Source code for pyart.aux_io.gamic_hdf5

Utilities for reading gamic hdf5 files.


# TODO to move out of aux_io namespace:
# * unit tests - need small sample files.
# * auto-detect file type with function
# * move to namespace

import datetime
import warnings

import numpy as np

from ..config import FileMetadata, get_fillvalue
from import make_time_unit_str, _test_arguments
from ..core.radar import Radar
    from .gamicfile import GAMICFile
    _H5PY_AVAILABLE = True
except ImportError:
    _H5PY_AVAILABLE = False
from ..exceptions import MissingOptionalDependency

LIGHT_SPEED = 2.99792458e8  # speed of light in meters per second

[docs]def read_gamic(filename, field_names=None, additional_metadata=None, file_field_names=False, exclude_fields=None, include_fields=None, valid_range_from_file=True, units_from_file=True, pulse_width=None, **kwargs): """ Read a GAMIC hdf5 file. Parameters ---------- filename : str Name of GAMIC HDF5 file to read data from. field_names : dict, optional Dictionary mapping field names in the file names to radar field names. Unlike other read functions, fields not in this dictionary or having a value of None are still included in the radar.fields dictionary, to exclude them use the `exclude_fields` parameter. Fields which are mapped by this dictionary will be renamed from key to value. additional_metadata : dict of dicts, optional This parameter is not used, it is included for uniformity. file_field_names : bool, optional True to force the use of the field names from the file in which case the `field_names` parameter is ignored. False will use to `field_names` parameter to rename fields. exclude_fields : list or None, optional List of fields to exclude from the radar object. This is applied after the `file_field_names` and `field_names` parameters. Set to None to include all fields specified by include_fields. include_fields : list or None, optional List of fields to include from the radar object. This is applied after the `file_field_names` and `field_names` parameters. Set to None to include all fields not specified by exclude_fields. valid_range_from_file : bool, optional True to extract valid range (valid_min and valid_max) for all field from the file when they are present. False will not extract these parameters. units_from_file : bool, optional True to extract the units for all fields from the file when available. False will not extract units using the default units for the fields. pulse_width : list or None, Mandatory for gamic radar processors which have pulsewidth enums. pulse_width should contain the pulsewidth' in us. Returns ------- radar : Radar Radar object. """ # check that h5py is available if not _H5PY_AVAILABLE: raise MissingOptionalDependency( "h5py is required to use read_gamic but is not installed") # test for non empty kwargs _test_arguments(kwargs) # create metadata retrieval object filemetadata = FileMetadata('gamic', field_names, additional_metadata, file_field_names, exclude_fields, include_fields) # Open HDF5 file and get handle gfile = GAMICFile(filename) # verify that all scans are present in file assert gfile.is_file_complete() # latitude, longitude and altitude latitude = filemetadata('latitude') longitude = filemetadata('longitude') altitude = filemetadata('altitude') latitude['data'] = gfile.where_attr('lat', 'float64') longitude['data'] = gfile.where_attr('lon', 'float64') altitude['data'] = gfile.where_attr('height', 'float64') # metadata metadata = filemetadata('metadata') metadata['original_container'] = 'GAMIC-HDF5' what_mapping = { 'version': 'gamic_version', 'sets_scheduled': 'sets_scheduled', 'object': 'gamic_object', 'date': 'gamic_date'} for gamic_key, metadata_key in what_mapping.items(): if gfile.is_attr_in_group('what', gamic_key): metadata[metadata_key] = gfile.raw_group_attr('what', gamic_key) how_keys = ['software', 'template_name', 'site_name', 'host_name', 'azimuth_beam', 'elevation_beam', 