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utils_tests.py
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utils_tests.py
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import os
if not os.path.exists("temp"):
os.mkdir("temp")
def add_pi_obj_func_test():
import os
import pyemu
pst = os.path.join("utils","dewater_pest.pst")
pst = pyemu.optimization.add_pi_obj_func(pst,out_pst_name=os.path.join("temp","dewater_pest.piobj.pst"))
print(pst.prior_information.loc["pi_obj_func","equation"])
#pst._update_control_section()
assert pst.control_data.nprior == 1
def fac2real_test():
import os
import numpy as np
import pyemu
# pp_file = os.path.join("utils","points1.dat")
# factors_file = os.path.join("utils","factors1.dat")
# pyemu.utils.gw_utils.fac2real(pp_file,factors_file,
# out_file=os.path.join("utils","test.ref"))
pp_file = os.path.join("utils", "points2.dat")
factors_file = os.path.join("utils", "factors2.dat")
pyemu.geostats.fac2real(pp_file, factors_file,
out_file=os.path.join("temp", "test.ref"))
arr1 = np.loadtxt(os.path.join("utils","fac2real_points2.ref"))
arr2 = np.loadtxt(os.path.join("temp","test.ref"))
#print(np.nansum(np.abs(arr1-arr2)))
#print(np.nanmax(np.abs(arr1-arr2)))
nmax = np.nanmax(np.abs(arr1-arr2))
assert nmax < 0.01
# import matplotlib.pyplot as plt
# diff = (arr1-arr2)/arr1 * 100.0
# diff[np.isnan(arr1)] = np.nan
# p = plt.imshow(diff,interpolation='n')
# plt.colorbar(p)
# plt.show()
def vario_test():
import numpy as np
import pyemu
contribution = 0.1
a = 2.0
for const in [pyemu.utils.geostats.ExpVario,pyemu.utils.geostats.GauVario,
pyemu.utils.geostats.SphVario]:
v = const(contribution,a)
h = v._h_function(np.array([0.0]))
assert h == contribution
h = v._h_function(np.array([a*1000]))
assert h == 0.0
v2 = const(contribution,a,anisotropy=2.0,bearing=90.0)
print(v2._h_function(np.array([a])))
def aniso_test():
import pyemu
contribution = 0.1
a = 2.0
for const in [pyemu.utils.geostats.ExpVario,pyemu.utils.geostats.GauVario,
pyemu.utils.geostats.SphVario]:
v = const(contribution,a)
v2 = const(contribution,a,anisotropy=2.0,bearing=90.0)
v3 = const(contribution,a,anisotropy=2.0,bearing=0.0)
pt0 = (0,0)
pt1 = (1,0)
assert v.covariance(pt0,pt1) == v2.covariance(pt0,pt1)
pt0 = (0,0)
pt1 = (0,1)
assert v.covariance(pt0,pt1) == v3.covariance(pt0,pt1)
def geostruct_test():
import pyemu
v1 = pyemu.utils.geostats.ExpVario(0.1,2.0)
v2 = pyemu.utils.geostats.GauVario(0.1,2.0)
v3 = pyemu.utils.geostats.SphVario(0.1,2.0)
g = pyemu.utils.geostats.GeoStruct(0.2,[v1,v2,v3])
pt0 = (0,0)
pt1 = (0,0)
print(g.covariance(pt0,pt1))
assert g.covariance(pt0,pt1) == 0.5
pt0 = (0,0)
pt1 = (1.0e+10,0)
assert g.covariance(pt0,pt1) == 0.2
def struct_file_test():
import os
import pyemu
structs = pyemu.utils.geostats.read_struct_file(
os.path.join("utils","struct.dat"))
#print(structs[0])
pt0 = (0,0)
pt1 = (0,0)
for s in structs:
assert s.covariance(pt0,pt1) == s.nugget + \
s.variograms[0].contribution
with open(os.path.join("utils","struct_out.dat"),'w') as f:
for s in structs:
s.to_struct_file(f)
structs1 = pyemu.utils.geostats.read_struct_file(
os.path.join("utils","struct_out.dat"))
for s in structs1:
assert s.covariance(pt0,pt1) == s.nugget + \
s.variograms[0].contribution
def covariance_matrix_test():
import os
import pandas as pd
import pyemu
pts = pd.read_csv(os.path.join("utils","points1.dat"),delim_whitespace=True,
header=None,names=["name","x","y"],usecols=[0,1,2])
struct = pyemu.utils.geostats.read_struct_file(
os.path.join("utils","struct.dat"))[0]
struct.variograms[0].covariance_matrix(pts.x,pts.y,names=pts.name)
print(struct.covariance_matrix(pts.x,pts.y,names=pts.name).x)
def setup_ppcov_simple():
import os
import platform
exe_file = os.path.join("utils","ppcov.exe")
print(platform.platform())
if not os.path.exists(exe_file) or not platform.platform().lower().startswith("win"):
print("can't run ppcov setup")
return
pts_file = os.path.join("utils","points1_test.dat")
str_file = os.path.join("utils","struct_test.dat")
args1 = [pts_file,'0.0',str_file,"struct1",os.path.join("utils","ppcov.struct1.out"),'','']
args2 = [pts_file,'0.0',str_file,"struct2",os.path.join("utils","ppcov.struct2.out"),'','']
args3 = [pts_file,'0.0',str_file,"struct3",os.path.join("utils","ppcov.struct3.out"),'','']
