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Commit 396b459d authored by Niklas Selke's avatar Niklas Selke
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Added 'constants.py' which contains constants used throughout the different... 

Added 'constants.py' which contains constants used throughout the different modules. The 'check_statistics' function now returns a list.
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toarstats/constants.py 0 → 100644
View file @ 396b459d
"""Collection of constants.
This module contains the following constants:
ALLOWED_SAMPLING_VALUES - all possible values for the sampling argument
STATISTICS_LIST - list of all available statistics and metrics
CLIMATIC_ZONE - dictionary containing all available climatic zones
SEASON_DICT - mapping of season names to months
ALLOWED_CROPS_VALUES - all possible values for the crops argument
RSTAGS - mapping of aggregation type to resampling tag
"""
ALLOWED_SAMPLING_VALUES = [
"daily", "monthly", "seasonal", "vegseason", "summer", "xsummer", "annual"
]
STATISTICS_LIST = [
"aot40", "average_values", "avgdma8epax", "dark_aot40", "dark_avg",
"data_capture", "daylight_aot40", "daylight_avg", "daytime_avg",
"diurnal_cycle", "dma8epa", "dma8epa_strict", "dma8epax",
"dma8epax_strict", "dma8eu", "dma8eu_strict", "drmdmax1h", "m7_avg",
"max1h_values", "maximum", "median", "minimum", "nighttime_avg", "nvgt050",
"nvgt060", "nvgt070", "nvgt080", "nvgt090", "nvgt100", "nvgt120",
"nvgtall", "perc05", "perc10", "perc25", "perc75", "perc90", "perc95",
"perc98", "perc99", "percentiles1", "percentiles2", "somo10",
"somo10_strict", "somo35", "somo35_strict", "standard_deviation",
"value_count", "w126", "w126_24h", "w90"
]
CLIMATIC_ZONE = {
-1: "undefined", 0: "unclassified", 1: "warm temperate moist",
2: "warm temperate dry", 3: "cool temperate moist",
4: "cool temperate dry", 5: "polar moist", 6: "polar dry",
7: "boreal moist", 8: "boreal dry", 9: "tropical montane",
10: "tropical wet", 11: "tropical moist", 12: "tropical dry"
}
SEASON_DICT = {
"DJF": [12, 1, 2], "MAM": [3, 4, 5], "JJA": [6, 7, 8], "SON": [9, 10, 11],
"NH-Summer": [4, 5, 6, 7, 8, 9], "SH-Summer": [10, 11, 12, 1, 2, 3],
"NH-XSummer": [3, 4, 5, 6, 7, 8, 9],
"SH-XSummer": [9, 10, 11, 12, 1, 2, 3], "wheat-boreal_moist-NH": [6, 7, 8],
"wheat-boreal_dry-NH": [6, 7, 8],
"wheat-cool_temperate_moist-NH": [4, 5, 6],
"wheat-cool_temperate_dry-NH": [4, 5, 6],
"wheat-warm_temperate_moist-NH": [3, 4, 5],
"wheat-warm_temperate_dry-NH": [3, 4, 5],
"wheat-tropical_montane-NH": [1, 2, 3], "wheat-tropical_wet-NH": [1, 2, 3],
"wheat-tropical_moist-NH": [1, 2, 3], "wheat-tropical_dry-NH": [1, 2, 3],
"wheat-tropical_moist-SH": [7, 8, 9], "wheat-tropical_dry-SH": [8, 9, 10],
"wheat-warm_temperate_moist-SH": [8, 9, 10],
"wheat-warm_temperate_dry-SH": [8, 9, 10],
"wheat-cool_temperate_moist_le30-SH": [2, 3, 4],
"wheat-cool_temperate_dry_le30-SH": [2, 3, 4],
"wheat-cool_temperate_moist_gt30-SH": [11, 12, 1],
"wheat-cool_temperate_dry_gt30-SH": [11, 12, 1],
"rice-cool_temperate_moist-NH": [5, 6, 7],
"rice-cool_temperate_dry-NH": [5, 6, 7],
"rice-warm_temperate_moist-NH": [6, 7, 8],
"rice-warm_temperate_dry-NH": [6, 7, 8],
"rice-tropical_moist-NH": [7, 8, 9], "rice-tropical_montane-NH": [7, 8, 9],
"rice-tropical_wet-NH": [7, 8, 9], "rice-tropical_dry-NH": [8, 9, 10],
"rice-tropical_moist-SH": [12, 1, 2], "rice-tropical_wet-SH": [12, 1, 2],
"rice-tropical_dry-SH": [1, 2, 3],
"rice-warm_temperate_moist-SH": [11, 12, 1],
"rice-warm_temperate_dry-SH": [1, 2, 3],
"rice-cool_temperate_moist-SH": [12, 1, 2],
"rice-cool_temperate_dry-SH": [12, 1, 2], "Jan": [1], "Feb": [2],
"Mar": [3], "Apr": [4], "May": [5], "Jun": [6], "Jul": [7], "Aug": [8],
"Sep": [9], "Oct": [10], "Nov": [11], "Dec": [12]
}
ALLOWED_CROPS_VALUES = ["rice", "wheat"]
RSTAGS = {
"daily": "D", "monthly": "MS", "seasonal": "AS", "summer": "AS",
"xsummer": "AS", "annual": "AS"
}
toarstats/defaults.py
View file @ 396b459d
"""Collection of default values for the package.
