async def on_c_got_step_results(self, sid, results):
with db.connection_context():
# Get the datapoint associated with the step (should be generated when step is sent)
datapoint = DataPoint.select().where(
DataPoint.step == results['step_id']).order_by(
DataPoint.created).get()
# Then we save the datapoint
if datapoint is not None:
datapoint.save_cryo_data(results)
def get_tags(
tag: str,
start: str = None,
end: str = None,
unit: str = "day",
):
if unit not in ['week', 'day', 'month', 'year']:
return {
'status': 'error',
'msg': "unit should be :week, day, month, year"
}
if start is not None:
start = dateparser.parse(str(start))
end = datetime.now()
if end is not None:
end = dateparser.parse(str(end))
if start is None:
start = end - relativedelta(days=1000)
if end is not None and start is not None:
if not validate_daterange(start, end):
return {
'status':
'error',
'msg':
"Invalid daterange, start date must be earlier than end date"
}
daily_metrics = []
datapoints = DataPoint.select().where((DataPoint.key == 'tag')
& (DataPoint.value == tag))
if datapoints.exists():
for datapoint in datapoints:
for point in datapoint.metrics:
m = point
m.pop('tag')
m['region'] = datapoint.region.region_id
time = datetime.strptime(m['time'].split(' ')[0], "%Y-%m-%d")
if time >= start and time <= end:
daily_metrics.append(m)
return {
'status': 'ok',
'date': {
'start': start.strftime('%Y-%m-%d'),
'end': end.strftime('%Y-%m-%d')
},
'results': daily_metrics
}
def suggestion(search: str, ratio=0.5, top=20):
edit = int(len(search) * ratio)
exp = NodeList([
SQL("levenshtein("), DataPoint.value,
SQL(", '{}') <= {}".format(search, edit)),
SQL(" order by levenshtein("), DataPoint.value,
SQL(", '{}')".format(search))
],
glue='')
datapoints = DataPoint.select().where(exp)
tags = []
if datapoints.exists():
for datapoint in datapoints[:top]:
tags.append(datapoint.value)
return {'tags': tags}
async def get_next_step(self):
with db.connection_context():
try:
# Get the next step
step = ExperimentStep.select().where(
ExperimentStep.step_done == False).order_by(
ExperimentStep.id).first()
# Check if the step is none, and skip to the catch clause if it is
if step is None:
raise DoesNotExist('Step does not exist')
# Check if the step has an associated datapoint
if DataPoint.select().where(
ExperimentStep == step).count() < 1:
step.generate_datapoint()
# Convert step to dict
step_d = model_to_dict(step)
# Set the experiment id (different from the step id)
step_d['experiment_configuration_id'] = step_d[
'experiment_configuration']['id']
# Remove datetime and experiment configuration from the dict
# They are not needed in the client, and they are not directly serializable to json (due to missing datetime format)
del (step_d['created'])
del (step_d['experiment_configuration'])
# Return the step if it exists
return step_d
# Check if the step even exists
except DoesNotExist:
# It is OK if it does not exist, we should just stop measuring
print('No more steps ready')
# Return None if no step exists
return None
def get_tags(tag: str,
start: str = None,
end: str = None,
unit: str = "day",
ratio: float = 1,
top: int = 5):
if unit not in ['week', 'day', 'month', 'year']:
return {
'status': 'error',
'msg': "unit should be :week, day, month, year"
}
if start is not None:
start = dateparser.parse(str(start))
end = datetime.now()
if end is not None:
end = dateparser.parse(str(end))
if start is None:
start = end - relativedelta(days=1000)
if end is not None and start is not None:
if not validate_daterange(start, end):
return {
'status':
'error',
'msg':
"Invalid daterange, start date must be earlier than end date"
}
daily_metrics = []
edit = int(len(tag) * ratio)
exp = NodeList([
SQL("levenshtein("), DataPoint.value,
SQL(", '{}') <= {}".format(tag, edit)),
SQL(" order by levenshtein("), DataPoint.value,
SQL(", '{}')".format(tag))
],
glue='')
datapoints = DataPoint.select().where(exp)