for args in [args1,args2,args3]:
in_file = os.path.join("utils","ppcov.in")
with open(in_file,'w') as f:
f.write('\n'.join(args))
os.system(exe_file + '<' + in_file)
def ppcov_simple_test():
import os
import numpy as np
import pandas as pd
import pyemu
pts_file = os.path.join("utils","points1_test.dat")
str_file = os.path.join("utils","struct_test.dat")
mat1_file = os.path.join("utils","ppcov.struct1.out")
mat2_file = os.path.join("utils","ppcov.struct2.out")
mat3_file = os.path.join("utils","ppcov.struct3.out")
ppc_mat1 = pyemu.Cov.from_ascii(mat1_file)
ppc_mat2 = pyemu.Cov.from_ascii(mat2_file)
ppc_mat3 = pyemu.Cov.from_ascii(mat3_file)
pts = pd.read_csv(pts_file,header=None,names=["name","x","y"],usecols=[0,1,2],
delim_whitespace=True)
struct1,struct2,struct3 = pyemu.utils.geostats.read_struct_file(str_file)
print(struct1)
print(struct2)
print(struct3)
for mat,struct in zip([ppc_mat1,ppc_mat2,ppc_mat3],[struct1,struct2,struct3]):
str_mat = struct.covariance_matrix(x=pts.x,y=pts.y,names=pts.name)
print(str_mat.row_names)
delt = mat.x - str_mat.x
assert np.abs(delt).max() < 1.0e-7
def setup_ppcov_complex():
import os
import platform
exe_file = os.path.join("utils","ppcov.exe")
print(platform.platform())
if not os.path.exists(exe_file) or not platform.platform().lower().startswith("win"):
print("can't run ppcov setup")
return
pts_file = os.path.join("utils","points1_test.dat")
str_file = os.path.join("utils","struct_complex.dat")
args1 = [pts_file,'0.0',str_file,"struct1",os.path.join("utils","ppcov.complex.struct1.out"),'','']
args2 = [pts_file,'0.0',str_file,"struct2",os.path.join("utils","ppcov.complex.struct2.out"),'','']
for args in [args1,args2]:
in_file = os.path.join("utils","ppcov.in")
with open(in_file,'w') as f:
f.write('\n'.join(args))
os.system(exe_file + '<' + in_file)
def ppcov_complex_test():
import os
import numpy as np
import pandas as pd
import pyemu
pts_file = os.path.join("utils","points1_test.dat")
str_file = os.path.join("utils","struct_complex.dat")
mat1_file = os.path.join("utils","ppcov.complex.struct1.out")
mat2_file = os.path.join("utils","ppcov.complex.struct2.out")
ppc_mat1 = pyemu.Cov.from_ascii(mat1_file)
ppc_mat2 = pyemu.Cov.from_ascii(mat2_file)
pts = pd.read_csv(pts_file,header=None,names=["name","x","y"],usecols=[0,1,2],
delim_whitespace=True)
struct1,struct2 = pyemu.utils.geostats.read_struct_file(str_file)
print(struct1)
print(struct2)
for mat,struct in zip([ppc_mat1,ppc_mat2],[struct1,struct2]):
str_mat = struct.covariance_matrix(x=pts.x,y=pts.y,names=pts.name)
delt = mat.x - str_mat.x
print(mat.x[:,0])
print(str_mat.x[:,0])
print(np.abs(delt).max())
assert np.abs(delt).max() < 1.0e-7
#break
def pp_to_tpl_test():
import os
import pyemu
pp_file = os.path.join("utils","points1.dat")
pp_df = pyemu.pp_utils.pilot_points_to_tpl(pp_file,name_prefix="test_")
print(pp_df.columns)
def tpl_to_dataframe_test():
import os
import pyemu
pp_file = os.path.join("utils","points1.dat")
pp_df = pyemu.pp_utils.pilot_points_to_tpl(pp_file,name_prefix="test_")
df_tpl = pyemu.pp_utils.pp_tpl_to_dataframe(pp_file+".tpl")
assert df_tpl.shape[0] == pp_df.shape[0]
# def to_mps_test():
# import os
# import pyemu
# jco_file = os.path.join("utils","dewater_pest.jcb")
# jco = pyemu.Jco.from_binary(jco_file)
# #print(jco.x)
# pst = pyemu.Pst(jco_file.replace(".jcb",".pst"))
# #print(pst.nnz_obs_names)
# oc_dict = {oc:"l" for oc in pst.nnz_obs_names}
# obj_func = {name:1.0 for name in pst.par_names}
#
# #pyemu.optimization.to_mps(jco=jco_file)
# #pyemu.optimization.to_mps(jco=jco_file,obs_constraint_sense=oc_dict)
# #pyemu.optimization.to_mps(jco=jco_file,obj_func="h00_00")
# decision_var_names = pst.parameter_data.loc[pst.parameter_data.pargp=="q","parnme"].tolist()
# pyemu.optimization.to_mps(jco=jco_file,obj_func=obj_func,decision_var_names=decision_var_names,
# risk=0.975)
def setup_pp_test():
import os
import pyemu
try:
import flopy
except:
return
model_ws = os.path.join("..","examples","Freyberg","extra_crispy")
ml = flopy.modflow.Modflow.load("freyberg.nam",model_ws=model_ws,check=False)
pp_dir = os.path.join("utils")
#ml.export(os.path.join("temp","test_unrot_grid.shp"))
sr = pyemu.helpers.SpatialReference().from_namfile(
os.path.join(ml.model_ws, ml.namefile),
delc=ml.dis.delc, delr=ml.dis.delr)
sr.rotation = 0.
