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f4a39ee | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 | # Copyright 2024 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Modules responsible for orography processing and initialization."""
from typing import Any, Callable, Mapping, Optional, Sequence
from dinosaur import coordinate_systems
from dinosaur import primitive_equations
from dinosaur import scales
from dinosaur import typing
from dinosaur import xarray_utils
import gin
import haiku as hk
import jax.numpy as jnp
import numpy as np
units = scales.units
OrographyModule = Callable[..., typing.Array]
FilterModule = Callable[..., typing.PyTreeFilterFn]
@gin.register
class ClippedOrography(hk.Module):
"""Module that initializes orography by converting to modal and clipping."""
def __init__(
self,
coords: coordinate_systems.CoordinateSystem,
dt: float,
physics_specs: Any,
aux_features: typing.AuxFeatures,
wavenumbers_to_clip: int = 1,
name: Optional[str] = None,
):
del dt, physics_specs
super().__init__(name=name)
self.coords = coords
self.wavenumbers_to_clip = wavenumbers_to_clip
self.nodal_orography = aux_features.get(
xarray_utils.OROGRAPHY, np.zeros(coords.horizontal.nodal_shape))
def __call__(self) -> typing.Array:
"""Returns orography converted to modal representation with clipping."""
return primitive_equations.truncated_modal_orography(
self.nodal_orography, self.coords, self.wavenumbers_to_clip)
@gin.register
class FilteredCustomOrography(hk.Module):
"""Module that initializes orography from external data."""
def __init__(
self,
coords: coordinate_systems.CoordinateSystem,
dt: float,
physics_specs: Any,
aux_features: typing.AuxFeatures,
orography_data_path: str,
filter_modules: Sequence[FilterModule] = tuple(),
renaming_dict: Optional[Mapping[str, str]] = None,
name: Optional[str] = None,
):
super().__init__(name=name)
ds = xarray_utils.ds_from_path_or_aux(orography_data_path, aux_features)
if renaming_dict is not None:
ds = ds.rename(renaming_dict)
nodal_orography = xarray_utils.nodal_orography_from_ds(ds)
# TODO(dkochkov) Insist on having units specified in variable attrs.
self.nodal_orography = physics_specs.nondimensionalize(
nodal_orography * units.meter) # pyrefly: ignore[unsupported-operation]
self.coords = coords
# Note: here we explicitly use linear truncation to preserve full signal.
# Smoothing is then achieved by interpolation to self.coords and filtering.
self.input_coords = xarray_utils.coordinate_system_from_dataset(
ds, truncation=xarray_utils.LINEAR, spmd_mesh=coords.spmd_mesh,
spherical_harmonics_impl=self.coords.horizontal.spherical_harmonics_impl
)
self.filter_fns = [
module(coords, dt, physics_specs, aux_features)
for module in filter_modules]
def __call__(self) -> typing.Array:
"""Returns orography converted to modal representation with filtering."""
return primitive_equations.filtered_modal_orography(
self.nodal_orography, self.coords, self.input_coords, self.filter_fns)
@gin.register
class LearnedOrography(hk.Module):
"""Module that uses learned parameters to correct orography."""
def __init__(
self,
coords: coordinate_systems.CoordinateSystem,
dt: float,
physics_specs: Any,
aux_features: typing.AuxFeatures,
base_orography_module: OrographyModule,
correction_scale: float,
name: Optional[str] = None,
):
super().__init__(name=name)
self.coords = coords
self.base_orography_fn = base_orography_module(
coords, dt, physics_specs, aux_features)
self.scale = correction_scale
# coords.horizontal.modal_shape can change based upon the required amount of
# padding for a particular implementation of spherical harmonics, but the
# mask should always have the same number of non-zero elements in the same
# order.
self.correction = hk.get_parameter(
'orography', (coords.horizontal.mask.sum(),), jnp.float32,
init=hk.initializers.Constant(0.0))
def __call__(self) -> typing.Array:
"""Returns orography in modal representation."""
mask = self.coords.horizontal.mask
correction_2d = jnp.zeros(self.coords.horizontal.modal_shape)
correction_2d = correction_2d.at[mask].set(self.correction)
return self.base_orography_fn() + correction_2d * self.scale # pytype: disable=not-callable # jax-ndarray
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