def push_projection_info(params, context, rundate):
taxon_name = None
common_name = None
conserve_status = None
# load the species metatadata
mdfilepath = os.path.join(params['env']['inputdir'], params['params'][
'species_occurrence_dataset']['uuid'], 'ala_metadata.json')
metadata = json.load(open(mdfilepath))
# Get scientific name
taxon_name = (metadata.get('classification', {}).get('scientificName')
or metadata.get('taxonConcept', {}).get('nameString')
or metadata.get('taxonConcept', {}).get('nameComplete'))
# Get common name
for record in metadata['commonNames']:
if record['nameString'] is not None:
common_name = record['nameString']
break
# Get conservation status
records = metadata.get('conservationStatuses', {})
for key in records.keys():
if records[key].get('status', None):
conserve_status = records[key].get('status')
break
md = {"common_name": common_name,
"scientific_name": taxon_name,
"uuid": metadata.get('taxonConcept', {}).get('guid'),
"kingdom": metadata.get('classification', {}).get('kingdom'),
"class": metadata.get('classification', {}).get('class'),
"family": metadata.get('classification', {}).get('family'),
"conservationStatuses": conserve_status,
"run_date": rundate,
"title": common_name or taxon_name,
"description": "Species Distribution Model and Climate Change projection of {} using Maxent algorithm.".format(common_name or taxon_name),
"current_proj_url": os.path.join(params['result']['results_dir'], 'current_projection.png'),
"future_proj_url": os.path.join(params['result']['results_dir'], '2085_projection.png'),
"algorithm": "Maxent",
"current_climate": "Australian Current Climate 1976 to 2005, 30arcsec (~1km)",
"future_climate": "Australian Climate Projection RCP85 based on UKMO-HADGEM1, 30arcsec (~1km) - 2085",
"gcm": "UKMO-HADGEM1",
"emission_scenario": "RCP85",
"projection_year": "current, 2085"
}
move_tasks = []
srcpath = os.path.join(params['env']['outputdir'], 'proj_metadata.json')
with open(srcpath, 'w') as f:
f.write(json.dumps(md, indent=4))
destpath = os.path.join(params['result']['results_dir'], 'proj_metadata.json')
move_tasks.append(('file://' + srcpath, destpath))
datamover.move(move_tasks, context)
def transfer_projections(params, context, filelist):
# TO-DO: Catch an exception if there isn't a .tif output file
# Fetch a tiff file that isn't a clamping mask
move_tasks = []
for srcpath in filelist:
fname = 'current_projection.png'
if not os.path.basename(srcpath).startswith('proj_current'):
fname = '2085_projection.png'
destpath = os.path.join(params['result']['results_dir'], fname)
move_tasks.append(('file://' + srcpath, destpath))
datamover.move(move_tasks, context)
def write_status_to_nectar(params, context, status):
move_tasks = []
# TODO: Figure out where the status file lives
srcpath = os.path.join(params['env']['outputdir'], 'state.json')
with open(srcpath, 'w') as f_json:
f_json.write(json.dumps({u'status': status,
'jobid': context['jobid']}, indent=4))
destpath = os.path.join(params['result']['results_dir'], 'state.json')
move_tasks.append(('file://' + srcpath, destpath))
datamover.move(move_tasks, context)
