def BerkeleyDB(bat):
if bat.build:
tools.extract('bdb')
bat.command('cd bdb\\build_windows')
# building the .NET solution also builds native DLLs
bat.devenv('BDB_dotNet_vs2010.sln')
else:
bat.validate_devenv()
bat.include('bdb\\build_windows\\*.h')
bat.bin('bdb\\build_windows\\AnyCPU\\{0}\\*.dll'.format(bat.config))
bat.bin('bdb\\build_windows\\win32\\{0}\\*.dll'.format(bat.config),
'bdb\\build_windows\\x64\\{0}\\*.dll'.format(bat.config))
bat.lib('bdb\\build_windows\\win32\\{0}\\*.lib'.format(bat.config),
'bdb\\build_windows\\x64\\{0}\\*.lib'.format(bat.config))
def Boost(bat):
def param(config, platform):
p = ' --hash --without-mpi toolset=msvc-{0}'.format(setup.VC_VERSION)
p += ' -sICU_PATH={0}\\{1}'.format(setup.INSTALL, platform)
p += ' -sZLIB_SOURCE={0}\\zlib'.format(os.getcwd())
p += ' variant={0} link=static runtime-link=static runtime-link=shared threading=multi'.format(config)
p += ' --prefix={0}\\{1}'.format(setup.INSTALL, platform)
p += ' address-model={0}'.format(64 if platform=='x64' else 32)
return p
if bat.build:
tools.extract('boost')
tools.extract('zlib')
bat.command('cd boost')
bat.command('b2 -a {0} install'.format(param(bat.config, bat.platform)))
def FreeType(bat):
if bat.build:
tools.extract('freetype')
# add missing x64 support
bat.command('copy /y archives\\freetype-project\\* freetype\\builds\\win32\\vc2010')
bat.command('cd freetype\\builds\\win32\\vc2010')
bat.devenv('freetype.sln')
else:
bat.validate_devenv()
bat.command('pushd freetype\\objs\\win32\\vc2010')
if bat.config == 'release':
bat.command('copy /y freetype246.lib freetype.lib')
bat.command('del freetype246.lib')
else:
bat.command('copy /y freetype246_d.lib freetyped.lib')
bat.command('del freetype246_d.lib')
bat.command('popd')
bat.include('freetype\\include')
bat.lib('freetype\\objs\\win32\\vc2010\\*.lib')
def get(self, request, modelName, id):
context = request.session
session_id = context['IndexInput']['id']
_model = self.class_map[modelName][0]
item = _model.objects.get(session_id=session_id,id=id)
if 's' in request.GET:
exclude = self.class_map[modelName][1]
_form = modelform_factory(_model,exclude=exclude)
form = _form(instance=item)
return render(request, 'updateItem.html', { 'modelName':modelName, 'form':form, 'status': 0 })
else:
return JsonResponse(extract(item))
def addText():
'''
获取text框中的文本，方便进行检索
'''
text = t.get('0.0', 'end')
info_dict = tools.extract(text, item_list) # 抽取信息
t.delete('0.0', 'end')
text = lb.get(lb.curselection())
text = re.sub(re.compile(r'#.*#: '), '', text)
text = tools.fullfill(text, info_dict) # 自动填充文本
text = re.sub(re.compile(r'<e>.*<e>'), '__', text)
# text = text.replace('<e>.*<e>', '____')
t.insert('end', text) # 获取当前选中的文本
def get(self, request, modelName, id):
context = request.session
session_id = context['IndexInput']['id']
_model = self.class_map[modelName][0]
item = _model.objects.get(session_id=session_id, id=id)
if 's' in request.GET:
exclude = self.class_map[modelName][1]
_form = modelform_factory(_model, exclude=exclude)
form = _form(instance=item)
return render(request, 'updateItem.html', {
'modelName': modelName,
'form': form,
'status': 0
})
else:
return JsonResponse(extract(item))
def drawColorbar(self):
"""
Draw the vertically-oriented colorbar.
* Not many customizable options here because the colorbar is a 'plt' object
* and the options are applied to attributes.
