Source code for improver.standardise
# -*- coding: utf-8 -*-
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"""Plugin to standardise metadata"""
from typing import Any, Dict, List, Optional
import numpy as np
from iris.coords import CellMethod
from iris.cube import Cube, CubeList
from iris.exceptions import CoordinateNotFoundError
from numpy import dtype, ndarray
from improver import BasePlugin
from improver.metadata.amend import amend_attributes
from improver.metadata.check_datatypes import (
check_units,
get_required_dtype,
get_required_units,
)
from improver.metadata.constants.time_types import TIME_COORDS
from improver.utilities.round import round_close
[docs]class StandardiseMetadata(BasePlugin):
"""Plugin to standardise cube metadata"""
[docs] @staticmethod
def _rm_air_temperature_status_flag(cube: Cube) -> Cube:
"""
Remove air_temperature status_flag coord by applying as NaN to cube data.
See https://github.com/metoppv/improver/pull/1839 for further details.
"""
coord_name = "air_temperature status_flag"
try:
coord = cube.coord(coord_name)
except CoordinateNotFoundError:
coord = None
if coord:
if coord.attributes != {
"flag_meanings": "above_surface_pressure below_surface_pressure",
"flag_values": np.array([0, 1], dtype="int8"),
}:
raise ValueError(
f"'{coord_name}' coordinate is not of the expected form."
)
ncube = CubeList()
for cc in cube.slices_over("realization"):
coord = cc.coord(coord_name)
if np.ma.is_masked(coord.points):
raise ValueError(
f"'{coord_name}' coordinate has unexpected mask values."
)
mask = np.asarray(coord.points)
cc.data[mask.astype(bool)] = np.nan
cc.remove_coord(coord_name)
ncube.append(cc)
cube = ncube.merge_cube()
return cube
[docs] @staticmethod
def _collapse_scalar_dimensions(cube: Cube) -> Cube:
"""
Demote any scalar dimensions (excluding "realization") on the input
cube to auxiliary coordinates.
Args:
cube: The cube
Returns:
The collapsed cube
"""
coords_to_collapse = []
for coord in cube.coords(dim_coords=True):
if len(coord.points) == 1 and "realization" not in coord.name():
coords_to_collapse.append(coord)
for coord in coords_to_collapse:
cube = next(cube.slices_over(coord))
return cube
[docs] @staticmethod
def _remove_scalar_coords(cube: Cube, coords_to_remove: List[str]) -> None:
"""Removes named coordinates from the input cube."""
for coord in coords_to_remove:
try:
cube.remove_coord(coord)
except CoordinateNotFoundError:
continue
[docs] @staticmethod
def _standardise_dtypes_and_units(cube: Cube) -> None:
"""
Modify input cube in place to conform to mandatory dtype and unit
standards.
Args:
cube:
Cube to be updated in place
"""
def as_correct_dtype(obj: ndarray, required_dtype: dtype) -> ndarray:
"""
Returns an object updated if necessary to the required dtype
Args:
obj:
The object to be updated
required_dtype:
The dtype required
Returns:
The updated object
"""
if obj.dtype != required_dtype:
return obj.astype(required_dtype)
return obj
cube.data = as_correct_dtype(cube.data, get_required_dtype(cube))
for coord in cube.coords():
if coord.name() in TIME_COORDS and not check_units(coord):
coord.convert_units(get_required_units(coord))
req_dtype = get_required_dtype(coord)
# ensure points and bounds have the same dtype
if np.issubdtype(req_dtype, np.integer):
coord.points = round_close(coord.points)
coord.points = as_correct_dtype(coord.points, req_dtype)
if coord.has_bounds():
if np.issubdtype(req_dtype, np.integer):
coord.bounds = round_close(coord.bounds)
coord.bounds = as_correct_dtype(coord.bounds, req_dtype)
[docs] @staticmethod
def _discard_redundant_cell_methods(cube: Cube) -> None:
"""
Removes cell method "point": "time" from cube if present.
"""
if not cube.cell_methods:
return
removable_cms = [
CellMethod(method="point", coords="time"),
]
updated_cms = []
for cm in cube.cell_methods:
if cm in removable_cms:
continue
updated_cms.append(cm)
cube.cell_methods = updated_cms
[docs] def process(
self,
cube: Cube,
new_name: Optional[str] = None,
new_units: Optional[str] = None,
coords_to_remove: Optional[List[str]] = None,
attributes_dict: Optional[Dict[str, Any]] = None,
) -> Cube:
"""
Perform compulsory and user-configurable metadata adjustments. The
compulsory adjustments are:
- to collapse any scalar dimensions apart from realization (which is expected
always to be a dimension);
- to cast the cube data and coordinates into suitable datatypes;
- to convert time-related metadata into the required units
- to remove cell method ("point": "time").
Args:
cube:
Input cube to be standardised
new_name:
Optional rename for output cube
new_units:
Optional unit conversion for output cube
coords_to_remove:
Optional list of scalar coordinates to remove from output cube
attributes_dict:
Optional dictionary of required attribute updates. Keys are
attribute names, and values are the required value or "remove".
Returns:
The processed cube
"""
cube = self._rm_air_temperature_status_flag(cube)
cube = self._collapse_scalar_dimensions(cube)
if new_name:
cube.rename(new_name)
if new_units:
cube.convert_units(new_units)
if coords_to_remove:
self._remove_scalar_coords(cube, coords_to_remove)
if attributes_dict:
amend_attributes(cube, attributes_dict)
self._discard_redundant_cell_methods(cube)
# this must be done after unit conversion as if the input is an integer
# field, unit conversion outputs the new data as float64
self._standardise_dtypes_and_units(cube)
return cube