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PCDCPParser.py 2.61 KiB
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  • """Parsing methods for the PCDCP Format."""
    
    
    import numpy
    from datetime import datetime
    
    # values that represent missing data points in PCDCP
    
    NINES = numpy.float64('9999999')
    NINES_RAW = numpy.float64('99999990')
    NINES_DEG = numpy.float64('9999')
    
    
    class PCDCPParser(object):
        """PCDCP parser.
    
        Attributes
        ----------
        header : dict
            parsed PCDCP header.
        times : array
            parsed timeseries times.
        data : dict
            keys are channel names (order listed in ``self.channels``).
            values are ``numpy.array`` of timeseries values, array values are
            ``numpy.nan`` when values are missing.
        """
    
        def __init__(self):
            """Create a new PCDCP parser."""
            # header fields
            self.header = {}
            # timestamps of data (datetime.datetime)
            self.times = []
            # dictionary of data (channel : numpy.array<float64>)
            self.data = {}
            # temporary storage for data being parsed
            self._parsedata = None
    
        def parse(self, data):
            """Parse a string containing PCDCP formatted data.
    
            Parameters
            ----------
            data : str
                PCDCP formatted file contents.
            """
            parsing_header = True
            lines = data.splitlines()
            for line in lines:
                if parsing_header:
                    self._parse_header(line)
                    parsing_header = False
                else:
                    self._parse_data(line)
            self._post_process()
    
        def _parse_header(self, line):
            """Parse header line.
    
            Adds value to ``self.header``.
            """
            self.header['header'] = line
            self.header['observatory'] = line[0:3]
            self.header['year'] = line[6:10]
            self.header['date'] = line[16:25]
            return
    
        def _parse_data(self, line):
            """Parse one data point in the timeseries.
    
            Adds time to ``self.times``.
            Adds channel values to ``self.data``.
            """
            t, d1, d2, d3, d4 = self._parsedata
            t.append(line[0:4])
    
            d1.append(int(line[5:13]))
            d2.append(int(line[14:22]))
            d3.append(int(line[23:31]))
            d4.append(int(line[32:40]))
    
    
        def _post_process(self):
            """Post processing after data is parsed.
    
            Converts data to numpy arrays.
            Replaces empty values with ``numpy.nan``.
            """
            self.times = self._parsedata[0]
            for channel, data in zip(self.channels, self._parsedata[1:]):
                data = numpy.array(data, dtype=numpy.float64)
                # filter empty values
                data[data == NINES] = numpy.nan
                self.data[channel] = data
            self._parsedata = None