* User needs to modify or extend this function.
"""
cbar = plt.colorbar()
try:
cbar.ax.set_ylabel(self.colorbar["title"])
except KeyError:
print " WARNING : Key 'title' not specified for colorbar."
print " : Leaving colorbar title blank. "
# Modify tick labels
axis_ticklabels = [i.get_text() for i in cbar.ax.get_yticklabels()]
if self.logplot['data']:
for i,atl in enumerate(axis_ticklabels):
if not "10^{" in atl: continue
atl = atl.strip("$")
power = r"10$^{\text{%s}}$"%tools.extract(atl)
tmp = atl.split("\\times")
if len(tmp)>1:
axis_ticklabels[i] = tmp[0]+r"$\times$"+power
else:
axis_ticklabels[i] = power
else:
axis_ticklabels = [i.strip("$") for i in axis_ticklabels]
cbar_fsize = int(mpl.rcParams['axes.labelsize']*0.75)
cbar.ax.set_yticklabels(axis_ticklabels,
fontsize=cbar_fsize)
# Modify tick sizes
for tick in ['major','minor']:
length = self.colorbar.get("ytick.{0}.size".format(tick),0)
cbar.ax.yaxis.set_tick_params(which=tick,length=length)
return
first_loop = False
instruciones2 = copy.deepcopy(instruciones)
except:
item = "fail"
print('First load of loopload fail')
if ins >= 1:
instruciones["instruciones"].pop(0)
if instruciones["instruciones"][0]["operation_type"] == "load":
#webContent = tools.split_and_load(instruciones["instruciones"][0]["pagina"])
webContent = tools.split_and_load1(instruciones["instruciones"][0])
link = instruciones["instruciones"][0]["pagina"]
if instruciones["instruciones"][0]["operation_type"] == "extract":
resultadosdict[
instruciones["instruciones"][0]["save_var"]] = tools.extract(
instruciones["instruciones"][0]["tag"],
instruciones["instruciones"][0]["regex"],
instruciones["instruciones"][0]["type"], link,
webContent) # Da error porque sigue en la misma instrucion.
if instruciones["instruciones"][0][
"operation_type"] == "loopload": #El nombre de la variable, por cada loop debe ser distinto
linklist = tools2.loopload(instruciones["instruciones"][0]["tag"],
webContent, link)
first_loop = True
if instruciones["instruciones"][0]["operation_type"] == "end":
try:
print("Iteracion :" + str(iter))
instruciones = copy.deepcopy(instruciones2)
resultados.append(resultadosdict)
resultadosdict = {}
webContent = tools.split_and_load(linklist[iter])
iter += 1
def extract_source_code(self):
"""
Find and extract source tarball for the component.
"""
# We look for a tar file
pattern = "{n}*.tar.*".format(n=self.component_data_dict["package_name"])
# Use 'package_version' in pattern if it is not None
if self.component_data_dict["version"] is not None:
pattern = "{n}*{v}*.tar.*".format(n=self.component_data_dict["package_name"],
v=self.component_data_dict["version"])
source_code_filename = tools.find_file(self.component_data_dict["sources_directory"],
pattern)
# Try a second run if 'source_code_filename' is None using only name as pattern.
if source_code_filename is None:
pattern = "{n}*.tar.*".format(n=self.component_data_dict["package_name"])
source_code_filename = tools.find_file(self.component_data_dict["sources_directory"],
pattern)
# Try to find a zip file in case the tar file was not found
if source_code_filename is None:
pattern = "{n}*.zip*".format(n=self.component_data_dict["package_name"])
# Use 'package_version' in pattern if it is not None
if self.component_data_dict["version"] is not None:
pattern = "{n}*{v}*.zip*".format(n=self.component_data_dict["package_name"],
v=self.component_data_dict["version"])
source_code_filename = tools.find_file(self.component_data_dict["sources_directory"],
pattern)
