles = interpolation_points = None         


    return Interpolation_function(time,
                                  quantities,
                                  quantity_names,
                                  vertex_coordinates,
                                  triangles,
                                  interpolation_points,
                                  verbose = verbose)





def multiple_replace(text, dictionary):
    """Multiple replace of words in text

    text:       String to be modified
    dictionary: Mapping of words that are to be substituted

    Python Cookbook 3.14 page 88 and page 90
    """

    import re
    
    #Create a regular expression from all of the dictionary keys
    #matching only entire words
    regex = re.compile(r'\b'+ \
                       r'\b|\b'.join(map(re.escape, dictionary.keys()))+ \
                       r'\b' )

    #For each match, lookup the corresponding value in the dictionary
    return regex.sub(lambda match: dictionary[match.group(0)], text)




def apply_expression_to_dictionary(expression, dictionary):#dictionary):
    """Apply arbitrary expression to values of dictionary

    Given an expression in terms of the keys, replace key by the
    corresponding values and evaluate.
   

    expression: Arbitrary, e.g. arithmetric, expression relating keys
                from dictionary. 

    dictionary: Mapping between symbols in expression and objects that
                will be evaluated by expression.
                Values in dictionary must support operators given in
                expression e.g. by overloading

    due to a limitation with Numeric, this can not evaluate 0/0
    In general, the user can fix by adding 1e-30 to the numerator.
    SciPy core can handle this situation.
    """

    import types
    import re

    assert isinstance(expression, basestring)
    assert type(dictionary) == types.DictType

    #Convert dictionary values to textual representations suitable for eval
    D = {}
    for key in dictionary:
        D[key] = 'dictionary["%s"]' %key

    #Perform substitution of variables    
    expression = multiple_replace(expression, D)

    #Evaluate and return
    try:
        return eval(expression)
    except NameError, e:
        msg = 'Expression "%s" could not be evaluated: %s' %(expression, e)
        raise NameError, msg
    except ValueError, e:
        msg = 'Expression "%s" could not be evaluated: %s' %(expression, e)
        raise ValueError, msg
    



####################################
####OBSOLETE STUFF


def angle(v1, v2):
    """Temporary Interface to new location"""

    import utilities.numerical_tools as NT      
    
    msg = 'angle has moved from util.py.  '
    msg += 'Please use "from utilities.numerical_tools import angle"'
    warn(msg, DeprecationWarning) 

    return NT.angle(v1, v2)
    
def anglediff(v0, v1):
    """Temporary Interface to new location"""

    import utilities.numerical_tools as NT
    
    msg = 'anglediff has moved from util.py.  '
    msg += 'Please use "from utilities.numerical_tools import anglediff"'
    warn(msg, DeprecationWarning) 

    return NT.anglediff(v0, v1)    

    
def mean(x):
    """Temporary Interface to new location"""

    import utilities.numerical_tools as NT    
    
    msg = 'mean has moved from util.py.  '
    msg += 'Please use "from utilities.numerical_tools import mean"'
    warn(msg, DeprecationWarning) 

    return NT.mean(x)    

def point_on_line(*args, **kwargs):
    """Temporary Interface to new location"""

    msg = 'point_on_line has moved from util.py.  '
    msg += 'Please use "from utilities.polygon import point_on_line"'
    warn(msg, DeprecationWarning) 

    return utilities.polygon.point_on_line(*args, **kwargs)     
    
def inside_polygon(*args, **kwargs):
    """Temporary Interface to new location"""

    print 'inside_polygon has moved from util.py.  ',
    print 'Please use "from utilities.polygon import inside_polygon"'

    return utilities.polygon.inside_polygon(*args, **kwargs)    
    
def outside_polygon(*args, **kwargs):
    """Temporary Interface to new location"""

    print 'outside_polygon has moved from util.py.  ',
    print 'Please use "from utilities.polygon import outside_polygon"'

    return utilities.polygon.outside_polygon(*args, **kwargs)    


def separate_points_by_polygon(*args, **kwargs):
    """Temporary Interface to new location"""

    print 'separate_points_by_polygon has moved from util.py.  ',
    print 'Please use "from utilities.polygon import separate_points_by_polygon"'

    return utilities.polygon.separate_points_by_polygon(*args, **kwargs)    



def read_polygon(*args, **kwargs):
    """Temporary Interface to new location"""

    print 'read_polygon has moved from util.py.  ',
    print 'Please use "from utilities.polygon import read_polygon"'

    return utilities.polygon.read_polygon(*args, **kwargs)    


def populate_polygon(*args, **kwargs):
    """Temporary Interface to new location"""

    print 'populate_polygon has moved from util.py.  ',
    print 'Please use "from utilities.polygon import populate_polygon"'

    return utilities.polygon.populate_polygon(*args, **kwargs)    

'''
this simply catches the screen output and files it to a file
'''
from os import sep

class Screen_Catcher:

    def __init__(self, filename):
        self.data = ''
        self.filename = filename

    def write(self, stuff):
        fid = open(self.filename, 'w')
        self.data = self.data + stuff
        fid.write(self.data)
        fid.close()


    
def sww2timeseries(swwfile,
                   gauge_filename,
                   label_id,
                   report = None,
                   plot_quantity = None,
                   time_min = None,
                   time_max = None,
                   title_on = None,
                   verbose = False):
    
    """ Read sww file and plot the time series for the
    prescribed quantities at defined gauge locations and
    prescribed time range.

