def Draw(self,x,y,time): if self.Time2Exit==None: self.Time2Exit=time if time-self.Time2Exit>10.0: Bladex.Quit() elif time-self.Time2Exit>5.0: self.CurrentBitmap = self.Bitmap2 Raster.SetPosition(0,0) Raster.DrawImage(640,480,"BGR","Stretch",self.CurrentBitmap.GetData()) self.DefDraw(x,y,time)
def __init__(self,Parent,Menudesc,StackMenu,VertPos=0):
#print "MenuTree.__init__()"
#print "MenuTree initial refcount",sys.getrefcount(self)
Width,Height=Raster.GetSize()
try:
Width,Height=Menudesc["Size"]
except KeyError:
pass
B_MenuFrameWidget.__init__(self,Parent,"MenuTree"+Menudesc["Name"],Width,Height,VertPos)
self.Menudesc=Menudesc
ValidIndex = 0
isValidIndex = 0
for i in Menudesc["ListDescr"]:
m_class=B_MenuItemTextNoFX
try:
m_class=i["Kind"]
except KeyError:
pass
vsep=0
try:
vsep=i["VSep"]
except KeyError:
pass
wSubMenu=m_class(self,i,StackMenu)
if not isValidIndex:
if wSubMenu.AcceptsFocus():
isValidIndex = 1
else:
ValidIndex = ValidIndex+1
HPos=0.5
HIndicator=BUIx.B_FrameWidget.B_FR_HRelative
HAnchor=BUIx.B_FrameWidget.B_FR_HCenter
try:
PosDscr=i["Position"]
HPos=PosDscr[0]
HIndicator=PosDscr[1]
HAnchor=PosDscr[2]
except KeyError:
pass
try:
PosDscr=i["PositionEx"]
HPos=PosDscr[0]
HIndicator=PosDscr[1]
HAnchor=PosDscr[2]
except KeyError:
B_MenuFrameWidget.AddMenuElement(self,wSubMenu,vsep,HPos,HIndicator,HAnchor)
if Menudesc.has_key("iFocus"):
self.SetFocus_Idx(Menudesc["iFocus"])
else:
self.SetFocus_Idx(ValidIndex)
def clip_cloud(self):
# Clip
# Cloud reprojected file
rc = os.path.join(self.tmp_dir, f"rc{self.scene_file_name}.tif")
r = R.Raster(img_path=rc)
# Only clip raster if it intersects limit of project
if r.intersects_trace_outline_aoi():
c = CR.ClipRaster(
img_path=rc,
tmp_dir=self.tmp_dir,
scene_file_name=self.scene_file_name,
output_dir=self.output_dir,
output_file_name=f"fmask_{self.output_file_name}")
c.clip_raster_by_mask()
else:
dst = os.path.join(self.output_dir,
f"fmask_{self.scene_file_name}")
shutil.move(src=rc, dst=dst)
# for k, S in enumerate(mesh.surfaces()):
# mesh = MT.TSurf.make(*S.as_arrays())
# for k, S in enumerate(mesh.surfaces()):
# mesh = MT.TSurf.make(*S.as_arrays())
# MT.to_vtu(mesh, "surface%03d.vtu" % k)
print("adding dtm")
filename = "raster2750.txt"
import Raster
info = Raster.RasterInfo(filename)
raw_data = np.loadtxt(filename, skiprows=6)
data = np.ma.array(raw_data, mask=raw_data == float(info.nodata))
centers = info.centers()
xyz = np.transpose(np.vstack([a.ravel() for a in centers] + [raw_data.ravel(),]))
xyz = xyz[raw_data.ravel() != float(info.nodata)]
# center dtm
xyz[:, 0] -= 1010922
xyz[:, 1] -= 6810940
# x = np.linspace(xmin-2*Lh, xmax+2*Lh)
# y = np.linspace(ymin-2*Lh, ymax+2*Lh)
def Draw(self,x,y,time): Raster.SetPosition(0,0) Raster.DrawImage(640,480,"BGR","Stretch",self.Bitmap.GetData()) self.DefDraw(x,y,time)
def Draw(self,x,y,time):
import string
import GotoMapVars
import Menu
char = Bladex.GetEntity("Player1")
x,y = Raster.GetSize()
Raster.SetPosition((x - 640)/2, (y - 480)/2)
Map = string.lower(Bladex.GetCurrentMap())
Specials = 1
Inventory = char.GetInventory()
HaveCrush = 0
for i in range(Inventory.nWeapons):
Weapon = Inventory.GetWeapon(i)
RootWeapon = Bladex.GetEntity(Weapon)
if RootWeapon.Kind == "CrushHammer":
