JorgeVB/code_unlearning_dataset · Datasets at Hugging Face

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override asyncio.Protocol def data_received(self, data): ''' override asyncio.Protocol ''' self._buffered_data.extend(data) while self._buffered_data: size = len(self._buffered_data) if self._data_package is None: if size < DataPackage.str...
override _SiriDBProtocol def connection_made(self, transport): ''' override _SiriDBProtocol ''' self.transport = transport self.remote_ip, self.port = transport.get_extra_info('peername')[:2] logging.debug( 'Connection made (address: {} port: {})' ...
Register a new SiriDB Server. This method is used by the SiriDB manage tool and should not be used otherwise. Full access rights are required for this request. def _register_server(self, server, timeout=30): '''Register a new SiriDB Server. This method is used by the SiriDB manage too...
Request a SiriDB configuration file. This method is used by the SiriDB manage tool and should not be used otherwise. Full access rights are required for this request. def _get_file(self, fn, timeout=30): '''Request a SiriDB configuration file. This method is used by the SiriDB manage ...
Convert GeoHash bits to a float. def _bits_to_float(bits, lower=-90.0, middle=0.0, upper=90.0): """Convert GeoHash bits to a float.""" for i in bits: if i: lower = middle else: upper = middle middle = (upper + lower) / 2 return middle
Convert a float to a list of GeoHash bits. def _float_to_bits(value, lower=-90.0, middle=0.0, upper=90.0, length=15): """Convert a float to a list of GeoHash bits.""" ret = [] for i in range(length): if value >= middle: lower = middle ret.append(1) else: upper = middle ret.append(...
Convert a GeoHash to a list of GeoHash bits. def _geohash_to_bits(value): """Convert a GeoHash to a list of GeoHash bits.""" b = map(BASE32MAP.get, value) ret = [] for i in b: out = [] for z in range(5): out.append(i & 0b1) i = i >> 1 ret += out[::-1] return ret
Convert a list of GeoHash bits to a GeoHash. def _bits_to_geohash(value): """Convert a list of GeoHash bits to a GeoHash.""" ret = [] # Get 5 bits at a time for i in (value[i:i+5] for i in xrange(0, len(value), 5)): # Convert binary to integer # Note: reverse here, the slice above doesn't work quite ri...
Decode a geohash. Returns a (lon,lat) pair. def decode(value): """Decode a geohash. Returns a (lon,lat) pair.""" assert value, "Invalid geohash: %s"%value # Get the GeoHash bits bits = _geohash_to_bits(value) # Unzip the GeoHash bits. lon = bits[0::2] lat = bits[1::2] # Convert to lat/lon return ( ...
Encode a (lon,lat) pair to a GeoHash. def encode(lonlat, length=12): """Encode a (lon,lat) pair to a GeoHash.""" assert len(lonlat) == 2, "Invalid lon/lat: %s"%lonlat # Half the length for each component. length /= 2 lon = _float_to_bits(lonlat[0], lower=-180.0, upper=180.0, length=length*5) lat = _float_t...
Return the adjacent geohash for a given direction. def adjacent(geohash, direction): """Return the adjacent geohash for a given direction.""" # Based on an MIT licensed implementation by Chris Veness from: # http://www.movable-type.co.uk/scripts/geohash.html assert direction in 'nsew', "Invalid direction: %s...
Return all neighboring geohashes. def neighbors(geohash): """Return all neighboring geohashes.""" return { 'n': adjacent(geohash, 'n'), 'ne': adjacent(adjacent(geohash, 'n'), 'e'), 'e': adjacent(geohash, 'e'), 'se': adjacent(adjacent(geohash, 's'), 'e'), 's': adjacent(geohash, 's'), 'sw'...
Make a function immediately return a function of no args which, when called, waits for the result, which will start being processed in another thread. Taken from https://wiki.python.org/moin/PythonDecoratorLibrary. def thunkify(thread_name=None, daemon=True, default_func=None): '''Make a function immediate...
Decorator function that sets Threading.Event() when keyboard interrupt (Ctrl+C) was raised Parameters ---------- _lambda : function Lambda function that points to Threading.Event() object Returns ------- wrapper : function Examples -------- @set_event_when_keyboard_interru...
Run name without whitespace def run_id(self): '''Run name without whitespace ''' s1 = re.sub('(.)([A-Z][a-z]+)', r'\1_\2', self.__class__.__name__) return re.sub('([a-z0-9])([A-Z])', r'\1_\2', s1).lower()
Configuration (namedtuple) def conf(self): '''Configuration (namedtuple) ''' conf = namedtuple('conf', field_names=self._conf.keys()) return conf(**self._conf)
Run configuration (namedtuple) def run_conf(self): '''Run configuration (namedtuple) ''' run_conf = namedtuple('run_conf', field_names=self._run_conf.keys()) return run_conf(**self._run_conf)
Default run configuration (namedtuple) def default_run_conf(self): '''Default run configuration (namedtuple) ''' default_run_conf = namedtuple('default_run_conf', field_names=self._default_run_conf.keys()) return default_run_conf(**self._default_run_conf)
Initialization before a new run. def _init(self, run_conf, run_number=None): '''Initialization before a new run. ''' self.stop_run.clear() self.abort_run.clear() self._run_status = run_status.running self._write_run_number(run_number) self._init_run_conf(run_conf...
Run given functions when a run is cancelled. def connect_cancel(self, functions): '''Run given functions when a run is cancelled. ''' self._cancel_functions = [] for func in functions: if isinstance(func, basestring) and hasattr(self, func) and callable(getattr(self, func)):...
Cancelling a run. def handle_cancel(self, kwargs): '''Cancelling a run. ''' for func in self._cancel_functions: f_args = getargspec(func)[0] f_kwargs = {key: kwargs[key] for key in f_args if key in kwargs} func(f_kwargs)
Stopping a run. Control for loops. Gentle stop/abort. This event should provide a more gentle abort. The run should stop ASAP but the run is still considered complete. def stop(self, msg=None): '''Stopping a run. Control for loops. Gentle stop/abort. This event should provide a more gentle ab...
Aborting a run. Control for loops. Immediate stop/abort. The implementation should stop a run ASAP when this event is set. The run is considered incomplete. def abort(self, msg=None): '''Aborting a run. Control for loops. Immediate stop/abort. The implementation should stop a run ASAP when th...
Runs a run in another thread. Non-blocking. Parameters ---------- run : class, object Run class or object. run_conf : str, dict, file Specific configuration for the run. use_thread : bool If True, run run in thread and returns blocking functio...
Runs runs from a primlist. Parameters ---------- primlist : string Filename of primlist. skip_remaining : bool If True, skip remaining runs, if a run does not exit with status FINISHED. Note ---- Primlist is a text file of the following f...
Determines the mean x and y beam spot position as a function of time. Therefore the data of a fixed number of read outs are combined ('combine_n_readouts'). The occupancy is determined for the given combined events and stored into a pdf file. At the end the beam x and y is plotted into a scatter plot with absolute ...
