def calcore_validate_model(model):
smile = 'COc1ccccc1NC(=O)CC(=O)C'
mol_path = ''
temperature = 10.0
r = prediction_model_calculate(model, smile, mol_path, temperature)
print r
def calculateTask(task, sid, model):
try:
generate_mol_image(task)
suite = SuiteTask.objects.get(sid=sid)
map_model_name = get_model_name(model['model'])
smile = task.file_obj.smiles.encode(
'utf-8') if task.file_obj.file_type != 'mol' else ''
# smile, mol_fpath 输入只选择一种方式(优先smile)
mol_fpath = os.path.join(
settings.SETTINGS_ROOT,
task.file_obj.file_obj.path) if not smile else None
try:
temperature = float(model.get('temperature'))
except:
temperature = DEFAULT_TEMPERATURE_ARGS
chemistry_logger.info(
'PredictionModel calculating: model name(%s),'
'smile(%s) mol path(%s) temperature(%s)', map_model_name, smile,
mol_fpath, temperature)
# 后台模型计算入口
predict_results = prediction_model_calculate(map_model_name, smile,
mol_fpath, temperature)
if task.file_obj.file_type == 'mol':
name = os.path.basename(mol_fpath).split('.')[0]
else:
name = smile
result = predict_results[name][map_model_name]
chemistry_logger.info('[task]result %s' % result)
except KeyError:
chemistry_logger.exception('still cannot support this model')
result = None
task.result_state = "We don't support this model now"
task.status = StatusCategory.objects.get(category=STATUS_FAILED)
suite.status_id = StatusCategory.objects.get(category=STATUS_FAILED)
except Exception as e:
chemistry_logger.exception('failed to submit task to prediction model')
result = None
task.result_state = str(e)
task.status = StatusCategory.objects.get(category=STATUS_FAILED)
suite.status_id = StatusCategory.objects.get(category=STATUS_FAILED)
else:
chemistry_logger.info("calculate Successfully in celery queue!")
task.result_state = "Calculate Successfully!"
task.status = StatusCategory.objects.get(category=STATUS_SUCCESS)
suite.status_id = StatusCategory.objects.get(category=STATUS_WORKING)
task.end_time = utils.get_real_now()
task.results = json.dumps(result)
suite.save()
task.save()
add_counter(suite.sid)
return result
def calculateTask(task, sid, model):
try:
generate_mol_image(task)
suite = SuiteTask.objects.get(sid=sid)
map_model_name = get_model_name(model['model'])
smile = task.file_obj.smiles.encode('utf-8') if task.file_obj.file_type != 'mol' else ''
# smile, mol_fpath 输入只选择一种方式(优先smile)
mol_fpath = os.path.join(settings.SETTINGS_ROOT, task.file_obj.file_obj.path) if not smile else None
try:
temperature = float(model.get('temperature'))
except:
temperature = DEFAULT_TEMPERATURE_ARGS
chemistry_logger.info('PredictionModel calculating: model name(%s),'
'smile(%s) mol path(%s) temperature(%s)',
map_model_name, smile, mol_fpath, temperature)
# 后台模型计算入口
predict_results = prediction_model_calculate(map_model_name, smile,
mol_fpath, temperature)
if task.file_obj.file_type == 'mol':
name = os.path.basename(mol_fpath).split('.')[0]
else:
name = smile
result = predict_results[name][map_model_name]
chemistry_logger.info('[task]result %s' % result)
except KeyError:
chemistry_logger.exception('still cannot support this model')
result = None
task.result_state = "We don't support this model now"
task.status = StatusCategory.objects.get(category=STATUS_FAILED)
suite.status_id = StatusCategory.objects.get(category=STATUS_FAILED)
except Exception as e:
chemistry_logger.exception('failed to submit task to prediction model')
result = None
task.result_state = str(e)
task.status = StatusCategory.objects.get(category=STATUS_FAILED)
suite.status_id = StatusCategory.objects.get(category=STATUS_FAILED)
else:
chemistry_logger.info("calculate Successfully in celery queue!")
task.result_state = "Calculate Successfully!"
task.status = StatusCategory.objects.get(category=STATUS_SUCCESS)
suite.status_id = StatusCategory.objects.get(category=STATUS_WORKING)
task.end_time = utils.get_real_now()
task.results = json.dumps(result)
suite.save()
task.save()
add_counter(suite.sid)
return result