HaveCrush = 1
if Map in GotoMapVars.BackLevelNames:
Specials = 0
else:
if (Map in GotoMapVars.LevelNames and GotoMapVars.LevelNames.index(Map) > 6) or ((char.Kind == "Dwarf_N") and HaveCrush):
Specials = 0
# Horizontal buttons range checking
if self.image < Specials:
self.image = (self.NumImages - (1 + self.addone))
if self.image > (self.NumImages - (1 + self.addone)):
self.image = Specials
# Vertical -Text- options range checking
if self.Text < 0:
self.Text = self.NumTexts - 1
if self.Text > self.NumTexts - 1:
self.Text = 0
# Set logic conditions
if self.image == 0:
Raster.DrawImage(640,480,"BGR","Normal",self.Specials.GetData())
if self.image == 1:
Raster.DrawImage(640,480,"BGR","Normal",self.Weapons.GetData())
if self.image == 2:
Raster.DrawImage(640,480,"BGR","Normal",self.Habilities.GetData())
if self.image == 3:
Raster.DrawImage(640,480,"BGR","Normal",self.Items.GetData())
if self.image == 4:
Raster.DrawImage(640,480,"BGR","Normal",self.MapText.GetData())
if self.image == 5:
if self.Text == 0:
Raster.DrawImage(640,480,"BGR","Normal",self.Tablets.GetData())
if self.Text == 1:
Raster.DrawImage(640,480,"BGR","Normal",self.Text1.GetData())
if self.Text == 2:
Raster.DrawImage(640,480,"BGR","Normal",self.Text2.GetData())
if self.Text == 3:
Raster.DrawImage(640,480,"BGR","Normal",self.Text3.GetData())
if ((self.image == 5)):
# and
# (
# (self.TextsAvail[1]) or
# (self.TextsAvail[2]) or
# (self.TextsAvail[3])
# )):
Menu.TBUDSoundAble = 1
else:
Menu.TBUDSoundAble = 0
self.DefDraw(x,y,time)
def __init__(self,Parent,Menudesc,StackMenu,VertPos=0):
import Language
import GotoMapVars
self.image = 1
self.NumImages = 6
self.Text = 0
self.NumTexts = 4
self.TextsAvail = [0, 0, 0, 0]
self.vidw = 1
self.vidh = 1
self.addone = 0
char = Bladex.GetEntity("Player1")
print char.Kind
Raster.UnifyRenderBuffers()
if "ORCMURAL" in GotoMapVars.BaList:
self.TextsAvail[1] = 1
if "ISLANDMURAL" in GotoMapVars.BaList:
self.TextsAvail[2] = 1
if "NEJEVMURAL" in GotoMapVars.BaList:
self.TextsAvail[3] = 1
# Range Vars
Inventory = Bladex.GetEntity("Player1").GetInventory()
if (not Inventory.nTablets > 0) and not (1 in GotoMapVars.PlacedTablets) and not (self.TextsAvail[1] or self.TextsAvail[2] or self.TextsAvail[3]):
self.addone = 1
if "SALATABLILLAS" in GotoMapVars.BaList or (1 in GotoMapVars.PlacedTablets) or (Inventory.nTablets > 0):
self.addone = 0
self.TextsAvail[0] = 1
self.Specials = BBLib.B_BitMap24()
self.Specials.ReadFromFile("..\\..\\Data\\TB\\" + Language.Current + "\\" + char.Kind + "\\plantillaspecials.jpg")
self.Items = BBLib.B_BitMap24()
self.Items.ReadFromFile("..\\..\\Data\\TB\\" + Language.Current +"\\Items\\plantillaGitems.jpg")
self.Weapons = BBLib.B_BitMap24()
self.Weapons.ReadFromFile("..\\..\\Data\\TB\\" + Language.Current + "\\" + char.Kind + "\\plantillaweapons.jpg")
self.Habilities = BBLib.B_BitMap24()
self.Habilities.ReadFromFile("..\\..\\Data\\TB\\" + Language.Current + "\\" + char.Kind + "\\plantillahabilities.jpg")
self.MapText = BBLib.B_BitMap24()
if not self.MapText.ReadFromFile("..\\..\\Data\\TB\\" + Language.Current + "\\" + char.Kind + "\\" + Bladex.GetCurrentMap() + ".jpg"):
self.MapText.ReadFromFile("..\\..\\Data\\TB\\" + Language.Current + "\\" + Bladex.GetCurrentMap() + ".jpg")
