def export_network(self):
'''
export the network from Hydra
'''
write_progress(2, self.steps)
net = self.connection.call(
'get_network', {
'network_id': self.network_id,
'include_data': 'Y',
'template_id': self.template_id,
'scenario_ids': [self.scenario_id]
})
log.info("Network retrieved")
attrs = self.connection.call('get_all_attributes', {})
log.info("%s attributes retrieved", len(attrs))
self.net = net
self.network = HydraNetwork()
self.network.load(net, attrs)
log.info("Loading net into network.")
nodes_map = dict()
for node in net.nodes:
nodes_map[node.id] = node.name
self.get_longest_node_link_name()
write_progress(3, self.steps)
self.output_file_contents.append("# Network-ID: " +
str(self.network_id))
self.output_file_contents.append("\n# Scenario-ID: " +
str(self.scenario_id))
self.output_file_contents.append("\n#" + "*" * 100)
self.write_nodes()
write_progress(4, self.steps)
self.write_links(nodes_map)
write_progress(5, self.steps)
self.export_node_groups()
nodes_types = self.network.get_node_types(template_id=self.template_id)
links_types = self.network.get_link_types(template_id=self.template_id)
self.export_node_types(nodes_types)
self.export_links_types(links_types)
write_progress(6, self.steps)
if len(self.time_index) > 0:
self.output_file_contents.append('\nset time_step:=')
for timestep in self.time_index.keys():
self.output_file_contents.append(" " + str(timestep))
self.output_file_contents.append(';\n')
self.output_file_contents.append('\nset actual_time_step:=')
for timestep in self.time_index.values():
self.output_file_contents.append(" " + str(timestep))
self.output_file_contents.append(';\n')
write_progress(7, self.steps)
if self.export_by_type is True:
self.export_data_using_types(nodes_types, links_types)
else:
self.export_data_using_attributes()
def export_network (self):
'''
export the network from Hydra
'''
write_progress(2, self.steps)
net = self.connection.call('get_network', {'network_id':self.network_id,
'include_data': 'Y',
'template_id':self.template_id,
'scenario_ids':[self.scenario_id]})
log.info("Network retrieved")
attrs = self.connection.call('get_all_attributes', {})
log.info("%s attributes retrieved", len(attrs))
self.net=net
self.network= HydraNetwork()
self.network.load(net , attrs)
log.info("Loading net into network.")
nodes_map=dict ()
for node in net.nodes:
nodes_map[node.id]=node.name
self.get_longest_node_link_name();
write_progress(3, self.steps)
self.output_file_contents.append("# Network-ID: "+str(self.network_id));
self.output_file_contents.append("\n# Scenario-ID: "+str(self.scenario_id));
self.output_file_contents.append("\n#" + "*"*100)
self.write_nodes()
write_progress(4, self.steps)
self.write_links(nodes_map)
write_progress(5, self.steps)
self.export_node_groups()
nodes_types=self.network.get_node_types(template_id=self.template_id)
links_types=self.network.get_link_types(template_id=self.template_id)
self.export_node_types(nodes_types)
self.export_links_types(links_types)
write_progress(6, self.steps)
if len(self.time_index)>0:
self.output_file_contents.append('\nset time_step:=')
for timestep in self.time_index.keys():
self.output_file_contents.append(" " +str(timestep))
self.output_file_contents.append(';\n')
self.output_file_contents.append('\nset actual_time_step:=')
for timestep in self.time_index.values():
self.output_file_contents.append(" " +str(timestep))
self.output_file_contents.append(';\n')
write_progress(7, self.steps)
if self.export_by_type is True:
self.export_data_using_types(nodes_types, links_types)
else:
self.export_data_using_attributes()
class Exporter (JSONPlugin):
def __init__(self, args, link_export_flag, steps):
if link_export_flag == 'l':
self.links_as_name = True
else:
self.links_as_name = False
self.steps=steps
self.use_gams_date_index=False
self.network_id = int(args.network)
self.scenario_id = int(args.scenario)
self.template_id = int(args.template_id) if args.template_id is not None else None
self.output_file = args.output
self.export_by_type =args.export_by_type
self.time_index = []
write_progress(1, self.steps)
self.output_file_contents=[];
self.output_file_contents.append("#%s\n"%("*"*78,))
self.output_file_contents.append("# Data exported from Hydra using PyomoPlugin.\n")
self.output_file_contents.append("# (c) Copyright 2015, University of Manchester\n")
self.time_index = {}
self.connect(args)
def export_network (self):
'''
export the network from Hydra
'''
write_progress(2, self.steps)
net = self.connection.call('get_network', {'network_id':self.network_id,
'include_data': 'Y',
'template_id':self.template_id,
'scenario_ids':[self.scenario_id]})
log.info("Network retrieved")
attrs = self.connection.call('get_all_attributes', {})
log.info("%s attributes retrieved", len(attrs))
self.net=net
self.network= HydraNetwork()
self.network.load(net , attrs)
log.info("Loading net into network.")
