def get_visualization_image(self, data_product_id='', visualization_parameters=None, callback=''):
# Error check
if not data_product_id:
raise BadRequest("The data_product_id parameter is missing")
if visualization_parameters == {}:
visualization_parameters = None
# Extract the retrieval related parameters. Definitely init all parameters first
query = None
if visualization_parameters :
query = {'parameters':[]}
# Error check and damage control. Definitely need time
if 'parameters' in visualization_parameters:
if not 'time' in visualization_parameters['parameters']:
visualization_parameters['parameters'].append('time')
query['parameters'] = visualization_parameters['parameters']
if 'stride_time' in visualization_parameters:
query['stride_time'] = visualization_parameters['stride_time']
if 'start_time' in visualization_parameters:
query['start_time'] = visualization_parameters['start_time']
if 'end_time' in visualization_parameters:
query['end_time'] = visualization_parameters['end_time']
# get the dataset_id associated with the data_product. Need it to do the data retrieval
ds_ids,_ = self.clients.resource_registry.find_objects(data_product_id, PRED.hasDataset, RT.DataSet, True)
if ds_ids is None or not ds_ids:
return None
# Ideally just need the latest granule to figure out the list of images
#replay_granule = self.clients.data_retriever.retrieve(ds_ids[0],{'start_time':0,'end_time':2})
retrieved_granule = self.clients.data_retriever.retrieve(ds_ids[0], query=query)
if retrieved_granule is None:
return None
# send the granule through the transform to get the matplotlib graphs
mpl_pdict_id = self.clients.dataset_management.read_parameter_dictionary_by_name('graph_image_param_dict',id_only=True)
mpl_stream_def = self.clients.pubsub_management.create_stream_definition('mpl', parameter_dictionary_id=mpl_pdict_id)
mpl_data_granule = VizTransformMatplotlibGraphsAlgorithm.execute(retrieved_granule, config=visualization_parameters, params=mpl_stream_def)
if mpl_data_granule == None:
return None
mpl_rdt = RecordDictionaryTool.load_from_granule(mpl_data_granule)
ret_dict = dict()
ret_dict['content_type'] = (get_safe(mpl_rdt, "content_type"))[0]
ret_dict['image_name'] = (get_safe(mpl_rdt, "image_name"))[0]
# reason for encoding as base64 string is otherwise message pack complains about the bit stream
ret_dict['image_obj'] = base64.encodestring((get_safe(mpl_rdt, "image_obj"))[0])
if callback == '':
return ret_dict
else:
return callback + "(" + simplejson.dumps(ret_dict) + ")"
def get_visualization_image(self, data_product_id='', visualization_parameters=None):
# Error check
if not data_product_id:
raise BadRequest("The data_product_id parameter is missing")
if visualization_parameters == {}:
visualization_parameters = None
# Extract the retrieval related parameters. Definitely init all parameters first
query = None
image_name = None
if visualization_parameters :
#query = {'parameters':[]}
query = {}
# Error check and damage control. Definitely need time
if 'parameters' in visualization_parameters:
if not 'time' in visualization_parameters['parameters']:
visualization_parameters['parameters'].append('time')
query['parameters'] = visualization_parameters['parameters']
if 'stride_time' in visualization_parameters:
query['stride_time'] = visualization_parameters['stride_time']
if 'start_time' in visualization_parameters:
query['start_time'] = visualization_parameters['start_time']
if 'end_time' in visualization_parameters:
query['end_time'] = visualization_parameters['end_time']