if (Bladex.GetCurrentMap() == "Tower_m16"):
inv = Bladex.GetEntity("Player1").GetInventory()
for i in range(inv.nWeapons):
if (Bladex.GetEntity(inv.GetWeapon(i)).Kind == "BladeSword2") or (Bladex.GetEntity(inv.GetWeapon(i)).Kind == "BladeSword2Barbarian"):
self.MapText.ReadFromFile("..\\..\\Data\\TB\\" + Language.Current + "\\" + "conTower_m16.jpg")
else:
self.MapText.ReadFromFile("..\\..\\Data\\TB\\" + Language.Current + "\\" + "sinTower_m16.jpg")
self.Tablets = BBLib.B_BitMap24()
if (Inventory.nTablets > 0) or (1 in GotoMapVars.PlacedTablets):
self.Tablets.ReadFromFile("..\\..\\Data\\TB\\"+ Language.Current + "\\tablillas.jpg")
self.Text1 = BBLib.B_BitMap24()
if self.TextsAvail[1]:
self.Text1.ReadFromFile("..\\..\\Data\\TB\\" + Language.Current + "\\muralorc.jpg")
self.Text2 = BBLib.B_BitMap24()
if self.TextsAvail[2]:
self.Text2.ReadFromFile("..\\..\\Data\\TB\\" + Language.Current + "\\muralisla1.jpg")
self.Text3 = BBLib.B_BitMap24()
if self.TextsAvail[3]:
self.Text3.ReadFromFile("..\\..\\Data\\TB\\" + Language.Current + "\\muralnejev.jpg")
BUIx.B_RectWidget.__init__(self,Parent,Menudesc["Name"],self.vidw,self.vidh)
self.Selected=0
self.Solid=0
self.Border=0
self.SetDrawFunc(self.Draw)
self.SndCorreGema=Bladex.CreateSound("..\\..\\Sounds\\golpe-2.wav","Chanje")
self.SndCorreGema.Volume=0.5
self.SndCorreGema.MinDistance=1000000.0
self.SndCorreGema.MaxDistance=2000000
if self.addone == 0:
while not self.TextsAvail[self.Text]:
self.Text = self.Text + 1
if self.Text > self.NumTexts - 1:
self.Text = 0
def RunCalibration(ConceptualModel, Paths, Basic_inputs, SpatialVarFun, SpatialVarArgs,
OF, OF_args, Q_obs, OptimizationArgs, printError=None):
"""
=======================================================================
RunCalibration(ConceptualModel, Paths, p2, Q_obs, UB, LB, SpatialVarFun, lumpedParNo, lumpedParPos, objective_function, printError=None, *args):
=======================================================================
this function runs the calibration algorithm for the conceptual distributed
hydrological model
Inputs:
----------
1-ConceptualModel:
[function] conceptual model and it should contain a function called simulate
1-Paths:
1-PrecPath:
[String] path to the Folder contains precipitation rasters
2-Evap_Path:
[String] path to the Folder contains Evapotranspiration rasters
3-TempPath:
[String] path to the Folder contains Temperature rasters
4-FlowAccPath:
[String] path to the Flow Accumulation raster of the catchment (it should
include the raster name and extension)
5-FlowDPath:
[String] path to the Flow Direction raster of the catchment (it should
include the raster name and extension)
2-Basic_inputs:
1-p2:
[List] list of unoptimized parameters
p2[0] = tfac, 1 for hourly, 0.25 for 15 min time step and 24 for daily time step
p2[1] = catchment area in km2
2-init_st:
[list] initial values for the state variables [sp,sm,uz,lz,wc] in mm
3-UB:
[Numeric] upper bound of the values of the parameters
4-LB:
[Numeric] Lower bound of the values of the parameters
3-Q_obs:
[Numeric] Observed values of discharge
6-lumpedParNo:
[int] nomber of lumped parameters, you have to enter the value of
the lumped parameter at the end of the list, default is 0 (no lumped parameters)
