def info(self, lims_json_path):
''' return a string that a bash script can use
to find the working directory, etc. to clean up.
'''
ocr = OptimizeConfigReader()
ocr.read_lims_file(lims_json_path)
print(self.app_config.data['runs'][0]['specimen_id'])
print(self.manifest.get_path('BASEDIR'))
def one_param_config():
ocr = OptimizeConfigReader()
lims_json_path = 'lims_message.json'
with patch(builtins.__name__ + ".open",
mock_open(read_data=LIMS_MESSAGE_ONE_PARAM_FILE)):
ocr.read_lims_file(lims_json_path)
return ocr
def no_param_config():
json_data = json.loads(LIMS_MESSAGE_ONE_PARAM_FILE)
json_data['well_known_files'] = []
lims_message_no_param_file = json.dumps(json_data)
ocr = OptimizeConfigReader()
lims_json_path = 'lims_message.json'
with patch(builtins.__name__ + ".open",
mock_open(read_data=lims_message_no_param_file)):
ocr.read_lims_file(lims_json_path)
return ocr
def make_fit(self):
self.load_manifest()
fit_types = ["f9", "f13"]
best_fit_values = {fit_type: None for fit_type in fit_types}
specimen_id = self.app_config.data['runs'][0]['specimen_id']
for fit_type in fit_types:
fit_type_dir = self.manifest.get_path('fit_type_path', fit_type)
if os.path.exists(fit_type_dir):
report = Report(self.app_config, fit_type)
report.generate_fit_file()
if fit_type in best_fit_values.keys():
best_fit_values[fit_type] = report.best_fit_value()
best_fit_type, min_fit_value = reduce(
lambda a, b: a if (a[1] < b[1]) else b,
(i for i in best_fit_values.items() if i[1] is not None))
best_fit_file = self.manifest.get_path('output_fit_file', specimen_id,
best_fit_type)
lims_upload_config = OptimizeConfigReader()
lims_upload_config.read_json(
self.manifest.get_path('neuronal_model_data'))
lims_upload_config.update_well_known_file(
best_fit_file,
well_known_file_type_id=OptimizeConfigReader.
NEURONAL_MODEL_PARAMETERS)
lims_upload_config.write_file(output_json)
def generate_manifest_lims(self, lims_json_path, manifest_path):
'''
Note
----
Other necessary files are also written.
'''
ocr = OptimizeConfigReader()
ocr.read_lims_file(lims_json_path)
ocr.to_manifest(manifest_path)
def generate_manifest_rma(self,
neuronal_model_id,
manifest_path,
api_url=None):
'''
Note
----
Other necessary files are also written.
'''
import json
from allensdk.api.api import Api
bma = BiophysicalModuleApi(api_url)
data = bma.get_neuronal_models(neuronal_model_id)
ocr = OptimizeConfigReader()
ocr.read_lims_message(data, 'lims_message.json')
with open('lims_message.json', 'w') as f:
f.write(json.dumps(data[0], sort_keys=True, indent=2))
ocr.to_manifest(manifest_path)