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scripts.py
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"""
Author: Wenyu Ouyang
Date: 2022-09-06 23:42:46
LastEditTime: 2024-11-11 16:44:31
LastEditors: Wenyu Ouyang
Description: examples for using hydrodataset
FilePath: \hydrodataset\examples\scripts.py
Copyright (c) 2021-2022 Wenyu Ouyang. All rights reserved.
"""
import os
import numpy as np
from hydrodataset import Camels
camels_aus_path = os.path.join("camels", "camels_aus")
camels_br_path = os.path.join("camels", "camels_br")
camels_cl_path = os.path.join("camels", "camels_cl")
camels_gb_path = os.path.join("camels", "camels_gb")
camels_us_path = os.path.join("camels", "camels_us")
camels_aus_v2_path = os.path.join("camels", "camels_aus_v2")
aus_v2_region = "AUS_v2"
aus_region = "AUS"
br_region = "BR"
cl_region = "CL"
gb_region = "GB"
us_region = "US"
# ------------------------------ US --------------------------------
# if files is not zipped, set download=True to unzip the files
camels_us = Camels(camels_us_path, download=False, region=us_region)
gage_ids = camels_us.read_object_ids()
flows = camels_us.read_target_cols(
gage_ids[:5], ["2013-01-01", "2014-01-01"], target_cols=["usgsFlow"]
)
print(flows)
gage_ids = camels_us.read_object_ids()
assert gage_ids.size == 671
attrs = camels_us.read_constant_cols(
gage_ids[:5], var_lst=["soil_conductivity", "elev_mean", "geol_1st_class"]
)
np.testing.assert_almost_equal(
attrs,
np.array(
[
[1.10652248, 250.31, 10.0],
[2.37500506, 92.68, 0.0],
[1.28980735, 143.8, 10.0],
[1.37329168, 247.8, 10.0],
[2.61515428, 310.38, 7.0],
]
),
)
forcings = camels_us.read_relevant_cols(
gage_ids[:5], ["1990-01-01", "2010-01-01"], var_lst=["dayl", "prcp", "srad"]
)
np.testing.assert_array_equal(forcings.shape, np.array([5, 7305, 3]))
flows = camels_us.read_target_cols(
gage_ids[:5], ["1990-01-01", "2010-01-01"], target_cols=["usgsFlow"]
)
np.testing.assert_array_equal(flows.shape, np.array([5, 7305, 1]))
streamflow_types = camels_us.get_target_cols()
np.testing.assert_array_equal(streamflow_types, np.array(["usgsFlow"]))
focing_types = camels_us.get_relevant_cols()
np.testing.assert_array_equal(
focing_types, np.array(["dayl", "prcp", "srad", "swe", "tmax", "tmin", "vp"])
)
attr_types = camels_us.get_constant_cols()
np.testing.assert_array_equal(
attr_types[:3], np.array(["gauge_lat", "gauge_lon", "elev_mean"])
)
# we highly recommend to cache the xrdataset for faster access
camels_us.cache_xrdataset()
forcings = camels_us.read_ts_xrdataset(
gage_id_lst=gage_ids[:5],
t_range=["2013-01-01", "2014-01-01"],
var_lst=["prcp", "srad", "tmax"],
)
flows = camels_us.read_ts_xrdataset(
gage_id_lst=gage_ids[:5],
t_range=["2013-01-01", "2014-01-01"],
# NOTE: the variable name is "streamflow" instead of "usgsFlow" after caching
var_lst=["streamflow"],
)
attrs = camels_us.read_attr_xrdataset(
gage_id_lst=gage_ids[:5],
var_lst=["soil_conductivity", "elev_mean", "geol_1st_class"],
)
# ------------------------------ AUS --------------------------------
camels_aus = Camels(camels_aus_path, download=False, region=aus_region)
gage_ids = camels_aus.read_object_ids()
assert gage_ids.size == 222
attrs = camels_aus.read_constant_cols(
gage_ids[:5], var_lst=["catchment_area", "slope_fdc", "geol_sec"]
)
np.testing.assert_array_equal(
attrs,
np.array(
[
[1.25773e04, 3.66793e-01, 6.00000e00],
[1.13929e04, 3.29998e-01, 6.00000e00],
[5.65300e02, 1.78540e-02, 6.00000e00],
[4.58300e02, 5.00234e-01, 6.00000e00],
[7.73170e03, 3.74751e-01, 1.00000e00],
]
),
)