"""Collection of default values.
This module contains the following constants:
DEFAULT_SEASONS - default list of seasons
......
toarstats/input_checks.py
View file @ 396b459d
......@@ -16,12 +16,8 @@ from collections import namedtuple
import numpy as np
import pandas as pd
from toarstats import ozone_metrics, stats
from toarstats.stats_utils import CLIMATIC_ZONE, RSTAGS, SEASON_DICT
SAMPLING_METHODS = ",".join(RSTAGS).replace("seasonal",
"seasonal,vegseason").split(",")
from toarstats.constants import (ALLOWED_CROPS_VALUES, ALLOWED_SAMPLING_VALUES,
CLIMATIC_ZONE, SEASON_DICT, STATISTICS_LIST)
def check_sampling(sampling_in):
......@@ -38,9 +34,9 @@ def check_sampling(sampling_in):
if not isinstance(sampling_in, str):
raise ValueError("The sampling argument must be a string")
sampling_out = sampling_in.strip()
if sampling_out not in SAMPLING_METHODS:
if sampling_out not in ALLOWED_SAMPLING_VALUES:
raise ValueError("The sampling argument must be one of"
f" {SAMPLING_METHODS}")
f" {ALLOWED_SAMPLING_VALUES}")
return sampling_out
......@@ -55,8 +51,7 @@ def check_statistics(statistics_in):
recognized or if the ``diurnal_cycle`` statistic
is not given alone
:return: A dictionary of statistics to calculate matched to their
respective function
:return: A list of statistics and metrics to calculate
"""
if not isinstance(statistics_in, (list, set, tuple, str)):
raise ValueError("The statistics argument must be a list, set, tuple"
......@@ -66,18 +61,18 @@ def check_statistics(statistics_in):
statistics_in_list = ([statistics_in]
if isinstance(statistics_in, str)
else list(statistics_in))
statistics_out = {}
statistics_out = []
for stat in statistics_in_list:
if not isinstance(stat, str):
raise ValueError("Statistics must be given as strings")
stat = stat.strip()
if stat in statistics_out:
continue
func = getattr(stats, stat, getattr(ozone_metrics, stat, None))
if func is not None:
statistics_out[stat] = func
if stat in STATISTICS_LIST:
statistics_out.append(stat)
else:
raise ValueError(f"{stat} is not a recognized statistic")
raise ValueError(f"{stat} is not a recognized statistic, available"
f" are {STATISTICS_LIST}")
if "diurnal_cycle" in statistics_out and len(statistics_out) > 1:
raise ValueError("Diurnal cycle can only be evaluated alone")
return statistics_out
......@@ -276,7 +271,8 @@ def check_seasons(seasons_in, seasons_req):
if season in SEASON_DICT:
seasons_out.append(season)
else:
raise ValueError(f"{season} is not a recognized season")
raise ValueError(f"{season} is not a recognized season, available"
f" are {SEASON_DICT}")
return seasons_out
......@@ -310,10 +306,11 @@ def check_crops(crops_in, crops_req):
crop = crop.strip()
if crop in crops_out:
continue
if crop in {"wheat", "rice"}:
if crop in ALLOWED_CROPS_VALUES:
crops_out.append(crop)
else:
raise ValueError(f"{crop} is not a recognized crop")
raise ValueError(f"{crop} is not a recognized crop, available are"
f" {ALLOWED_CROPS_VALUES}")
return crops_out
......
toarstats/stats_utils.py
View file @ 396b459d
"""Collection of dictionaries and helper functions for the package.