# Try a second run if 'source_code_filename' is None using only name as pattern.
if source_code_filename is None:
pattern = "{n}*.zip*".format(n=self.component_data_dict["package_name"])
source_code_filename = tools.find_file(
self.component_data_dict["sources_directory"],
pattern
)
# Give error if None
if source_code_filename is None:
msg = "Can't find source code file for '{n}' with pattern: '{p}'"
msg = msg.format(n=self.component_data_dict["name"], p=pattern)
printer.error(msg)
# Extract
tools.extract(source_code_filename)
# We get the name of the extracted directory
pattern = "{n}*".format(n=self.component_data_dict["package_name"])
# Use 'package_version' in pattern if it is not None
if self.component_data_dict["version"] is not None:
pattern = "{n}*{v}*".format(n=self.component_data_dict["package_name"],
v=self.component_data_dict["version"])
# Find directory using pattern
self.component_data_dict["extracted_directory"] = tools.find_directory(
self.component_data_dict["sources_directory"],
pattern)
# Try a second run if 'extracted_directory' is None using only name as pattern.
# If found, get the realpath
if self.component_data_dict["extracted_directory"] is None:
pattern = "{n}*".format(n=self.component_data_dict["package_name"])
self.component_data_dict["extracted_directory"] = tools.find_directory(
self.component_data_dict["sources_directory"],
pattern
)
else:
self.component_data_dict["extracted_directory"] = os.path.realpath(
self.component_data_dict["extracted_directory"]
)
# Fail if not found 'extracted_directroy'
if self.component_data_dict["extracted_directory"] is None:
msg = "Can't find extracted directory for '{n}' with pattern: '{p}'"
msg = msg.format(n=self.component_data_dict["name"], p=pattern)
printer.error(msg)
# Generate build_dir if necessary.
if self.component_data_dict["require_build_dir"] is True:
# Generate and save 'build_directory' path
value = os.path.realpath(
os.path.join(
self.component_data_dict["extracted_directory"],
self.build_directory_name
)
)
tools.add_to_dictionary(self.component_data_dict,
"build_directory_path",
value,
concat=False)
# Create directory
tools.create_directory(self.component_data_dict["build_directory_path"])
else:
# If not, build component into the extracted directory
tools.add_to_dictionary(self.component_data_dict,
"build_directory_path",
self.component_data_dict["extracted_directory"],
concat=False)
# Set directory owner if we are building the 'toolchain'
if self.component_data_dict["builder_name"] == "toolchain":
tools.set_recursive_owner_and_group(self.component_data_dict["extracted_directory"],
self.component_data_dict["run_as_username"])
def build_reader():
reader = root.TMVA.Reader("reader")
var_mJJ = array('f',[0])
var_deltaYJJ = array('f',[0])
var_metPt = array('f',[0])
var_ptBalance = array('f',[0])
var_subleadJetEta = array('f',[0])
var_leadJetPt = array('f',[0])
var_photonEta = array('f',[0])
var_ptBalanceRed = array('f',[0])
var_nJets = array('f',[0])
var_sinDeltaPhiJJOver2 = array('f',[0])
var_deltaYJPh = array('f',[0])
reader.AddVariable("mJJ", var_mJJ)
reader.AddVariable("deltaYJJ", var_deltaYJJ)
reader.AddVariable("metPt", var_metPt)
