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Source code for iris.fileformats.nimrod

# Copyright Iris contributors
#
# This file is part of Iris and is released under the LGPL license.
# See COPYING and COPYING.LESSER in the root of the repository for full
# licensing details.
"""Provides NIMROD file format capabilities."""

import glob
import os
import struct
import sys

import numpy as np

import iris
from iris.exceptions import TranslationError
import iris.fileformats.nimrod_load_rules

# general header (int16) elements 1-31 (Fortran bytes 1-62)
general_header_int16s = (
    "vt_year",
    "vt_month",
    "vt_day",
    "vt_hour",
    "vt_minute",
    "vt_second",
    "dt_year",
    "dt_month",
    "dt_day",
    "dt_hour",
    "dt_minute",
    "datum_type",
    "datum_len",
    "experiment_num",
    "horizontal_grid_type",
    "num_rows",
    "num_cols",
    "nimrod_version",
    "field_code",
    "vertical_coord_type",
    "reference_vertical_coord_type",
    "data_specific_float32_len",
    "data_specific_int16_len",
    "origin_corner",
    "int_mdi",
    "period_minutes",
    "num_model_levels",
    "proj_biaxial_ellipsoid",
    "ensemble_member",
    "model_origin_id",
    "averagingtype",
)


# general header (float32) elements 32-59 (Fortran bytes 63-174)
general_header_float32s = (
    "vertical_coord",
    "reference_vertical_coord",
    "y_origin",
    "row_step",
    "x_origin",
    "column_step",
    "float32_mdi",
    "MKS_data_scaling",
    "data_offset",
    "x_offset",
    "y_offset",
    "true_origin_latitude",
    "true_origin_longitude",
    "true_origin_easting",
    "true_origin_northing",
    "tm_meridian_scaling",
    "threshold_value_alt",
    "threshold_value",
)


# data specific header (float32) elements 60-104 (Fortran bytes 175-354)
data_header_float32s = (
    "tl_y",
    "tl_x",
    "tr_y",
    "tr_x",
    "br_y",
    "br_x",
    "bl_y",
    "bl_x",
    "sat_calib",
    "sat_space_count",
    "ducting_index",
    "elevation_angle",
    "neighbourhood_radius",
    "threshold_vicinity_radius",
    "recursive_filter_alpha",
    "threshold_fuzziness",
    "threshold_duration_fuzziness",
)


# data specific header (char) elements 105-107 (bytes 355-410)
# units, source and title


# data specific header (int16) elements 108-159 (Fortran bytes 411-512)
data_header_int16s = (
    "threshold_type",
    "probability_method",
    "recursive_filter_iterations",
    "member_count",
    "probability_period_of_event",
    "data_header_int16_05",
    "soil_type",
    "radiation_code",
    "data_header_int16_08",
    "data_header_int16_09",
    "data_header_int16_10",
    "data_header_int16_11",
    "data_header_int16_12",
    "data_header_int16_13",
    "data_header_int16_14",
    "data_header_int16_15",
    "data_header_int16_16",
    "data_header_int16_17",
    "data_header_int16_18",
    "data_header_int16_19",
    "data_header_int16_20",
    "data_header_int16_21",
    "data_header_int16_22",
    "data_header_int16_23",
    "data_header_int16_24",
    "data_header_int16_25",
    "data_header_int16_26",
    "data_header_int16_27",
    "data_header_int16_28",
    "data_header_int16_29",
    "data_header_int16_30",
    "data_header_int16_31",
    "data_header_int16_32",
    "data_header_int16_33",
    "data_header_int16_34",
    "data_header_int16_35",
    "data_header_int16_36",
    "data_header_int16_37",
    "data_header_int16_38",
    "data_header_int16_39",
    "data_header_int16_40",
    "data_header_int16_41",
    "data_header_int16_42",
    "data_header_int16_43",
    "data_header_int16_44",
    "data_header_int16_45",
    "data_header_int16_46",
    "data_header_int16_47",
    "data_header_int16_48",
    "data_header_int16_49",
    "period_seconds",
)


def _read_chars(infile, num):
    """Read characters from the (big-endian) file."""
    instr = infile.read(num)
    result = struct.unpack(">%ds" % num, instr)[0]
    result = result.decode()
    return result