par_info_unrot = pyemu.pp_utils.setup_pilotpoints_grid(sr=sr, prefix_dict={0: "hk1",1:"hk2"},
every_n_cell=2, pp_dir=pp_dir, tpl_dir=pp_dir,
shapename=os.path.join("temp", "test_unrot.shp"),
)
#print(par_info_unrot.parnme.value_counts())
gs = pyemu.geostats.GeoStruct(variograms=pyemu.geostats.ExpVario(a=1000,contribution=1.0))
ok = pyemu.geostats.OrdinaryKrige(gs,par_info_unrot)
ok.calc_factors_grid(sr)
sr2 = pyemu.helpers.SpatialReference.from_gridspec(
os.path.join(ml.model_ws, "test.spc"), lenuni=2)
par_info_drot = pyemu.pp_utils.setup_pilotpoints_grid(sr=sr2, prefix_dict={0: ["hk1_", "sy1_", "rch_"]},
every_n_cell=2, pp_dir=pp_dir, tpl_dir=pp_dir,
shapename=os.path.join("temp", "test_unrot.shp"),
)
ok = pyemu.geostats.OrdinaryKrige(gs, par_info_unrot)
ok.calc_factors_grid(sr2)
par_info_mrot = pyemu.pp_utils.setup_pilotpoints_grid(ml,prefix_dict={0:["hk1_","sy1_","rch_"]},
every_n_cell=2,pp_dir=pp_dir,tpl_dir=pp_dir,
shapename=os.path.join("temp","test_unrot.shp"))
ok = pyemu.geostats.OrdinaryKrige(gs, par_info_unrot)
ok.calc_factors_grid(ml.sr)
sr.rotation = 15
#ml.export(os.path.join("temp","test_rot_grid.shp"))
#pyemu.gw_utils.setup_pilotpoints_grid(ml)
par_info_rot = pyemu.pp_utils.setup_pilotpoints_grid(sr=sr,every_n_cell=2, pp_dir=pp_dir, tpl_dir=pp_dir,
shapename=os.path.join("temp", "test_rot.shp"))
ok = pyemu.geostats.OrdinaryKrige(gs, par_info_unrot)
ok.calc_factors_grid(sr)
print(par_info_unrot.x)
print(par_info_drot.x)
print(par_info_mrot.x)
print(par_info_rot.x)
def read_hob_test():
import os
import pyemu
hob_file = os.path.join("utils","HOB.txt")
df = pyemu.gw_utils.modflow_hob_to_instruction_file(hob_file)
print(df.obsnme)
def read_pval_test():
import os
import pyemu
pval_file = os.path.join("utils", "meras_trEnhance.pval")
pyemu.gw_utils.modflow_pval_to_template_file(pval_file)
def pp_to_shapefile_test():
import os
import pyemu
try:
import shapefile
except:
print("no pyshp")
return
pp_file = os.path.join("utils","points1.dat")
shp_file = os.path.join("temp","points1.dat.shp")
pyemu.pp_utils.write_pp_shapfile(pp_file)
def write_tpl_test():
import os
import pyemu
tpl_file = os.path.join("utils","test_write.tpl")
in_file = os.path.join("temp","tpl_test.dat")
par_vals = {"q{0}".format(i+1):12345678.90123456 for i in range(7)}
pyemu.pst_utils.write_to_template(par_vals,tpl_file,in_file)
def read_pestpp_runstorage_file_test():
import os
import pyemu
rnj_file = os.path.join("utils","freyberg.rnj")
#rnj_file = os.path.join("..", "..", "verification", "10par_xsec", "master_opt1","pest.rnj")
p1,o1 = pyemu.helpers.read_pestpp_runstorage(rnj_file)
p2,o2 = pyemu.helpers.read_pestpp_runstorage(rnj_file,9)
diff = p1 - p2
diff.sort_values("parval1",inplace=True)
def smp_to_ins_test():
import os
import pyemu
smp = os.path.join("utils","TWDB_wells.smp")
ins = os.path.join('temp',"test.ins")
try:
pyemu.pst_utils.smp_to_ins(smp,ins)
except:
pass
else:
raise Exception("should have failed")
pyemu.smp_utils.smp_to_ins(smp,ins,True)
def master_and_workers():
import shutil
import pyemu
worker_dir = os.path.join("..","verification","10par_xsec","template_mac")
master_dir = os.path.join("temp","master")
if not os.path.exists(master_dir):
os.mkdir(master_dir)
assert os.path.exists(worker_dir)
pyemu.helpers.start_workers(worker_dir,"pestpp","pest.pst",1,
worker_root="temp",master_dir=master_dir)
#now try it from within the master dir
base_cwd = os.getcwd()
os.chdir(master_dir)
pyemu.helpers.start_workers(os.path.join("..","..",worker_dir),
"pestpp","pest.pst",3,
master_dir='.')
