test_conf.py

"""Define tests for confidence calculation."""

import os  # noqa

import ancillary_data as anc
import numpy as np
import pytest
import xarray as xr

from mvcm import conf


@pytest.fixture
def fixturepath():
    """Define path."""
    return os.path.join(os.path.dirname(__file__), "fixtures")


@pytest.fixture
def rad():
    """Define dummy radiance array."""
    return np.arange(260, 282)


@pytest.fixture
def single_threshold():
    """Define dummy single thresholds."""
    return [267, 270, 273, 1]


@pytest.fixture
def double_threshold():
    """Define dummy double thresholds."""
    return [264, 267, 270, 273, 276, 279, 1]


@pytest.fixture
def reference_data(fixturepath):
    """Define reference file name."""
    return os.path.join(fixturepath, "ref_conf.npz")


def test_single_threshold(rad, single_threshold, reference_data):
    """Test single threshold compuputation."""
    ref_confidence = np.load(reference_data)["ref_sgl"]
    ref_confidence_flipped = np.load(reference_data)["ref_sgl_flipped"]

    c = conf.conf_test_new(rad, single_threshold)
    assert np.all(c == ref_confidence)

    single_threshold[0:-1] = single_threshold[-2::-1]
    c = conf.conf_test_new(rad, single_threshold)
    assert np.all(c == ref_confidence_flipped)


def test_double_threshold(rad, double_threshold, reference_data):
    """Test double threshold computation."""
    ref_confidence = np.load(reference_data)["ref_dbl"]
    ref_confidence_flipped = np.load(reference_data)["ref_dbl_flipped"]

    c = conf.conf_test_dble(rad, double_threshold)
    assert np.all(c == ref_confidence)

    double_threshold[0:-1] = double_threshold[-2::-1]
    c = conf.conf_test_dble(rad, double_threshold)
    assert np.all(c == ref_confidence_flipped)


def test_c_single_threshold(rad, single_threshold, reference_data):
    """Test C version of single threshold computation."""
    ref_confidence = np.load(reference_data)["ref_sgl"]
    ref_confidence_flipped = np.load(reference_data)["ref_sgl_flipped"]

    locut = np.full(np.shape(rad), single_threshold[0], dtype=np.float32)
    midpt = np.full(np.shape(rad), single_threshold[1], dtype=np.float32)
    hicut = np.full(np.shape(rad), single_threshold[2], dtype=np.float32)
    power = np.full(np.shape(rad), single_threshold[3], dtype=np.float32)

    c = anc.py_conf_test(np.array(rad, dtype=np.float32), locut, hicut, power, midpt)
    # NOTE: I have to use allclose() because the ref_confidence has been computed with doouble
    # precision and the C version returns single precision, which has some rounding differences
    assert np.allclose(c, ref_confidence)

    single_threshold[0:-1] = single_threshold[-2::-1]
    locut = np.full(np.shape(rad), single_threshold[0], dtype=np.float32)
    midpt = np.full(np.shape(rad), single_threshold[1], dtype=np.float32)
    hicut = np.full(np.shape(rad), single_threshold[2], dtype=np.float32)
    power = np.full(np.shape(rad), single_threshold[3], dtype=np.float32)

    c = anc.py_conf_test(np.array(rad, dtype=np.float32), locut, hicut, power, midpt)
    assert np.allclose(c, ref_confidence_flipped)


def test_xr_single_threshold(rad, single_threshold, reference_data):
    """Test xarray version of single threshold computation."""
    ref_confidence = np.load(reference_data)["ref_sgl"]
    ref_confidence_flipped = np.load(reference_data)["ref_sgl_flipped"]

    c = conf.asymm_confidence(xr.DataArray(rad), np.array(single_threshold))
    assert np.allclose(c.values, ref_confidence)

    single_threshold[0:-1] = single_threshold[-2::-1]
    c = conf.asymm_confidence(xr.DataArray(rad), np.array(single_threshold))
    assert np.allclose(c.values, ref_confidence_flipped)