nodes_map=dict ()
for node in net.nodes:
nodes_map[node.id]=node.name
self.get_longest_node_link_name();
write_progress(3, self.steps)
self.output_file_contents.append("# Network-ID: "+str(self.network_id));
self.output_file_contents.append("\n# Scenario-ID: "+str(self.scenario_id));
self.output_file_contents.append("\n#" + "*"*100)
self.write_nodes()
write_progress(4, self.steps)
self.write_links(nodes_map)
write_progress(5, self.steps)
self.export_node_groups()
nodes_types=self.network.get_node_types(template_id=self.template_id)
links_types=self.network.get_link_types(template_id=self.template_id)
self.export_node_types(nodes_types)
self.export_links_types(links_types)
write_progress(6, self.steps)
if len(self.time_index)>0:
self.output_file_contents.append('\nset time_step:=')
for timestep in self.time_index.keys():
self.output_file_contents.append(" " +str(timestep))
self.output_file_contents.append(';\n')
self.output_file_contents.append('\nset actual_time_step:=')
for timestep in self.time_index.values():
self.output_file_contents.append(" " +str(timestep))
self.output_file_contents.append(';\n')
write_progress(7, self.steps)
if self.export_by_type is True:
self.export_data_using_types(nodes_types, links_types)
else:
self.export_data_using_attributes()
def get_longest_node_link_name(self):
'''
get the length of longest node and link name to be used
for file format
'''
node_name_len=0
for node in self.network.nodes:
if len(node.name)>node_name_len:
node_name_len=len(node.name)
self.ff='{0:<'+str(2*node_name_len+5)+'}'
self.ff__=2*node_name_len+5
def save_file(self):
'''
save output file
'''
write_progress(8, self.steps)
log.info("writing data to file")
file = open(self.output_file, "w")
file.write("".join(self.output_file_contents))
file.close()
def write_nodes(self):
'''
write nodes to output file
'''
self.output_file_contents.append("\n\nset nodes := ")
for node in self.network.nodes:
self.output_file_contents.append(" "+node.name)
self.output_file_contents.append(';')
def write_links(self, nodes_map):
'''
write links to output file
'''
self.output_file_contents.append("\n\nset links:= ")
for link in self.network.links:
if self.links_as_name is False:
self.output_file_contents.append("\n"+ link.from_node+" "+link.to_node)
else:
self.output_file_contents.append("\n"+ link.name)
self.output_file_contents.append(';\n')
def export_node_groups(self):
"Export node groups if there are any."
node_groups = []
self.output_file_contents.append("\n#Nodes groups\n")
for group in self.network.groups:
group_nodes = self.network.get_node(group=group.ID)
if len(group_nodes) > 0:
node_groups.append(group)
self.output_file_contents.append("\nset "+group.name+":= \n")
for node in group_nodes:
self.output_file_contents.append(node.name+'\n')
self.output_file_contents.append(';\n')
def export_node_types(self, nodes_types):
"Export node groups if there are any."
self.output_file_contents.append("\n#Nodes types\n")
for node_type in nodes_types:
self.output_file_contents.append("\nset "+node_type+":= \n")
#for node in self.network.nodes:
for node in self.network.get_node(node_type=node_type):
self.output_file_contents += node.name + '\n'
self.output_file_contents.append(';\n')
def export_links_types(self, links_types):
"Export node groups if there are any."
