root/sodar/trunk/sodar/scintec/maindata.py

"""
Module to handle Scintec sodar .mnd files.

>>> from sodar.scintec import maindata
"""

__author__ = 'Chris Calloway'
__email__ = 'cbc@chriscalloway.org'
__copyright__ = 'Copyright 2009 UNC-CH Department of Marine Science'
__license__ = 'GPL2'

from datetime import datetime, timedelta

class MainData(list):
    """
    Contain data from a Scintec sodar .mnd file.
    
    The data is contained as a list of Profile objects
    along with some attributes which apply to all the Profile objects.
    
    Parse a known good .mnd file:
    >>> main_data = MainData(good_mnd)
    >>> len(main_data)
    48
    >>> main_data.format
    'FORMAT-1'
    >>> main_data.first
    datetime.datetime(2009, 11, 17, 0, 30)
    >>> main_data.file_count
    0
    >>> main_data.comment_count
    6
    >>> main_data.variable_count
    6
    >>> main_data.elevation_count
    39
    >>> main_data.comments == {'device serial number':'A-F-0050',
    ...                        'station code':'billymitchell',
    ...                        'software version':'APRun 1.31',
    ...                        'antenna azimuth angle [deg]':'0',
    ...                        'height above ground [m]':'0',
    ...                        'height above sea level [m]':'0'}
    True
    >>> main_data.variables == [{'label':'height','symbol':'z',
    ...                              'units':'m','type':'Z1',
    ...                              'mask':'0','gap':'99999',},
    ...                         {'label':'wind speed','symbol':'speed',
    ...                              'units':'m/s','type':'G1',
    ...                              'mask':'0','gap':'99.99',},
    ...                         {'label':'wind direction','symbol':'dir',
    ...                              'units':'deg','type':'R1',
    ...                              'mask':'0','gap':'999.9',},
    ...                         {'label':'wind W','symbol':'W',
    ...                              'units':'m/s','type':'S',
    ...                              'mask':'0','gap':'99.99',},
    ...                         {'label':'sigma W','symbol':'sigW',
    ...                              'units':'m/s','type':'S',
    ...                              'mask':'0','gap':'99.99',},
    ...                         {'label':'backscatter','symbol':'bck',
    ...                              'units':'','type':'S',
    ...                              'mask':'0','gap':'9.99E+37',},]
    True
    >>> main_data.error == {'label':'error code',
    ...                 'bits':'- - - - - - - - groundclutter - - - - - - -',
    ...                 'mask':'IIIIIIIIWIIIIIII',}
    True
    
    Parse the first profile:
    >>> len(main_data[0])
    39
    >>> main_data(datetime(2009, 11, 17, 0, 30)).stop
    datetime.datetime(2009, 11, 17, 0, 30)
    >>> main_data(datetime(2009, 11, 17, 0, 0),True).start
    datetime.datetime(2009, 11, 17, 0, 0)
    >>> main_data[0].variables
    ['z', 'speed', 'dir', 'W', 'sigW', 'bck', 'error']
    >>> main_data[0][0] == {'z':'10', 'speed':'99.99', 'dir':'999.9',
    ...                     'W':'-0.05', 'sigW':'0.40', 'bck':'5.46E+03',
    ...                     'error':'0'}
    True
    >>> main_data[0](10) == {'z':'10', 'speed':'99.99', 'dir':'999.9',
    ...                      'W':'-0.05', 'sigW':'0.40', 'bck':'5.46E+03',
    ...                      'error':'0'}
    True
    >>> main_data[0][-1] == {'z':'200', 'speed':'99.99', 'dir':'999.9',
    ...                      'W':'-0.07', 'sigW':'99.99', 'bck':'9.99E+37',
    ...                      'error':'0'}
    True
    >>> main_data[0](200) == {'z':'200', 'speed':'99.99', 'dir':'999.9',
    ...                       'W':'-0.07', 'sigW':'99.99', 'bck':'9.99E+37',
    ...                       'error':'0'}
    True
    
    Parse the last profile:
    >>> len(main_data[-1])
    39
    >>> main_data(datetime(2009, 11, 18, 0, 0)).stop
    datetime.datetime(2009, 11, 18, 0, 0)
    >>> main_data(datetime(2009, 11, 17, 23, 0),True).start
    datetime.datetime(2009, 11, 17, 23, 0)
    >>> main_data[-1].variables
    ['z', 'speed', 'dir', 'W', 'sigW', 'bck', 'error']
    >>> main_data[-1][0] == {'z':'10', 'speed':'99.99', 'dir':'999.9',
    ...                      'W':'-0.32', 'sigW':'99.99', 'bck':'9.99E+37',
    ...                      'error':'0'}
    True
    >>> main_data[-1](10) == {'z':'10', 'speed':'99.99', 'dir':'999.9',
    ...                       'W':'-0.32', 'sigW':'99.99', 'bck':'9.99E+37',
    ...                       'error':'0'}
    True
    >>> main_data[-1][-1] == {'z':'200', 'speed':'15.05', 'dir':'71.8',
    ...                       'W':'-0.19', 'sigW':'0.53', 'bck':'9.99E+37',
    ...                       'error':'0'}
    True
    >>> main_data[-1](200) == {'z':'200', 'speed':'15.05', 'dir':'71.8',
    ...                        'W':'-0.19', 'sigW':'0.53', 'bck':'9.99E+37',
    ...                        'error':'0'}
    True
    """
    