forcings = camels_aus.read_relevant_cols(
gage_ids[:5],
["1990-01-01", "2010-01-01"],
# For the AUS region, there are two forcing types,
# but we didn't specify the forcing type in forcing_type argument,
# because it is more convenient to use the forcing_name directly.
# As one can see, all the forcing names have a postfix
var_lst=["precipitation_AWAP", "et_morton_actual_SILO", "tmin_SILO"],
)
np.testing.assert_array_equal(forcings.shape, np.array([5, 7305, 3]))
flows = camels_aus.read_target_cols(
gage_ids[:5],
["1990-01-01", "2010-01-01"],
target_cols=["streamflow_MLd", "streamflow_mmd"],
)
np.testing.assert_array_equal(flows.shape, np.array([5, 7305, 2]))
streamflow_types = camels_aus.get_target_cols()
np.testing.assert_array_equal(
streamflow_types,
np.array(
[
"streamflow_MLd",
"streamflow_MLd_inclInfilled",
"streamflow_mmd",
"streamflow_QualityCodes",
]
),
)
focing_types = camels_aus.get_relevant_cols()
np.testing.assert_array_equal(
np.sort(focing_types),
np.sort(
[
"precipitation_AWAP",
"precipitation_SILO",
"precipitation_var_AWAP",
"et_morton_actual_SILO",
"et_morton_point_SILO",
"et_morton_wet_SILO",
"et_short_crop_SILO",
"et_tall_crop_SILO",
"evap_morton_lake_SILO",
"evap_pan_SILO",
"evap_syn_SILO",
"solarrad_AWAP",
"tmax_AWAP",
"tmin_AWAP",
"vprp_AWAP",
"mslp_SILO",
"radiation_SILO",
"rh_tmax_SILO",
"rh_tmin_SILO",
"tmax_SILO",
"tmin_SILO",
"vp_deficit_SILO",
"vp_SILO",
]
),
)
attr_types = camels_aus.get_constant_cols()
np.testing.assert_array_equal(
attr_types[:3], np.array(["station_name", "drainage_division", "river_region"])
)
# # ---------------------------- AUS-V2 -------------------------------
camels_aus_v2 = Camels(camels_aus_v2_path, download=False, region=aus_v2_region)
gage_ids = camels_aus_v2.read_object_ids()
assert gage_ids.size == 561
attrs = camels_aus_v2.read_constant_cols(
gage_ids[:5], var_lst=["catchment_area", "geol_sec", "metamorph"]
)
print(attrs)
forcings = camels_aus_v2.read_relevant_cols(
gage_ids[:5],
["1990-01-01", "2010-01-01"],
var_lst=["precipitation_AGCD", "et_morton_actual_SILO", "tmin_SILO"],
)
print(forcings.shape)
flows = camels_aus_v2.read_target_cols(
gage_ids[:5],
["1990-01-01", "2010-01-01"],
target_cols=["streamflow_MLd", "streamflow_mmd"],
)
print(flows.shape)
streamflow_types = camels_aus_v2.get_target_cols()
print(streamflow_types)
focing_types = camels_aus_v2.get_relevant_cols()
print(focing_types)
attr_types = camels_aus_v2.get_constant_cols()
print(attr_types)
# ------------------------------ BR --------------------------------
camels_br = Camels(camels_br_path, download=False, region=br_region)
gage_ids = camels_br.read_object_ids()
assert gage_ids.size == 897
attrs = camels_br.read_constant_cols(
gage_ids[:5], var_lst=["geol_class_1st", "p_mean", "runoff_ratio"]
)
np.testing.assert_array_equal(
attrs,
np.array(
[
[8.0, 6.51179, 0.55336],
[6.0, 5.38941, 0.72594],
[6.0, 5.70191, 0.759],
[6.0, 5.19877, 0.39463],
[8.0, 5.49805, 0.38579],
]
),
)
forcings = camels_br.read_relevant_cols(
gage_ids[:5],
["1995-01-01", "2015-01-01"],
var_lst=[
"precipitation_chirps",
"evapotransp_gleam",
"potential_evapotransp_gleam",
"temperature_min_cpc",
],
)
np.testing.assert_array_equal(forcings.shape, np.array([5, 7305, 4]))
# start from 1995/01/01 end with 2017/04/30
flows = camels_br.read_target_cols(
gage_ids[:5],
["1995-01-01", "2015-01-01"],
target_cols=["streamflow_m3s", "streamflow_mm_selected_catchments"],
)
