def export_parameters_using_attributes(self,
resources,
datatype,
res_type=None):
"""
Export scalars or descriptors.
"""
islink = res_type == 'LINK'
attributes = []
attr_names = []
for resource in resources:
for attr in resource.attributes:
if attr.dataset_type == datatype and attr.is_var is False:
translated_attr_name = translate_attr_name(attr.name)
attr.name = translated_attr_name
if attr.name not in attr_names:
attributes.append(attr)
attr_names.append(attr.name)
if len(attributes) > 0:
for attribute in attributes:
nname = "\nparam " + attribute.name + ':='
contents = []
#self.output_file_contents.append("\nparam "+attribute.name+':=')
for resource in resources:
attr = resource.get_attribute(attr_name=attribute.name)
if attr is None or attr.value is None or attr.dataset_type != datatype:
continue
if res_type is None:
name = resource.name
elif islink is True and self.links_as_name is False:
name = get_link_name_for_param(resource)
else:
name = ""
#self.output_file_contents.append("\n "+name+" "+str(attr.value.values()[0][0]))
contents.append("\n " + self.ff.format(name) +
self.ff.format(str(attr.value)))
if len(contents) > 0:
self.output_file_contents.append(nname)
for st in contents:
self.output_file_contents.append(st)
self.output_file_contents.append(';\n')
def export_parameters_using_attributes(self, resources, datatype, res_type=None):
"""
Export scalars or descriptors.
"""
islink = res_type == 'LINK'
attributes = []
attr_names = []
for resource in resources:
for attr in resource.attributes:
if attr.dataset_type == datatype and attr.is_var is False:
translated_attr_name = translate_attr_name(attr.name)
attr.name = translated_attr_name
if attr.name not in attr_names:
attributes.append(attr)
attr_names.append(attr.name)
if len(attributes) > 0:
for attribute in attributes:
nname="\nparam "+attribute.name+':='
contents=[]
#self.output_file_contents.append("\nparam "+attribute.name+':=')
for resource in resources:
attr = resource.get_attribute(attr_name=attribute.name)
if attr is None or attr.value is None or attr.dataset_type != datatype:
continue
if res_type is None:
name=resource.name
elif islink is True and self.links_as_name is False:
name=get_link_name_for_param(resource)
else:
name=""
#self.output_file_contents.append("\n "+name+" "+str(attr.value.values()[0][0]))
contents.append("\n "+self.ff.format(name)+self.ff.format(str(attr.value)))
if len(contents)>0:
self.output_file_contents.append(nname)
for st in contents:
self.output_file_contents.append(st)
self.output_file_contents.append(';\n')
def export_arrays(self, resources):
"""Export arrays.
"""
attributes = []
attr_names = []
for resource in resources:
for attr in resource.attributes:
if attr.dataset_type == 'array' and attr.is_var is False:
attr.name = translate_attr_name(attr.name)
if attr.name not in attr_names:
attributes.append(attr)
attr_names.append(attr.name)
if len(attributes) > 0:
# We have to write the complete array information for every single
# node, because they might have different sizes.
for resource in resources:
# This exporter only supports 'rectangular' arrays
for attribute in attributes:
attr = resource.get_attribute(attr_name=attribute.name)
if attr is not None and attr.value is not None:
array=json.loads(attr.value)
dim = self.get_dim(array)
self.output_file_contents.append('# Array %s for node %s, ' % \
(attr.name, resource.name))
self.output_file_contents.append('dimensions are %s\n\n' % dim)
# Generate array indices
#self.output_file_contents.append('SETS:=\n\n')
indexvars = list(ascii_lowercase)
for i, n in enumerate(dim):
self.output_file_contents.append("set "+ indexvars[i] + '_' + \
resource.name + '_' + attr.name + \
'_'+str(i)+':=\n')
for idx in range(n):
self.output_file_contents.append(str(idx) + '\n')
self.output_file_contents.append(';\n\n')
self.output_file_contents.append('param ' + resource.name + '_' + \
attr.name + ':=')
ydim = dim[-1]
if len(dim)>1:
for y in range(ydim):
self.output_file_contents.append('{0:20}'.format(y))
self.output_file_contents.append('\n')
i=0
count=0
for item in array:
self.output_file_contents.append("\n")
self.output_file_contents.append('{0:20}'.format(""))
if(type(item) is list):
self.output_file_contents.append(format('['+str(i)+','+str(i)+']'))
i+=1
for value in item:
self.output_file_contents.append(' {0:20}'.format(value))
else:
i+=1
self.output_file_contents.append('{0:20}'.format(item))
count+=1
self.output_file_contents.append(';\n')
self.output_file_contents.append('\n\n')
def export_timeseries_using_attributes(self, resources, res_type=None):
"""
Export time series.