[docs]class NimrodField: """ A data field from a NIMROD file. Capable of converting itself into a :class:`~iris.cube.Cube` References: Met Office (2003): Met Office Rain Radar Data from the NIMROD System. NCAS British Atmospheric Data Centre, date of citation. http://catalogue.ceda.ac.uk/uuid/82adec1f896af6169112d09cc1174499 """ def __init__(self, from_file=None): """ Create a NimrodField object and optionally read from an open file. Example:: with open("nimrod_file", "rb") as infile: field = NimrodField(infile) """ if from_file is not None: self.read(from_file)
[docs] def read(self, infile): """Read the next field from the given file object.""" self._read_header(infile) self._read_data(infile)
def _read_header_subset(self, infile, names, dtype): # Read contiguous header items of the same data type. values = np.fromfile(infile, dtype=dtype, count=len(names)) if sys.byteorder == "little": values.byteswap(True) for i, name in enumerate(names): setattr(self, name, values[i]) def _read_header(self, infile): """Load the 512 byte header (surrounded by 4-byte length).""" leading_length = struct.unpack(">L", infile.read(4))[0] if leading_length != 512: raise TranslationError("Expected header leading_length of 512") # general header (int16) elements 1-31 (bytes 1-62) self._read_header_subset(infile, general_header_int16s, np.int16) # general header (float32) elements 32-59 (bytes 63-174) self._read_header_subset(infile, general_header_float32s, np.float32) # skip unnamed floats infile.seek(4 * (28 - len(general_header_float32s)), os.SEEK_CUR) # data specific header (float32) elements 60-104 (bytes 175-354) self._read_header_subset(infile, data_header_float32s, np.float32) # skip unnamed floats infile.seek(4 * (45 - len(data_header_float32s)), os.SEEK_CUR) # data specific header (char) elements 105-107 (bytes 355-410) self.units = _read_chars(infile, 8) self.source = _read_chars(infile, 24) self.title = _read_chars(infile, 24) # data specific header (int16) elements 108- (bytes 411-512) self._read_header_subset(infile, data_header_int16s, np.int16) # skip unnamed int16s infile.seek(2 * (51 - len(data_header_int16s)), os.SEEK_CUR) trailing_length = struct.unpack(">L", infile.read(4))[0] if trailing_length != leading_length: raise TranslationError( "Expected header trailing_length of {}, " "got {}.".format(leading_length, trailing_length) ) def _read_data(self, infile): """ Read the data array: int8, int16, int32 or float32 (surrounded by 4-byte length, at start and end) """ # what are we expecting? num_data = int(self.num_rows) * int(self.num_cols) num_data_bytes = int(num_data) * int(self.datum_len) # format string for unpacking the file.read() # 0:real if self.datum_type == 0: numpy_dtype = np.float32 # 1:int elif self.datum_type == 1: if self.datum_len == 1: numpy_dtype = np.int8 elif self.datum_len == 2: numpy_dtype = np.int16 elif self.datum_len == 4: numpy_dtype = np.int32 else: raise TranslationError( "Undefined datum length " "%d" % self.datum_type ) # 2:byte elif self.datum_type == 2: numpy_dtype = np.byte else: raise TranslationError("Undefined data type") leading_length = struct.unpack(">L", infile.read(4))[0] if leading_length != num_data_bytes: raise TranslationError( "Expected data leading_length of %d" % num_data_bytes ) self.data = np.fromfile(infile, dtype=numpy_dtype, count=num_data) if sys.byteorder == "little": self.data.byteswap(True) trailing_length = struct.unpack(">L", infile.read(4))[0] if trailing_length != leading_length: raise TranslationError( "Expected data trailing_length of %d" % num_data_bytes ) # Form the correct shape. self.data = self.data.reshape(self.num_rows, self.num_cols)
[docs]def load_cubes(filenames, callback=None): """ Loads cubes from a list of NIMROD filenames. Args: * filenames - list of NIMROD filenames to load Kwargs: * callback - a function which can be passed on to :func:`iris.io.run_callback` .. note:: The resultant cubes may not be in the same order as in the files. """ if isinstance(filenames, str): filenames = [filenames] for filename in filenames: for path in glob.glob(filename): with open(path, "rb") as infile: while True: try: field = NimrodField(infile) except struct.error: # End of file. Move on to the next file. break cube = iris.fileformats.nimrod_load_rules.run(field) # Were we given a callback? if callback is not None: cube = iris.io.run_callback( callback, cube, field, filename ) if cube is None: continue yield cube