def status(self):
url = self.get_absolute_url()
if process_is_running(url):
status = """Analysis is currently running."""
if self.progress[0] == 0:
status += " (Pre-processing)"
code = 2
elif process_is_complete(url):
status = "Analysis completed. Compiling results..."
code = 3
elif process_is_pending(url):
status = "Analysis is in the queue but not yet running."
res = get_process_result(url)
code = 1
if res is not None:
status += ".. "
status += str(res)
else:
status = "An error occured while running this analysis."
code = 0
res = get_process_result(url)
if res is not None:
status += "..<br/> "
status += str(res)
status += "<br/>Please edit the scenario and try again. If the problem persists, please contact us."
return (code, "<p>%s</p>" % status)
def status(self):
url = self.get_absolute_url()
if process_is_running(url):
status = """Analysis for <em>%s</em> is currently running.""" % (self.name,)
code = 2
elif process_is_complete(url):
status = "%s processing is done." % self.name
code = 3
elif process_is_pending(url):
status = "%s is in the queue but not yet running." % self.name
res = get_process_result(url)
code = 1
if res is not None:
status += ".. "
status += str(res)
else:
status = "An error occured while running this analysis."
code = 0
res = get_process_result(url)
if res is not None:
status += "..<br/> "
status += str(res)
status += "<br/>Please edit the scenario and try again. If the problem persists, please contact us."
return (code, "<p>%s</p>" % status)
def process_results(self):
if process_is_complete(self.get_absolute_url()):
chosen = get_process_result(self.get_absolute_url())
wshds = PlanningUnit.objects.filter(pk__in=chosen)
self.output_best = json.dumps({'best': [str(x.pk) for x in wshds]})
ssoln = [x.strip().split(',') for x in
open(os.path.join(self.outdir,"output","seak_ssoln.csv"),'r').readlines()][1:]
selected = {}
for s in ssoln:
num = int(s[1])
if num > 0:
selected[int(s[0])] = num
self.output_pu_count = json.dumps(selected)
super(Analysis, self).save() # save without calling save()
self.invalidate_cache()
def reserve_energy(state):
"""
The "Objective Function"...
Calculates the 'energy' of the reserve.
Should incorporate costs of reserve and penalties
for not meeting species targets.
Note: This example is extremely simplistic compared to
the Marxan objective function (see Appendix B in Marxan manual)
but at least we have access to it!
"""
start = datetime.now()
target_dict = {}
penalty_dict = {}
for cfkey in cfkeys:
if cfkey in state:
target_dict[cfkey] = 0.5
else:
target_dict[cfkey] = 0
penalty_dict[cfkey] = 1.0
scalefactor = 5
name = (
str(len([k for k, v in target_dict.items() if v > 0]))
+ ": "
+ " ".join([x.split("---")[1] for x in state])[:100]
)
wp = Scenario(
input_targets=json.dumps(target_dict),
input_penalties=json.dumps(penalty_dict),
input_relativecosts=json.dumps(costs_dict),
input_geography=json.dumps(geography_list),
input_scalefactor=scalefactor,
name=name,
user=user,
)
wp.save()
url = wp.get_absolute_url()
time.sleep(3) # assuming it takes at least X secs
while not process_is_complete(url):
time.sleep(0.2)
wp.process_results()
res = wp.results
energy = res["surrogate"]["objective_score"]
elapsed = datetime.now() - start
print "Scenario %d\t\t%s secs\t\tscore = %s" % (
wp.id,
elapsed.seconds + elapsed.microseconds / 1000000.0,
energy,
)
return energy