'sdp_name', 'sw_version', 'sdp_version', 'simulated'] for key in how_keys: if gfile.is_attr_in_group('how', key): metadata[key] = gfile.raw_group_attr('how', key) # sweep_start_ray_index, sweep_end_ray_index sweep_start_ray_index = filemetadata('sweep_start_ray_index') sweep_end_ray_index = filemetadata('sweep_end_ray_index') sweep_start_ray_index['data'] = gfile.start_ray.astype('int32') sweep_end_ray_index['data'] = gfile.end_ray.astype('int32') # sweep number sweep_number = filemetadata('sweep_number') try: sweep_number['data'] = gfile.what_attrs('set_idx', 'int32') except KeyError: sweep_number['data'] = np.arange(gfile.nsweeps, dtype='int32') # sweep_type scan_type = gfile.raw_scan0_group_attr('what', 'scan_type').lower() if hasattr(scan_type, 'decode'): scan_type = scan_type.decode('utf-8') # check that all scans in the volume are the same type if not gfile.is_file_single_scan_type(): raise NotImplementedError('Mixed scan_type volume.') if scan_type not in ['ppi', 'rhi']: message = "Unknown scan type: %s, reading as RHI scans." % (scan_type) warnings.warn(message) scan_type = 'rhi' # sweep_mode, fixed_angle sweep_mode = filemetadata('sweep_mode') fixed_angle = filemetadata('fixed_angle') if scan_type == 'rhi': sweep_mode['data'] = np.array(gfile.nsweeps * ['rhi']) fixed_angle['data'] = gfile.how_attrs('azimuth', 'float32') elif scan_type == 'ppi': sweep_mode['data'] = np.array(gfile.nsweeps * ['azimuth_surveillance']) fixed_angle['data'] = gfile.how_attrs('elevation', 'float32') # time time = filemetadata('time') t_data = gfile.ray_header('timestamp', 'int64') start_epoch = t_data[0] // 1.e6 # truncate to second resolution start_time = datetime.datetime.utcfromtimestamp(start_epoch) time['units'] = make_time_unit_str(start_time) time['data'] = ((t_data - start_epoch * 1.e6) / 1.e6).astype('float64') # range _range = filemetadata('range') ngates = int(gfile.raw_scan0_group_attr('how', 'bin_count')) range_start = float(gfile.raw_scan0_group_attr('how', 'range_start')) #n_samples insertion range_samples = int(gfile.raw_scan0_group_attr('how', 'range_samples')) range_step = float(gfile.raw_scan0_group_attr('how', 'range_step'))*range_samples # range_step may need to be scaled by range_samples # XXX This gives distances to start of gates not center, this matches # Radx but may be incorrect, add range_step / 2. for center _range['data'] = (np.arange(ngates, dtype='float32') * range_step + range_start) _range['meters_to_center_of_first_gate'] = range_start _range['meters_between_gates'] = range_step # elevation elevation = filemetadata('elevation') start_angle = gfile.ray_header('elevation_start', 'float32') stop_angle = gfile.ray_header('elevation_stop', 'float32') elevation['data'] = _avg_radial_angles(start_angle, stop_angle) # azimuth azimuth = filemetadata('azimuth') start_angle = gfile.ray_header('azimuth_start', 'float32') stop_angle = gfile.ray_header('azimuth_stop', 'float32') azimuth['data'] = _avg_radial_angles(start_angle, stop_angle) % 360. # fields fields = {} moment_groups = gfile.moment_groups() moment_names = gfile.moment_names(moment_groups) for moment_name, group in zip(moment_names, moment_groups): field_name = filemetadata.get_field_name(moment_name) if field_name is None: continue field_dic = filemetadata(field_name) field_dic['data'] = gfile.moment_data(group, 'float32') field_dic['_FillValue'] = get_fillvalue() if valid_range_from_file: try: valid_min = gfile.raw_scan0_group_attr(group, 'dyn_range_min') valid_max = gfile.raw_scan0_group_attr(group, 'dyn_range_max') field_dic['valid_min'] = valid_min.decode('utf-8') field_dic['valid_max'] = valid_max.decode('utf-8') except: pass if units_from_file: try: units = gfile.raw_scan0_group_attr(group, 'unit') field_dic['units'] = units.decode('utf-8') except: pass fields[field_name] = field_dic # ray_angle_res ray_angle_res = filemetadata('ray_angle_res') ray_angle_res['data'] = gfile.how_attrs('angle_step', 