Exemple #1
0
def test_bufr_read(monkeypatch):
    """Test reading data and data quality on Metop-A MHS BUFR file."""
    monkeypatch.setenv("BUFR_TABLES", os.path.join(test_dir, "bufrtables"))
    monkeypatch.setenv("BUFR_TABLES_TYPE", "bufrdc")
    from trollbufr import load_file
    from trollbufr.bufr import Bufr
    test_file = os.path.join(test_dir, "metop_mhs.bufr")
    bufr = Bufr(os.environ["BUFR_TABLES_TYPE"], os.environ["BUFR_TABLES"])
    # laod test file and iterate over BUFR
    for blob, size, header in load_file.next_bufr(test_file):
        # test header for first BUFR
        assert header == "IEMX01 EUMP 150722"
        assert size == 48598
        # decode BUFR message
        bufr.decode(blob)
        # iterate over subsets
        for report in bufr.next_subset():
            i = 0
            # iterate over all descriptor/data sets
            for k, m, (v, q) in report.next_data():
                i += 1
                if i >= 4:
                    # after first 3 descriptor/data sets just count
                    continue
                if i <= 3:
                    # type-marker for first 3 descriptor is not None
                    assert m is not None
                    continue
                # assert descriptor, data value, quality
                assert m is not None
                assert k == 8070
                assert v == 3
                assert q is None
                # look-up and assert name and unit
                kn, ku = bufr.get_tables().lookup_elem(k)
                assert kn.strip() == "TOVS/ATOVS PRODUCT QUALIFIER"
                assert ku.strip() == "CODE TABLE 8070"
            # assert there were 88 descriptors in the subset
            assert i == 88
            # leave for-loops, all tests are done
            break
        break
Exemple #2
0
def read_bufr_to_json(args):
    """Read and decode BUFR, write as JSON formatted file.
    """
    bufr = Bufr(args.tables_type, args.tables_path)
    json_data = []
    bufr_i = -1
    for fn_in in args.in_file:
        for blob, _, header in load_file.next_bufr(fn_in):
            bufr_i += 1
            if args.bulletin is not None and bufr_i != args.bulletin:
                continue
            json_data_item = {
                "heading": header,
                "file": os.path.basename(fn_in),
                "index": bufr_i,
                "status": False,
                "error": None,
                "bufr": None,
            }
            try:
                json_bufr = bufr.decode(blob,
                                        load_tables=True,
                                        as_array=args.array)
            except Exception as e:
                logger.error(e,
                             exc_info=1 and logger.isEnabledFor(logging.DEBUG))
                json_data_item["error"] = str(e)
            else:
                json_data_item["status"] = True
                json_data_item["bufr"] = json_bufr
            finally:
                json_data.append(json_data_item)
    import json
    out_fh = open(args.out_file, "w") or sys.stdout
    with out_fh as fh_out:
        if args.sparse:
            json.dump(json_data, fh_out)
        else:
            json.dump(json_data, fh_out, indent=3, separators=(',', ': '))
Exemple #3
0
logging.getLogger('').addHandler(handler)

from trollbufr.bufr import Bufr
from trollbufr import load_file
import numpy as np

TESTFILE = 'TestBulletin_468'
PNGFILE = 'metopa_iasi_ctp_%s.png'
AREA = 'euro'

lon = []
lat = []
pres = []
bfr = Bufr("bufrdc", ".")
for blob, size, header in load_file.next_bufr(TESTFILE):
    bfr.decode(blob)
    print header, bfr.get_meta()['datetime']
    for subset in bfr.next_subset():
        gotit = 0
        for k, m, (v, q) in subset.next_data():
            if gotit:
                continue
            if k == 5001:
                lat.append((0, 0, v))
            if k == 6001:
                lon.append((0, 0, v))
            if k == 7004:
                pres.append((0, 0, v))
                gotit = 1
lons = np.concatenate(lon)
lats = np.concatenate(lat)
Exemple #4
0
def read_synop(file, params, min=None, max=None):
    """ Reading bufr files for synoptical station data and provide dictionary
    with weather data for cloud base height and visibility.
    The results are subsequently filtered by cloud base height and visibility

    Arguments:
        file    Bufr file with synop reports
        params    List of parameter names that will be extracted
        min    Threshold for minimum value of parameter
        max    Threshold for maximum value of parameter