if datapoints.exists():
for datapoint in datapoints[:top]:
datapoint_metrics = []
for point in datapoint.metrics:
m = point
m.pop('tag')
m['region'] = datapoint.region.region_id
time = datetime.strptime(m['time'].split(' ')[0], "%Y-%m-%d")
if time >= start and time <= end:
datapoint_metrics.append(m)
daily_metrics.append({
'tag': datapoint.value,
'data': datapoint_metrics
})
return {
'status': 'ok',
'date': {
'start': start.strftime('%Y-%m-%d'),
'end': end.strftime('%Y-%m-%d')
},
'results': daily_metrics
}
async def export_data(request):
# Check id exists
if 'id' not in request.query:
return web.Response(text='Could not find the requested id',
content_type='text/html')
# Grab the id
config_id = request.query['id']
# Now we want to start the export
# Open connection to database
with db.connection_context():
# Grab the configuration first
ecl = ExperimentConfiguration.select().where(
ExperimentConfiguration.id == config_id).dicts()
# Check if we have a result
if len(ecl) > 0:
# Grab the first result (There should only be one when we query by id)
ec = ecl[0]
# Convert date format
ec['created'] = ec['created'].isoformat()
# Compute the number of points taken
ec['n_points_taken'] = ExperimentStep.select() \
.where(ExperimentStep.experiment_configuration == ec['id']) \
.where(ExperimentStep.step_done == True) \
.count()
# Compute the number of points taken
ec['n_points_total'] = ExperimentStep.select() \
.where(ExperimentStep.experiment_configuration == ec['id']) \
.count()
# Add an empty array to contain steps
ec['steps'] = []
# Now we're done processing the configuration
# Next we get all the datapoints that were saved
# We start by iterating over all the steps in the experiment
for step in ExperimentStep.select().where(
ExperimentStep.experiment_configuration ==
ec['id']).dicts():
# Convert date format
step['created'] = step['created'].isoformat()
# Add an empty array to contain datapoints
step['datapoints'] = []
# And we iterate through all the datapoints for the step
for dp in DataPoint.select().where(
DataPoint.step == step['id']):
# Create a dict to contain the collected information
datapoint_dict = {
'id': dp.id,
'created': dp.created.isoformat(),
'magnetism_datapoints': [],
'temperature_datapoints': [],
'pressure_datapoints': []
}
# Next we find the magnetism datapoint
for mdp in MagnetismDataPoint.select().where(
MagnetismDataPoint.datapoint == dp):
# For this we find the magnetism measurements (where we actually store the data)
mdps = MagnetismMeasurement.select().where(
MagnetismMeasurement.magnetism_data_point == mdp)
# Save it to the datapoint dict
for magnetism_datapoint in list(mdps.dicts()):
datapoint_dict['magnetism_datapoints'].append(
magnetism_datapoint)
# And we find the cryodatapoint
for cdp in CryogenicsDataPoint.select().where(
CryogenicsDataPoint.datapoint == dp):
# Similarly we find pressure and temperature datapoints
pdps = PressureDataPoint.select().where(
PressureDataPoint.cryo_data_point == cdp)
tdps = TemperatureDataPoint.select().where(
TemperatureDataPoint.cryo_data_point == cdp)
# Save them to the datapoint dict
for pressure_datapoint in list(pdps.dicts()):
datapoint_dict['pressure_datapoints'].append(
pressure_datapoint)
for temperature_datapoint in list(tdps.dicts()):
# Convert date format
temperature_datapoint[
'created'] = temperature_datapoint[
'created'].isoformat()
# Append the temperature
datapoint_dict['temperature_datapoints'].append(
temperature_datapoint)
# Save the datapoint to the step
step['datapoints'].append(datapoint_dict)
# Save the step to the configuration
ec['steps'].append(step)
# And finally we send the response data
return web.json_response(
headers={'Content-Disposition': f'Attachment'},
body=json.dumps(ec))
else:
return web.Response(text='Attempted to export ' + str(config_id) +
' but no such config found',
content_type='text/html')