    def __init__(self, mnd, *args):
        """
        Parse main daily Scintec sodar .mnd file.
        
        MainData(mnd[,file_path]) -> <MainData object>
        
        Where:
         
            mnd is a str object containing the complete contents read from a
            Scintec .mnd daily sodar file including all line endings,
            
            file_path is an optional str object representing the path to
            a file which contains the referenced .mnd daily sodar file.
        
        Parse a known good .mnd file:
        >>> main_data = MainData(good_mnd)
        >>> main_data = MainData(good_mnd,good_path)
        >>> main_data.path == good_path
        True
        """
        
        super(self.__class__, self).__init__()
        
        self.path = ''
        
        # Optional args: smoke 'em if ya got 'em.
        try:
            self.path = str(args[0])
        except IndexError:
            pass
        
        # Divide the data into blocks
        # across boundaries separated by blank lines.
        blocks = [block.strip()
                  for block
                  in mnd.split('\n\n')
                  if block.strip()]
        
        # The first block is the specification of the format header.
        # Divide it into lines.
        format_header_spec = [line.strip()
                              for line
                              in blocks[0].split('\n')
                              if line.strip()]
                              
        self.format = format_header_spec[0]
        
        timestamp = format_header_spec[1]
        date, first, file_count = timestamp.split()
        date_year, date_month, date_day = date.split('-')
        first_hour, first_minute, first_second = first.split(':')
        self.first = datetime(int(date_year),
                              int(date_month),
                              int(date_day),
                              int(first_hour),
                              int(first_minute), # omit optional microseconds
                              int(first_second)) # and tzinfo
        self.file_count = int(file_count)
        
        self.instrument_type = format_header_spec[2]
        
        comment_count, variable_count, elevation_count = \
            format_header_spec[3].split()
        self.comment_count = int(comment_count)
        self.variable_count = int(variable_count)
        self.elevation_count = int(elevation_count)
        
        # The second block is the body of the format header.
        # Divide it into lines.
        file_header_body = [line.strip()
                            for line
                            in blocks[1].split('\n')
                            if not line.strip().startswith('#')]
        self.comments = dict([(name.strip(),value.strip())
                               for line
                               in file_header_body[0:self.comment_count]
                                   for name,value
                                   in (line.split(':'),)])
        self.file_type = file_header_body[self.comment_count]
        self.variables = [{'label':label.strip(),
                           'symbol':symbol.strip(),
                           'units':units.strip(),
                           'type':vtype.strip(),
                           'mask':mask.strip(),
                           'gap':gap.strip(),}
                          for line
                          in file_header_body[self.comment_count + 1:-1]
                              for label,symbol,units,vtype,mask,gap
                              in (line.split('#'),)]
        self.error = [{'label':label.strip(),
                       'bits':bits.strip(),
                       'mask':mask.strip(),}
                      for label,bits,units,vtype,mask
                      in (file_header_body[-1].split('#'),)][0]
                       
        
        # All the remaing blocks are individual profiles
        # in chronological order.
        self.extend([Profile([line.strip()
                              for line
                              in block.split('\n')
                              if line.strip()])
                     for block
                     in blocks[2:]])
    
    def __call__(self,timestamp,start=False):
        """
        Get a profile by timestamp
        
        MainData_instance(timestamp[,start]) -> <Profile object>
        
        Where:
        
            timestamp is a datetime.datetime object representing either
            the start or stop timestamp of the Profile object returned.
            
            start is a bool object. If start is False (default), then
            timestamp is matched to the stop timestamp of the returned
            Profile object. Otherwise, if start is True, then timestamp is
            matched to the start timestamp of the returned Profile object.
        
