Runme01_Cal_stats.py

# %%
#5T 1H 6H 1D
#1H 3H 6H 1D
# datatime not datetime
import dotmap
from datetime import datetime as dt
from Library.Cal_stats_lib.utils.utils import *
from Library.Cal_stats_lib.utils.stats_calculation import *

args = yaml.load(open('./config/default.yaml'), Loader=yaml.FullLoader)
args = dotmap.DotMap(args)

# step 1 get the input
rawData = pd.read_csv('./01 Input_data/test.csv', index_col='datatime')
rawData.index = pd.to_datetime(rawData.index)
pDryThreshold=0.5

# step 1.5 check the value
if len(rawData.columns.values) != 1:
    print('the raw data have more than one column!! Check again!!')
else:
    rawData = rawData[rawData.columns.values[0]]
    ## delete all the negative number
    ## assign flags
    rawData = rawData.drop(rawData.index[rawData < 0.0])

# step 2 read which kind of property
prop = pd.read_csv(args.IO.config_path, index_col=0, header=None)
propertyList = prop.loc['prop'].dropna().to_numpy()
print('The used properties: {}'.format(propertyList))

# step 3 read the timescale
timeScaleList = prop.loc['time'].dropna().to_numpy()
meanTimeScale = prop.loc['timeForMean'].dropna().to_numpy()
outputMean = prop.loc['OutputTimeScaleForMean'].dropna().to_numpy()
print('The time scales: {}'.format(timeScaleList))
print('The time scale of Mean: {}'.format(meanTimeScale))
print(f'Output time scale for Mean: {outputMean}')

if outputMean[0] not in meanTimeScale.tolist():
    print('-'*50)
    print(f'Mean will not be calculated because {outputMean} is not in timeForMean, please choose the scale from timeForMean.')
    
# step 4-6 calculate and output statistical properties and their weights
createStatisticalFile(rawData, propertyList, timeScaleList, meanTimeScale, outputMean, args.IO.stats_file_path, args.IO.weight_file_path, pDryThreshold)


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