# If an image_name was given, it means the image is already in the storage. Just need the latest granule.
# ignore other paramters passed
if 'image_name' in visualization_parameters:
image_name = visualization_parameters['image_name']
# get the dataset_id associated with the data_product. Need it to do the data retrieval
ds_ids,_ = self.clients.resource_registry.find_objects(data_product_id, PRED.hasDataset, RT.Dataset, True)
if ds_ids is None or not ds_ids:
log.warn("Specified data_product does not have an associated dataset")
return None
# Ideally just need the latest granule to figure out the list of images
if image_name:
retrieved_granule = self.clients.data_retriever.retrieve_last_data_points(ds_ids[0], 10)
else:
retrieved_granule = self.clients.data_retriever.retrieve(ds_ids[0], query=query)
if retrieved_granule is None:
return None
# no need to pass data through transform if its already a pre-computed image
if image_name:
mpl_data_granule = retrieved_granule
else:
# send the granule through the transform to get the matplotlib graphs
mpl_pdict_id = self.clients.dataset_management.read_parameter_dictionary_by_name('graph_image_param_dict',id_only=True)
mpl_stream_def = self.clients.pubsub_management.create_stream_definition('mpl', parameter_dictionary_id=mpl_pdict_id)
mpl_data_granule = VizTransformMatplotlibGraphsAlgorithm.execute(retrieved_granule, config=visualization_parameters, params=mpl_stream_def)
if mpl_data_granule == None:
return None
mpl_rdt = RecordDictionaryTool.load_from_granule(mpl_data_granule)
ret_dict = dict()
ret_dict['content_type'] = (get_safe(mpl_rdt, "content_type"))[0]
ret_dict['image_name'] = (get_safe(mpl_rdt, "image_name"))[0]
# reason for encoding as base64 string is otherwise message pack complains about the bit stream
#ret_dict['image_obj'] = base64.encodestring((get_safe(mpl_rdt, "image_obj"))[0])
ret_dict['image_obj'] = (get_safe(mpl_rdt, "image_obj"))[0]
return ret_dict
def get_visualization_image(self, data_product_id='', visualization_parameters=None, callback=''):
# Error check
if not data_product_id:
raise BadRequest("The data_product_id parameter is missing")
if visualization_parameters == {}:
visualization_parameters = None
# Extract the retrieval related parameters. Definitely init all parameters first
query = None
image_name = None
if visualization_parameters :
#query = {'parameters':[]}
query = {}
# Error check and damage control. Definitely need time
if 'parameters' in visualization_parameters:
if not 'time' in visualization_parameters['parameters']:
visualization_parameters['parameters'].append('time')
query['parameters'] = visualization_parameters['parameters']
if 'stride_time' in visualization_parameters:
query['stride_time'] = visualization_parameters['stride_time']
if 'start_time' in visualization_parameters:
query['start_time'] = visualization_parameters['start_time']
if 'end_time' in visualization_parameters:
query['end_time'] = visualization_parameters['end_time']
# If an image_name was given, it means the image is already in the storage. Just need the latest granule.
# ignore other paramters passed
if 'image_name' in visualization_parameters:
image_name = visualization_parameters['image_name']
# get the dataset_id associated with the data_product. Need it to do the data retrieval
ds_ids,_ = self.clients.resource_registry.find_objects(data_product_id, PRED.hasDataset, RT.Dataset, True)
if ds_ids is None or not ds_ids:
log.warn("Specified data_product does not have an associated dataset")
return None
# Ideally just need the latest granule to figure out the list of images
if image_name:
retrieved_granule = self.clients.data_retriever.retrieve_last_data_points(ds_ids[0], 10)
else:
retrieved_granule = self.clients.data_retriever.retrieve(ds_ids[0], query=query)
#print " >>>>>>>>>>>> RETRIEVED GRANULE : " , retrieved_granule
if retrieved_granule is None:
return None
# no need to pass data through transform if its already a pre-computed image
if image_name:
mpl_data_granule = retrieved_granule
else:
# send the granule through the transform to get the matplotlib graphs
mpl_pdict_id = self.clients.dataset_management.read_parameter_dictionary_by_name('graph_image_param_dict',id_only=True)
mpl_stream_def = self.clients.pubsub_management.create_stream_definition('mpl', parameter_dictionary_id=mpl_pdict_id)
mpl_data_granule = VizTransformMatplotlibGraphsAlgorithm.execute(retrieved_granule, config=visualization_parameters, params=mpl_stream_def)
if mpl_data_granule == None:
return None
mpl_rdt = RecordDictionaryTool.load_from_granule(mpl_data_granule)
ret_dict = dict()
ret_dict['content_type'] = (get_safe(mpl_rdt, "content_type"))[0]
ret_dict['image_name'] = (get_safe(mpl_rdt, "image_name"))[0]
# reason for encoding as base64 string is otherwise message pack complains about the bit stream
ret_dict['image_obj'] = base64.encodestring((get_safe(mpl_rdt, "image_obj"))[0])
if callback == '':
return ret_dict
else:
return callback + "(" + simplejson.dumps(ret_dict) + ")"