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Rewrite tests with standard data and for pytest (comment #7 in PR #3572)
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@ThomasRieutord
ThomasRieutord committed Jul 31, 2024
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"""Testing program for the MetPy boundary layer module"""

import numpy as np

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Import of 'np' is not used.
from metpy.units import units
from metpy.calc import boundarylayer
import pandas as pd

import metpy.calc as mpcalc

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Module 'metpy.calc' is imported with both 'import' and 'import from'.
from metpy.calc import boundarylayer
from metpy.cbook import get_test_data
from metpy.units import units

# SAMPLE DATA
# ===========
col_names = ["pressure", "height", "temperature", "dewpoint", "direction", "speed"]

# Raw data
# --------
# Sample taken from a real radiosonding made at Trappes (France) the 2018-08-02 11:01

SAMPLE_HEIGHT = np.array(
[
189.95, 228.08, 282.48, 337.66, 380.98, 424.59, 456.27, 490.51,
525.4, 561.28, 595.6, 620.15, 654.14, 697.99, 742.43, 778.43,
820.95, 870.18, 916.58, 960.31, 1004.73, 1050.9, 1109.05, 1162.18,
1203.71, 1255.9, 1302.08, 1345.05, 1393.14, 1444.82, 1485.64, 1541.92,
1590.16, 1631.41, 1674.2, 1716.32, 1767.26, 1818.96, 1858.13, 1905.87,
1955.06, 2005.74, 2051.76, 2102.09, 2154.78, 2201.7, 2254.76, 2300.89,
2345.48, 2404.11, 2448.66, 2502.18, 2561.29, 2603.77, 2652.56,
2704.48, 2747.04, 2794.74, 2841.13, 2891.76, 2938.83, 2991.56,
3041.57, 3104.81, 3161.18, 3219.26, 3268.16, 3312.8, 3365.91, 3403.13,
3451.95, 3511.36, 3561.1, 3610.11, 3647.65, 3687.3, 3735.96, 3801.44,
3849.53, 3908.12, 3965.21, 4016.0, 4062.18, 4104.46, 4153.43, 4191.55,
4237.61, 4280.69, 4317.76, 4359.39, 4405.79, 4445.88, 4490.97, 4539.87,
4584.26, 4635.39, 4677.75, 4714.34, 4753.45, 4793.44
]
) * units.metres

SAMPLE_TEMPERATURE = np.array(
[
298.21, 299.87, 299.16, 298.61, 298.15, 297.7 , 297.37, 297.01,
296.57, 296.25, 295.93, 295.64, 295.36, 294.99, 294.54, 294.17,
293.78, 293.29, 292.9 , 292.41, 292.01, 291.55, 291.04, 290.8 ,
290.48, 290.04, 289.67, 289.26, 288.77, 288.33, 287.95, 287.42,
286.94, 286.54, 286.17, 285.8 , 285.36, 284.99, 284.72, 284.33,
283.85, 283.82, 284.01, 284.06, 285.07, 285.63, 285.7 , 285.58,
285.31, 284.99, 284.91, 284.72, 284.5 , 284.33, 284.16, 283.94,
283.67, 283.43, 283.19, 282.81, 282.48, 282.2 , 281.96, 281.79,
281.41, 280.92, 280.59, 280.17, 279.68, 279.38, 279.01, 278.71,
278.44, 278.43, 278.36, 278.25, 278.16, 277.54, 277.02, 276.45,
276.4 , 276.42, 276.26, 275.99, 275.65, 275.36, 274.97, 274.7 ,
274.5 , 274.29, 274.07, 273.88, 273.73, 273.46, 273.21, 272.78,
272.49, 272.33, 272.24, 272.46
]
) * units.kelvin