os.chdir(base_cwd)
def first_order_pearson_regul_test():
import os
from pyemu import Schur
from pyemu.utils.helpers import first_order_pearson_tikhonov,zero_order_tikhonov
w_dir = "la"
sc = Schur(jco=os.path.join(w_dir,"pest.jcb"))
pt = sc.posterior_parameter
zero_order_tikhonov(sc.pst)
first_order_pearson_tikhonov(sc.pst,pt,reset=False)
print(sc.pst.prior_information)
sc.pst.rectify_pi()
assert sc.pst.control_data.pestmode == "regularization"
sc.pst.write(os.path.join('temp','test.pst'))
def zero_order_regul_test():
import os
import pyemu
pst = pyemu.Pst(os.path.join("pst","inctest.pst"))
pyemu.helpers.zero_order_tikhonov(pst)
print(pst.prior_information)
assert pst.control_data.pestmode == "regularization"
pst.write(os.path.join('temp','test.pst'))
pyemu.helpers.zero_order_tikhonov(pst,reset=False)
assert pst.prior_information.shape[0] == pst.npar_adj * 2
def kl_test():
import os
import numpy as np
import pandas as pd
import pyemu
import matplotlib.pyplot as plt
try:
import flopy
except:
print("flopy not imported...")
return
model_ws = os.path.join("..","verification","Freyberg","extra_crispy")
ml = flopy.modflow.Modflow.load("freyberg.nam",model_ws=model_ws,check=False)
str_file = os.path.join("..","verification","Freyberg","structure.dat")
arr_tru = np.loadtxt(os.path.join("..","verification",
"Freyberg","extra_crispy",
"hk.truth.ref")) + 20
basis_file = os.path.join("utils","basis.jco")
tpl_file = os.path.join("utils","test.tpl")
factors_file = os.path.join("temp","factors.dat")
num_eig = 100
prefixes = ["hk1"]
df = pyemu.utils.helpers.kl_setup(num_eig=num_eig, sr=ml.sr,
struct=str_file,
factors_file=factors_file,
basis_file=basis_file,
prefixes=prefixes,islog=False)
basis = pyemu.Matrix.from_binary(basis_file)
basis = basis[:,:num_eig]
arr_tru = np.atleast_2d(arr_tru.flatten()).transpose()
proj = np.dot(basis.T.x,arr_tru)[:num_eig]
#proj.autoalign = False
back = np.dot(basis.x, proj)
back = back.reshape(ml.nrow,ml.ncol)
df.parval1 = proj
arr = pyemu.geostats.fac2real(df,factors_file,out_file=None)
fig = plt.figure(figsize=(10, 10))
ax1, ax2 = plt.subplot(121),plt.subplot(122)
mn,mx = arr_tru.min(),arr_tru.max()
print(arr.max(), arr.min())
print(back.max(),back.min())
diff = np.abs(back - arr)
print(diff.max())
assert diff.max() < 1.0e-5
def ok_test():
import os
import pandas as pd
import pyemu
str_file = os.path.join("utils","struct_test.dat")
pts_data = pd.DataFrame({"x":[1.0,2.0,3.0],"y":[0.,0.,0.],"name":["p1","p2","p3"]})
gs = pyemu.utils.geostats.read_struct_file(str_file)[0]
ok = pyemu.utils.geostats.OrdinaryKrige(gs,pts_data)
interp_points = pts_data.copy()
kf = ok.calc_factors(interp_points.x,interp_points.y)
#for ptname in pts_data.name:
for i in kf.index:
assert len(kf.loc[i,"inames"])== 1
assert kf.loc[i,"ifacts"][0] == 1.0
assert sum(kf.loc[i,"ifacts"]) == 1.0
print(kf)
def ok_grid_test():
try:
import flopy
except:
return
import numpy as np
import pandas as pd
import pyemu
nrow,ncol = 10,5
delr = np.ones((ncol)) * 1.0/float(ncol)
delc = np.ones((nrow)) * 1.0/float(nrow)
num_pts = 0
ptx = np.random.random(num_pts)
pty = np.random.random(num_pts)
ptname = ["p{0}".format(i) for i in range(num_pts)]
pts_data = pd.DataFrame({"x":ptx,"y":pty,"name":ptname})
pts_data.index = pts_data.name
pts_data = pts_data.loc[:,["x","y","name"]]
sr = flopy.utils.SpatialReference(delr=delr,delc=delc)
pts_data.loc["i0j0", :] = [sr.xcentergrid[0,0],sr.ycentergrid[0,0],"i0j0"]
