def format_to_monthly_dict(values):
"""
Format array of values into a dictionary with monthly keys.
Parameters
----------
values: list
List containing lists of monthly values; shape is n x 12
Returns
-------
values_dict : dictionary
Dictionary containing monthly keys with corresponding values.
Notes
-----
{
"January": [2.0, 1.0],
"February": [0.98, 0.99],
"March": [0.97, 1.10],
"April": [1.04, 1.02],
"May": [1.10, 0.99],
"June": [0.99, 0.98],
"July": [0.87, 0.75],
"August": [0.75, 0.95],
"September": [0.95, 0.9],
"October": [0.98, 0.8],
"November": [1.10, 1.05],
"December": [2.0, 1.10]
}
"""
assert np.shape(values)[1] == 12
months = [
"January", "February", "March", "April", "May", "June", "July",
"August", "September", "October", "November", "December"
]
values_dict = helpers.create_monthly_dict()
month_enum_list = list(enumerate(months))
for values_list in values:
for index, month in month_enum_list:
values_dict[month].append(values_list[index])
return values_dict
def format_to_monthly_dict(values):
"""
Format array of values into a dictionary with monthly keys.
Parameters
----------
values: list
List containing lists of monthly values; shape is n x 12
Returns
-------
values_dict : dictionary
Dictionary containing monthly keys with corresponding values.
Notes
-----
{
"January": [2.0, 1.0],
"February": [0.98, 0.99],
"March": [0.97, 1.10],
"April": [1.04, 1.02],
"May": [1.10, 0.99],
"June": [0.99, 0.98],
"July": [0.87, 0.75],
"August": [0.75, 0.95],
"September": [0.95, 0.9],
"October": [0.98, 0.8],
"November": [1.10, 1.05],
"December": [2.0, 1.10]
}
"""
assert np.shape(values)[1] == 12
months = ["January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December"]
values_dict = helpers.create_monthly_dict()
month_enum_list = list(enumerate(months))
for values_list in values:
for index, month in month_enum_list:
values_dict[month].append(values_list[index])
return values_dict
def calculate_avg_delta_values(deltas_data, tile_list):
"""
Get monthly averaged delta data values for a specific list of tiles.
Parameters
----------
delta_data : list
List of dictionaries holding data from delta data files.
Returns
-------
avg_delta_values : dictionary
Dictionary keys corresponding to delta variable type (i.e. precipitation (Ppt)) holding averaged data values for a specific list of tiles.
Notes
-----
avg_delta_values = {
"Ppt": {
"January": 2.0,
"February": 0.98,
"March": 0.97,
"April": 1.04,
"May": 1.10,
"June": 0.99,
"July": 0.87,
"August": 0.75,
"September": 0.95,
"October": 0.98,
"November": 1.10,
"December": 2.0
}
}
"""
# check that each tile in tile list is contained in the deltas_data
for tile in tile_list:
if tile not in deltas_data["Tile"]:
raise ValueError, "Tile {} is not contined in deltas_data".format(
tile)
# initialize avg_delta_values with keys corresponding to variable type
avg_delta_values = {}
variable_type = deltas_data["Variable"]
avg_delta_values[variable_type] = helpers.create_monthly_dict()
# get delta values that correspond to a list of tiles
values = get_monthly_values(deltas_data, tile_list=tile_list)
# format the values into a dictionary containing monthly keys
values_dict = format_to_monthly_dict(values)
# compute average of delta values for each month and put it in avg_delta_values
for key, value in values_dict.iteritems():
avg_value = np.average(value)
avg_delta_values[variable_type][key] = avg_value
return avg_delta_values
def calculate_avg_delta_values(deltas_data, tile_list):
"""
Get monthly averaged delta data values for a specific list of tiles.
Parameters
----------
delta_data : list
List of dictionaries holding data from delta data files.
Returns
-------
avg_delta_values : dictionary
Dictionary keys corresponding to delta variable type (i.e. precipitation (Ppt)) holding averaged data values for a specific list of tiles.
Notes
-----
avg_delta_values = {
"Ppt": {
"January": 2.0,
"February": 0.98,
"March": 0.97,
"April": 1.04,
"May": 1.10,
"June": 0.99,
"July": 0.87,
"August": 0.75,
"September": 0.95,
"October": 0.98,
"November": 1.10,
"December": 2.0
}
}
"""
# check that each tile in tile list is contained in the deltas_data
for tile in tile_list:
if tile not in deltas_data["Tile"]:
raise ValueError, "Tile {} is not contined in deltas_data".format(tile)
# initialize avg_delta_values with keys corresponding to variable type
avg_delta_values = {}
variable_type = deltas_data["Variable"]
avg_delta_values[variable_type] = helpers.create_monthly_dict()
# get delta values that correspond to a list of tiles
values = get_monthly_values(deltas_data, tile_list = tile_list)
# format the values into a dictionary containing monthly keys
values_dict = format_to_monthly_dict(values)
# compute average of delta values for each month and put it in avg_delta_values
for key, value in values_dict.iteritems():
avg_value = np.average(value)
avg_delta_values[variable_type][key] = avg_value
return avg_delta_values