        Access profiles by timestamp:
        >>> main_data = MainData(good_mnd)
        >>> main_data(datetime(2009, 11, 17, 0, 30)).stop
        datetime.datetime(2009, 11, 17, 0, 30)
        >>> main_data(datetime(2009, 11, 17, 0, 0),True).start
        datetime.datetime(2009, 11, 17, 0, 0)
        >>> main_data(datetime(2009, 11, 18, 0, 0)).stop
        datetime.datetime(2009, 11, 18, 0, 0)
        >>> main_data(datetime(2009, 11, 17, 23, 0),True).start
        datetime.datetime(2009, 11, 17, 23, 0)
        >>> main_data(datetime(2009, 11, 16, 0, 30))
        Traceback (most recent call last):
           ...
        ValueError: Timestamp datetime.datetime(2009, 11, 16, 0, 30)
        not found in 'MainData' object
        >>> main_data('OK')
        Traceback (most recent call last):
            ...
        ValueError: Timestamp 'OK' not found in 'MainData' object
        """
        
        for profile in self:
            if start:
                boundary = profile.start
            else:
                boundary = profile.stop
            if boundary == timestamp:
                return profile
        raise ValueError, ' '.join(['Timestamp',
                                    repr(timestamp),
                                    'not found in',
                                    repr(self.__class__.__name__),
                                    'object'])

class Profile(list):
    """
    Contain data for single profile from a Scintec sodar .mnd file.
    
    The data is contained as a list of Observation objects
    along with some attributes which apply to all the Profile objects.
    
    Parse a known good profile block:
    >>> profile = Profile(good_profile)
    
    Access the timestamp attributes:
    >>> profile.start
    datetime.datetime(2009, 11, 17, 0, 0)
    >>> profile.stop
    datetime.datetime(2009, 11, 17, 0, 30)
    
    Access the variable list:
    >>> profile.variables
    ['z', 'speed', 'dir', 'W', 'sigW', 'bck', 'error']
    
    Access observations by sequence number:
    >>> profile[0] == {'z':'10', 'speed':'99.99', 'dir':'999.9',
    ...                'W':'-0.05', 'sigW':'0.40', 'bck':'5.46E+03',
    ...                'error':'0'}
    True
    >>> profile[-1] == {'z':'200', 'speed':'99.99', 'dir':'999.9',
    ...                 'W':'-0.07', 'sigW':'99.99', 'bck':'9.99E+37',
    ...                 'error':'0'}
    True
    
    Access observations by elevation:
    >>> profile(10) == {'z':'10', 'speed':'99.99', 'dir':'999.9',
    ...                 'W':'-0.05', 'sigW':'0.40', 'bck':'5.46E+03',
    ...                 'error':'0'}
    True
    >>> profile(200) == {'z':'200', 'speed':'99.99', 'dir':'999.9',
    ...                  'W':'-0.07', 'sigW':'99.99', 'bck':'9.99E+37',
    ...                  'error':'0'}
    True
    """
    
    def __init__(self, profile_block):
        """
        Parse a profile block from a main daily Scintec sodar .mnd file.
        
        Profile(profile_data) -> <Profile object>
        
        Where:
        
            profile_block is a list of str objects containing all the lines
            from a single profile in a Scintec .mnd daily sodar file.
        
        Parse a known good profile block:
        >>> profile = Profile(good_profile)
        
        Access the timestamp attributes:
        >>> profile.start
        datetime.datetime(2009, 11, 17, 0, 0)
        >>> profile.stop
        datetime.datetime(2009, 11, 17, 0, 30)
        
        Access the variable list:
        >>> profile.variables
        ['z', 'speed', 'dir', 'W', 'sigW', 'bck', 'error']
        
        Access observations by sequence number:
        >>> profile[0] == {'z':'10', 'speed':'99.99', 'dir':'999.9',
        ...                'W':'-0.05', 'sigW':'0.40', 'bck':'5.46E+03',
        ...                'error':'0'}
        True
        >>> profile[-1] == {'z':'200', 'speed':'99.99', 'dir':'999.9',
        ...                 'W':'-0.07', 'sigW':'99.99', 'bck':'9.99E+37',
        ...                 'error':'0'}
        True
        >>> profile[100000]
        Traceback (most recent call last):
            ...
        IndexError: list index out of range
        """
        
        super(self.__class__, self).__init__()

        # The first line in the profile block is the timestamp.       
        timestamp = profile_block[0]
        date, stop, duration = timestamp.split()
        date_year, date_month, date_day = date.split('-')
        stop_hour, stop_minute, stop_second = stop.split(':')
        duration_hour, duration_minute, duration_second = duration.split(':')
        interval = timedelta(0,                    # days
                             int(duration_second),
                             0,                    # microseconds
                             0,                    # milliseconds
                             int(duration_minute),
                             int(duration_hour))   # omit optional weeks
        self.stop = datetime(int(date_year),
                             int(date_month),
                             int(date_day),
                             int(stop_hour),
                             int(stop_minute),     # omit optional microseconds
                             int(stop_second))     # and tzinfo
        self.start = self.stop - interval
        
        # The second line in the profile block is
        # a commented list of variable names
        self.variables = profile_block[1].split()[1:]
        
        # All the remaining lines in the profile block are
        # individual obervation columns in the same order
        # as the variable names.
        super(self.__class__, self).extend([Observation(observation.split(),
                                                        self.variables)
                                            for observation
                                            in profile_block[2:]])
    
    def __call__(self,elevation):
        """
        Get an observation by elevation.
        