for link_type in links_types:
self.output_file_contents.append("\nset "+link_type+":= \n")
for link in self.network.get_link(link_type=link_type):
if self.links_as_name is False:
self.output_file_contents.append("\n"+ link.from_node+" "+link.to_node)
else:
self.output_file_contents.append("\n"+ link.name)
self.output_file_contents.append(';\n')
def export_data_using_types(self, nodes_types, links_types):
log.info("Exporting data")
self.time_table={}
# Export node data for each node type
self.export_parameters_using_types([self.network], "NETWORK", 'scalar')
self.export_parameters_using_types([self.network], "NETWORK", 'descriptor')
self.export_timeseries_using_types([self.network], "NETWORK")
for node_type in nodes_types:
nodes = self.network.get_node(node_type=node_type)
self.export_parameters_using_types(nodes, node_type, 'scalar')
self.export_parameters_using_types(nodes, node_type, 'descriptor')
self.export_timeseries_using_types(nodes, node_type)
self.export_arrays(nodes)
for link_type in links_types:
links = self.network.get_link(link_type=link_type)
self.export_parameters_using_types(links, link_type, 'scalar', res_type='LINK')
self.export_parameters_using_types(links, link_type,'descriptor', res_type='LINK')
self.export_timeseries_using_types(links, link_type, res_type='LINK')
self.export_arrays(links)
#
def export_data_using_attributes (self):
log.info("Exporting data")
# Export node data for each node type
#for node_type in nodes_types:
self.time_table={}
self.export_parameters_using_attributes([self.network], 'scalar', res_type='NETWORK')
self.export_parameters_using_attributes([self.network], 'descriptor', res_type='NETWORK')
self.export_timeseries_using_attributes([self.network], res_type='NETWORK')
self.export_arrays(self.network.nodes)
#nodes = self.network.get_node(node_type=node_type)
self.export_parameters_using_attributes(self.network.nodes, 'scalar')
self.export_parameters_using_attributes(self.network.nodes, 'descriptor')
self.export_timeseries_using_attributes(self.network.nodes)
self.export_arrays(self.network.nodes)
#for link_type in links_types:
#links = self.network.get_link(link_type=link_type)
self.export_parameters_using_attributes(self.network.links, 'scalar', res_type='LINK')
self.export_parameters_using_attributes(self.network.links, 'descriptor', res_type='LINK')
self.export_timeseries_using_attributes(self.network.links, res_type='LINK')
self.export_arrays(self.network.links)
#
def export_parameters_using_types(self, resources, obj_type, datatype, res_type=None):
"""Export scalars or descriptors. """
self.network.attributes
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+"_"+obj_type+':='
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_timeseries_using_types(self, resources, obj_type, 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(self.time_index is None):
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 None or attr.dataset_id is None:
continue
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+"_"+obj_type+":\n")
self.output_file_contents.append(self.write_time())
for resource in resources:
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
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))
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')
class Exporter(JSONPlugin):
def __init__(self, args, link_export_flag, steps):
if link_export_flag == 'l':
self.links_as_name = True
else:
self.links_as_name = False
self.steps = steps
self.use_gams_date_index = False
self.network_id = int(args.network)
self.scenario_id = int(args.scenario)
self.template_id = int(
args.template_id) if args.template_id is not None else None
self.output_file = args.output
self.export_by_type = args.export_by_type
self.time_index = []
write_progress(1, self.steps)
self.output_file_contents = []
self.output_file_contents.append("#%s\n" % ("*" * 78, ))
self.output_file_contents.append(
"# Data exported from Hydra using PyomoPlugin.\n")
self.output_file_contents.append(
"# (c) Copyright 2015, University of Manchester\n")
self.time_index = {}
self.connect(args)
def export_network(self):
'''
export the network from Hydra
'''
write_progress(2, self.steps)
net = self.connection.call(
'get_network', {
'network_id': self.network_id,
'include_data': 'Y',
'template_id': self.template_id,
'scenario_ids': [self.scenario_id]
})
log.info("Network retrieved")
attrs = self.connection.call('get_all_attributes', {})
log.info("%s attributes retrieved", len(attrs))
self.net = net
self.network = HydraNetwork()
self.network.load(net, attrs)
log.info("Loading net into network.")
nodes_map = dict()
for node in net.nodes:
nodes_map[node.id] = node.name
self.get_longest_node_link_name()
write_progress(3, self.steps)
self.output_file_contents.append("# Network-ID: " +
str(self.network_id))
self.output_file_contents.append("\n# Scenario-ID: " +
str(self.scenario_id))
self.output_file_contents.append("\n#" + "*" * 100)
self.write_nodes()
write_progress(4, self.steps)
self.write_links(nodes_map)
write_progress(5, self.steps)
self.export_node_groups()
nodes_types = self.network.get_node_types(template_id=self.template_id)
links_types = self.network.get_link_types(template_id=self.template_id)
self.export_node_types(nodes_types)
self.export_links_types(links_types)
write_progress(6, self.steps)
if len(self.time_index) > 0:
self.output_file_contents.append('\nset time_step:=')
for timestep in self.time_index.keys():
self.output_file_contents.append(" " + str(timestep))
self.output_file_contents.append(';\n')
self.output_file_contents.append('\nset actual_time_step:=')
for timestep in self.time_index.values():
self.output_file_contents.append(" " + str(timestep))
self.output_file_contents.append(';\n')
write_progress(7, self.steps)
if self.export_by_type is True:
self.export_data_using_types(nodes_types, links_types)
else:
self.export_data_using_attributes()
def get_longest_node_link_name(self):
'''
get the length of longest node and link name to be used
for file format
'''
node_name_len = 0
for node in self.network.nodes:
if len(node.name) > node_name_len:
node_name_len = len(node.name)
self.ff = '{0:<' + str(2 * node_name_len + 5) + '}'
self.ff__ = 2 * node_name_len + 5
def save_file(self):
'''
save output file
'''
write_progress(8, self.steps)
log.info("writing data to file")
file = open(self.output_file, "w")
file.write("".join(self.output_file_contents))
file.close()
def write_nodes(self):
'''
write nodes to output file
'''
self.output_file_contents.append("\n\nset nodes := ")
for node in self.network.nodes:
self.output_file_contents.append(" " + node.name)
self.output_file_contents.append(';')
def write_links(self, nodes_map):
'''
write links to output file
'''
self.output_file_contents.append("\n\nset links:= ")
for link in self.network.links:
if self.links_as_name is False:
self.output_file_contents.append("\n" + link.from_node + " " +
link.to_node)
else:
self.output_file_contents.append("\n" + link.name)
self.output_file_contents.append(';\n')
def export_node_groups(self):
"Export node groups if there are any."