pts_data.loc["imxjmx", :] = [sr.xcentergrid[-1, -1], sr.ycentergrid[-1, -1], "imxjmx"]
str_file = os.path.join("utils","struct_test.dat")
gs = pyemu.utils.geostats.read_struct_file(str_file)[0]
ok = pyemu.utils.geostats.OrdinaryKrige(gs,pts_data)
kf = ok.calc_factors_grid(sr,verbose=False,var_filename=os.path.join("temp","test_var.ref"),minpts_interp=1)
ok.to_grid_factors_file(os.path.join("temp","test.fac"))
def ok_grid_zone_test():
try:
import flopy
except:
return
import numpy as np
import pandas as pd
import pyemu
nrow,ncol = 10,5
delr = np.ones((ncol)) * 1.0/float(ncol)
delc = np.ones((nrow)) * 1.0/float(nrow)
num_pts = 0
ptx = np.random.random(num_pts)
pty = np.random.random(num_pts)
ptname = ["p{0}".format(i) for i in range(num_pts)]
pts_data = pd.DataFrame({"x":ptx,"y":pty,"name":ptname})
pts_data.index = pts_data.name
pts_data = pts_data.loc[:,["x","y","name"]]
sr = flopy.utils.SpatialReference(delr=delr,delc=delc)
pts_data.loc["i0j0", :] = [sr.xcentergrid[0,0],sr.ycentergrid[0,0],"i0j0"]
pts_data.loc["imxjmx", :] = [sr.xcentergrid[-1, -1], sr.ycentergrid[-1, -1], "imxjmx"]
pts_data.loc[:,"zone"] = 1
pts_data.zone.iloc[1] = 2
print(pts_data.zone.unique())
str_file = os.path.join("utils","struct_test.dat")
gs = pyemu.utils.geostats.read_struct_file(str_file)[0]
ok = pyemu.utils.geostats.OrdinaryKrige(gs,pts_data)
zone_array = np.ones((nrow,ncol))
zone_array[0,0] = 2
kf = ok.calc_factors_grid(sr,verbose=False,
var_filename=os.path.join("temp","test_var.ref"),
minpts_interp=1,zone_array=zone_array)
ok.to_grid_factors_file(os.path.join("temp","test.fac"))
def ppk2fac_verf_test():
import os
import numpy as np
import pyemu
try:
import flopy
except:
return
ws = os.path.join("..","verification","Freyberg")
gspc_file = os.path.join(ws,"grid.spc")
pp_file = os.path.join(ws,"pp_00_pp.dat")
str_file = os.path.join(ws,"structure.complex.dat")
ppk2fac_facfile = os.path.join(ws,"ppk2fac_fac.dat")
pyemu_facfile = os.path.join("temp","pyemu_facfile.dat")
sr = flopy.utils.SpatialReference.from_gridspec(gspc_file)
ok = pyemu.utils.OrdinaryKrige(str_file,pp_file)
ok.calc_factors_grid(sr,maxpts_interp=10)
ok.to_grid_factors_file(pyemu_facfile)
zone_arr = np.loadtxt(os.path.join(ws,"extra_crispy","ref","ibound.ref"))
pyemu_arr = pyemu.utils.fac2real(pp_file,pyemu_facfile,out_file=None)
ppk2fac_arr = pyemu.utils.fac2real(pp_file,ppk2fac_facfile,out_file=None)
pyemu_arr[zone_arr == 0] = np.NaN
pyemu_arr[zone_arr == -1] = np.NaN
ppk2fac_arr[zone_arr == 0] = np.NaN
ppk2fac_arr[zone_arr == -1] = np.NaN
diff = np.abs(pyemu_arr - ppk2fac_arr)
print(diff)
assert np.nansum(diff) < 1.0e-6,np.nansum(diff)
# def opt_obs_worth():
# import os
# import pyemu
# wdir = os.path.join("utils")
# os.chdir(wdir)
# pst = pyemu.Pst(os.path.join("supply2_pest.fosm.pst"))
# zero_weight_names = [n for n,w in zip(pst.observation_data.obsnme,pst.observation_data.weight) if w == 0.0]
# #print(zero_weight_names)
# #for attr in ["base_jacobian","hotstart_resfile"]:
# # pst.pestpp_options[attr] = os.path.join(wdir,pst.pestpp_options[attr])
# #pst.template_files = [os.path.join(wdir,f) for f in pst.template_files]
# #pst.instruction_files = [os.path.join(wdir,f) for f in pst.instruction_files]
# #print(pst.template_files)
# df = pyemu.optimization.get_added_obs_importance(pst,obslist_dict={"zeros":zero_weight_names})
# os.chdir("..")
# print(df)
def mflist_budget_test():
import pyemu
import os
try:
import flopy
except:
print("no flopy...")