        Profile_instance(elevation) -> <Observation object>
        
        Where:
        
            elevation is a numeric or str object representing the elevation
            (value keyed by 'z') of the Observation object.
        
        Access observations by elevation:
        >>> profile = Profile(good_profile)
        >>> profile(10) == {'z':'10', 'speed':'99.99', 'dir':'999.9',
        ...                 'W':'-0.05', 'sigW':'0.40', 'bck':'5.46E+03',
        ...                 'error':'0'}
        True
        >>> profile(200) == {'z':'200', 'speed':'99.99', 'dir':'999.9',
        ...                  'W':'-0.07', 'sigW':'99.99', 'bck':'9.99E+37',
        ...                  'error':'0'}
        True
        >>> profile(100000)
        Traceback (most recent call last):
            ...
        ValueError: Elevation 100000 not found in 'Profile' object
        >>> profile('10') == {'z':'10', 'speed':'99.99', 'dir':'999.9',
        ...                   'W':'-0.05', 'sigW':'0.40', 'bck':'5.46E+03',
        ...                   'error':'0'}
        True
        >>> profile('200') == {'z':'200', 'speed':'99.99', 'dir':'999.9',
        ...                    'W':'-0.07', 'sigW':'99.99', 'bck':'9.99E+37',
        ...                    'error':'0'}
        True
        >>> profile('100000')
        Traceback (most recent call last):
            ...
        ValueError: Elevation '100000' not found in 'Profile' object
        """
        
        for observation in self:
            if observation['z'] == str(int(elevation)):
                return observation
        raise ValueError, ' '.join(['Elevation',
                                    repr(elevation),
                                    'not found in',
                                    repr(self.__class__.__name__),
                                    'object'])

class Observation(dict):
    """
    Contain data for single observation from a Scintec sodar .mnd files.
    
    The data is contained as a dictionary of variable name/value pairs.
    
    The variable values may also be accessed as attributes of the instance.
    
    Parse a known good observation:
    >>> observation = Observation(good_observation,good_variables)
    >>> observation == {'z':'10', 'speed':'99.99', 'dir':'999.9',
    ...                 'W':'-0.05', 'sigW':'0.40', 'bck':'5.46E+03',
    ...                 'error':'0'}
    True
    """
    
    def __init__(self,data,variables):
        """
        Parse an observation from a main daily Scintec sodar .mnd file.
        
        Observation(data,variables) -> <Observation object>
        
        Where:
         
            data is a list of str object representing variable values,
            
            variables is a list of str objects representing variable names.
        
        Parse a known good observation:
        >>> observation = Observation(good_observation,good_variables)
        >>> observation == {'z':'10', 'speed':'99.99', 'dir':'999.9',
        ...                 'W':'-0.05', 'sigW':'0.40', 'bck':'5.46E+03',
        ...                 'error':'0'}
        True
        
        Raise an Exception if more variable names than values:
        >>> extra_variables = good_variables + ['extra']
        >>> observation = Observation(good_observation,extra_variables)
        Traceback (most recent call last):
            ...
        ValueError: Same number of variable names and values required in
        'Observation' object
        
        Raise an Exception if more variable values than names:
        >>> extra_observation = good_observation + ['extra']
        >>> observation = Observation(extra_observation,good_variables)
        Traceback (most recent call last):
            ...
        ValueError: Same number of variable names and values required in
        'Observation' object
        """
        
        super(self.__class__, self).__init__()
        
        if len(variables) == len(data):
            # And update the dictionary with the variable names/values.
            super(self.__class__, self).update(dict(zip(variables,data)))
        else:
            # Unless there are an unequal number of variable names/values.
            raise ValueError, ' '.join(['Same number of variable',
                                        'names and values required in',
                                        repr(self.__class__.__name__),
                                        'object',])

def _test():
    """
    Run module tests in script mode.
    
    >>> from sodar.scintec.maindata import _test
    """
    
    import doctest
    from sodar.tests import suite
    mnd,mnd_path,profile,variables,observation = \
        suite.setUpGoodMndData()
    doctest.testmod(extraglobs=dict(good_mnd=mnd,
                                    good_path=mnd_path,
                                    good_profile=profile,
                                    good_variables=variables,
                                    good_observation=observation),
                    optionflags=doctest.NORMALIZE_WHITESPACE)

if __name__ == "__main__":
    _test()