    Input variables:

    swwfile         - name of sww file
                    - assume that all conserved quantities have been stored
                    
    gauge_filename  - name of file containing gauge data
                        - name, easting, northing
                    - OR (this is not yet done)
                        - structure which can be converted to a Numeric array,
                          such as a geospatial data object
                      
    label_id        - used in generating latex output. It will be part of
                      the directory name of file_loc (typically the timestamp).
                      Helps to differentiate latex files for different simulations
                      for a particular scenario.
                      
    report          - if True, then write figures to report_figures directory in
                      relevant production directory
                    - if False, figures are already stored with sww file
                    - default to False
    
    plot_quantity   - list containing quantities to plot, they must
                      be the name of an existing quantity or one of
                      the following possibilities
                    - possibilities:
                        - stage; 'stage'
                        - depth; 'depth'
                        - velocity; calculated as absolute momentum
                         (pointwise) divided by depth; 'velocity'
                        - bearing; calculated as the angle of the momentum
                          vector (xmomentum, ymomentum) from the North; 'bearing'
                        - absolute momentum; calculated as
                          sqrt(xmomentum^2 + ymomentum^2); 'momentum'
                        - x momentum; 'xmomentum'
                        - y momentum; 'ymomentum'
                    - default will be ['stage', 'velocity', 'bearing']

    time_min         - beginning of user defined time range for plotting purposes
                        - default will be first available time found in swwfile
                        
    time_max         - end of user defined time range for plotting purposes
                        - default will be last available time found in swwfile
                        
    title_on        - if True, export standard graphics with title
                    - if False, export standard graphics without title


                      
    Output:
    
    - time series data stored in .csv for later use if required.
      Name = gauges_timeseries followed by gauge name 
    - latex file will be generated in same directory as where script is
      run (usually production scenario directory.
      Name = latexoutputlabel_id.tex

    Other important information:
    
    It is assumed that the used has stored all the conserved quantities
    and elevation during the scenario run, i.e.
    ['stage', 'elevation', 'xmomentum', 'ymomentum']
    If this has not occurred then sww2timeseries will not work.
                      
    """

    
    k = _sww2timeseries(swwfile,
                        gauge_filename,
                        label_id,
                        report,
                        plot_quantity,
                        time_min,
                        time_max,
                        title_on,
                        verbose)

    return k

def _sww2timeseries(swwfile,
                    gauge_filename,
                    label_id,
                    report = None,
                    plot_quantity = None,
                    time_min = None,
                    time_max = None,
                    title_on = None,
                    verbose = False):   

    assert type(swwfile) == type(''),\
               'The sww filename must be a string'

    try:
        fid = open(swwfile)
    except Exception, e:
        msg = 'File "%s" could not be opened: Error="%s"'\
                  %(swwfile, e)
        raise msg

    index = swwfile.rfind(sep)
    file_loc = swwfile[:index+1]
        
    assert type(gauge_filename) == type(''),\
               'Gauge filename must be a string'
    
    try:
        fid = open(gauge_filename)
    except Exception, e:
        msg = 'File "%s" could not be opened: Error="%s"'\
                  %(gauge_filename, e)
        raise msg

    if report is None:
        report = False
        
    assert type(plot_quantity) == list,\
               'plot_quantity must be a list'
    
    if plot_quantity is None:
        plot_quantity = ['depth', 'velocity', 'bearing']
    else:
        check_list(plot_quantity)

    if title_on is None:
        title_on = True
     
    assert type(label_id) == type(''),\
               'label_id to sww2timeseries must be a string'
    
    if verbose: print '\n Gauges obtained from: %s \n' %gauge_filename
    gauges, locations = get_gauges_from_file(gauge_filename)

    sww_quantity = ['stage', 'elevation', 'xmomentum', 'ymomentum']

    f = file_function(swwfile,
                      quantities = sww_quantity,
                      interpolation_points = gauges,
                      verbose = True,
                      use_cache = True)