Determines the number of events as a function of time. Therefore the data of a fixed number of read outs are combined ('combine_n_readouts'). The number of events is taken from the meta data info and stored into a pdf file. Parameters ---------- scan_base: list of str scan base names (e.g.: ['...
Determines the number of cluster per event as a function of time. Therefore the data of a fixed number of read outs are combined ('combine_n_readouts'). Parameters ---------- scan_base: list of str scan base names (e.g.: ['//data//SCC_50_fei4_self_trigger_scan_390', ] include_no_cluster: bool ...
Takes a hit table and stores only selected hits into a new table. The selection is done on an event base and events are selected if they have a certain number of cluster or cluster size. To increase the analysis speed a event index for the input hit file is created first. Since a cluster hit table can be created to...
Takes a hit table and stores only selected hits into a new table. The selection of hits is done with a numexp string. Only if this expression evaluates to true the hit is taken. One can also select hits from cluster conditions. This selection is done on an event basis, meaning events are selected where the clus...
This method takes multiple hit files and determines the cluster size for different scan parameter values of Parameters ---------- input_files_hits: string output_file_cluster_size: string The data file with the results parameter: string The name of the parameter to separate the dat...
Reads in the cluster info table in chunks and histograms the seed pixels into one occupancy array. The 3rd dimension of the occupancy array is the number of different scan parameters used Parameters ---------- analyzed_data_file : string HDF5 filename of the file containing the cluster table. I...
Takes the hit table and analyzes the hits per scan parameter Parameters ---------- analyze_data : analysis.analyze_raw_data.AnalyzeRawData object with an opened hit file (AnalyzeRawData.out_file_h5) or a file name with the hit data given (AnalyzeRawData._analyzed_data_file) scan_parameters : list o...
Interprets raw data from Tektronix returns: lists of x, y values in seconds/volt def interpret_data_from_tektronix(preamble, data): ''' Interprets raw data from Tektronix returns: lists of x, y values in seconds/volt''' # Y mode ("WFMPRE:PT_FMT"): # Xn = XZEro + XINcr (n - PT_Off) # Yn = YZEro ...
Reading Chip S/N Note ---- Bits [MSB-LSB] \| [15] \| [14-6] \| [5-0] Content \| reserved \| wafer number \| chip number def read_chip_sn(self): '''Reading Chip S/N Note ---- Bits [MSB-LSB] \| [15] \| [14-6] \| [5-0] Content \| reserved \| ...
The function reads the global register, interprets the data and returns the register value. Parameters ---------- name : register name overwrite_config : bool The read values overwrite the config in RAM if true. Returns ------- register value def read_global_register(sel...
The function reads the pixel register, interprets the data and returns a masked numpy arrays with the data for the chosen pixel register. Pixels without any data are masked. Parameters ---------- pix_regs : iterable, string List of pixel register to read (e.g. Enable, C_High, ...). ...
Get FEI4 status of module. If FEI4 is not ready, resetting service records is necessary to bring the FEI4 to a defined state. Returns ------- value : bool True if FEI4 is ready, False if the FEI4 was powered up recently and is not ready. def is_fe_ready(self): '''Get FEI4 status o...
Invert pixel mask (0->1, 1(and greater)->0). Parameters ---------- mask : array-like Mask. Returns ------- inverted_mask : array-like Inverted Mask. def invert_pixel_mask(mask): '''Invert pixel mask (0->1, 1(and greater)->0). Parameters ---------- ...
Generate pixel mask. Parameters ---------- steps : int Number of mask steps, e.g. steps=3 (every third pixel is enabled), steps=336 (one pixel per column), steps=672 (one pixel per double column). shift : int Shift mask by given value to the bottom (towards higher row numbers). F...
Generate mask from column and row lists Parameters ---------- column : iterable, int List of colums values. row : iterable, int List of row values. default : int Value of pixels that are not selected by the mask. value : int Value of pixels that are se...
Generate box shaped mask from column and row lists. Takes the minimum and maximum value from each list. Parameters ---------- column : iterable, int List of colums values. row : iterable, int List of row values. default : int Value of pixels that are not selected by...
Generate xtalk mask (row - 1, row + 1) from pixel mask. Parameters ---------- mask : ndarray Pixel mask. Returns ------- ndarray Xtalk mask. Example ------- Input: [[1 0 0 0 0 0 1 0 0 0 ... 0 0 0 0 1 0 0 0 0 0] [0 0 0 1 0 0 0 0 0 1 ... 0 1 ...
Generate chessboard/checkerboard mask. Parameters ---------- column_distance : int Column distance of the enabled pixels. row_distance : int Row distance of the enabled pixels. column_offset : int Additional column offset which shifts the columns by the given amount...
Implementation of the scan loops (mask shifting, loop over double columns, repeatedly sending any arbitrary command). Parameters ---------- command : BitVector (FEI4) command that will be sent out serially. repeat_command : int The number of repetitions command will be sent out e...
Resetting Service Records This will reset Service Record counters. This will also bring back alive some FE where the output FIFO is stuck (no data is coming out in run mode). This should be only issued after power up and in the case of a stuck FIFO, otherwise the BCID counter starts jumping. def re...
Resetting Bunch Counter def reset_bunch_counter(self): '''Resetting Bunch Counter ''' logging.info('Resetting Bunch Counter') commands = [] commands.extend(self.register.get_commands("RunMode")) commands.extend(self.register.get_commands("BCR")) self.send_...
Masking array elements when equal 0.0 or greater than 10 times the median Parameters ---------- hist : array_like Input data. Returns ------- masked array Returns copy of the array with masked elements. def generate_threshold_mask(hist): '''Masking array elements when equa...
Takes a numpy array and returns the array reduced to unique rows. If columns are defined only these columns are taken to define a unique row. The returned array can have all columns of the original array or only the columns defined in use_columns. Parameters ---------- array : numpy.ndarray use_colu...
Takes an array and calculates ranges [start, stop[. The last range end is none to keep the same length. Parameters ---------- arr : array like append_last: bool If True, append item with a pair of last array item and None. Returns ------- numpy.array The array formed by pai...
Does the same than np.in1d but uses the fact that ar1 and ar2 are sorted. Is therefore much faster. def in1d_sorted(ar1, ar2): """ Does the same than np.in1d but uses the fact that ar1 and ar2 are sorted. Is therefore much faster. """ if ar1.shape[0] == 0 or ar2.shape[0] == 0: # check for empty array...
