def __init__(self, timestamp, caching=False, set_label=None, temp_label='Sample temperature', recalculate=False):
"""Save all data in 'DATA' dict object"""
# Various attributes
self.pickle_format = 'tpd__{}__{}.pickle'
self.exps = {}
#self.caching = True if CACHING is True or caching is True else False
self.caching = caching
if CACHING is not None:
self.caching = CACHING
self.timestamp = {}
self.timestamp['date'] = timestamp
self.timestamp['unix'] = time.mktime(datetime.datetime.strptime(
timestamp, "%Y-%m-%d %H:%M:%S").timetuple())
# Try to load from file
cache_file = []
load_from_pickle = False
if self.caching and not recalculate:
list_of_files = path.os.listdir(CACHE_DIR)
for name in list_of_files:
if name.startswith('tpd__{}__'.format(timestamp)):
cache_file.append(name)
if len(cache_file) == 1:
with open(path.join(CACHE_DIR, cache_file[0]), 'rb') as f:
copy = pickle.load(f)
self.name = copy.name
self.labels = copy.labels
self.data = copy.data
self.exps = copy.exps
load_from_pickle = True
print(' *** Loaded TPD data from pickle: {} ***'.format(self.name))
elif len(cache_file) > 1:
print('Found multiple pickles matching timestamp:\n{}'.format(cache_file))
# Get data from database
if load_from_pickle is False:
# Connect to database
db = Cinfdata('omicron',
use_caching=caching,
grouping_column='time',
)
# Get data in unit seconds
group_data = db.get_data_group(timestamp, scaling_factors=(1E-3, None))
group_meta = db.get_metadata_group(timestamp)
# Get a list of labels and group data
print(group_meta)
self.name = group_meta[list(group_meta.keys())[0]]['Comment'].replace('/', '')
self.labels = [group_meta[key]['mass_label'] for key in group_data.keys()]
self.data = {group_meta[key]['mass_label']: group_data[key] for key in group_data.keys()}
print('Loaded data from Experiment: "{}"'.format(self.name))
self.isolate_experiments(set_label=set_label, temp_label=temp_label)
def __init__(self, timestamp, caching=False):
"""Save all data in 'DATA' dict object"""
# Connect to database
db = Cinfdata('omicron',
use_caching=caching,
grouping_column='time',
)
# Get data in unit seconds
group_data = db.get_data_group(timestamp, scaling_factors=(1E-3, None))
group_meta = db.get_metadata_group(timestamp)
# Get a list of labels and group data
self.name = group_meta[list(group_meta.keys())[0]]['Comment']
self.labels = [group_meta[key]['mass_label'] for key in group_data.keys()]
self.data = {group_meta[key]['mass_label']: group_data[key] for key in group_data.keys()}
print('Loaded data from Experiment: "{}"'.format(self.name))
def __init__(self, timestamp, caching=True):
"""Save all data in 'DATA' dict object"""
# Connect to database
db = Cinfdata('omicron',
use_caching=caching,
grouping_column='time',
)
# Get data in unit seconds
group_data = db.get_data_group(timestamp, scaling_factors=(1E-3, None))
group_meta = db.get_metadata_group(timestamp)
# Get a list of labels and group data
self.name = group_meta[list(group_meta.keys())[0]]['Comment']
self.labels = [group_meta[key]['mass_label'] for key in group_data.keys()]
self.data = {group_meta[key]['mass_label']: group_data[key] for key in group_data.keys()}
print('Loaded data from Experiment: "{}"'.format(self.name))
def download_cinfdata_set(
setup="sniffer", group_id=None, grouping_column=None, **kwargs
):
if grouping_column is None:
grouping_column, group_id = kwargs.popitem()
from .Combining import synchronize
try:
from cinfdata import Cinfdata
except ImportError:
print(
"the cinfdata module must be on your python path. It's here: \n"
+ "https://github.com/CINF/cinf_database/blob/master/cinfdata.py"
)
try:
cinfd = Cinfdata(
setup,
grouping_column=grouping_column,
allow_wildcards=True,
label_column="mass_label",
)
except:
raise # untill I know exactly which error I'm trying to catch.
print("couldn't connect. You should run gstm")
# os.system('gstm')
raise RuntimeError("Couldn't connect to cinfdata!")