    T = f.get_time()

    if max(f.quantities['xmomentum']) > 1.e10:
        msg = 'Not all conserved quantities available from sww file. \n sww2timeseries requires all conserved quantities stored in sww file'
        raise Exception, msg
        
    if time_min is None:
        time_min = min(T)
    else:
        if time_min < min(T):
            msg = 'Minimum time entered not correct - please try again'
            raise Exception, msg

    if time_max is None:
        time_max = max(T)
    else:
        if time_max > max(T):
            msg = 'Maximum time entered not correct - please try again'
            raise Exception, msg

    if verbose: print 'Inputs OK - going to generate figures'

    return generate_figures(plot_quantity, file_loc, report,
                            f, gauges, locations,
                            time_min, time_max, title_on, label_id, verbose)
                         

def get_gauges_from_file(filename):
    fid = open(filename)
    lines = fid.readlines()
    fid.close()
    
    gauges = []
    gaugelocation = []
    line1 = lines[0]
    line11 = line1.split(',')
    for i in range(len(line11)):
        if line11[i].strip('\n').strip(' ') == 'Easting': east_index = i
        if line11[i].strip('\n').strip(' ') == 'Northing': north_index = i
        if line11[i].strip('\n').strip(' ') == 'Name': name_index = i
    
    for line in lines[1:]:
        fields = line.split(',')
        gauges.append([float(fields[east_index]), float(fields[north_index])])
        loc = fields[name_index]
        gaugelocation.append(loc.strip('\n'))
    
    return gauges, gaugelocation

def check_list(quantity):

    all_quantity = ['stage', 'depth', 'momentum', 'xmomentum',
                    'ymomentum', 'velocity', 'bearing', 'elevation']

    p = list(set(quantity).difference(set(all_quantity)))
    if len(p) <> 0:
        msg = 'Quantities %s do not exist - please try again' %p
        raise Exception, msg
        
    return 

def calc_bearing(uh, vh):

    from math import atan, degrees
    
    angle = degrees(atan(vh/(uh+1.e-15)))
    if (0 < angle < 90.0):
        if vh > 0:
            bearing = 90.0 - abs(angle)
        if vh < 0:
            bearing = 270.0 - abs(angle)
    if (-90 < angle < 0):
        if vh < 0:
            bearing = 90.0 - abs(angle)
        if vh > 0:
            bearing = 270.0 - abs(angle)
    if angle == 0: bearing = 0.0
            
    return bearing

def generate_figures(plot_quantity, file_loc, report, f, gauges,
                     locations, time_min, time_max, title_on, label_id, verbose):

    from math import sqrt, atan, degrees
    from Numeric import ones
    from os import sep, altsep, getcwd, mkdir, access, F_OK, environ
    from pylab import ion, hold, plot, axis, figure, legend, savefig, xlabel, ylabel, title, close

    filename = file_loc.split(sep)
        
    if report == True:
        label_id1 = label_id.replace(sep,'')
        label_id2 = label_id1.replace('_','')
        texfile = 'latexoutput%s' %(label_id2)
        texfilename = texfile + '.tex' 
        if verbose: print '\n Latex output printed to %s \n' %texfilename

        fid = open(texfilename, 'w')
        s = '\\begin{center} \n \\begin{tabular}{|l|l|l|}\hline \n \\bf{Gauge Name} & \\bf{Easting} & \\bf{Northing} \\\\ \hline \n'
        fid.write(s)
        gauges1 = gauges
        for name, gauges1 in zip(locations, gauges1):
            east = gauges1[0]
            north = gauges1[1]
            s = '%s & %.2f & %.2f \\\\ \hline \n' %(name, east, north)
            fid.write(s)

        s = '\\end{tabular} \n \\end{center} \n \n'
        fid.write(s)
    else:
        texfile = ''
    
    ##### loop over each gauge #####
    for k, g in enumerate(gauges):
        if verbose: print 'Gauge %d of %d' %(k, len(gauges))
        model_time = []
        stages = []
        elevations = []
        momenta = []
        xmom = []
        ymom = []
        velocity = []
        bearings = []
        depths = []
        max_depth = 0
        max_momentum = 0
        max_velocity = 0      
        
        #### generate quantities #######
        for i, t in enumerate(f.get_time()): 

            if time_min <= t <= time_max:

                w = f(t, point_id = k)[0]
                z = f(t, point_id = k)[1]
                uh = f(t, point_id = k)[2]
                vh = f(t, point_id = k)[3]
                gaugeloc = locations[k]
                depth = w-z
                
                m = sqrt(uh*uh + vh*vh)   
                vel = m / (depth + 1.e-30) 
                bearing = calc_bearing(uh, vh)

                model_time.append(t)        
                stages.append(w)
                elevations.append(z)
                xmom.append(uh)
                ymom.append(vh)
                momenta.append(m)
                velocity.append(vel)
                bearings.append(bearing)
                depths.append(depth)

                if depth > max_depth: max_depth = w-z
                if m > max_momentum: max_momentum = m
                if vel > max_velocity: max_velocity = vel