Returns the dy/dx(x) via central difference method Parameters ---------- x : array like y : array like Returns ------- dy/dx : array like def central_difference(x, y): '''Returns the dy/dx(x) via central difference method Parameters ---------- x : array like y : array...
Takes 2D point data (x,y) and creates a profile histogram similar to the TProfile in ROOT. It calculates the y mean for every bin at the bin center and gives the y mean error as error bars. Parameters ---------- x : array like data x positions y : array like data y positions n_b...
Takes different hit files (hit_files), extracts the number of events or the scan time (reference) per scan parameter (parameter) and returns an array with a normalization factor. This normalization factor has the length of the number of different parameters. If a cluster_file is specified also the number of clu...
Takes a list of files, searches for the parameter name in the file name and returns a ordered dict with the file name in the first dimension and the corresponding parameter value in the second. The file names can be sorted by the parameter value, otherwise the order is kept. If unique is true every parameter is...
Generate a list of .h5 files which have a similar file name. Parameters ---------- scan_base : list, string List of string or string of the scan base names. The scan_base will be used to search for files containing the string. The .h5 file extension will be added automatically. filter : list, s...
Takes a list of files, searches for the parameter name in the file name and in the file. Returns a ordered dict with the file name in the first dimension and the corresponding parameter values in the second. If a scan parameter appears in the file name and in the file the first parameter setting has to be in th...
Checks if the parameter names of all files are similar. Takes the dictionary from get_parameter_from_files output as input. def check_parameter_similarity(files_dict): """ Checks if the parameter names of all files are similar. Takes the dictionary from get_parameter_from_files output as input. """ tr...
Takes the dict of hdf5 files and combines their meta data tables into one new numpy record array. Parameters ---------- meta_data_v2 : bool True for new (v2) meta data format, False for the old (v1) format. def combine_meta_data(files_dict, meta_data_v2=True): """ Takes the dict of hdf5 fi...
Returns the dy/dx(x) with the fit and differentiation of a spline curve Parameters ---------- x : array like y : array like Returns ------- dy/dx : array like def smooth_differentiation(x, y, weigths=None, order=5, smoothness=3, derivation=1): '''Returns the dy/dx(x) with the fit and ...
Takes two sorted arrays and return the intersection ar1 in ar2, ar2 in ar1. Parameters ---------- ar1 : (M,) array_like Input array. ar2 : array_like Input array. Returns ------- ar1, ar1 : ndarray, ndarray The intersection values. def reduce_sorted_to_intersect(a...
Returns the values that appear at least twice in array. Parameters ---------- array : array like Returns ------- numpy.array def get_not_unique_values(array): '''Returns the values that appear at least twice in array. Parameters ---------- array : array like Returns ...
Takes the analyzed meta_data table and returns the indices where the scan parameter changes Parameters ---------- meta_data_array : numpy.recordarray scan_parameter_name : string Returns ------- numpy.ndarray: first dimension: scan parameter value second dimension: index wh...
Selects the hits with condition. E.g.: condition = 'rel_BCID == 7 & event_number < 1000' Parameters ---------- hits_array : numpy.array condition : string A condition that is applied to the hits in numexpr. Only if the expression evaluates to True the hit is taken. Returns ------- ...
Selects the hits that occurred in events and optional selection criterion. If a event range can be defined use the get_data_in_event_range function. It is much faster. Parameters ---------- hits_array : numpy.array events : array assume_sorted : bool Is true if the events to select ...
Takes the hit table of a hdf5 file and returns hits in chunks for each unique combination of scan_parameters. Yields the hits in chunks, since they usually do not fit into memory. Parameters ---------- input_file_hits : pytable hdf5 file Has to include a hits node scan_parameters : iterable...
Selects the data (rows of a table) that occurred in the given event range [event_start, event_stop[ Parameters ---------- array : numpy.array event_start : int, None event_stop : int, None assume_sorted : bool Set to true if the hits are sorted by the event_number. Increases speed. ...
Selects the hits that occurred in events and writes them to a pytable. This function reduces the in RAM operations and has to be used if the get_hits_in_events function raises a memory error. Also a condition can be set to select hits. Parameters ---------- hit_table_in : pytable.table hit_table_ou...
Selects the hits that occurred in given event range [event_start, event_stop[ and write them to a pytable. This function reduces the in RAM operations and has to be used if the get_data_in_event_range function raises a memory error. Also a condition can be set to select hits. Parameters ---------- h...
Selects the events with a certain number of cluster. Parameters ---------- event_number : numpy.array Returns ------- numpy.array def get_events_with_n_cluster(event_number, condition='n_cluster==1'): '''Selects the events with a certain number of cluster. Parameters ---------- ...
Selects the events with cluster of a given cluster size. Parameters ---------- event_number : numpy.array cluster_size : numpy.array condition : string Returns ------- numpy.array def get_events_with_cluster_size(event_number, cluster_size, condition='cluster_size==1'): '''Selects...
Selects the events with a certain error code. Parameters ---------- event_number : numpy.array event_status : numpy.array select_mask : int The mask that selects the event error code to check. condition : int The value the selected event error code should have. Returns ...
Takes the numpy meta data array and returns the different scan parameter settings and the name aligned in a dictionary Parameters ---------- meta_data_array : numpy.ndarray unique: boolean If true only unique values for each scan parameter are returned Returns ------- python.dict{s...
Takes the meta data array and returns the scan parameter values as a view of a numpy array only containing the parameter data . Parameters ---------- meta_data_array : numpy.ndarray The array with the scan parameters. scan_parameters : list of strings The name of the scan parameters to t...
Takes the scan parameter array and creates a scan parameter index labeling the unique scan parameter combinations. Parameters ---------- scan_parameter : numpy.ndarray The table with the scan parameters. Returns ------- numpy.Histogram def get_scan_parameters_index(scan_parameter): ...