return
model_ws = os.path.join("..","examples","Freyberg_transient")
ml = flopy.modflow.Modflow.load("freyberg.nam",model_ws=model_ws,check=False,load_only=[])
list_filename = os.path.join(model_ws,"freyberg.list")
assert os.path.exists(list_filename)
df = pyemu.gw_utils.setup_mflist_budget_obs(list_filename,start_datetime=ml.start_datetime)
print(df)
def mtlist_budget_test():
import pyemu
import pandas as pd
import os
try:
import flopy
except:
print("no flopy...")
return
list_filename = os.path.join("utils","mt3d.list")
assert os.path.exists(list_filename)
frun_line,ins_files, df = pyemu.gw_utils.setup_mtlist_budget_obs(
list_filename,start_datetime='1-1-1970')
assert len(ins_files) == 2
frun_line,ins_files, df = pyemu.gw_utils.setup_mtlist_budget_obs(
list_filename,start_datetime='1-1-1970', gw_prefix='')
assert len(ins_files) == 2
frun_line, ins_files, df = pyemu.gw_utils.setup_mtlist_budget_obs(
list_filename, start_datetime=None)
assert len(ins_files) == 2
list_filename = os.path.join("utils", "mt3d_imm_sor.lst")
assert os.path.exists(list_filename)
frun_line, ins_files, df = pyemu.gw_utils.setup_mtlist_budget_obs(
list_filename, start_datetime='1-1-1970')
def geostat_prior_builder_test():
import os
import numpy as np
import pyemu
pst_file = os.path.join("pst","pest.pst")
pst = pyemu.Pst(pst_file)
# print(pst.parameter_data)
tpl_file = os.path.join("utils", "pp_locs.tpl")
str_file = os.path.join("utils", "structure.dat")
cov = pyemu.helpers.geostatistical_prior_builder(pst_file,{str_file:tpl_file})
d1 = np.diag(cov.x)
df = pyemu.pp_utils.pp_tpl_to_dataframe(tpl_file)
df.loc[:,"zone"] = np.arange(df.shape[0])
gs = pyemu.geostats.read_struct_file(str_file)
cov = pyemu.helpers.geostatistical_prior_builder(pst_file,{gs:df},
sigma_range=4)
nnz = np.count_nonzero(cov.x)
assert nnz == pst.npar_adj
d2 = np.diag(cov.x)
assert np.array_equiv(d1, d2)
pst.parameter_data.loc[pst.par_names[1:10], "partrans"] = "tied"
pst.parameter_data.loc[pst.par_names[1:10], "partied"] = pst.par_names[0]
cov = pyemu.helpers.geostatistical_prior_builder(pst, {gs: df},
sigma_range=4)
nnz = np.count_nonzero(cov.x)
assert nnz == pst.npar_adj
ttpl_file = os.path.join("temp", "temp.dat.tpl")
with open(ttpl_file, 'w') as f:
f.write("ptf ~\n ~ temp1 ~\n")
pst.add_parameters(ttpl_file, ttpl_file.replace(".tpl", ""))
pst.parameter_data.loc["temp1", "parubnd"] = 1.1
pst.parameter_data.loc["temp1", "parlbnd"] = 0.9
cov = pyemu.helpers.geostatistical_prior_builder(pst, {str_file: tpl_file})
assert cov.shape[0] == pst.npar_adj
def geostat_draws_test():
import os
import numpy as np
import pyemu
pst_file = os.path.join("pst","pest.pst")
pst = pyemu.Pst(pst_file)
print(pst.parameter_data)
tpl_file = os.path.join("utils", "pp_locs.tpl")
str_file = os.path.join("utils", "structure.dat")
pe = pyemu.helpers.geostatistical_draws(pst_file,{str_file:tpl_file})
assert (pe.shape == pe.dropna().shape)
pst.parameter_data.loc[pst.par_names[1:10], "partrans"] = "tied"
pst.parameter_data.loc[pst.par_names[1:10], "partied"] = pst.par_names[0]
pe = pyemu.helpers.geostatistical_draws(pst, {str_file: tpl_file})
assert (pe.shape == pe.dropna().shape)
df = pyemu.pp_utils.pp_tpl_to_dataframe(tpl_file)
df.loc[:,"zone"] = np.arange(df.shape[0])
gs = pyemu.geostats.read_struct_file(str_file)
pe = pyemu.helpers.geostatistical_draws(pst_file,{gs:df},
sigma_range=4)
ttpl_file = os.path.join("temp", "temp.dat.tpl")
with open(ttpl_file, 'w') as f:
f.write("ptf ~\n ~ temp1 ~\n")
pst.add_parameters(ttpl_file, ttpl_file.replace(".tpl", ""))
pst.parameter_data.loc["temp1", "parubnd"] = 1.1
pst.parameter_data.loc["temp1", "parlbnd"] = 0.9
pst.parameter_data.loc[pst.par_names[1:10],"partrans"] = "tied"
