def ConsDaysOverOrLower(Data,Dates,Value,Comparation='Over'):
'''
DESCRIPTION:
This function calculates the number of consecutive days with
values over or lower a specific value and also gives the dates at
the beginning and end of evey season.
_______________________________________________________________________
INPUT:
+ Data: Data that needs to be counted.
+ Dates: Dates of the data, can be in datetime or string vector.
if the Dates are in a string vector it has to be in
yyyy/mm/dd.
+ Value: Value to search days over or lower.
+ Comparation: String with the comparation that is going to be
done.
It can recognize the following strings:
String | Interpretation
'Over', 'over' or '>' | >
'Lower', 'lower' or '<'| <
'>=' | >=
'<=' | <=
_______________________________________________________________________
OUTPUT:
The output is the dictionary results with the following keys:
- TotalNumDays: Vector with total number of consecutive days
above or below the value.
- TotalPrecCount: Vector with the total of values during the
different number of days, works with
precipitation, averages needs to be
determined manually.
- TotalDateB: Starting dates of the different events.
- MaxNumDays: Maximum number of consecutive days above
or below the value.
- MaxPrecCount_MaxDay: Maximum values in the maximum day.
- MaxNumDays_MaxPrec: Maximum days in the maximum values.
- DateMaxDays: Beginnig date of the maximum days count.
'''
# keys
keys = ['TotalNumDays','TotalPrecCount','TotalDateB','MaxNumDays',\
'MaxPrecCount','DateMaxDays','MaxPrecCount_MaxDay','MaxNumDays_MaxPrec']
# Determine operation
Comp = utl.Oper_Det(Comparation)
# ----------------
# Error managment
# ----------------
if Comp == -1:
return -1
# Dates Error managment
if isinstance(Dates[0],str):
DatesP = DUtil.Dates_str2datetime(Dates)
if list(DatesP)[0] == -1:
return -1
elif isinstance(DatesP[0],datetime):
Er = utl.ShowError('DaysOverOrLower','Hydro_Analysis','Dates are not in days')
return Er
else:
DatesP = Dates
if isinstance(DatesP[0],datetime):
Er = utl.ShowError('DaysOverOrLower','Hydro_Analysis','Dates are not in days')
return Er
# --------------
# Calculations
# --------------
results = dict()
results['TotalNumDays'] = [] # List with all the days
results['TotalPrecCount'] = [] # List for the total
results['TotalDateB'] = [] # List of dates
x = np.where(Comp(Data,Value))[0]
if len(x) > 1:
# Loop to calculate all the days
DaysCount = 1 # Days counter
PrecCount = Data[x[0]] # Value counter
for i in range(1,len(x)):
if x[i] == x[i-1]+1:
DaysCount += 1
PrecCount += Data[x[i]]
else:
results['TotalNumDays'].append(DaysCount)
results['TotalPrecCount'].append(PrecCount)
results['TotalDateB'].append(DatesP[x[i]-DaysCount])
DaysCount = 0
PrecCount = 0
if i == len(x)-1:
results['TotalNumDays'].append(DaysCount)
results['TotalPrecCount'].append(PrecCount)
results['TotalDateB'].append(DatesP[x[i]-DaysCount])
DaysCount = 0
PrecCount = 0
results['TotalNumDays'] = np.array(results['TotalNumDays'])
# Maximum number of days
results['MaxNumDays'] = np.max(results['TotalNumDays'])
x = np.where(results['TotalNumDays'] == results['MaxNumDays'])[0]
results['TotalPrecCount'] = np.array(results['TotalPrecCount'])
# Maximum value counter of number of days that was max
results['MaxPrecCount_MaxDay'] = np.max(results['TotalPrecCount'][x])
# Maximum value in those days
results['MaxPrecCount'] = np.max(results['TotalPrecCount'])
x = np.where(results['TotalPrecCount'] == results['MaxPrecCount'])[0]
# Maximum number of days of the maximum value
results['MaxNumDays_MaxPrec'] = np.max(results['TotalNumDays'][x])
# Beginning date of the maximum
results['TotalDateB'] = np.array(results['TotalDateB'])
xx = np.where(results['TotalNumDays'] == results['MaxNumDays'])[0]
results['DateMaxDays'] = results['TotalDateB'][xx]
else:
for ikey,key in enumerate(keys):
if ikey > 2:
results[key] = 0
else:
results[key] = np.array([0])
return results
def DaysOverOrLower(Data,Dates,Value,flagMonths=False,Comparation='Over'):
'''
DESCRIPTION:
This function calculates the days over or lower one specific value
in every year or month and year of the series.
_______________________________________________________________________
INPUT:
+ Data: Data that needs to be counted.
+ Dates: Dates of the data, can be in datetime or string vector.
if the Dates are in a string vector it has to be in
yyyy/mm/dd.
+ Value: Value to search days over or lower.
+ flagMonths: flag to know if the count would be monthly.
True: to make the count monthly.
False: to make the count annualy.
+ Comparation: String with the comparation that is going to be
done.
It can recognize the following strings:
String | Interpretation
'Over', 'over' or '>' | >
'Lower', 'lower' or '<'| <
'>=' | >=
'<=' | <=
_______________________________________________________________________
OUTPUT:
- results: number of days over or lower a value for every year or
month.
- An: Dates where the operation was made.
'''
# Determine operation
Comp = utl.Oper_Det(Comparation)
# ----------------
# Error managment
# ----------------
if Comp == -1:
return -1, -1
# Dates Error managment
if isinstance(Dates[0],str):
DatesP = DUtil.Dates_str2datetime(Dates)
if list(DatesP)[0] == -1:
return -1, -1
elif isinstance(DatesP[0],datetime):
Er = utl.ShowError('DaysOverOrLower','Hydro_Analysis','Dates are not in days')
return Er, Er
else:
DatesP = Dates
if isinstance(DatesP[0],datetime):
Er = utl.ShowError('DaysOverOrLower','Hydro_Analysis','Dates are not in days')
return Er, Er
# ----------------
# Dates managment
# ----------------
if flagMonths:
An = DUtil.Dates_datetime2str(DatesP,Date_Format='%Y/%m')
if list(An)[0] == -1:
return -1,-1
else:
An = DUtil.Dates_datetime2str(DatesP,Date_Format='%Y')
if list(An)[0] == -1:
return -1,-1
# ----------------
# Calculations
# ----------------
results = []
if flagMonths:
for i in range(DatesP[0].year,DatesP[-1].year+1):
for j in range(1,13):
if j < 10:
m = '%s/0%s' %(i,j)
else:
m = '%s/%s' %(i,j)
x = np.where(An == m)[0]
P = Data[x]
xx = np.where(Comp(P,Value))[0]
if sum(~np.isnan(P)) >= 0.70*len(P):
results.append(len(xx))
else:
results.append(np.nan)
else:
for i in range(DatesP[0].year,DatesP[-1].year+1):
x = np.where(An == str(i))[0]
P = Data[x]
xx = np.where(Comp(P,Value))[0]
if sum(~np.isnan(P)) >= 0.70*len(P):
results.append(len(xx))
else:
results.append(np.nan)
return results,An