    Returns list of station dictionaries for given thresholds
    """
    result = {}
    bfr = Bufr("libdwd", os.getenv("BUFR_TABLES"))
    for blob, size, header in load_file.next_bufr(file):
        bfr.decode(blob)
        try:
            for subset in bfr.next_subset():
                stationdict = {}
                for (k, m, v, q) in subset.next_data():
                    if k == 1015:  # Station name
                        stationdict['name'] = v.strip()
                    if k == 5001:  # Latitude
                        stationdict['lat'] = v
                    if k == 6001:  # Longitude
                        stationdict['lon'] = v
                    if k == 7030:  # Altitude
                        stationdict['altitude'] = v
                    elif k == 4001:  # Year
                        stationdict['year'] = v
                    elif k == 4002:  # Month
                        stationdict['month'] = v
                    elif k == 4003:  # Day
                        stationdict['day'] = v
                    elif k == 4004:  # Hour
                        stationdict['hour'] = v
                    elif k == 4005:  # Hour
                        stationdict['minute'] = v
                    elif k == 20003:  # Present weather
                        stationdict['present weather'] = v
                        # Values from 40 to 49 are refering to fog and ice fog
                        # Patchy fog or fog edges value 11 or 12
                    elif k == 20004:  # Past weather
                        stationdict['past weather'] = v
                        # Values from 40 to 49 are refering to fog and ice fog
                        # Patchy fog or fog edges value 11 or 12
                    elif k == 20013:  # Cloud base height
                        if v is not None:
                            if ('cbh' in stationdict.keys()
                                    and stationdict["cbh"] is not None):
                                if stationdict['cbh'] > v:
                                    stationdict['cbh'] = v
                            else:
                                stationdict['cbh'] = v
                        else:
                            stationdict['cbh'] = None
                    elif k == 2001:  # Auto/manual measurement
                        # 1 - 3 : Manual human observations. Manned stations
                        # 0, 4 - 7 : Only automatic observations
                        stationdict['type'] = v
                    elif k == 20001:  # Visibility
                        stationdict['visibility'] = v
                    elif k == 12101:  # Mean air temperature in K
                        stationdict['air temperature'] = v
                    elif k == 12103:  # Dew point temperature in K
                        stationdict['dew point'] = v
                    elif k == 20010:  # Cloud cover in %
                        stationdict['cloudcover'] = v
                    elif k == 13003:  # Relative humidity in %
                        stationdict['relative humidity'] = v
                    elif k == 11001:  # Wind direction in degree
                        stationdict['wind direction'] = v
                    elif k == 11002:  # Wind speed in m s-1
                        stationdict['wind speed'] = v
                    elif k == 1002:  # WMO station number
                        stationdict['wmo'] = v
                # Apply thresholds
                stationtime = datetime(
                    stationdict['year'],
                    stationdict['month'],
                    stationdict['day'],
                    stationdict['hour'],
                    stationdict['minute'],
                ).strftime("%Y%m%d%H%M%S")
                paralist = []
                if not isinstance(params, list):
                    params = [params]
                for param in params:
                    if param not in stationdict:
                        res = None
                    elif min is not None and stationdict[param] < min:
                        res = None
                    elif max is not None and stationdict[param] >= max:
                        res = None
                    elif stationdict[param] is None:
                        res = None
                    else:
                        res = stationdict[param]
                    paralist.append(res)
                if all([i is None for i in paralist]):
                    continue
                # Add station data to result list
                if stationtime in result.keys():
                    result[stationtime].append([
                        stationdict['name'], stationdict['altitude'],
                        stationdict['lat'], stationdict['lon']
                    ] + paralist)
                else:
                    result[stationtime] = [[
                        stationdict['name'], stationdict['altitude'],
                        stationdict['lat'], stationdict['lon']
                    ] + paralist]
        except DummyException as e:
            "ERROR: Unresolved station request: {}".format(e)
    return (result)
logging.getLogger('').addHandler(handler)

from trollbufr.bufr import Bufr
from trollbufr import load_file
import numpy as np

TESTFILE = 'TestBulletin_468'
PNGFILE = 'metopa_iasi_ctp_%s.png'
AREA = 'euro'

lon = []
lat = []
pres = []
bfr = Bufr("bufrdc", ".")
for blob, size, header in load_file.next_bufr(TESTFILE):
    bfr.decode(blob)
    print header, bfr.get_meta()['datetime']
    for subset in bfr.next_subset():
        gotit = 0
        for k, m, (v, q) in subset.next_data():
            if gotit:
                continue
            if k == 5001:
                lat.append((0, 0, v))
            if k == 6001:
                lon.append((0, 0, v))
            if k == 7004:
                pres.append((0, 0, v))
                gotit = 1
lons = np.concatenate(lon)
lats = np.concatenate(lat)