def schur_test():
import os
from pyemu import Schur
w_dir = os.path.join("..","..","verification","henry")
forecasts = ["pd_ten","c_obs10_2"]
sc = Schur(jco=os.path.join(w_dir,"pest.jcb"),forecasts=forecasts)
print(sc.prior_forecast)
print(sc.posterior_forecast)
print(sc.get_contribution_dataframe_groups())
print(sc.get_importance_dataframe_groups())
def schur_test_nonpest():
import numpy as np
from pyemu import Matrix, Cov, Schur
#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"
s = Schur(jco=jco,parcov=parcov,obscov=obscov,forecasts=forecasts)
print(s.get_parameter_summary())
print(s.get_forecast_summary())
#this should fail
passed = False
try:
print(s.get_contribution_dataframe_groups())
passed = True
except Exception as e:
print(str(e))
if passed:
raise Exception("should have failed")
#this should fail
passed = False
try:
print(s.get_importance_dataframe_groups())
passed = True
except Exception as e:
print(str(e))
if passed:
raise Exception("should have failed")
print(s.get_contribution_dataframe({"group1":["p1","p3"]}))
print(s.get_importance_dataframe({"group1":["o1","o3"]}))