'float32') # rays_are_indexed rays_are_indexed = filemetadata('rays_are_indexed') rays_are_indexed['data'] = np.array( [['false', 'true'][i] for i in gfile.how_attrs('angle_sync', 'uint8')]) # target_scan_rate target_scan_rate = filemetadata('target_scan_rate') target_scan_rate['data'] = gfile.how_attrs('scan_speed', 'float32') # scan_rate scan_rate = filemetadata('scan_rate') scan_rate['data'] = target_scan_rate['data'] if scan_type == 'ppi': azs_names = ['az_speed', 'azimuth_speed'] azs_name = azs_names[0] for azs_name in azs_names: if gfile.is_field_in_ray_header(azs_name): scan_rate['data'] = gfile.ray_header(azs_name, 'float32') break elif scan_type == 'rhi': els_names = ['el_speed', 'elevation_speed'] els_name = els_names[0] for els_name in els_names: if gfile.is_field_in_ray_header(els_name): scan_rate['data'] = gfile.ray_header(els_name, 'float32') break else: scan_rate = None # instrument_parameters instrument_parameters = _get_instrument_params(gfile, filemetadata, pulse_width) gfile.close() return Radar( time, _range, fields, metadata, scan_type, latitude, longitude, altitude, sweep_number, sweep_mode, fixed_angle, sweep_start_ray_index, sweep_end_ray_index, azimuth, elevation, instrument_parameters=instrument_parameters, ray_angle_res=ray_angle_res, rays_are_indexed=rays_are_indexed, scan_rate=scan_rate, target_scan_rate=target_scan_rate)
def _get_instrument_params(gfile, filemetadata, pulse_width): """ Return a dictionary containing instrument parameters. """ instrument_params = {} dic = filemetadata('frequency') dic['data'] = np.array( [LIGHT_SPEED / gfile.raw_scan0_group_attr('how', 'radar_wave_length')], dtype='float32') instrument_params['frequency'] = dic dic = filemetadata('radar_beam_width_h') dic['data'] = gfile.how_attr('azimuth_beam', 'float32') instrument_params['radar_beam_width_h'] = dic dic = filemetadata('radar_beam_width_v') dic['data'] = gfile.how_attr('elevation_beam', 'float32') instrument_params['radar_beam_width_v'] = dic dic = filemetadata('pulse_width') pw_names = ['pulse_width_us', 'pulse_width_mks', 'pulse_width'] pw_name = 'pulse_width_us' dic['data'] = None for pw_name in pw_names: if gfile.is_attr_in_group('/scan0/how', pw_name): if pw_name == 'pulse_width': dic['data'] = gfile.sweep_expand( pulse_width[gfile.how_attrs(pw_name, 'int')[0]] * 1e-6) else: dic['data'] = gfile.sweep_expand( gfile.how_attrs(pw_name, 'float32') * 1e-6) break instrument_params['pulse_width'] = dic dic = filemetadata('prt') dic['data'] = gfile.sweep_expand(1. / gfile.how_attrs('PRF', 'float32')) instrument_params['prt'] = dic unfolding = gfile.how_attrs('unfolding', 'int32') dic = filemetadata('prt_mode') dic['data'] = np.array([_prt_mode_from_unfolding(i) for i in unfolding]) instrument_params['prt_mode'] = dic dic = filemetadata('prt_ratio') dic['data'] = gfile.sweep_expand( [[1, 2./3., 3./4., 4./5.][i] for i in unfolding]) instrument_params['prt_ratio'] = dic dic = filemetadata('unambiguous_range') dic['data'] = gfile.sweep_expand(gfile.how_attrs('range', 'float32')) instrument_params['unambiguous_range'] = dic if gfile.is_attr_in_group('/scan0/how/extended', 'nyquist_velocity'): dic = filemetadata('nyquist_velocity') dic['data'] = gfile.sweep_expand( gfile.how_ext_attrs('nyquist_velocity')) instrument_params['nyquist_velocity'] = dic dic = filemetadata('n_samples') dic['data'] = gfile.sweep_expand( gfile.how_attrs('range_samples', 'int32') * gfile.how_attrs('time_samples', 'int32'), dtype='int32') instrument_params['n_samples'] = dic return instrument_params def _avg_radial_angles(angle1, angle2): """ Return the average angle between two radial angles. """ return np.angle( (np.exp(1.j*np.deg2rad(angle1)) + np.exp(1.j*np.deg2rad(angle2))) / 2., deg=True) def _prt_mode_from_unfolding(unfolding): """ Return 'fixed' or 'staggered' depending on unfolding flag """ if unfolding == 0: return 'fixed' else: return 'staggered'