Takes the numpy meta data array and returns the first rows with unique combinations of different scan parameter values for selected scan parameters. If selected columns only is true, the returned histogram only contains the selected columns. Parameters ---------- meta_data_array : numpy.ndarray ...
Takes the table with a event_number column and returns chunks with the size up to chunk_size. The chunks are chosen in a way that the events are not splitted. Additional parameters can be set to increase the readout speed. Events between a certain range can be selected. Also the start and the stop indices limit...
Takes the hit array and masks all pixels with a certain occupancy. Parameters ---------- hits : array like If dim > 2 the additional dimensions are summed up. min_cut_threshold : float A number to specify the minimum threshold, which pixel to take. Pixels are masked if occupancy...
Calculates a correction factor for single hit clusters at the given GDACs from the cluster_size_histogram via cubic interpolation. Parameters ---------- gdacs : array like The GDAC settings where the threshold should be determined from the calibration calibration_gdacs : array like GDAC...
Calculates the mean threshold from the threshold calibration at the given gdac settings. If the given gdac value was not used during caluibration the value is determined by interpolation. Parameters ---------- gdacs : array like The GDAC settings where the threshold should be determined from th...
Calculates the threshold for all pixels in threshold_calibration_array at the given GDAC settings via linear interpolation. The GDAC settings used during calibration have to be given. Parameters ---------- gdacs : array like The GDAC settings where the threshold should be determined from the calibr...
Calculates the number of cluster in every event. Parameters ---------- cluster_table : pytables.table Returns ------- numpy.Histogram def get_n_cluster_per_event_hist(cluster_table): '''Calculates the number of cluster in every event. Parameters ---------- cluster_table : pyt...
Quick and dirty function to give as redmine compatible iverview table def get_data_statistics(interpreted_files): '''Quick and dirty function to give as redmine compatible iverview table ''' print '\| File Name \| File Size \| Times Stamp \| Events \| Bad Events \| Measurement time \| # SR \| Hits ...
Finds contiguous True regions of the boolean array "condition". Returns a 2D array where the first column is the start index of the region and the second column is the end index. http://stackoverflow.com/questions/4494404/find-large-number-of-consecutive-values-fulfilling-condition-in-a-numpy-array def con...
Checking FEI4 raw data array for corrupted data. def check_bad_data(raw_data, prepend_data_headers=None, trig_count=None): """Checking FEI4 raw data array for corrupted data. """ consecutive_triggers = 16 if trig_count == 0 else trig_count is_fe_data_header = logical_and(is_fe_word, is_data_header) ...
Converts array into chunks with consecutive elements of given step size. http://stackoverflow.com/questions/7352684/how-to-find-the-groups-of-consecutive-elements-from-an-array-in-numpy def consecutive(data, stepsize=1): """Converts array into chunks with consecutive elements of given step size. http://sta...
Printing FEI4 data from raw data file for debugging. def print_raw_data_file(input_file, start_index=0, limit=200, flavor='fei4b', select=None, tdc_trig_dist=False, trigger_data_mode=0, meta_data_v2=True): """Printing FEI4 data from raw data file for debugging. """ with tb.open_file(input_file + '.h5', mod...
Printing FEI4 raw data array for debugging. def print_raw_data(raw_data, start_index=0, limit=200, flavor='fei4b', index_offset=0, select=None, tdc_trig_dist=False, trigger_data_mode=0): """Printing FEI4 raw data array for debugging. """ if not select: select = ['DH', 'TW', "AR", "VR", "SR", "DR", ...
Updates the widget to show the ETA or total time when finished. def update(self, pbar): 'Updates the widget to show the ETA or total time when finished.' self.n_refresh += 1 if pbar.currval == 0: return 'ETA: --:--:--' elif pbar.finished: return 'Time: %s' % sel...
Fit spline to the profile histogramed data, differentiate, determine MPV and plot. Parameters ---------- x_p, y_p : array like data points (x,y) y_p_e : array like error bars in y def plot_result(x_p, y_p, y_p_e, smoothed_data, smoothed_data_diff, filename=None): ''...
Generating HitOr calibration file (_calibration.h5) from raw data file and plotting of calibration data. Parameters ---------- output_filename : string Input raw data file name. plot_pixel_calibrations : bool, iterable If True, genearating additional pixel calibration plots. If l...
Interval timer decorator. Taken from: http://stackoverflow.com/questions/12435211/python-threading-timer-repeat-function-every-n-seconds/12435256 def interval_timed(interval): '''Interval timer decorator. Taken from: http://stackoverflow.com/questions/12435211/python-threading-timer-repeat-function-every...
Interval timer function. Taken from: http://stackoverflow.com/questions/22498038/improvement-on-interval-python/22498708 def interval_timer(interval, func, args, *kwargs): '''Interval timer function. Taken from: http://stackoverflow.com/questions/22498038/improvement-on-interval-python/22498708 '''...
Sends a run status mail with the traceback to a specified E-Mail address if a run crashes. def send_mail(subject, body, smtp_server, user, password, from_addr, to_addrs): ''' Sends a run status mail with the traceback to a specified E-Mail address if a run crashes. ''' logging.info('Send status E-Mail (' +...
Extracts the configuration of the modules. def _parse_module_cfgs(self): ''' Extracts the configuration of the modules. ''' # Adding here default run config parameters. if "dut" not in self._conf or self._conf["dut"] is None: raise ValueError('Parameter "dut" not defined.') ...
Sets the default parameters if they are not specified. def _set_default_cfg(self): ''' Sets the default parameters if they are not specified. ''' # adding special conf for accessing all DUT drivers self._module_cfgs[None] = { 'flavor': None, 'chip_address': None,...
Initialize all modules consecutively def init_modules(self): ''' Initialize all modules consecutively''' for module_id, module_cfg in self._module_cfgs.items(): if module_id in self._modules or module_id in self._tx_module_groups: if module_id in self._modules: ...
Start runs on all modules sequentially. Sets properties to access current module properties. def do_run(self): ''' Start runs on all modules sequentially. Sets properties to access current module properties. ''' if self.broadcast_commands: # Broadcast FE commands ...
Releasing hardware resources. def close(self): '''Releasing hardware resources. ''' try: self.dut.close() except Exception: logging.warning('Closing DUT was not successful') else: logging.debug('Closed DUT')
Handling of the data. Parameters ---------- data : list, tuple Data tuple of the format (data (np.array), last_time (float), curr_time (float), status (int)) def handle_data(self, data, new_file=False, flush=True): '''Handling of the data. Parameters ------...