7-lumpedParPos:
[List] list of order or position of the lumped parameter among all
the parameters of the lumped model (order starts from 0 to the length
of the model parameters), default is [] (empty), the following order
of parameters is used for the lumped HBV model used
[ltt, utt, rfcf, sfcf, ttm, cfmax, cwh, cfr, fc, beta, e_corr, etf, lp,
c_flux, k, k1, alpha, perc, pcorr, Kmuskingum, Xmuskingum]
8-objective_function:
[function] objective function to calculate the performance of the model
and to be used in the calibration
9-*args:
other arguments needed on the objective function
Outputs:
----------
1- st:
[4D array] state variables
2- q_out:
[1D array] calculated Discharge at the outlet of the catchment
3- q_uz:
[3D array] Distributed discharge for each cell
Example:
----------
PrecPath = prec_path="meteodata/4000/calib/prec"
Evap_Path = evap_path="meteodata/4000/calib/evap"
TempPath = temp_path="meteodata/4000/calib/temp"
FlowAccPath = "GIS/4000/acc4000.tif"
FlowDPath = "GIS/4000/fd4000.tif"
ParPath = "meteodata/4000/"+"parameters.txt"
p2=[1, 227.31]
st, q_out, q_uz_routed = RunModel(PrecPath,Evap_Path,TempPath,DemPath,
FlowAccPath,FlowDPath,ParPath,p2)
"""
### inputs validation
# data type
assert len(Paths) == 5, "Paths should include 5 folder pathes " +str(len(Paths))+" paths are only provided"
PrecPath=Paths[0]
Evap_Path=Paths[1]
TempPath=Paths[2]
# DemPath=Paths[3]
FlowAccPath=Paths[3]
FlowDPath=Paths[4]
assert type(PrecPath)== str, "PrecPath input should be string type"
assert type(Evap_Path)== str, "Evap_Path input should be string type"
assert type(TempPath)== str, "TempPath input should be string type"
# assert type(DemPath)== str, "DemPath input should be string type"
assert type(FlowAccPath)== str, "FlowAccPath input should be string type"
assert type(FlowDPath)== str, "FlowDPath input should be string type"
# input values
# dem_ext=DemPath[-4:]
# assert dem_ext == ".tif", "please add the extension at the end of the DEM raster path input"
acc_ext=FlowAccPath[-4:]
assert acc_ext == ".tif", "please add the extension at the end of the Flow accumulation raster path input"
fd_ext=FlowDPath[-4:]
assert fd_ext == ".tif", "please add the extension at the end of the Flow Direction path input"
# check wether the path exists or not
assert os.path.exists(PrecPath), PrecPath + " you have provided does not exist"
assert os.path.exists(Evap_Path), Evap_Path+" path you have provided does not exist"
assert os.path.exists(TempPath), TempPath+" path you have provided does not exist"
# assert os.path.exists(DemPath), DemPath+ " you have provided does not exist"
assert os.path.exists(FlowAccPath), FlowAccPath + " you have provided does not exist"
assert os.path.exists(FlowDPath), FlowDPath+ " you have provided does not exist"
# check wether the folder has the rasters or not
assert len(os.listdir(PrecPath)) > 0, PrecPath+" folder you have provided is empty"
assert len(os.listdir(Evap_Path)) > 0, Evap_Path+" folder you have provided is empty"
assert len(os.listdir(TempPath)) > 0, TempPath+" folder you have provided is empty"
# basic inputs
# check if all inputs are included
assert all(["p2","init_st","UB","LB","snow "][i] in Basic_inputs.keys() for i in range(4)), "Basic_inputs should contain ['p2','init_st','UB','LB'] "
