def calc_winter_highflow_POR(matrix, exceedance_percent):
exceedance_object = {}
exceedance_value = {}
current_flow_object = {}
freq = {}
duration = {}
timing = {}
magnitude = {}
average_annual_flow = np.nanmedian(matrix)
for i in exceedance_percent:
exceedance_value[i] = np.nanpercentile(matrix, 100 - i)
exceedance_object[i] = []
current_flow_object[i] = None
freq[i] = 0
duration[i] = []
timing[i] = []
magnitude[i] = []
for column_number, flow_column in enumerate(matrix[0]):
for row_number, flow_row in enumerate(matrix[:, column_number]):
for percent in exceedance_percent:
if flow_row < exceedance_value[percent] and current_flow_object[
percent] or row_number == len(
matrix[:, column_number]
) - 1 and current_flow_object[percent]:
"""End of a object if it falls below threshold, or end of column"""
current_flow_object[percent].end_date = row_number + 1
duration[percent].append(
current_flow_object[percent].duration)
magnitude[percent].append(
max(current_flow_object[percent].flow) /
average_annual_flow)
current_flow_object[percent] = None
elif flow_row >= exceedance_value[percent]:
if not current_flow_object[percent]:
"""Begining of a object"""
exceedance_object[percent].append(
FlowExceedance(row_number + 1, None, 1, percent))
current_flow_object[percent] = exceedance_object[
percent][-1]
current_flow_object[percent].add_flow(flow_row)
timing[percent].append(row_number + 1)
freq[percent] = freq[percent] + 1
else:
"""Continue of a object"""
current_flow_object[percent].add_flow(flow_row)
current_flow_object[
percent].duration = current_flow_object[
percent].duration + 1
return timing, duration, freq, magnitude
def calc_winter_highflow_annual(matrix, exceedance_percent, winter_params = def_winter_params):
params = set_user_params(winter_params, def_winter_params)
max_zero_allowed_per_year, max_nan_allowed_per_year = params.values()
"""Get peak percentiles calculated from each year's peak flow values"""
peak_flows = []
peak_percentiles = [2,5,10,20,50] # for peak flow metrics
high_percentiles = [2,5,10,20] # for high flow metrics
peak_exceedance_values = []
highflow_exceedance_values = []
for column_number, _ in enumerate(matrix[0]):
flow_data = matrix[:, column_number]
peak_flows.append(np.nanmax(flow_data))
for percentile in peak_percentiles:
peak_exceedance_values.append(np.nanpercentile(peak_flows, 100 - percentile))
"""Add high flow percentiles and peak flow exceedance vals together for final list of exceedance values"""
highflow_exceedance_values = []
for i in high_percentiles:
highflow_exceedance_values.append(np.nanpercentile(matrix, 100 - i))
exceedance_values = peak_exceedance_values + highflow_exceedance_values # five peak exceedance vals plus four high flow exceedance vals
exceedance_value = {}
freq = {}
duration = {}
timing = {}
magnitude = {}
peak_magnitude = {}
for i, value in enumerate(exceedance_values):
exceedance_value[i] = value
freq[i] = []
duration[i] = []
timing[i] = []
magnitude[i] = []
peak_magnitude[i] = []
for column_number, flow_column in enumerate(matrix[0]):
if np.isnan(matrix[:, column_number]).sum() > max_nan_allowed_per_year or np.count_nonzero(matrix[:, column_number] == 0) > max_zero_allowed_per_year:
for i, value in enumerate(exceedance_values):
freq[i].append(None)
duration[i].append(None)
timing[i].append(None)
magnitude[i].append(None)
peak_magnitude[i].append(None)
continue
exceedance_object = {}
exceedance_duration = {}
current_flow_object = {}
peak_flow = {}
"""Init current flow object"""
for i, value in enumerate(exceedance_values):
exceedance_object[i] = []
exceedance_duration[i] = []
current_flow_object[i] = None
peak_flow[i] = []
"""Loop through each flow value for the year to check if they pass exceedance threshold"""
for row_number, flow_row in enumerate(matrix[:, column_number]):
for i, value in enumerate(exceedance_values):
if bool(flow_row < exceedance_value[i] and current_flow_object[i]) or bool(row_number == len(matrix[:, column_number]) - 1 and current_flow_object[i]):
"""End of an object if it falls below threshold, or end of column"""
current_flow_object[i].end_date = row_number + 1
current_flow_object[i].get_max_magnitude()