override asyncio.Protocol def data_received(self, data): ''' override asyncio.Protocol ''' self._buffered_data.extend(data) while self._buffered_data: size = len(self._buffered_data) if self._data_package is None: if size < DataPackage.str...

override _SiriDBProtocol def connection_made(self, transport): ''' override _SiriDBProtocol ''' self.transport = transport self.remote_ip, self.port = transport.get_extra_info('peername')[:2] logging.debug( 'Connection made (address: {} port: {})' ...

Register a new SiriDB Server. This method is used by the SiriDB manage tool and should not be used otherwise. Full access rights are required for this request. def _register_server(self, server, timeout=30): '''Register a new SiriDB Server. This method is used by the SiriDB manage too...

Request a SiriDB configuration file. This method is used by the SiriDB manage tool and should not be used otherwise. Full access rights are required for this request. def _get_file(self, fn, timeout=30): '''Request a SiriDB configuration file. This method is used by the SiriDB manage ...

Convert GeoHash bits to a float. def _bits_to_float(bits, lower=-90.0, middle=0.0, upper=90.0): """Convert GeoHash bits to a float.""" for i in bits: if i: lower = middle else: upper = middle middle = (upper + lower) / 2 return middle

Convert a float to a list of GeoHash bits. def _float_to_bits(value, lower=-90.0, middle=0.0, upper=90.0, length=15): """Convert a float to a list of GeoHash bits.""" ret = [] for i in range(length): if value >= middle: lower = middle ret.append(1) else: upper = middle ret.append(...

Convert a GeoHash to a list of GeoHash bits. def _geohash_to_bits(value): """Convert a GeoHash to a list of GeoHash bits.""" b = map(BASE32MAP.get, value) ret = [] for i in b: out = [] for z in range(5): out.append(i & 0b1) i = i >> 1 ret += out[::-1] return ret

Convert a list of GeoHash bits to a GeoHash. def _bits_to_geohash(value): """Convert a list of GeoHash bits to a GeoHash.""" ret = [] # Get 5 bits at a time for i in (value[i:i+5] for i in xrange(0, len(value), 5)): # Convert binary to integer # Note: reverse here, the slice above doesn't work quite ri...

Decode a geohash. Returns a (lon,lat) pair. def decode(value): """Decode a geohash. Returns a (lon,lat) pair.""" assert value, "Invalid geohash: %s"%value # Get the GeoHash bits bits = _geohash_to_bits(value) # Unzip the GeoHash bits. lon = bits[0::2] lat = bits[1::2] # Convert to lat/lon return ( ...

Encode a (lon,lat) pair to a GeoHash. def encode(lonlat, length=12): """Encode a (lon,lat) pair to a GeoHash.""" assert len(lonlat) == 2, "Invalid lon/lat: %s"%lonlat # Half the length for each component. length /= 2 lon = _float_to_bits(lonlat[0], lower=-180.0, upper=180.0, length=length*5) lat = _float_t...

Return the adjacent geohash for a given direction. def adjacent(geohash, direction): """Return the adjacent geohash for a given direction.""" # Based on an MIT licensed implementation by Chris Veness from: # http://www.movable-type.co.uk/scripts/geohash.html assert direction in 'nsew', "Invalid direction: %s...