np.testing.assert_array_equal(flows.shape, np.array([5, 7305, 2]))
streamflow_types = camels_br.get_target_cols()
np.testing.assert_array_equal(
streamflow_types,
np.array(
[
"streamflow_m3s",
"streamflow_mm_selected_catchments",
"streamflow_simulated",
]
),
)
focing_types = camels_br.get_relevant_cols()
np.testing.assert_array_equal(
focing_types,
np.array(
[
"precipitation_chirps",
"precipitation_mswep",
"precipitation_cpc",
"evapotransp_gleam",
"evapotransp_mgb",
"potential_evapotransp_gleam",
"temperature_min_cpc",
"temperature_mean_cpc",
"temperature_max_cpc",
]
),
)
attr_types = camels_br.get_constant_cols()
np.testing.assert_array_equal(
attr_types[:3], np.array(["p_mean", "pet_mean", "et_mean"])
)
# ------------------------------ CL --------------------------------
camels_cl = Camels(camels_cl_path, download=False, region=cl_region)
gage_ids = camels_cl.read_object_ids()
assert gage_ids.size == 516
attrs = camels_cl.read_constant_cols(
gage_ids[:5], var_lst=["geol_class_1st", "crop_frac"]
)
np.testing.assert_almost_equal(
attrs,
np.array(
[
[9.0, 0.0],
[9.0, 0.014243],
[9.0, 0.020827],
[10.0, 0.1055],
[10.0, 0.0684],
]
),
decimal=4,
)
forcings = camels_cl.read_relevant_cols(
gage_ids[:5],
["1995-01-01", "2015-01-01"],
var_lst=["pet_8d_modis", "precip_cr2met", "swe"],
)
np.testing.assert_array_equal(forcings.shape, np.array([5, 7305, 3]))
flows = camels_cl.read_target_cols(
gage_ids[:5],
["1995-01-01", "2015-01-01"],
target_cols=["streamflow_m3s", "streamflow_mm"],
)
np.testing.assert_array_equal(flows.shape, np.array([5, 7305, 2]))
streamflow_types = camels_cl.get_target_cols()
np.testing.assert_array_equal(
streamflow_types, np.array(["streamflow_m3s", "streamflow_mm"])
)
focing_types = camels_cl.get_relevant_cols()
np.testing.assert_array_equal(
focing_types,
np.array(
[
"precip_cr2met",
"precip_chirps",
"precip_mswep",
"precip_tmpa",
"tmin_cr2met",
"tmax_cr2met",
"tmean_cr2met",
"pet_8d_modis",
"pet_hargreaves",
"swe",
]
),
)
attr_types = camels_cl.get_constant_cols()
np.testing.assert_array_equal(
attr_types[:3], np.array(["gauge_name", "gauge_lat", "gauge_lon"])
)
# ------------------------------ GB --------------------------------
camels_gb = Camels(camels_gb_path, download=False, region=gb_region)
gage_ids = camels_gb.read_object_ids()
assert gage_ids.size == 671
attrs = camels_gb.read_constant_cols(
gage_ids[:5], var_lst=["p_mean", "slope_fdc", "gauge_name"]
)
np.testing.assert_array_equal(
attrs,
np.array(
[
[2.29, 1.94, 596.0],
[2.31, 1.95, 670.0],
[2.65, 4.01, 647.0],
[2.31, 1.54, 393.0],
[2.29, 1.47, 217.0],
]
),
)
forcings = camels_gb.read_relevant_cols(
gage_ids[:5],
["1995-01-01", "2015-01-01"],
var_lst=["precipitation", "pet", "temperature", "peti"],
)
np.testing.assert_array_equal(forcings.shape, np.array([5, 7305, 4]))
flows = camels_gb.read_target_cols(
gage_ids[:5],
["1995-01-01", "2015-01-01"],
target_cols=["discharge_spec", "discharge_vol"],
)
np.testing.assert_array_equal(flows.shape, np.array([5, 7305, 2]))
streamflow_types = camels_gb.get_target_cols()
np.testing.assert_array_equal(
streamflow_types, np.array(["discharge_spec", "discharge_vol"])
)
focing_types = camels_gb.get_relevant_cols()
np.testing.assert_array_equal(
focing_types,
np.array(
[
"precipitation",
"pet",
"temperature",
"peti",
"humidity",
"shortwave_rad",
"longwave_rad",
"windspeed",
]
),
)
attr_types = camels_gb.get_constant_cols()
np.testing.assert_array_equal(
attr_types[:3], np.array(["p_mean", "pet_mean", "aridity"])
)