pst.parameter_data.loc[pst.par_names[1:10], "partied"] = pst.par_names[0]
pe = pyemu.helpers.geostatistical_draws(pst, {str_file: tpl_file})
assert (pe.shape == pe.dropna().shape)
# def linearuniversal_krige_test():
# try:
# import flopy
# except:
# return
#
# import numpy as np
# import pandas as pd
# import pyemu
# nrow,ncol = 10,5
# delr = np.ones((ncol)) * 1.0/float(ncol)
# delc = np.ones((nrow)) * 1.0/float(nrow)
#
# num_pts = 0
# ptx = np.random.random(num_pts)
# pty = np.random.random(num_pts)
# ptname = ["p{0}".format(i) for i in range(num_pts)]
# pts_data = pd.DataFrame({"x":ptx,"y":pty,"name":ptname})
# pts_data.index = pts_data.name
# pts_data = pts_data.loc[:,["x","y","name"]]
#
#
# sr = flopy.utils.SpatialReference(delr=delr,delc=delc)
# pts_data.loc["i0j0", :] = [sr.xcentergrid[0,0],sr.ycentergrid[0,0],"i0j0"]
# pts_data.loc["imxjmx", :] = [sr.xcentergrid[-1, -1], sr.ycentergrid[-1, -1], "imxjmx"]
# pts_data.loc["i0j0","value"] = 1.0
# pts_data.loc["imxjmx","value"] = 0.0
#
# str_file = os.path.join("utils","struct_test.dat")
# gs = pyemu.utils.geostats.read_struct_file(str_file)[0]
# luk = pyemu.utils.geostats.LinearUniversalKrige(gs,pts_data)
# df = luk.estimate_grid(sr,verbose=True,
# var_filename=os.path.join("utils","test_var.ref"),
# minpts_interp=1)
def gslib_2_dataframe_test():
import os
import pyemu
gslib_file = os.path.join("utils","ch91pt.shp.gslib")
df = pyemu.geostats.gslib_2_dataframe(gslib_file)
print(df)
def sgems_to_geostruct_test():
import os
import pyemu
xml_file = os.path.join("utils", "ch00")
gs = pyemu.geostats.read_sgems_variogram_xml(xml_file)
def load_sgems_expvar_test():
import os
import numpy as np
#import matplotlib.pyplot as plt
import pyemu
dfs = pyemu.geostats.load_sgems_exp_var(os.path.join("utils","ch00_expvar"))
xmn,xmx = 1.0e+10,-1.0e+10
for d,df in dfs.items():
xmn = min(xmn,df.x.min())
xmx = max(xmx,df.x.max())
xml_file = os.path.join("utils", "ch00")
gs = pyemu.geostats.read_sgems_variogram_xml(xml_file)
v = gs.variograms[0]
#ax = gs.plot(ls="--")
#plt.show()
#x = np.linspace(xmn,xmx,100)
#y = v.inv_h(x)
#
#plt.plot(x,y)
#plt.show()
def read_hydmod_test():
import os
import numpy as np
import pandas as pd
import pyemu
try:
import flopy
except:
return
df, outfile = pyemu.gw_utils.modflow_read_hydmod_file(os.path.join('utils','freyberg.hyd.bin'),
os.path.join('temp','freyberg.hyd.bin.dat'))
df = pd.read_csv(os.path.join('temp', 'freyberg.hyd.bin.dat'), delim_whitespace=True)
dftrue = pd.read_csv(os.path.join('utils', 'freyberg.hyd.bin.dat.true'), delim_whitespace=True)
assert np.allclose(df.obsval.values, dftrue.obsval.values)
def make_hydmod_insfile_test():
import os
import shutil
import pyemu
try:
import flopy
except:
return
shutil.copy2(os.path.join('utils','freyberg.hyd.bin'),os.path.join('temp','freyberg.hyd.bin'))
pyemu.gw_utils.modflow_hydmod_to_instruction_file(os.path.join('temp','freyberg.hyd.bin'))
#assert open(os.path.join('utils','freyberg.hyd.bin.dat.ins'),'r').read() == open('freyberg.hyd.dat.ins', 'r').read()
assert os.path.exists(os.path.join('temp','freyberg.hyd.bin.dat.ins'))
def plot_summary_test():
import os
import pandas as pd
import pyemu
try:
import matplotlib.pyplot as plt
except:
return
par_df = pd.read_csv(os.path.join("utils","freyberg_pp.par.usum.csv"),
index_col=0)
idx = list(par_df.index.map(lambda x: x.startswith("HK")))
par_df = par_df.loc[idx,:]
ax = pyemu.plot_utils.plot_summary_distributions(par_df,label_post=True)
plt.savefig(os.path.join("temp","hk_par.png"))
plt.close()
df = os.path.join("utils","freyberg_pp.pred.usum.csv")
figs,axes = pyemu.plot_utils.plot_summary_distributions(df,subplots=True)
#plt.show()
for i,fig in enumerate(figs):