Return all neighboring geohashes. def neighbors(geohash): """Return all neighboring geohashes.""" return { 'n': adjacent(geohash, 'n'), 'ne': adjacent(adjacent(geohash, 'n'), 'e'), 'e': adjacent(geohash, 'e'), 'se': adjacent(adjacent(geohash, 's'), 'e'), 's': adjacent(geohash, 's'), 'sw'...

Make a function immediately return a function of no args which, when called, waits for the result, which will start being processed in another thread. Taken from https://wiki.python.org/moin/PythonDecoratorLibrary. def thunkify(thread_name=None, daemon=True, default_func=None): '''Make a function immediate...

Decorator function that sets Threading.Event() when keyboard interrupt (Ctrl+C) was raised Parameters ---------- _lambda : function Lambda function that points to Threading.Event() object Returns ------- wrapper : function Examples -------- @set_event_when_keyboard_interru...

Run name without whitespace def run_id(self): '''Run name without whitespace ''' s1 = re.sub('(.)([A-Z][a-z]+)', r'\1_\2', self.__class__.__name__) return re.sub('([a-z0-9])([A-Z])', r'\1_\2', s1).lower()

Configuration (namedtuple) def conf(self): '''Configuration (namedtuple) ''' conf = namedtuple('conf', field_names=self._conf.keys()) return conf(**self._conf)

Run configuration (namedtuple) def run_conf(self): '''Run configuration (namedtuple) ''' run_conf = namedtuple('run_conf', field_names=self._run_conf.keys()) return run_conf(**self._run_conf)

Default run configuration (namedtuple) def default_run_conf(self): '''Default run configuration (namedtuple) ''' default_run_conf = namedtuple('default_run_conf', field_names=self._default_run_conf.keys()) return default_run_conf(**self._default_run_conf)

Initialization before a new run. def _init(self, run_conf, run_number=None): '''Initialization before a new run. ''' self.stop_run.clear() self.abort_run.clear() self._run_status = run_status.running self._write_run_number(run_number) self._init_run_conf(run_conf...

Run given functions when a run is cancelled. def connect_cancel(self, functions): '''Run given functions when a run is cancelled. ''' self._cancel_functions = [] for func in functions: if isinstance(func, basestring) and hasattr(self, func) and callable(getattr(self, func)):...

Cancelling a run. def handle_cancel(self, **kwargs): '''Cancelling a run. ''' for func in self._cancel_functions: f_args = getargspec(func)[0] f_kwargs = {key: kwargs[key] for key in f_args if key in kwargs} func(**f_kwargs)

Stopping a run. Control for loops. Gentle stop/abort. This event should provide a more gentle abort. The run should stop ASAP but the run is still considered complete. def stop(self, msg=None): '''Stopping a run. Control for loops. Gentle stop/abort. This event should provide a more gentle ab...

Aborting a run. Control for loops. Immediate stop/abort. The implementation should stop a run ASAP when this event is set. The run is considered incomplete. def abort(self, msg=None): '''Aborting a run. Control for loops. Immediate stop/abort. The implementation should stop a run ASAP when th...

Runs a run in another thread. Non-blocking. Parameters ---------- run : class, object Run class or object. run_conf : str, dict, file Specific configuration for the run. use_thread : bool If True, run run in thread and returns blocking functio...

Runs runs from a primlist. Parameters ---------- primlist : string Filename of primlist. skip_remaining : bool If True, skip remaining runs, if a run does not exit with status FINISHED. Note ---- Primlist is a text file of the following f...

Determines the mean x and y beam spot position as a function of time. Therefore the data of a fixed number of read outs are combined ('combine_n_readouts'). The occupancy is determined for the given combined events and stored into a pdf file. At the end the beam x and y is plotted into a scatter plot with absolute ...

Determines the number of events as a function of time. Therefore the data of a fixed number of read outs are combined ('combine_n_readouts'). The number of events is taken from the meta data info and stored into a pdf file. Parameters ---------- scan_base: list of str scan base names (e.g.: ['...

Determines the number of cluster per event as a function of time. Therefore the data of a fixed number of read outs are combined ('combine_n_readouts'). Parameters ---------- scan_base: list of str scan base names (e.g.: ['//data//SCC_50_fei4_self_trigger_scan_390', ] include_no_cluster: bool ...

Takes a hit table and stores only selected hits into a new table. The selection is done on an event base and events are selected if they have a certain number of cluster or cluster size. To increase the analysis speed a event index for the input hit file is created first. Since a cluster hit table can be created to...

Takes a hit table and stores only selected hits into a new table. The selection of hits is done with a numexp string. Only if this expression evaluates to true the hit is taken. One can also select hits from cluster conditions. This selection is done on an event basis, meaning events are selected where the clus...

This method takes multiple hit files and determines the cluster size for different scan parameter values of Parameters ---------- input_files_hits: string output_file_cluster_size: string The data file with the results parameter: string The name of the parameter to separate the dat...

Reads in the cluster info table in chunks and histograms the seed pixels into one occupancy array. The 3rd dimension of the occupancy array is the number of different scan parameters used Parameters ---------- analyzed_data_file : string HDF5 filename of the file containing the cluster table. I...

Takes the hit table and analyzes the hits per scan parameter Parameters ---------- analyze_data : analysis.analyze_raw_data.AnalyzeRawData object with an opened hit file (AnalyzeRawData.out_file_h5) or a file name with the hit data given (AnalyzeRawData._analyzed_data_file) scan_parameters : list o...

Interprets raw data from Tektronix returns: lists of x, y values in seconds/volt def interpret_data_from_tektronix(preamble, data): ''' Interprets raw data from Tektronix returns: lists of x, y values in seconds/volt''' # Y mode ("WFMPRE:PT_FMT"): # Xn = XZEro + XINcr (n - PT_Off) # Yn = YZEro ...