reader.AddVariable("ptBalance", var_ptBalance)
reader.AddVariable("subleadJetEta", var_subleadJetEta)
reader.AddVariable("leadJetPt", var_leadJetPt)
reader.AddVariable("photonEta", var_photonEta)
reader.AddVariable("ptBalanceRed", var_ptBalanceRed)
reader.AddVariable("nJets", var_nJets)
reader.AddVariable("sinDeltaPhiJJOver2",var_sinDeltaPhiJJOver2)
reader.AddVariable("deltaYJPh", var_deltaYJPh)
reader.BookMVA("MLP", "dataloader/weights/TMVAClassification_MLP.weights.xml")
SDataframe, BDataframe = extract()
SDataframe["BDToutput"] = 0.0
BDataframe["BDToutput"] = 0.0
output = []
for i, row in SDataframe.iterrows():
var_mJJ[0] = row["mJJ"]
var_deltaYJJ[0] = row["deltaYJJ"]
var_metPt[0] = row["metPt"]
var_ptBalance[0] = row["ptBalance"]
var_subleadJetEta[0] = row["subleadJetEta"]
var_leadJetPt[0] = row["leadJetPt"]
var_photonEta[0] = row["photonEta"]
var_ptBalanceRed[0] = row["ptBalanceRed"]
var_nJets[0] = row["nJets"]
var_sinDeltaPhiJJOver2[0] = row["sinDeltaPhiJJOver2"]
var_deltaYJPh[0] = row["deltaYJPh"]
output.append(reader.EvaluateMVA("MLP"))
SDataframe["BDToutput"] = output
output = []
for i, row in BDataframe.iterrows():
var_mJJ[0] = row["mJJ"]
var_deltaYJJ[0] = row["deltaYJJ"]
var_metPt[0] = row["metPt"]
var_ptBalance[0] = row["ptBalance"]
var_subleadJetEta[0] = row["subleadJetEta"]
var_leadJetPt[0] = row["leadJetPt"]
var_photonEta[0] = row["photonEta"]
var_ptBalanceRed[0] = row["ptBalanceRed"]
var_nJets[0] = row["nJets"]
var_sinDeltaPhiJJOver2[0] = row["sinDeltaPhiJJOver2"]
var_deltaYJPh[0] = row["deltaYJPh"]
output.append(reader.EvaluateMVA("MLP"))
BDataframe["BDToutput"] = output
print("После отборов классификатора")
print(sum(SDataframe[SDataframe["BDToutput"] > 0.682]["weightModified"]))
print(sum(BDataframe[BDataframe["BDToutput"] > 0.682]["weightModified"]))
print("Фиксированные")
df = SDataframe[SDataframe["phCentrality"] < 0.455]
df = df[df["mJJ"] > 697]
df = df[df["ptBalance"] < 0.064]
df = df[df["deltaYJJ"] > 2.227]
print(sum(df["weightModified"]))
df = BDataframe[BDataframe["phCentrality"] < 0.455]
df = df[df["mJJ"] > 697]
df = df[df["ptBalance"] < 0.064]
df = df[df["deltaYJJ"] > 2.227]
print(sum(df["weightModified"]))
# import matplotlib.pyplot as plt
# fig, ax = plt.subplots()
# ax.hist(SDataframe["BDToutput"], weights=SDataframe["weightModified"], bins=50, color="blue", alpha=0.5, label="signal")
# ax.hist(BDataframe["BDToutput"], weights=BDataframe["weightModified"], bins=50, color="red", alpha=0.5, label="background")
# ax.legend()
# ax.set_xlabel("BDToutput")
# ax.set_ylabel("N of events")
# plt.show()
# canvas = root.TCanvas("canvas", "CANVAS", 1920, 1080)
SHist = root.TH1F("", "", 50, 0, 1)
BHist = root.TH1F("", "", 50, 0, 1)
BHist.SetStats(False)
SHist.SetStats(False)
BHist.SetLineWidth(2)
BHist.SetLineColor(2)
BHist.SetFillColor(2)
BHist.SetFillStyle(3004)
BHist.GetXaxis().CenterTitle()
BHist.GetYaxis().SetTitle("Fraction of events")
BHist.GetYaxis().CenterTitle()
BHist.GetXaxis().SetTitleOffset(1.2)
BHist.SetMinimum(0)
SHist.SetLineWidth(2)
SHist.SetLineColor(4)
SHist.SetFillColorAlpha(4, 0.2)
SHist.GetXaxis().CenterTitle()
SHist.GetYaxis().SetTitle("Fraction of events")
SHist.GetYaxis().CenterTitle()
SHist.GetXaxis().SetTitleOffset(1.2)