plt.figure(fig.number)
plt.savefig(os.path.join("temp","test_pred_{0}.png".format(i)))
plt.close(fig)
df = os.path.join("utils","freyberg_pp.par.usum.csv")
figs, axes = pyemu.plot_utils.plot_summary_distributions(df,subplots=True)
for i,fig in enumerate(figs):
plt.figure(fig.number)
plt.savefig(os.path.join("temp","test_par_{0}.png".format(i)))
plt.close(fig)
def hds_timeseries_test():
import os
import shutil
import numpy as np
import pandas as pd
try:
import flopy
except:
return
import pyemu
model_ws =os.path.join("..","examples","Freyberg_transient")
org_hds_file = os.path.join(model_ws, "freyberg.hds")
hds_file = os.path.join("temp", "freyberg.hds")
org_cbc_file = org_hds_file.replace(".hds",".cbc")
cbc_file = hds_file.replace(".hds", ".cbc")
shutil.copy2(org_hds_file, hds_file)
shutil.copy2(org_cbc_file, cbc_file)
m = flopy.modflow.Modflow.load("freyberg.nam", model_ws=model_ws, check=False)
kij_dict = {"test1": [0, 0, 0], "test2": (1, 1, 1), "test": (0, 10, 14)}
pyemu.gw_utils.setup_hds_timeseries(hds_file, kij_dict, include_path=True)
# m.change_model_ws("temp",reset_external=True)
# m.write_input()
# pyemu.os_utils.run("mfnwt freyberg.nam",cwd="temp")
cmd, df1 = pyemu.gw_utils.setup_hds_timeseries(cbc_file, kij_dict, include_path=True, prefix="stor",
text="storage", fill=0.0)
cmd,df2 = pyemu.gw_utils.setup_hds_timeseries(cbc_file, kij_dict, model=m, include_path=True, prefix="stor",
text="storage",fill=0.0)
print(df1)
d = np.abs(df1.obsval.values - df2.obsval.values)
print(d.max())
assert d.max() == 0.0,d
try:
pyemu.gw_utils.setup_hds_timeseries(cbc_file, kij_dict, model=m, include_path=True, prefix="consthead",
text="constant head")
except:
pass
else:
raise Exception("should have failed")
try:
pyemu.gw_utils.setup_hds_timeseries(cbc_file, kij_dict, model=m, include_path=True, prefix="consthead",
text="JUNK")
except:
pass
else:
raise Exception("should have failed")
pyemu.gw_utils.setup_hds_timeseries(hds_file, kij_dict, include_path=True,prefix="hds")
m = flopy.modflow.Modflow.load("freyberg.nam",model_ws=model_ws,load_only=[],check=False)
pyemu.gw_utils.setup_hds_timeseries(hds_file, kij_dict,model=m,include_path=True)
pyemu.gw_utils.setup_hds_timeseries(hds_file, kij_dict, model=m, include_path=True,prefix="hds")
org_hds_file = os.path.join("utils", "MT3D001.UCN")
hds_file = os.path.join("temp", "MT3D001.UCN")
shutil.copy2(org_hds_file, hds_file)
kij_dict = {"test1": [0, 0, 0], "test2": (1, 1, 1)}
pyemu.gw_utils.setup_hds_timeseries(hds_file, kij_dict, include_path=True)
pyemu.gw_utils.setup_hds_timeseries(hds_file, kij_dict, include_path=True, prefix="hds")
m = flopy.modflow.Modflow.load("freyberg.nam", model_ws=model_ws, load_only=[], check=False)
pyemu.gw_utils.setup_hds_timeseries(hds_file, kij_dict, model=m, include_path=True)
pyemu.gw_utils.setup_hds_timeseries(hds_file, kij_dict, model=m, include_path=True, prefix="hds")
# df1 = pd.read_csv(out_file, delim_whitespace=True)
# pyemu.gw_utils.apply_hds_obs(hds_file)
# df2 = pd.read_csv(out_file, delim_whitespace=True)
# diff = df1.obsval - df2.obsval
def grid_obs_test():
import os
import shutil
import numpy as np
import pandas as pd
try:
import flopy
except:
return
import pyemu
m_ws = os.path.join("..", "examples", "freyberg_sfr_update")
org_hds_file = os.path.join("..","examples","Freyberg_Truth","freyberg.hds")
org_multlay_hds_file = os.path.join(m_ws, "freyberg.hds") # 3 layer version
org_ucn_file = os.path.join(m_ws, "MT3D001.UCN") # mt example
hds_file = os.path.join("temp","freyberg.hds")
multlay_hds_file = os.path.join("temp", "freyberg_3lay.hds")
ucn_file = os.path.join("temp", "MT3D001.UCN")
out_file = hds_file+".dat"
multlay_out_file = multlay_hds_file+".dat"