p2 = Basic_inputs['p2']
init_st = Basic_inputs["init_st"]
UB = Basic_inputs['UB']
LB = Basic_inputs['LB']
snow = Basic_inputs['snow']
assert len(UB)==len(LB), "length of UB should be the same like LB"
# check objective_function
assert callable(OF) , "second argument should be a function"
if OF_args== None :
OF_args=[]
# read data
### meteorological data
prec=Raster.ReadRastersFolder(PrecPath)
evap=Raster.ReadRastersFolder(Evap_Path)
temp=Raster.ReadRastersFolder(TempPath)
print("meteorological data are read successfully")
#### GIS data
# dem= gdal.Open(DemPath)
acc=gdal.Open(FlowAccPath)
fd=gdal.Open(FlowDPath)
print("GIS data are read successfully")
### optimization
# get arguments
store_history=OptimizationArgs[0]
history_fname=OptimizationArgs[1]
# check optimization arguement
assert store_history !=0 or store_history != 1,"store_history should be 0 or 1"
assert type(history_fname) == str, "history_fname should be of type string "
assert history_fname[-4:] == ".txt", "history_fname should be txt file please change extension or add .txt ad the end of the history_fname"
print('Calibration starts')
### calculate the objective function
def opt_fun(par):
try:
# parameters
klb=float(par[-2])
kub=float(par[-1])
par=par[:-2]
par_dist=SpatialVarFun(par,*SpatialVarArgs,kub=kub,klb=klb)
#run the model
_, q_out, q_uz_routed, q_lz_trans=Wrapper.Dist_model(ConceptualModel,
acc, fd, prec, evap,
temp, par_dist, p2,
snow , init_st)
# calculate performance of the model
try:
error=OF(Q_obs,q_out,q_uz_routed,q_lz_trans,*OF_args)
except TypeError: # if no of inputs less than what the function needs
assert 1==5, "the objective function you have entered needs more inputs please enter then in a list as *args"
# print error
if printError != 0:
print(error)
print(par)
fail = 0
except:
error = np.nan
fail = 1
return error, [], fail
### define the optimization components
opt_prob = Optimization('HBV Calibration', opt_fun)
for i in range(len(LB)):
opt_prob.addVar('x{0}'.format(i), type='c', lower=LB[i], upper=UB[i])
print(opt_prob)
opt_engine = ALHSO(etol=0.0001,atol=0.0001,rtol=0.0001, stopiters=10,
hmcr=0.5,par=0.5) #,filename='mostafa.out'
Optimizer.__init__(opt_engine,def_options={
'hms':[int,9], # Memory Size [1,50]
'hmcr':[float,0.95], # Probability rate of choosing from memory [0.7,0.99]
'par':[float,0.99], # Pitch adjustment rate [0.1,0.99]
'dbw':[int,2000], # Variable Bandwidth Quantization
'maxoutiter':[int,2e3], # Maximum Number of Outer Loop Iterations (Major Iterations)
'maxinniter':[int,2e2], # Maximum Number of Inner Loop Iterations (Minor Iterations)
'stopcriteria':[int,1], # Stopping Criteria Flag
'stopiters':[int,20], # Consecutively Number of Outer Iterations for which the Stopping Criteria must be Satisfied
'etol':[float,0.0001], # Absolute Tolerance for Equality constraints
'itol':[float,0.0001], # Absolute Tolerance for Inequality constraints
'atol':[float,0.0001], # Absolute Tolerance for Objective Function 1e-6
'rtol':[float,0.0001], # Relative Tolerance for Objective Function
'prtoutiter':[int,0], # Number of Iterations Before Print Outer Loop Information
'prtinniter':[int,0], # Number of Iterations Before Print Inner Loop Information