SHist.SetMinimum(0)
for out, weight in zip(SDataframe["BDToutput"], SDataframe["weightModified"]):
SHist.Fill(out, weight)
for out, weight in zip(BDataframe["BDToutput"], BDataframe["weightModified"]):
BHist.Fill(out, weight)
aplt.set_atlas_style()
fig, ax = aplt.subplots(1, 1, name="fig1", figsize=(800, 600))
#####################################
ax.plot(SHist, "E1")
ax.plot(BHist, "E1")
######################################
ax.add_margins(top=0.16)
ax.set_xlabel("MLP classifier response")
ax.set_ylabel("Fraction of events")
# aplt.atlas_label(text="Internal", loc="upper left")
ax.text(0.2, 0.92, "#sqrt{s} = 13 TeV, 139 fb^{-1}", size=27, align=13)
# ax.text(0.205, 0.865, "Z_{#gamma} inc. region", size=27, align=13)
legend = root.TLegend(0.65, 0.8, 0.95, 0.92)
legend.SetFillColorAlpha(0, 0)
legend.AddEntry(SHist, "Signal", "F")
legend.AddEntry(BHist, "Background", "F")
legend.Draw()
# fig.savefig("histogramms/{}.pdf".format("BDToutput"))
# input()
return make_selections(SDataframe, BDataframe)
def build_reader(model_id):
reader = root.TMVA.Reader("reader")
var_mJJ = array('f', [0])
var_deltaYJJ = array('f', [0])
var_metPt = array('f', [0])
var_ptBalance = array('f', [0])
var_subleadJetEta = array('f', [0])
var_leadJetPt = array('f', [0])
var_photonEta = array('f', [0])
var_ptBalanceRed = array('f', [0])
var_nJets = array('f', [0])
var_sinDeltaPhiJJOver2 = array('f', [0])
var_deltaYJPh = array('f', [0])
reader.AddVariable("mJJ", var_mJJ)
reader.AddVariable("deltaYJJ", var_deltaYJJ)
reader.AddVariable("metPt", var_metPt)
reader.AddVariable("ptBalance", var_ptBalance)
reader.AddVariable("subleadJetEta", var_subleadJetEta)
reader.AddVariable("leadJetPt", var_leadJetPt)
reader.AddVariable("photonEta", var_photonEta)
reader.AddVariable("ptBalanceRed", var_ptBalanceRed)
reader.AddVariable("nJets", var_nJets)
reader.AddVariable("sinDeltaPhiJJOver2", var_sinDeltaPhiJJOver2)
reader.AddVariable("deltaYJPh", var_deltaYJPh)
reader.BookMVA(
"MLP",
f"dataloader/weights/TMVAClassification_MLP{model_id}.weights.xml")
SDataframe, BDataframe = extract()
SDataframe["BDToutput"] = 0.0
BDataframe["BDToutput"] = 0.0
print("Веса до применения классификатора:")
print(np.sum(SDataframe["weightModified"]))
print(np.sum(BDataframe["weightModified"]))
output = []
for i, row in SDataframe.iterrows():
var_mJJ[0] = row["mJJ"]
var_deltaYJJ[0] = row["deltaYJJ"]
var_metPt[0] = row["metPt"]
var_ptBalance[0] = row["ptBalance"]
var_subleadJetEta[0] = row["subleadJetEta"]
var_leadJetPt[0] = row["leadJetPt"]
var_photonEta[0] = row["photonEta"]
var_ptBalanceRed[0] = row["ptBalanceRed"]
var_nJets[0] = row["nJets"]
var_sinDeltaPhiJJOver2[0] = row["sinDeltaPhiJJOver2"]
var_deltaYJPh[0] = row["deltaYJPh"]
output.append(reader.EvaluateMVA("MLP"))
SDataframe["BDToutput"] = output
output = []
for i, row in BDataframe.iterrows():
var_mJJ[0] = row["mJJ"]
var_deltaYJJ[0] = row["deltaYJJ"]
var_metPt[0] = row["metPt"]
var_ptBalance[0] = row["ptBalance"]
var_subleadJetEta[0] = row["subleadJetEta"]
var_leadJetPt[0] = row["leadJetPt"]
var_photonEta[0] = row["photonEta"]
var_ptBalanceRed[0] = row["ptBalanceRed"]
var_nJets[0] = row["nJets"]
var_sinDeltaPhiJJOver2[0] = row["sinDeltaPhiJJOver2"]