"""
islink = res_type == 'LINK'
attributes = []
attr_names = []
attrb_tables={}
for resource in resources:
for attr in resource.attributes:
if attr.dataset_type == 'timeseries' and attr.is_var is False:
if(len(self.time_index) is 0):
raise HydraPluginError("Missing time axis or start date, end date and time step or bad format")
attr.name = translate_attr_name(attr.name)
if attr.name not in attr_names:
attrb_tables[attr.name]=attr
attributes.append(attr)
attr_names.append(attr.name)
if len(attributes) > 0:
dataset_ids = []
all_res_data={}
#Identify the datasets that we need data for
for attribute in attributes:
for resource in resources:
attr = resource.get_attribute(attr_name=attribute.name)
if attr is not None and attr.dataset_id is not None:
dataset_ids.append(attr.dataset_id)
value=json.loads(attr.value)
all_res_data[attr.dataset_id]=value
#We need to get the value at each time in the specified time axis,
#so we need to identify the relevant timestamps.
soap_times = []
for t, timestamp in enumerate(self.time_index.values()):
soap_times.append(date_to_string(timestamp))
#Get all the necessary data for all the datasets we have.
#all_data = self.connection.call('get_multiple_vals_at_time',
# {'dataset_ids':dataset_ids,
# 'timestamps' : soap_times})
for attribute in attributes:
self.output_file_contents.append("\nparam "+attribute.name+":\n")
self.output_file_contents.append(self.write_time())
for resource in resources:
attr = resource.get_attribute(attr_name=attribute.name)
if attr is None or attr.dataset_id is None or attr.dataset_type != 'timeseries':
continue
try:
all_data = self.get_time_value(attr.value, self.time_index.values())
except Exception, e:
log.exception(e)
all_data = None
if all_data is None:
raise HydraPluginError("Error finding value attribute %s on"
"resource %s"%(attr.name, resource.name))
name=resource.name
if islink is True and self.links_as_name is False:
name=get_link_name(resource)
#self.output_file_contents.append("\n "+name)
nname="\n "+name;
self.output_file_contents.append(self.ff.format(nname))
for timestamp in self.time_index.values():
tmp = all_data[timestamp]
if isinstance(tmp, list):
data="-".join(tmp)
ff_='{0:<'+self.array_len+'}'
data_str = ff_.format(str(data))
else:
data=str(tmp)
data_str = self.ff.format(str(float(data)))
self.output_file_contents.append(data_str)
self.output_file_contents.append(';\n')
def export_arrays(self, resources):
"""Export arrays.
"""
attributes = []
attr_names = []
for resource in resources:
for attr in resource.attributes:
if attr.dataset_type == 'array' and attr.is_var is False:
attr.name = translate_attr_name(attr.name)
if attr.name not in attr_names:
attributes.append(attr)
attr_names.append(attr.name)
if len(attributes) > 0:
