def __init__(self, *args, **kwargs):
"""Initialize the Batch class.
The initialization accepts arbitrary arguments and keyword arguments.
It first looks for the file_name and db_reader keyword arguments.
Usage:
b = Batch((name, (project)), **kwargs)
Examples:
>>> b = Batch("experiment001", "main_project")
>>> b = Batch("experiment001", "main_project", batch_col="b02")
>>> b = Batch(name="experiment001", project="main_project", batch_col="b02")
>>> b = Batch(file_name="cellpydata/batchfiles/cellpy_batch_experiment001.json")
Keyword Args (priority):
file_name (str or pathlib.Path): journal file name to load.
db_reader (str): data-base reader to use (defaults to "default" as given
in the config-file or prm-class).
Args:
*args: name (str) (project (str))
Keyword Args (other):
default_log_level (str): custom log-level (defaults to None (i.e. default log-level in cellpy)).
custom_log_dir (str or pathlib.Path): custom folder for putting the log-files.
force_raw_file (bool): load from raw regardless (defaults to False).
force_cellpy (bool): load cellpy-files regardless (defaults to False).
force_recalc (bool): Always recalculate (defaults to False).
export_cycles (bool): Extract and export individual cycles to csv (defaults to True).
export_raw (bool): Extract and export raw-data to csv (defaults to True).
export_ica (bool): Extract and export individual dQ/dV data to csv (defaults to True).
accept_errors (bool): Continue automatically to next file if error is raised (defaults to False).
nom_cap (float): give a nominal capacity if you want to use another value than
the one given in the config-file or prm-class.
"""
default_log_level = kwargs.pop("log_level", None)
custom_log_dir = kwargs.pop("custom_log_dir", None)
if default_log_level is not None or custom_log_dir is not None:
log.setup_logging(
custom_log_dir=custom_log_dir,
default_level=default_log_level,
reset_big_log=True,
)
db_reader = kwargs.pop("db_reader", "default")
file_name = kwargs.pop("file_name", None)
logging.debug("creating CyclingExperiment")
self.experiment = CyclingExperiment(db_reader=db_reader)
logging.info("created CyclingExperiment")
self.experiment.force_cellpy = kwargs.pop("force_cellpy", False)
self.experiment.force_raw = kwargs.pop("force_raw_file", False)
self.experiment.force_recalc = kwargs.pop("force_recalc", False)
self.experiment.export_cycles = kwargs.pop("export_cycles", True)
self.experiment.export_raw = kwargs.pop("export_raw", True)
self.experiment.export_ica = kwargs.pop("export_ica", False)
self.experiment.accept_errors = kwargs.pop("accept_errors", False)
self.experiment.nom_cap = kwargs.pop("nom_cap", None)
if not file_name:
if len(args) > 0:
self.experiment.journal.name = args[0]
if len(args) > 1:
self.experiment.journal.project = args[1]
for key in kwargs:
if key == "name":
self.experiment.journal.name = kwargs[key]
elif key == "project":
self.experiment.journal.project = kwargs[key]
elif key == "batch_col":
self.experiment.journal.batch_col = kwargs[key]
else:
self.experiment.journal.from_file(file_name=file_name)
self.exporter = CSVExporter()
self.exporter._assign_dumper(ram_dumper)
self.exporter.assign(self.experiment)
self.plotter = CyclingSummaryPlotter()
self.plotter.assign(self.experiment)
self._journal_name = self.journal_name
self.headers_step_table = get_headers_step_table()
cellpy_limits,
cellpy_units,
get_headers_summary,
get_headers_normal,
get_headers_step_table,
)
CELLPY_FILE_VERSION = 5
MINIMUM_CELLPY_FILE_VERSION = 1
STEP_TABLE_VERSION = 5
RAW_TABLE_VERSION = 5
SUMMARY_TABLE_VERSION = 5
HEADERS_NORMAL = get_headers_normal()
HEADERS_SUMMARY = get_headers_summary()
HEADERS_STEP_TABLE = get_headers_step_table()
class FileID(object):
"""class for storing information about the raw-data files.
This class is used for storing and handling raw-data file information.
It is important to keep track of when the data was extracted from the
raw-data files so that it is easy to know if the hdf5-files used for
@storing "treated" data is up-to-date.
Attributes:
name (str): Filename of the raw-data file.
full_name (str): Filename including path of the raw-data file.
size (float): Size of the raw-data file.
last_modified (datetime): Last time of modification of the raw-data
"#FFFEA3",
"#B0E0E6",
],
"seaborn-dark-palette": [
"#001C7F",
"#017517",
"#8C0900",
"#7600A1",
"#B8860B",
"#006374",
],
}
hdr_summary = get_headers_summary()
hdr_raw = get_headers_normal()
hdr_steps = get_headers_step_table()
hdr_journal = get_headers_journal()
def _hv_bokeh_available():
if not hv_available:
print("You need holoviews. But I cannot load it. Aborting...")
return False
if not bokeh_available:
print("You need Bokeh. But I cannot find it. Aborting...")
return False
return True
def find_column(columns, label=None, end="cycle_index"):
"""find columns based on how the column-name ends.