Reading Chip S/N Note ---- Bits [MSB-LSB] | [15] | [14-6] | [5-0] Content | reserved | wafer number | chip number def read_chip_sn(self): '''Reading Chip S/N Note ---- Bits [MSB-LSB] | [15] | [14-6] | [5-0] Content | reserved | ...

The function reads the global register, interprets the data and returns the register value. Parameters ---------- name : register name overwrite_config : bool The read values overwrite the config in RAM if true. Returns ------- register value def read_global_register(sel...

The function reads the pixel register, interprets the data and returns a masked numpy arrays with the data for the chosen pixel register. Pixels without any data are masked. Parameters ---------- pix_regs : iterable, string List of pixel register to read (e.g. Enable, C_High, ...). ...

Get FEI4 status of module. If FEI4 is not ready, resetting service records is necessary to bring the FEI4 to a defined state. Returns ------- value : bool True if FEI4 is ready, False if the FEI4 was powered up recently and is not ready. def is_fe_ready(self): '''Get FEI4 status o...

Invert pixel mask (0->1, 1(and greater)->0). Parameters ---------- mask : array-like Mask. Returns ------- inverted_mask : array-like Inverted Mask. def invert_pixel_mask(mask): '''Invert pixel mask (0->1, 1(and greater)->0). Parameters ---------- ...

Generate pixel mask. Parameters ---------- steps : int Number of mask steps, e.g. steps=3 (every third pixel is enabled), steps=336 (one pixel per column), steps=672 (one pixel per double column). shift : int Shift mask by given value to the bottom (towards higher row numbers). F...

Generate mask from column and row lists Parameters ---------- column : iterable, int List of colums values. row : iterable, int List of row values. default : int Value of pixels that are not selected by the mask. value : int Value of pixels that are se...

Generate box shaped mask from column and row lists. Takes the minimum and maximum value from each list. Parameters ---------- column : iterable, int List of colums values. row : iterable, int List of row values. default : int Value of pixels that are not selected by...

Generate xtalk mask (row - 1, row + 1) from pixel mask. Parameters ---------- mask : ndarray Pixel mask. Returns ------- ndarray Xtalk mask. Example ------- Input: [[1 0 0 0 0 0 1 0 0 0 ... 0 0 0 0 1 0 0 0 0 0] [0 0 0 1 0 0 0 0 0 1 ... 0 1 ...

Generate chessboard/checkerboard mask. Parameters ---------- column_distance : int Column distance of the enabled pixels. row_distance : int Row distance of the enabled pixels. column_offset : int Additional column offset which shifts the columns by the given amount...

Implementation of the scan loops (mask shifting, loop over double columns, repeatedly sending any arbitrary command). Parameters ---------- command : BitVector (FEI4) command that will be sent out serially. repeat_command : int The number of repetitions command will be sent out e...

Resetting Service Records This will reset Service Record counters. This will also bring back alive some FE where the output FIFO is stuck (no data is coming out in run mode). This should be only issued after power up and in the case of a stuck FIFO, otherwise the BCID counter starts jumping. def re...

Resetting Bunch Counter def reset_bunch_counter(self): '''Resetting Bunch Counter ''' logging.info('Resetting Bunch Counter') commands = [] commands.extend(self.register.get_commands("RunMode")) commands.extend(self.register.get_commands("BCR")) self.send_...

Masking array elements when equal 0.0 or greater than 10 times the median Parameters ---------- hist : array_like Input data. Returns ------- masked array Returns copy of the array with masked elements. def generate_threshold_mask(hist): '''Masking array elements when equa...

Takes a numpy array and returns the array reduced to unique rows. If columns are defined only these columns are taken to define a unique row. The returned array can have all columns of the original array or only the columns defined in use_columns. Parameters ---------- array : numpy.ndarray use_colu...

Takes an array and calculates ranges [start, stop[. The last range end is none to keep the same length. Parameters ---------- arr : array like append_last: bool If True, append item with a pair of last array item and None. Returns ------- numpy.array The array formed by pai...

Does the same than np.in1d but uses the fact that ar1 and ar2 are sorted. Is therefore much faster. def in1d_sorted(ar1, ar2): """ Does the same than np.in1d but uses the fact that ar1 and ar2 are sorted. Is therefore much faster. """ if ar1.shape[0] == 0 or ar2.shape[0] == 0: # check for empty array...

Returns the dy/dx(x) via central difference method Parameters ---------- x : array like y : array like Returns ------- dy/dx : array like def central_difference(x, y): '''Returns the dy/dx(x) via central difference method Parameters ---------- x : array like y : array...

Takes 2D point data (x,y) and creates a profile histogram similar to the TProfile in ROOT. It calculates the y mean for every bin at the bin center and gives the y mean error as error bars. Parameters ---------- x : array like data x positions y : array like data y positions n_b...

Takes different hit files (hit_files), extracts the number of events or the scan time (reference) per scan parameter (parameter) and returns an array with a normalization factor. This normalization factor has the length of the number of different parameters. If a cluster_file is specified also the number of clu...

Takes a list of files, searches for the parameter name in the file name and returns a ordered dict with the file name in the first dimension and the corresponding parameter value in the second. The file names can be sorted by the parameter value, otherwise the order is kept. If unique is true every parameter is...

Generate a list of .h5 files which have a similar file name. Parameters ---------- scan_base : list, string List of string or string of the scan base names. The scan_base will be used to search for files containing the string. The .h5 file extension will be added automatically. filter : list, s...

Takes a list of files, searches for the parameter name in the file name and in the file. Returns a ordered dict with the file name in the first dimension and the corresponding parameter values in the second. If a scan parameter appears in the file name and in the file the first parameter setting has to be in th...