var_deltaYJPh[0] = row["deltaYJPh"]
output.append(reader.EvaluateMVA("MLP"))
BDataframe["BDToutput"] = output
SHist = root.TH1F("", "", 50, 0, 1)
BHist = root.TH1F("", "", 50, 0, 1)
BHist.SetStats(False)
SHist.SetStats(False)
BHist.SetLineWidth(2)
BHist.SetLineColor(2)
BHist.SetFillColor(2)
BHist.SetFillStyle(3004)
BHist.GetXaxis().CenterTitle()
BHist.GetYaxis().SetTitle("Fraction of events")
BHist.GetYaxis().CenterTitle()
BHist.GetXaxis().SetTitleOffset(1.2)
BHist.SetMinimum(0)
SHist.SetLineWidth(2)
SHist.SetLineColor(4)
SHist.SetFillColorAlpha(4, 0.2)
SHist.GetXaxis().CenterTitle()
SHist.GetYaxis().SetTitle("Fraction of events")
SHist.GetYaxis().CenterTitle()
SHist.GetXaxis().SetTitleOffset(1.2)
SHist.SetMinimum(0)
for out, weight in zip(SDataframe["BDToutput"],
SDataframe["weightModified"]):
SHist.Fill(out, weight)
for out, weight in zip(BDataframe["BDToutput"],
BDataframe["weightModified"]):
BHist.Fill(out, weight)
aplt.set_atlas_style()
fig, ax = aplt.subplots(1, 1, name="fig1", figsize=(800, 600))
#####################################
ax.plot(SHist, "E1")
ax.plot(BHist, "E1")
######################################
ax.add_margins(top=0.16)
# ax.add_margins(top=0.2)
ax.set_xlabel(f"MLP{model_id} classifier response")
ax.set_ylabel("Fraction of events")
ax.text(0.2, 0.92, "#sqrt{s} = 13 TeV, 139 fb^{-1}", size=27, align=13)
legend = root.TLegend(0.65, 0.8, 0.95, 0.92)
legend.SetFillColorAlpha(0, 0)
legend.AddEntry(SHist, "Signal", "F")
legend.AddEntry(BHist, "Background", "F")
legend.Draw()
fig.savefig(f"MLP{model_id}output.pdf")
# input()
return make_selections(SDataframe, BDataframe)
def post(self, request, *args, **kwargs):
#all saved to session
context = request.session
#process inputs from inputMain
#process gwOpt and swsOpt
indexInput = IndexInput.objects.get(id=context['IndexInput']['id'])
if request.POST['gwOpt'] != 'on' or request.POST['swsOpt'] != 'on':
if request.POST['gwOpt'] != 'on':
indexInput.gwOpt = False
if request.POST['swsOpt'] != 'on':
indexInput.swsOpt = False
indexInput.save()
#process WatershedLandUse
context['WatershedLandUse'] = {}
for watershd_id in context['rangeWSD']:
if not WatershedLandUse.objects.filter(
session_id=indexInput.id,
watershd_id=watershd_id).exists():
watershedLandUse = WatershedLandUse(session_id=indexInput.id,
watershd_id=watershd_id)
else:
watershedLandUse = WatershedLandUse.objects.get(
session_id=indexInput.id, watershd_id=watershd_id)
watershedLandUse.HSG = request.POST['HSG_' + twonum(watershd_id)]
watershedLandUse.FeedlotPercentPaved = request.POST[
'PctFeedlot_' + twonum(watershd_id)]
watershedLandUse.Total = request.POST['TAreaWSD_' +
twonum(watershd_id)]
for i in range(1, 7):
setattr(
watershedLandUse, WatershedLandUse_index_map[i],
request.POST['LuseAreaWSD_' + str(i) +
twonum(watershd_id)])
watershedLandUse.save()
#prepare data for rendering template
context['WatershedLandUse'][watershd_id] = extract(
watershedLandUse)
#process AgriAnimal
for watershd_id in context['rangeWSD']:
if not AgriAnimal.objects.filter(session_id=indexInput.id,
watershd_id=watershd_id).exists():
agriAnimal = AgriAnimal(session_id=indexInput.id,
watershd_id=watershd_id)
else:
agriAnimal = AgriAnimal.objects.get(session_id=indexInput.id,
watershd_id=watershd_id)
agriAnimal.numMonthsManureApplied = request.POST[
'NumMonManure_' + twonum(watershd_id)]
for i in range(1, 9):
setattr(
agriAnimal, AgriAnimal_index_map[i],
request.POST['Animals_' + str(i) + twonum(watershd_id)])
agriAnimal.save()
#process SepticNillegal
for watershd_id in context['rangeWSD']:
if not SepticNillegal.objects.filter(
session_id=indexInput.id,
watershd_id=watershd_id).exists():
septicNillegal = SepticNillegal(session_id=indexInput.id,
watershd_id=watershd_id)
else:
septicNillegal = SepticNillegal.objects.get(
session_id=indexInput.id, watershd_id=watershd_id)
septicNillegal.numSepticSystems = request.POST['NumSpSys_' +
twonum(watershd_id)]
septicNillegal.PopulationPerSeptic = request.POST[
'PpSpSys_' + twonum(watershd_id)]
septicNillegal.SepticFailureRate_Percent = request.POST[
'SpFailRate_' + twonum(watershd_id)]
septicNillegal.Wastewater_Direct_Discharge_numPeople = request.POST[
'NumPpDrtDc_' + twonum(watershd_id)]
septicNillegal.Direct_Discharge_Reduction_Percent = request.POST[
'RdcDrtDc_' + twonum(watershd_id)]
septicNillegal.save()
#process UniversalSoilLossEquation
for watershd_id in context['rangeWSD']:
if not UniversalSoilLossEquation.objects.filter(
session_id=indexInput.id,
watershd_id=watershd_id).exists():
ele = UniversalSoilLossEquation(session_id=indexInput.id,
watershd_id=watershd_id)
else:
ele = UniversalSoilLossEquation.objects.get(
session_id=indexInput.id, watershd_id=watershd_id)
for i in range(1, 6):
setattr(
ele, "Cropland_" + UniversalSoilLossEquation_index_map[i],
request.POST['usleCropland_' + str(i) +
twonum(watershd_id)])
for i in range(1, 6):
setattr(
ele,
"Pastureland_" + UniversalSoilLossEquation_index_map[i],
request.POST['uslePasture_' + str(i) +
twonum(watershd_id)])
for i in range(1, 6):
setattr(
ele, "Forest_" + UniversalSoilLossEquation_index_map[i],
request.POST['usleForest_' + str(i) + twonum(watershd_id)])
for i in range(1, 6):
setattr(
ele,
"UserDefined_" + UniversalSoilLossEquation_index_map[i],
request.POST['usleUser_' + str(i) + twonum(watershd_id)])
ele.save()
#load LanduseDistribution
context['LanduseDistributionInput'] = list2dictWthKey(
'watershd_id',
LanduseDistributionInput.objects.filter(
session_id=indexInput.id).values())
return render(request, 'bmpMain.html', {
'ctx': context,
'req': request
})
def bjam(bat):
if bat.build:
tools.extract('boost')
bat.command('cd boost')
bat.command('bootstrap.bat >bjam.log')
def post(self, request, *args, **kwargs):
#all saved to session
context = request.session
#process inputs from inputMain
#process gwOpt and swsOpt
indexInput = IndexInput.objects.get(id=context['IndexInput']['id'])
if request.POST['gwOpt']!='on' or request.POST['swsOpt']!='on':
if request.POST['gwOpt']!='on':
indexInput.gwOpt=False
if request.POST['swsOpt']!='on':
indexInput.swsOpt=False
indexInput.save()
#process WatershedLandUse
context['WatershedLandUse'] = {}
for watershd_id in context['rangeWSD'] :
if not WatershedLandUse.objects.filter(session_id=indexInput.id, watershd_id=watershd_id).exists():
watershedLandUse = WatershedLandUse(
session_id=indexInput.id,
watershd_id=watershd_id