This module contains the following constants:
CLIMATIC_ZONE - dictionary containing all available climatic zones
RSTAGS - mapping of aggregation type to resampling tag
SEASON_DICT - mapping of season names to months
This module contains the following functions:
aot40stat - evaluate the sum of values above the given threshold
calc_data_capture - calculate the data capture fraction
......@@ -28,88 +23,10 @@ import datetime as dt
import numpy as np
import pandas as pd
from toarstats.constants import CLIMATIC_ZONE, RSTAGS, SEASON_DICT
from toarstats.solar_position import calc_zenith
CLIMATIC_ZONE = {-1: "undefined",
0: "unclassified",
1: "warm temperate moist",
2: "warm temperate dry",
3: "cool temperate moist",
4: "cool temperate dry",
5: "polar moist",
6: "polar dry",
7: "boreal moist",
8: "boreal dry",
9: "tropical montane",
10: "tropical wet",
11: "tropical moist",
12: "tropical dry"}
RSTAGS = {"daily": "D",
"monthly": "MS",
"seasonal": "AS",
"summer": "AS",
"xsummer": "AS",
"annual": "AS"}
SEASON_DICT = {"DJF": [12, 1, 2],
"MAM": [3, 4, 5],
"JJA": [6, 7, 8],
"SON": [9, 10, 11],
"NH-Summer": [4, 5, 6, 7, 8, 9],
"SH-Summer": [10, 11, 12, 1, 2, 3],
"NH-XSummer": [3, 4, 5, 6, 7, 8, 9],
"SH-XSummer": [9, 10, 11, 12, 1, 2, 3],
"wheat-boreal_moist-NH": [6, 7, 8],
"wheat-boreal_dry-NH": [6, 7, 8],
"wheat-cool_temperate_moist-NH": [4, 5, 6],
"wheat-cool_temperate_dry-NH": [4, 5, 6],
"wheat-warm_temperate_moist-NH": [3, 4, 5],
"wheat-warm_temperate_dry-NH": [3, 4, 5],
"wheat-tropical_montane-NH": [1, 2, 3],
"wheat-tropical_wet-NH": [1, 2, 3],
"wheat-tropical_moist-NH": [1, 2, 3],
"wheat-tropical_dry-NH": [1, 2, 3],
"wheat-tropical_moist-SH": [7, 8, 9],
"wheat-tropical_dry-SH": [8, 9, 10],
"wheat-warm_temperate_moist-SH": [8, 9, 10],
"wheat-warm_temperate_dry-SH": [8, 9, 10],
"wheat-cool_temperate_moist_le30-SH": [2, 3, 4],
"wheat-cool_temperate_dry_le30-SH": [2, 3, 4],
"wheat-cool_temperate_moist_gt30-SH": [11, 12, 1],
"wheat-cool_temperate_dry_gt30-SH": [11, 12, 1],
"rice-cool_temperate_moist-NH": [5, 6, 7],
"rice-cool_temperate_dry-NH": [5, 6, 7],
"rice-warm_temperate_moist-NH": [6, 7, 8],
"rice-warm_temperate_dry-NH": [6, 7, 8],
"rice-tropical_moist-NH": [7, 8, 9],
"rice-tropical_montane-NH": [7, 8, 9],
"rice-tropical_wet-NH": [7, 8, 9],
"rice-tropical_dry-NH": [8, 9, 10],
"rice-tropical_moist-SH": [12, 1, 2],
"rice-tropical_wet-SH": [12, 1, 2],
"rice-tropical_dry-SH": [1, 2, 3],
"rice-warm_temperate_moist-SH": [11, 12, 1],
"rice-warm_temperate_dry-SH": [1, 2, 3],
"rice-cool_temperate_moist-SH": [12, 1, 2],
"rice-cool_temperate_dry-SH": [12, 1, 2],
"Jan": [1],
"Feb": [2],
"Mar": [3],
"Apr": [4],
"May": [5],
"Jun": [6],
"Jul": [7],
"Aug": [8],
"Sep": [9],
"Oct": [10],
"Nov": [11],
"Dec": [12]}
def aot40stat(df, dfref, sampling, how, mincount=None, minfrac=0.75,
month_list=None, threshold=0.):
"""Evaluate the sum of values above the given threshold.
......
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