# We have to write the complete array information for every single
# node, because they might have different sizes.
for resource in resources:
# This exporter only supports 'rectangular' arrays
for attribute in attributes:
attr = resource.get_attribute(attr_name=attribute.name)
if attr is not None and attr.value is not None:
array = json.loads(attr.value)
dim = self.get_dim(array)
self.output_file_contents.append('# Array %s for node %s, ' % \
(attr.name, resource.name))
self.output_file_contents.append(
'dimensions are %s\n\n' % dim)
# Generate array indices
#self.output_file_contents.append('SETS:=\n\n')
indexvars = list(ascii_lowercase)
for i, n in enumerate(dim):
self.output_file_contents.append("set "+ indexvars[i] + '_' + \
resource.name + '_' + attr.name + \
'_'+str(i)+':=\n')
for idx in range(n):
self.output_file_contents.append(
str(idx) + '\n')
self.output_file_contents.append(';\n\n')
self.output_file_contents.append('param ' + resource.name + '_' + \
attr.name + ':=')
ydim = dim[-1]
if len(dim) > 1:
for y in range(ydim):
self.output_file_contents.append(
'{0:20}'.format(y))
self.output_file_contents.append('\n')
i = 0
count = 0
for item in array:
self.output_file_contents.append("\n")
self.output_file_contents.append(
'{0:20}'.format(""))
if (type(item) is list):
self.output_file_contents.append(
format('[' + str(i) + ',' + str(i) + ']'))
i += 1
for value in item:
self.output_file_contents.append(
' {0:20}'.format(value))
else:
i += 1
self.output_file_contents.append(
'{0:20}'.format(item))
count += 1
self.output_file_contents.append(';\n')
self.output_file_contents.append('\n\n')
def export_timeseries_using_attributes(self, resources, res_type=None):
"""
Export time series.
"""
islink = res_type == 'LINK'
attributes = []
attr_names = []
attrb_tables = {}
for resource in resources:
for attr in resource.attributes:
if attr.dataset_type == 'timeseries' and attr.is_var is False:
if (len(self.time_index) is 0):
raise HydraPluginError(
"Missing time axis or start date, end date and time step or bad format"
)
attr.name = translate_attr_name(attr.name)
if attr.name not in attr_names:
attrb_tables[attr.name] = attr
attributes.append(attr)
attr_names.append(attr.name)
if len(attributes) > 0:
dataset_ids = []
all_res_data = {}
#Identify the datasets that we need data for
for attribute in attributes:
for resource in resources:
attr = resource.get_attribute(attr_name=attribute.name)
if attr is not None and attr.dataset_id is not None:
dataset_ids.append(attr.dataset_id)
value = json.loads(attr.value)
all_res_data[attr.dataset_id] = value
#We need to get the value at each time in the specified time axis,
#so we need to identify the relevant timestamps.
soap_times = []
for t, timestamp in enumerate(self.time_index.values()):
soap_times.append(date_to_string(timestamp))
#Get all the necessary data for all the datasets we have.
#all_data = self.connection.call('get_multiple_vals_at_time',
# {'dataset_ids':dataset_ids,
# 'timestamps' : soap_times})
for attribute in attributes:
self.output_file_contents.append("\nparam " + attribute.name +
":\n")
self.output_file_contents.append(self.write_time())
for resource in resources:
attr = resource.get_attribute(attr_name=attribute.name)
if attr is None or attr.dataset_id is None or attr.dataset_type != 'timeseries':
continue
try:
all_data = self.get_time_value(
attr.value, self.time_index.values())
except Exception, e:
log.exception(e)
all_data = None
if all_data is None:
raise HydraPluginError(
"Error finding value attribute %s on"
"resource %s" % (attr.name, resource.name))
name = resource.name
if islink is True and self.links_as_name is False:
name = get_link_name(resource)
#self.output_file_contents.append("\n "+name)
nname = "\n " + name
self.output_file_contents.append(self.ff.format(nname))
for timestamp in self.time_index.values():
tmp = all_data[timestamp]
if isinstance(tmp, list):
data = "-".join(tmp)
ff_ = '{0:<' + self.array_len + '}'
data_str = ff_.format(str(data))
else:
data = str(tmp)
data_str = self.ff.format(str(float(data)))
self.output_file_contents.append(data_str)
self.output_file_contents.append(';\n')