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import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import os
from glob import glob
from importlib import reload
import sowfa_precursor
sowfa_precursor = reload(sowfa_precursor)
%matplotlib inline

Creat sowfa_precursor object and enter neccisary user inputs



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perInf_15_5 =  sowfa_precursor.Sim(
    dir='/projects/windsim/mlawson/wake_steering/stableABLRuns/infPer_0.15m_5m',
    log='log.1qm.ABLSolver',
    time_dir='0',
    avg_time=29000,
    avg_width=2000,
    z_level=90.0)
perInf_15_5.input['heights'] = np.array([0,1/2,1,3/2,2,3,4,5])*perInf_15_5.input['windHeight']

Make Plots



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perInf_15_5.theta_w_avg_cell()



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perInf_15_5.Umean_avg_nonnormalized()



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perInf_15_5.Tmean_avg_nonnormalized()



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perInf_15_5.variances_avg_cell()