SAMPLE_PRESSURE = np.array(
[
1002.2, 997.9, 991.8, 985.6, 980.7, 975.8, 972.3, 968.5,
964.7, 960.7, 956.9, 954.2, 950.5, 945.7, 940.9, 937. ,
932.4, 927.1, 922.1, 917.5, 912.7, 907.8, 901.7, 896.1,
891.8, 886.4, 881.6, 877.1, 872.2, 866.9, 862.7, 857. ,
852.1, 848. , 843.7, 839.5, 834.4, 829.3, 825.4, 820.7,
815.9, 811. , 806.5, 801.6, 796.6, 792.1, 787.1, 782.8,
778.7, 773.2, 769.1, 764.2, 758.8, 754.9, 750.5, 745.9,
742.1, 737.8, 733.7, 729.3, 725.1, 720.5, 716.2, 710.7,
705.9, 700.9, 696.8, 693. , 688.6, 685.4, 681.4, 676.4,
672.3, 668.3, 665.2, 662. , 658.1, 652.8, 649. , 644.3,
639.8, 635.8, 632.1, 628.8, 625. , 622.1, 618.6, 615.3,
612.4, 609.3, 605.7, 602.7, 599.3, 595.7, 592.4, 588.6,
585.5, 582.8, 580. , 577.1
]
) * units.hPa

SAMPLE_U = np.array(
[
0. , -0.73, -1.5 , -0.59, -4.14, -4.51, -4.43, 2.96, -3.86,
-2.88, -5.79, -4.24, 0.58, -2.2 , 1.32, -7.32, -3.77, 2.55,
0.72, -1.2 , -6.18, 1.37, 1.58, 0.8 , -3.12, -0.15, -4.4 ,
-1.47, -4.68, 1.28, 5.19, -3. , -4.52, -2.9 , 3.09, 4.48,
-0.15, -2.97, -0.66, 0.57, 2.18, 0.31, -3.66, 1.06, 5.57,
-3.97, 1.53, 1.78, -3.44, -2.01, -0.88, 1.65, -0.61, 2.06,
4.27, 0.69, -3.39, 2.82, -0.58, -3.63, -2.08, -4.77, -4.05,
-3.07, 3.34, -6.44, -0.3 , 1.55, -3.61, -0.01, 4. , -4.53,
5.44, 3.21, 2.98, 4.87, 2.02, 2.42, 3.78, 0.89, -5.65,
-1.22, 4.81, -0.24, -0.72, 1.79, 3. , 2.38, 1.38, 6.35,
9.45, 3.71, -1.24, 2.25, 2.12, 2.8 , 5.71, 5.61, 6.78,
7.99
]
) * units.meter_per_second

SAMPLE_V = np.array(
[
-0.01, -1.56, -3.73, 7.87, -2.07, -1.8, -5.91, 3.86, -1.62, -2.82,
-2.19, -4.74, -5.87, 0.32, -3.34, -0.71, 4.32, -0.97, 3.56, 5.26,
2.46, -1.88, -4.58, -3.45, 2.76, -3.63, 1.13, 4.07, -2.67, -4.55,
2.43, -0.38, -1.97, -0.58, -2.32, -1.24, 2.76, -1.25, -2.11, 3.64,
-3.37, -3.37, 3.03, 4.87, -0.88, 0.25, 0.52, -6.89, -3.69, -0.01,
1.7, 0.47, 0.46, 0.03, 0.17, 1.4, 1.97, -1.81, 0.1, -5.69, -5.77,
-6.36, -6.09, -0.36, -1.96, -5.48, 1.39, -0.93, -3.39, -0.04, 1.71,
1.68, 1.59, -4.38, -2.79, -4.65, -1.84, -0.01, 3.58, -3.44, -4.42,
-8.27, -11.55, -10.06, -9.23, -9.33, -4.06, -5.7, -5.42, -5.49,
-6.71, -7.8, -4.16, -3.03, -8.58, -7.86, -4.35, -4.4, -4.45, -1.89
]
) * units.meter_per_second

SAMPLE_RELATIVE_HUMIDITY = np.array(
[
48.5, 45.2, 45. , 46. , 47.6, 48.2, 49.4, 50.5, 51.6, 52.4, 53.2,
54.4, 55.3, 55.5, 56.7, 58.2, 59. , 60.6, 61.2, 62.9, 64.4, 65.7,
66.7, 67.1, 66.6, 66.9, 67. , 67.7, 69.6, 71.6, 72.8, 73.3, 75.5,
76.9, 78.1, 79.4, 81.3, 82.1, 80.6, 80.8, 82.9, 76.9, 62.1, 57.6,
29.1, 24.4, 21.9, 28.3, 28.5, 28.2, 28.1, 27.1, 28.7, 28.7, 25.8,
31.3, 31.6, 33.9, 32.4, 37. , 40. , 40.9, 37.7, 37.2, 41. , 43.4,
44.8, 49. , 50.6, 52.8, 49.9, 46.4, 39.4, 28.3, 30.7, 26.7, 23.8,
41.3, 45. , 48.2, 27.7, 18. , 14.8, 16.1, 17.3, 16.4, 16.2, 15.7,
14.9, 14.8, 14.5, 13.4, 12.4, 14.6, 15.3, 15.5, 15.3, 14.7, 13.8,
11.7
]
) * units.percent