exceedance_duration[i].append(current_flow_object[i].duration)
peak_flow[i] = np.nanmax(flow_row)
current_flow_object[i] = None
elif flow_row >= exceedance_value[i]:
if not current_flow_object[i]:
"""Beginning of an object"""
exceedance_object[i].append(
FlowExceedance(row_number, None, 1, i))
current_flow_object[i] = exceedance_object[i][-1]
current_flow_object[i].add_flow(flow_row)
else:
"""Continuing an object"""
current_flow_object[i].add_flow(flow_row)
current_flow_object[i].duration = current_flow_object[i].duration + 1
for i, value in enumerate(exceedance_values):
freq[i].append(None if len(exceedance_object[i])==0 else len(exceedance_object[i]))
duration[i].append(
None if np.nansum(exceedance_duration[i])==0 else np.nansum(exceedance_duration[i]) if not np.isnan(np.nansum(exceedance_duration[i])) else None)
timing[i].append(median_of_time(exceedance_object[i]))
magnitude[i].append(exceedance_value[i])
_timing = {2: timing[0], 5: timing[1], 10: timing[2], 20: timing[3], 50: timing[4], 12: timing[5], 15: timing[6], 110: timing[7], 120: timing[8],}
_duration = {2: duration[0], 5: duration[1], 10: duration[2], 20: duration[3], 50: duration[4], 12: duration[5], 15: duration[6], 110: duration[7], 120: duration[8],}
_freq = {2: freq[0], 5: freq[1], 10: freq[2], 20: freq[3], 50: freq[4], 12: freq[5], 15: freq[6], 110: freq[7], 120: freq[8],}
_magnitude = {2: magnitude[0], 5: magnitude[1], 10: magnitude[2], 20: magnitude[3], 50: magnitude[4], 12: magnitude[5], 15: magnitude[6], 110: magnitude[7], 120: magnitude[8],}
return _timing, _duration, _freq, _magnitude
def calc_winter_highflow_annual(matrix, exceedance_percent, winter_params=def_winter_params):
max_nan_allowed_per_year = winter_params['max_nan_allowed_per_year']
max_zero_allowed_per_year = winter_params['max_zero_allowed_per_year']
exceedance_value = {}
freq = {}
duration = {}
timing = {}
magnitude = {}
for i in exceedance_percent:
exceedance_value[i] = np.nanpercentile(matrix, 100 - i)
freq[i] = []
duration[i] = []
timing[i] = []
magnitude[i] = []
for column_number, flow_column in enumerate(matrix[0]):
if np.isnan(matrix[:, column_number]).sum() > max_nan_allowed_per_year or np.count_nonzero(matrix[:, column_number] == 0) > max_zero_allowed_per_year:
for percent in exceedance_percent:
freq[percent].append(None)
duration[percent].append(None)
timing[percent].append(None)
magnitude[percent].append(None)
continue
exceedance_object = {}
exceedance_duration = {}
current_flow_object = {}
"""Init current flow object"""
for percent in exceedance_percent:
exceedance_object[percent] = []
exceedance_duration[percent] = []
current_flow_object[percent] = None
"""Loop through each flow value for the year to check if they pass exceedance threshold"""
for row_number, flow_row in enumerate(matrix[:, column_number]):
for percent in exceedance_percent:
if bool(flow_row < exceedance_value[percent] and current_flow_object[percent]) or bool(row_number == len(matrix[:, column_number]) - 1 and current_flow_object[percent]):
"""End of an object if it falls below threshold, or end of column"""
current_flow_object[percent].end_date = row_number + 1
current_flow_object[percent].get_max_magnitude()
exceedance_duration[percent].append(
current_flow_object[percent].duration)
current_flow_object[percent] = None
elif flow_row >= exceedance_value[percent]:
if not current_flow_object[percent]:
"""Beginning of an object"""
exceedance_object[percent].append(
FlowExceedance(row_number, None, 1, percent))
current_flow_object[percent] = exceedance_object[percent][-1]
current_flow_object[percent].add_flow(flow_row)
else:
"""Continuing an object"""
current_flow_object[percent].add_flow(flow_row)
current_flow_object[percent].duration = current_flow_object[percent].duration + 1
for percent in exceedance_percent:
freq[percent].append(len(exceedance_object[percent]))
duration[percent].append(
np.nanmedian(exceedance_duration[percent]) if not np.isnan(np.nanmedian(exceedance_duration[percent])) else None)
timing[percent].append(median_of_time(exceedance_object[percent]))
magnitude[percent].append(exceedance_value[percent])
return timing, duration, freq, magnitude