        #### finished generating quantities #####
                
        #### generate figures ###
        ion()
        hold(False)

        for i in range(len(plot_quantity)):
            which_quantity = plot_quantity[i]
            figure(i+1, frameon = False)
            if which_quantity == 'depth':
                plot(model_time, depths, '-')
                units = 'm'
            if which_quantity == 'stage':
                plot(model_time, stages, '-')
                units = 'm'
            if which_quantity == 'momentum':
                plot(model_time, momenta, '-')
                units = 'm^2 / sec'
            if which_quantity == 'xmomentum':
                plot(model_time, xmom, '-')
                units = 'm^2 / sec'
            if which_quantity == 'ymomentum':
                plot(model_time, ymom, '-')
                units = 'm^2 / sec'
            if which_quantity == 'velocity':
                plot(model_time, velocity, '-')
                units = 'm / sec'
            if which_quantity == 'bearing':
                due_east = 90.0*ones([len(model_time)])
                due_west = 270.0*ones([len(model_time)])
                plot(model_time, bearings, '-', model_time, due_west, '-.',
                     model_time, due_east, '-.')
                units = 'degrees from North'
                ax = axis([time_min, time_max, 0, 360])
                legend(('Bearing','West','East'))

            xlabel('time (secs)')
            ylabel('%s (%s)' %(which_quantity, units))

            gaugeloc1 = gaugeloc.replace(' ','')
            graphname = '%sgauge%s_%s' %(file_loc, gaugeloc1, which_quantity)

            if report == True:

                figdir = getcwd()+sep+'report_figures'+sep
                if access(figdir,F_OK) == 0 :
                    mkdir (figdir)
                latex_file_loc = figdir.replace(sep,altsep)

                # storing files in production directory
                graphname_latex = '%sgauge%s%s%s' %(latex_file_loc, gaugeloc1, which_quantity, label_id2)
                # giving location in latex output file
                graphname_report = '%sgauge%s%s%s' %('report_figures'+altsep, gaugeloc1, which_quantity, label_id2)
                        
                label = '%s%sgauge%s' %(label_id2, which_quantity, gaugeloc1) 
                caption = 'Time series for %s at %s gauge location' %(which_quantity, gaugeloc)
                s = '\\begin{figure}[hbt] \n \\centerline{\includegraphics[width=100mm, height=75mm]{%s%s}} \n' %(graphname_report, '.png')
                fid.write(s)
                s = '\\caption{%s} \n \label{fig:%s} \n \end{figure} \n \n' %(caption, label)
                fid.write(s)
                savefig(graphname_latex) # save figures in production directory for report generation
            
            if title_on == True:
                title('%s scenario: %s at %s gauge' %(label_id, which_quantity, gaugeloc))

            savefig(graphname) # save figures with sww file

    
        thisfile = file_loc+sep+'gauges_time_series'+'_'+gaugeloc+'.csv'
        fid_out = open(thisfile, 'w')
        s = 'Time, Depth, Momentum, Velocity \n'
        fid_out.write(s)
        for i_t, i_d, i_m, i_vel in zip(model_time, depths, momenta, velocity):
            s = '%.2f, %.2f, %.2f, %.2f\n' %(i_t, i_d, i_m, i_vel)
            fid_out.write(s)
            
        #### finished generating figures ###

    close('all')
    
    return texfile

def plot_polygons(bounding_polygon,
                  interior_polygon,
                  figname,
                  verbose = False):
    
    """ Take bounding and interior polygons and plot.

    Inputs:

    bounding_polygon - polygon used in create_mesh_from_regions
    
    interior_polygon - list of polygons used in create_mesh_from_regions
                        
    figname          - name to save figure to
                   
    """

    
    k = _plot_polygons(bounding_polygon,
                       interior_polygon,
                       figname,
                       verbose)

    return k

def _plot_polygons(bounding_polygon,
                   interior_polygon,
                   figname,
                   verbose = False):   

    from pylab import ion, hold, plot, axis, figure, legend, savefig, xlabel, ylabel, title, close

    assert type(bounding_polygon) == list,\
               'bounding_polygon must be a list'

    assert type(interior_polygon) == list,\
               'interior_polygon must be a list'

    ion()
    hold(True)

    x_bound, y_bound = poly_xy(bounding_polygon)
    
    for i in range(len(interior_polygon)):
        x_int, y_int = poly_xy(interior_polygon[i])
        plot(x_bound,y_bound,'r-',x_int,y_int,'r-')
        xlabel('x')
        ylabel('y')

    savefig(figname)

    close('all')

    return

def poly_xy(poly):
    x = []
    y = []
    n = len(poly)
    for i in range(n+1):
        if i == n:
            thispt = poly[0]
        else:
            thispt = poly[i]
        x.append(thispt[0])
        y.append(thispt[1])

    return x, y