# Deduced data
# ------------
potential_temperature = mpcalc.potential_temperature(SAMPLE_PRESSURE, SAMPLE_TEMPERATURE)
dewpoint = mpcalc.dewpoint_from_relative_humidity(SAMPLE_TEMPERATURE, SAMPLE_RELATIVE_HUMIDITY)
specific_humidity = mpcalc.specific_humidity_from_dewpoint(SAMPLE_PRESSURE, dewpoint)
df = pd.read_fwf(
get_test_data("may4_sounding.txt", as_file_obj=False),

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skiprows=5,
usecols=[0, 1, 2, 3, 6, 7],
names=col_names,
)

# Drop any rows with all NaN values for T, Td, winds
df = df.dropna(
subset=("temperature", "dewpoint", "direction", "speed"), how="all"
).reset_index(drop=True)

height = df["height"].values * units.metres
pressure = df["pressure"].values * units.hPa
temperature = df["temperature"].values * units.degC
dewpoint = df["dewpoint"].values * units.degC
wind_speed = df["speed"].values * units.knots
wind_dir = df["direction"].values * units.degrees

u, v = mpcalc.wind_components(wind_speed, wind_dir)
relative_humidity = mpcalc.relative_humidity_from_dewpoint(temperature, dewpoint)
potential_temperature = mpcalc.potential_temperature(pressure, temperature)
specific_humidity = mpcalc.specific_humidity_from_dewpoint(pressure, dewpoint)


# BOUNDARY LAYER HEIGHT ESTIMATIONS
# =================================

blh = boundarylayer.blh_from_richardson_bulk(SAMPLE_HEIGHT, potential_temperature, SAMPLE_U, SAMPLE_V)
print(f"Estimated boundary layer height with blh_from_richardson_bulk:\t {blh}")
def test_blh_from_richardson_bulk():
blh = boundarylayer.blh_from_richardson_bulk(height, potential_temperature, u, v)
blh_true = 1397 * units.meter
assert blh == blh_true


blh = boundarylayer.blh_from_parcel(SAMPLE_HEIGHT, potential_temperature)
print(f"Estimated boundary layer height with blh_from_parcel:\t {blh}")
def test_blh_from_parcel():
blh = boundarylayer.blh_from_parcel(height, potential_temperature)
blh_true = 610 * units.meter
assert blh == blh_true

blh = boundarylayer.blh_from_humidity_gradient(SAMPLE_HEIGHT, SAMPLE_RELATIVE_HUMIDITY)
print(f"Estimated boundary layer height with blh_from_humidity_gradient (relative humidity):\t {blh}")

blh = boundarylayer.blh_from_humidity_gradient(SAMPLE_HEIGHT, specific_humidity)
print(f"Estimated boundary layer height with blh_from_humidity_gradient (specific humidity):\t {blh}")
def test_blh_from_concentration_gradient():
blh = boundarylayer.blh_from_concentration_gradient(height, specific_humidity)
blh_true = 1766 * units.meter
assert blh == blh_true

blh = boundarylayer.blh_from_temperature_inversion(SAMPLE_HEIGHT, SAMPLE_TEMPERATURE)
print(f"Estimated boundary layer height with blh_from_temperature_inversion (absolute temperature):\t {blh}")

blh = boundarylayer.blh_from_temperature_inversion(SAMPLE_HEIGHT, potential_temperature)
print(f"Estimated boundary layer height with blh_from_temperature_inversion (potential temperature):\t {blh}")
def test_blh_from_temperature_inversion():
blh = boundarylayer.blh_from_temperature_inversion(height, potential_temperature)
blh_true = 610 * units.meter
assert blh == blh_true

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