def clean(self):
# invoke superclass cleaning method
super(OpenClimateGisForm2, self).clean()
# validate calculation
if 'calc' in self.cleaned_data and hasText(self.cleaned_data['calc']) and self.cleaned_data['calc'].lower() != 'none':
# calculation group must be selected
if len( self.cleaned_data['calc_group'] ) == 0:
self._errors["calc_group"] = self.error_class(["Calculation Group(s) not selected."])
# validate keyword values
func = self.cleaned_data['calc']
calc = ocgisCalculations.getCalc(func)
if 'keywords' in calc:
for i, keyword in enumerate(calc["keywords"]):
parN = 'par%s' % (i+1)
value = self.cleaned_data[parN]
if keyword["type"]=="float":
try:
x = float(value)
except ValueError:
self._errors[parN] = self.error_class(["Invalid float value for keyword: "+keyword["name"]])
elif keyword["type"] == "string":
if "values" in keyword:
if not value.lower() in keyword["values"]:
self._errors[parN] = self.error_class(["Invalid string value for keyword: "+keyword["name"]])
if 'prefix' in self.cleaned_data and re.search(INVALID_CHARS, self.cleaned_data['prefix']):
self._errors['prefix'] = self.error_class(["The prefix contains invalid characters."])
if not self.is_valid():
print 'VALIDATION ERRORS: %s' % self.errors
# return cleaned data
return self.cleaned_data
def get_context_data(self, form, **kwargs):
context = super(OpenClimateGisWizard, self).get_context_data(form=form, **kwargs)
# before rendering of first form: send data and geometry choices
if self.steps.current == self.steps.first:
context.update({"datasets": json.dumps(ocgisDatasets.datasets)})
context.update({"geometries": json.dumps(ocgisGeometries.geometries)})
elif self.steps.current == "1": # note: string type
context.update({"calculations": json.dumps(ocgisCalculations.calcs)})
# before very last view: create summary of user choices
elif self.steps.current == self.steps.last:
job_data = {}
# retrieve form data for all previous views
for step in self.steps.all:
if step != self.steps.current:
cleaned_data = self.get_cleaned_data_for_step(step)
if cleaned_data.has_key("dataset_category"):
job_data["dataset_category"] = cleaned_data["dataset_category"]
if cleaned_data.has_key("dataset"):
job_data["dataset"] = cleaned_data["dataset"]
if cleaned_data.has_key("variable"):
job_data["variable"] = cleaned_data["variable"]
if cleaned_data.has_key("geometry") and hasText(cleaned_data["geometry"]):
job_data["geometry"] = cleaned_data["geometry"]
if cleaned_data.has_key("geometry_id") and len(cleaned_data["geometry_id"]) > 0:
job_data["geometry_id"] = formatListForDisplay(cleaned_data["geometry_id"])
if cleaned_data.has_key("latmin") and cleaned_data["latmin"] is not None:
job_data["latmin"] = float(cleaned_data["latmin"])
if cleaned_data.has_key("latmax") and cleaned_data["latmax"] is not None:
job_data["latmax"] = float(cleaned_data["latmax"])
if cleaned_data.has_key("lonmin") and cleaned_data["lonmin"] is not None:
job_data["lonmin"] = float(cleaned_data["lonmin"])
if cleaned_data.has_key("lonmax") and cleaned_data["lonmax"] is not None:
job_data["lonmax"] = float(cleaned_data["lonmax"])
if cleaned_data.has_key("lat") and cleaned_data["lat"] is not None:
job_data["lat"] = float(cleaned_data["lat"])
if cleaned_data.has_key("lon") and cleaned_data["lon"] is not None:
job_data["lon"] = float(cleaned_data["lon"])
if cleaned_data.has_key("datetime_start") and cleaned_data["datetime_start"] is not None:
job_data["datetime_start"] = cleaned_data["datetime_start"]
if cleaned_data.has_key("datetime_stop") and cleaned_data["datetime_stop"] is not None:
job_data["datetime_stop"] = cleaned_data["datetime_stop"]
if cleaned_data.has_key("timeregion_month") and cleaned_data["timeregion_month"] is not None:
job_data["timeregion_month"] = get_month_string(cleaned_data["timeregion_month"])
if cleaned_data.has_key("timeregion_year") and cleaned_data["timeregion_year"] is not None:
job_data["timeregion_year"] = cleaned_data["timeregion_year"]
if cleaned_data.has_key("calc") and cleaned_data["calc"] is not None and cleaned_data["calc"] != "":
job_data["calc"] = ocgisCalculations.getCalc(cleaned_data["calc"])["name"]
if cleaned_data.has_key("par1") and cleaned_data["par1"] is not None:
job_data["par1"] = cleaned_data["par1"]
if cleaned_data.has_key("par2") and cleaned_data["par2"] is not None:
job_data["par2"] = cleaned_data["par2"]
if cleaned_data.has_key("par3") and cleaned_data["par3"] is not None:
job_data["par3"] = cleaned_data["par3"]
if cleaned_data.has_key("calc_group"):
calc_groups = []
for group in cleaned_data["calc_group"]:
calc_groups.append(ocgisChoices(Config.CALCULATION_GROUP)[group])
job_data["calc_group"] = formatListForDisplay(calc_groups)
if cleaned_data.has_key("calc_raw"):
job_data["calc_raw"] = bool(cleaned_data["calc_raw"])
if cleaned_data.has_key("spatial_operation"):
job_data["spatial_operation"] = ocgisChoices(Config.SPATIAL_OPERATION)[
cleaned_data["spatial_operation"]
]
if cleaned_data.has_key("aggregate"):
job_data["aggregate"] = bool(cleaned_data["aggregate"])
if cleaned_data.has_key("output_format"):
job_data["output_format"] = ocgisChoices(Config.OUTPUT_FORMAT)[cleaned_data["output_format"]]
if cleaned_data.has_key("prefix"):
job_data["prefix"] = cleaned_data["prefix"]
if cleaned_data.has_key("with_auxiliary_files"):
job_data["with_auxiliary_files"] = bool(cleaned_data["with_auxiliary_files"])
context.update({"job_data": job_data})
return context