'xinit':[int,0], # Initial Position Flag (0 - no position, 1 - position given)
'rinit':[float,1.0], # Initial Penalty Factor
'fileout':[int,store_history], # Flag to Turn On Output to filename
'filename':[str,'parameters.txt'], # We could probably remove fileout flag if filename or fileinstance is given
'seed':[float,0.5], # Random Number Seed (0 - Auto-Seed based on time clock)
'scaling':[int,1], # Design Variables Scaling Flag (0 - no scaling, 1 - scaling between [-1,1])
})
res = opt_engine(opt_prob)
return res
def Draw(self, x, y, time):
if self.GetVisible() == 0:
return
#self.SetAlpha(0.5)
foc = self.GetHasFocus()
if foc != self._foc:
self.SelectionFilterUpdated = 0
self.FilterIncX = 0
self.FilterUpdated = 0
self._foc = foc
w, h = self.GetSize()
if foc:
if self.ActionName:
if ActionDescriptor.has_key(self.ActionName):
netwidgets.LabelName = MenuText.GetMenuText(
ActionDescriptor[self.ActionName])
else:
netwidgets.LabelName = " "
if self.ChangingKey:
mult = math.cos(time * 2)
self.SetColor(80 * mult + 150, 80 * mult + 150,
45 * mult + 105)
self.DefDraw(x, y, time)
return
elif self.SelectionFilterUpdated:
Raster.SetPosition(x - self.FilterIncX, y - self.FilterIncY)
Raster.DrawImage(w + 2 * self.FilterIncX,
h + 2 * self.FilterIncY, "RGB", "Native",
self.SelectionFilter.GetImageBuffer())
self.SetColor(252, 247, 167)
self.DefDraw(x, y, time)
self.SetColor(207, 144, 49)
return
else:
## if self.Filter is None:
## self.CreateBlur(x,y,time)
## Raster.SetPosition(x-2,y-2)
## Raster.DrawImage(w+4,h+4,"RGB","Native",self.Filter.GetImageBuffer())
## if Raster.GetClipActive():
## print self.Name(),"ClipActive:",Raster.GetClipWindow()
## else:
## print self.Name(),"ClipNoActive:"
self.DefDraw(x, y, time)
return
if foc:
#self.CreateDistorsion(x,y,time)
#if self.Filter is None:
# self.CreateBlur(x,y,time)
# self.FilterUpdated=1
#sfw,sfh=self.Filter.GetDimension()
#self.SelectionFilter.CopySubBuffer(self.FilterIncX-2,0,sfw,sfh,self.Filter.GetImageBuffer(),"AddInc")
#self.SelectionFilter.GetFromBuffer2("Substract")
#Raster.SetPosition(x-self.FilterIncX,y-self.FilterIncY)
#Raster.DrawImage(w+2*self.FilterIncX,h+2*self.FilterIncY,"RGB","Native",self.SelectionFilter.GetImageBuffer())
self.SetColor(252, 247, 167)
self.DefDraw(x, y, time)
self.SetColor(207, 144, 49)
if self.FilterIncX > 25:
self.SelectionFilterUpdated = 1
else:
self.SelectionFilterUpdated = 0
output_img_path = os.path.join(tmp_dir, f"r{output_file_name}.TIF")
rprj = RR.RasterReproject(input_img_path, output_img_path)
rprj.reproject_raster_to_epsg4674()
# Clip
img_path = f"{tmp_dir}/r{output_file_name}.TIF"
c = CR.ClipRaster(
img_path=img_path,
tmp_dir=tmp_dir,
scene_file_name=parameter_satellite["scene_file_name"],
output_dir=output_dir,
output_file_name=output_file_name)
r = R.Raster(img_path=img_path)
if r.intersects_trace_outline_aoi():
c.clip_raster_by_mask(band_order=[1, 2, 3])
else:
import RasterTranslate as RT
rt = RT.RasterTranslate(img_path=img_path,
output_dir=output_dir,
output_file_name=output_file_name)
rt.translate_8bit(band_order=[1, 2, 3])
# Make pyramid
img_path = os.path.join(output_dir, f"{output_file_name}.TIF")
PR.PyramidRaster(img_path=img_path).create_img_pyramid()
# Save when file was processed in postgres database