# obj = cinfd.get_metadata_group('2018-03-30 14:13:17')
# all_datasets = cinfd.get_metadata_group('%')
# the_list = [(ID, d['time'], d['comment']) for ID, d in all_datasets.items()]
# print(the_list)
obj = cinfd.get_metadata_group(group_id)
# print(str(obj)) #
idlists = {} # keys will be time as string. values will be corresponding id's
for key, value in obj.items():
# label = value['mass_label']
# print(label)
timestamp = str(value["time"])
if timestamp not in idlists:
idlists[timestamp] = []
idlists[timestamp] += [value["id"]]
datasets = {}
for timestamp, idlist in idlists.items():
if len(idlist) == 0:
print("No data associated with timestamp '" + timestamp + "'.")
continue
dataset = {"title": timestamp, "data_type": "MS"}
metadatas = dict([(i, cinfd.get_metadata(i)) for i in idlist])
unixtimes = [metadatas[i]["unixtime"] for i in idlist]
if len(set(unixtimes)) > 1:
msg = "unix times don't match for timestamp '" + timestamp + "'!"
raise ValueError(msg)
dataset["tstamp"] = unixtimes[0]
dataset["timestamp"] = metadatas[idlist[0]]["time"].strftime("%H:%M:%S")
labels = [metadatas[i]["mass_label"] for i in idlist]
if "Mass Scan" in labels:
dataset["scan_type"] = "mass"
else:
dataset["scan_type"] = "time"
dataset["data_cols"] = set()
dataset["timecols"] = {}
for i in idlist: # avoiding id since it's got a builtin meaning
data = cinfd.get_data(i)
label = metadatas[i]["mass_label"]
if len(data.shape) == 1:
dataset[label] = data
dataset["data_cols"].add(label)
elif data.shape[1] == 2:
x = data[:, 0]
y = data[:, 1]
x_label = label + "-x"
y_label = label + "-y"
dataset["timecols"][y_label] = x_label # Fixed 20B26!!!
dataset[x_label] = x * 1e-3 # cinfdata saves time in ms!!!
dataset[y_label] = y
dataset["data_cols"].add(x_label)
dataset["data_cols"].add(y_label)
datasets[timestamp] = dataset
timescans = [
dataset for dataset in datasets.values() if dataset["scan_type"] == "time"
]
combined = synchronize(timescans, t_zero="first")
return combined
def download_cinfdata_set(setup='sniffer',
group_id=None,
grouping_column=None,
**kwargs):
if grouping_column is None:
grouping_column, group_id = kwargs.popitem()
from .Combining import synchronize
try:
from cinfdata import Cinfdata
except ImportError:
print(
'the cinfdata module must be on your python path. It\'s here: \n' +
'https://github.com/CINF/cinf_database/blob/master/cinfdata.py')
try:
cinfd = Cinfdata(setup,
grouping_column=grouping_column,
allow_wildcards=True,
label_column='mass_label')
except:
raise #untill I know exactly which error I'm trying to catch.
print('couldn\'t connect. You should run gstm')
#os.system('gstm')
raise RuntimeError('Couldn\'t connect to cinfdata!')
#obj = cinfd.get_metadata_group('2018-03-30 14:13:17')
#all_datasets = cinfd.get_metadata_group('%')
#the_list = [(ID, d['time'], d['comment']) for ID, d in all_datasets.items()]
#print(the_list)
obj = cinfd.get_metadata_group(group_id)
#print(str(obj)) #
idlists = {
} # keys will be time as string. values will be corresponding id's
for key, value in obj.items():
#label = value['mass_label']
#print(label)
timestamp = str(value['time'])
if timestamp not in idlists:
idlists[timestamp] = []
idlists[timestamp] += [value['id']]
datasets = {}
for timestamp, idlist in idlists.items():
if len(idlist) == 0:
print('No data associated with timestamp \'' + timestamp + '\'.')
continue
dataset = {'title': timestamp, 'data_type': 'MS'}
metadatas = dict([(i, cinfd.get_metadata(i)) for i in idlist])
unixtimes = [metadatas[i]['unixtime'] for i in idlist]
if len(set(unixtimes)) > 1:
msg = 'unix times don\'t match for timestamp \'' + timestamp + '\'!'
raise ValueError(msg)
dataset['tstamp'] = unixtimes[0]
dataset['timestamp'] = metadatas[idlist[0]]['time'].strftime(
'%H:%M:%S')
labels = [metadatas[i]['mass_label'] for i in idlist]
if 'Mass Scan' in labels:
dataset['scan_type'] = 'mass'
else:
dataset['scan_type'] = 'time'
dataset['data_cols'] = set()
dataset['timecols'] = {}
for i in idlist: #avoiding id since it's got a builtin meaning
data = cinfd.get_data(i)
label = metadatas[i]['mass_label']
if len(data.shape) == 1:
dataset[label] = data
dataset['data_cols'].add(label)
elif data.shape[1] == 2:
x = data[:, 0]
y = data[:, 1]
x_label = label + '-x'
y_label = label + '-y'
dataset['timecols'][x_label] = y_label
dataset[x_label] = x * 1e-3 # cinfdata saves time in ms!!!
dataset[y_label] = y
dataset['data_cols'].add(x_label)
dataset['data_cols'].add(y_label)
datasets[timestamp] = dataset
timescans = [
dataset for dataset in datasets.values()
if dataset['scan_type'] == 'time'
]
combined = synchronize(timescans, t_zero='first')
return combined
