def errvar_test():
import os
from pyemu import ErrVar
w_dir = os.path.join("..", "verification", "henry")
forecasts = ["pd_ten", "c_obs10_2"]
ev = ErrVar(jco=os.path.join(w_dir, "pest.jcb"), forecasts=forecasts)
print(ev.prior_forecast)
print(ev.get_errvar_dataframe())
def __init__(self, jco, par_info_file=None):
"""Computes parameter identifiability for a PEST jco file,
using the ErrVar class in pyemu (https://github.com/jtwhite79/pyemu)
"""
self._Pest = Pest(jco, par_info_file=par_info_file)
self.parinfo = self._Pest.parinfo
self.la = ErrVar(jco)
self.parinfo = None
if par_info_file is not None:
self.parinfo = pd.read_csv(par_info_file, index_col='Name')
self.ident_df = None
def errvar_test_nonpest():
import numpy as np
from pyemu import ErrVar, Matrix, Cov
#non-pest
pnames = ["p1","p2","p3"]
onames = ["o1","o2","o3","o4"]
npar = len(pnames)
nobs = len(onames)
j_arr = np.random.random((nobs,npar))
jco = Matrix(x=j_arr,row_names=onames,col_names=pnames)
parcov = Cov(x=np.eye(npar),names=pnames)
obscov = Cov(x=np.eye(nobs),names=onames)
forecasts = "o2"
omitted = "p3"
e = ErrVar(jco=jco,parcov=parcov,obscov=obscov,forecasts=forecasts,
omitted_parameters=omitted)
svs = [0,1,2,3,4,5]
print(e.get_errvar_dataframe(svs))