node_groups = []
self.output_file_contents.append("\n#Nodes groups\n")
for group in self.network.groups:
group_nodes = self.network.get_node(group=group.ID)
if len(group_nodes) > 0:
node_groups.append(group)
self.output_file_contents.append("\nset " + group.name +
":= \n")
for node in group_nodes:
self.output_file_contents.append(node.name + '\n')
self.output_file_contents.append(';\n')
def export_node_types(self, nodes_types):
"Export node groups if there are any."
self.output_file_contents.append("\n#Nodes types\n")
for node_type in nodes_types:
self.output_file_contents.append("\nset " + node_type + ":= \n")
#for node in self.network.nodes:
for node in self.network.get_node(node_type=node_type):
self.output_file_contents += node.name + '\n'
self.output_file_contents.append(';\n')
def export_links_types(self, links_types):
"Export node groups if there are any."
for link_type in links_types:
self.output_file_contents.append("\nset " + link_type + ":= \n")
for link in self.network.get_link(link_type=link_type):
if self.links_as_name is False:
self.output_file_contents.append("\n" + link.from_node +
" " + link.to_node)
else:
self.output_file_contents.append("\n" + link.name)
self.output_file_contents.append(';\n')
def export_data_using_types(self, nodes_types, links_types):
log.info("Exporting data")
self.time_table = {}
# Export node data for each node type
self.export_parameters_using_types([self.network], "NETWORK", 'scalar')
self.export_parameters_using_types([self.network], "NETWORK",
'descriptor')
self.export_timeseries_using_types([self.network], "NETWORK")
for node_type in nodes_types:
nodes = self.network.get_node(node_type=node_type)
self.export_parameters_using_types(nodes, node_type, 'scalar')
self.export_parameters_using_types(nodes, node_type, 'descriptor')
self.export_timeseries_using_types(nodes, node_type)
self.export_arrays(nodes)
for link_type in links_types:
links = self.network.get_link(link_type=link_type)
self.export_parameters_using_types(links,
link_type,
'scalar',
res_type='LINK')
self.export_parameters_using_types(links,
link_type,
'descriptor',
res_type='LINK')
self.export_timeseries_using_types(links,
link_type,
res_type='LINK')
self.export_arrays(links)
#
def export_data_using_attributes(self):
log.info("Exporting data")
# Export node data for each node type
#for node_type in nodes_types:
self.time_table = {}
self.export_parameters_using_attributes([self.network],
'scalar',
res_type='NETWORK')
self.export_parameters_using_attributes([self.network],
'descriptor',
res_type='NETWORK')
self.export_timeseries_using_attributes([self.network],
res_type='NETWORK')
self.export_arrays(self.network.nodes)
#nodes = self.network.get_node(node_type=node_type)
self.export_parameters_using_attributes(self.network.nodes, 'scalar')
self.export_parameters_using_attributes(self.network.nodes,
'descriptor')
self.export_timeseries_using_attributes(self.network.nodes)
self.export_arrays(self.network.nodes)
#for link_type in links_types:
#links = self.network.get_link(link_type=link_type)
self.export_parameters_using_attributes(self.network.links,
'scalar',
res_type='LINK')
self.export_parameters_using_attributes(self.network.links,
'descriptor',
res_type='LINK')
self.export_timeseries_using_attributes(self.network.links,
res_type='LINK')
self.export_arrays(self.network.links)
#
def export_parameters_using_types(self,
resources,
obj_type,
datatype,
res_type=None):
"""Export scalars or descriptors. """
self.network.attributes
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 + "_" + obj_type + ':='
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_timeseries_using_types(self,
resources,
obj_type,
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 (self.time_index is None):
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 None or attr.dataset_id is None:
continue
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 +
"_" + obj_type + ":\n")
self.output_file_contents.append(self.write_time())
for resource in resources:
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
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))
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')