)
else:
watershedLandUse = WatershedLandUse.objects.get(session_id=indexInput.id, watershd_id=watershd_id)
watershedLandUse.HSG = request.POST['HSG_' + twonum(watershd_id)]
watershedLandUse.FeedlotPercentPaved = request.POST['PctFeedlot_' + twonum(watershd_id)]
watershedLandUse.Total = request.POST['TAreaWSD_' + twonum(watershd_id)]
for i in range(1,7):
setattr( watershedLandUse,WatershedLandUse_index_map[i],request.POST['LuseAreaWSD_'+str(i)+twonum(watershd_id)] )
watershedLandUse.save()
#prepare data for rendering template
context['WatershedLandUse'][watershd_id] = extract(watershedLandUse)
#process AgriAnimal
for watershd_id in context['rangeWSD'] :
if not AgriAnimal.objects.filter(session_id=indexInput.id, watershd_id=watershd_id).exists():
agriAnimal = AgriAnimal(
session_id=indexInput.id,
watershd_id=watershd_id
)
else:
agriAnimal = AgriAnimal.objects.get(session_id=indexInput.id, watershd_id=watershd_id)
agriAnimal.numMonthsManureApplied = request.POST['NumMonManure_' + twonum(watershd_id)]
for i in range(1,9):
setattr( agriAnimal,AgriAnimal_index_map[i],request.POST['Animals_'+str(i)+twonum(watershd_id)] )
agriAnimal.save()
#process SepticNillegal
for watershd_id in context['rangeWSD'] :
if not SepticNillegal.objects.filter(session_id=indexInput.id, watershd_id=watershd_id).exists():
septicNillegal = SepticNillegal(
session_id=indexInput.id,
watershd_id=watershd_id
)
else:
septicNillegal = SepticNillegal.objects.get(session_id=indexInput.id, watershd_id=watershd_id)
septicNillegal.numSepticSystems = request.POST['NumSpSys_' + twonum(watershd_id)]
septicNillegal.PopulationPerSeptic = request.POST['PpSpSys_' + twonum(watershd_id)]
septicNillegal.SepticFailureRate_Percent = request.POST['SpFailRate_' + twonum(watershd_id)]
septicNillegal.Wastewater_Direct_Discharge_numPeople = request.POST['NumPpDrtDc_' + twonum(watershd_id)]
septicNillegal.Direct_Discharge_Reduction_Percent = request.POST['RdcDrtDc_' + twonum(watershd_id)]
septicNillegal.save()
#process UniversalSoilLossEquation
for watershd_id in context['rangeWSD'] :
if not UniversalSoilLossEquation.objects.filter(session_id=indexInput.id, watershd_id=watershd_id).exists():
ele = UniversalSoilLossEquation(
session_id=indexInput.id,
watershd_id=watershd_id
)
else:
ele = UniversalSoilLossEquation.objects.get(session_id=indexInput.id, watershd_id=watershd_id)
for i in range(1,6):
setattr( ele,"Cropland_"+UniversalSoilLossEquation_index_map[i],request.POST['usleCropland_'+str(i)+twonum(watershd_id)] )
for i in range(1,6):
setattr( ele,"Pastureland_"+UniversalSoilLossEquation_index_map[i],request.POST['uslePasture_'+str(i)+twonum(watershd_id)] )
for i in range(1,6):
setattr( ele,"Forest_"+UniversalSoilLossEquation_index_map[i],request.POST['usleForest_'+str(i)+twonum(watershd_id)] )
for i in range(1,6):
setattr( ele,"UserDefined_"+UniversalSoilLossEquation_index_map[i],request.POST['usleUser_'+str(i)+twonum(watershd_id)] )
ele.save()
#load LanduseDistribution
context['LanduseDistributionInput'] = list2dictWthKey('watershd_id',LanduseDistributionInput.objects.filter(session_id=indexInput.id).values())
return render(request, 'bmpMain.html', { 'ctx':context, 'req' : request })