Checks if the parameter names of all files are similar. Takes the dictionary from get_parameter_from_files output as input. def check_parameter_similarity(files_dict): """ Checks if the parameter names of all files are similar. Takes the dictionary from get_parameter_from_files output as input. """ tr...

Takes the dict of hdf5 files and combines their meta data tables into one new numpy record array. Parameters ---------- meta_data_v2 : bool True for new (v2) meta data format, False for the old (v1) format. def combine_meta_data(files_dict, meta_data_v2=True): """ Takes the dict of hdf5 fi...

Returns the dy/dx(x) with the fit and differentiation of a spline curve Parameters ---------- x : array like y : array like Returns ------- dy/dx : array like def smooth_differentiation(x, y, weigths=None, order=5, smoothness=3, derivation=1): '''Returns the dy/dx(x) with the fit and ...

Takes two sorted arrays and return the intersection ar1 in ar2, ar2 in ar1. Parameters ---------- ar1 : (M,) array_like Input array. ar2 : array_like Input array. Returns ------- ar1, ar1 : ndarray, ndarray The intersection values. def reduce_sorted_to_intersect(a...

Returns the values that appear at least twice in array. Parameters ---------- array : array like Returns ------- numpy.array def get_not_unique_values(array): '''Returns the values that appear at least twice in array. Parameters ---------- array : array like Returns ...

Takes the analyzed meta_data table and returns the indices where the scan parameter changes Parameters ---------- meta_data_array : numpy.recordarray scan_parameter_name : string Returns ------- numpy.ndarray: first dimension: scan parameter value second dimension: index wh...

Selects the hits with condition. E.g.: condition = 'rel_BCID == 7 & event_number < 1000' Parameters ---------- hits_array : numpy.array condition : string A condition that is applied to the hits in numexpr. Only if the expression evaluates to True the hit is taken. Returns ------- ...

Selects the hits that occurred in events and optional selection criterion. If a event range can be defined use the get_data_in_event_range function. It is much faster. Parameters ---------- hits_array : numpy.array events : array assume_sorted : bool Is true if the events to select ...

Takes the hit table of a hdf5 file and returns hits in chunks for each unique combination of scan_parameters. Yields the hits in chunks, since they usually do not fit into memory. Parameters ---------- input_file_hits : pytable hdf5 file Has to include a hits node scan_parameters : iterable...

Selects the data (rows of a table) that occurred in the given event range [event_start, event_stop[ Parameters ---------- array : numpy.array event_start : int, None event_stop : int, None assume_sorted : bool Set to true if the hits are sorted by the event_number. Increases speed. ...

Selects the hits that occurred in events and writes them to a pytable. This function reduces the in RAM operations and has to be used if the get_hits_in_events function raises a memory error. Also a condition can be set to select hits. Parameters ---------- hit_table_in : pytable.table hit_table_ou...

Selects the hits that occurred in given event range [event_start, event_stop[ and write them to a pytable. This function reduces the in RAM operations and has to be used if the get_data_in_event_range function raises a memory error. Also a condition can be set to select hits. Parameters ---------- h...

Selects the events with a certain number of cluster. Parameters ---------- event_number : numpy.array Returns ------- numpy.array def get_events_with_n_cluster(event_number, condition='n_cluster==1'): '''Selects the events with a certain number of cluster. Parameters ---------- ...

Selects the events with cluster of a given cluster size. Parameters ---------- event_number : numpy.array cluster_size : numpy.array condition : string Returns ------- numpy.array def get_events_with_cluster_size(event_number, cluster_size, condition='cluster_size==1'): '''Selects...

Selects the events with a certain error code. Parameters ---------- event_number : numpy.array event_status : numpy.array select_mask : int The mask that selects the event error code to check. condition : int The value the selected event error code should have. Returns ...

Takes the numpy meta data array and returns the different scan parameter settings and the name aligned in a dictionary Parameters ---------- meta_data_array : numpy.ndarray unique: boolean If true only unique values for each scan parameter are returned Returns ------- python.dict{s...

Takes the meta data array and returns the scan parameter values as a view of a numpy array only containing the parameter data . Parameters ---------- meta_data_array : numpy.ndarray The array with the scan parameters. scan_parameters : list of strings The name of the scan parameters to t...

Takes the scan parameter array and creates a scan parameter index labeling the unique scan parameter combinations. Parameters ---------- scan_parameter : numpy.ndarray The table with the scan parameters. Returns ------- numpy.Histogram def get_scan_parameters_index(scan_parameter): ...

Takes the numpy meta data array and returns the first rows with unique combinations of different scan parameter values for selected scan parameters. If selected columns only is true, the returned histogram only contains the selected columns. Parameters ---------- meta_data_array : numpy.ndarray ...

Takes the table with a event_number column and returns chunks with the size up to chunk_size. The chunks are chosen in a way that the events are not splitted. Additional parameters can be set to increase the readout speed. Events between a certain range can be selected. Also the start and the stop indices limit...

Takes the hit array and masks all pixels with a certain occupancy. Parameters ---------- hits : array like If dim > 2 the additional dimensions are summed up. min_cut_threshold : float A number to specify the minimum threshold, which pixel to take. Pixels are masked if occupancy...

Calculates a correction factor for single hit clusters at the given GDACs from the cluster_size_histogram via cubic interpolation. Parameters ---------- gdacs : array like The GDAC settings where the threshold should be determined from the calibration calibration_gdacs : array like GDAC...

Calculates the mean threshold from the threshold calibration at the given gdac settings. If the given gdac value was not used during caluibration the value is determined by interpolation. Parameters ---------- gdacs : array like The GDAC settings where the threshold should be determined from th...

Calculates the threshold for all pixels in threshold_calibration_array at the given GDAC settings via linear interpolation. The GDAC settings used during calibration have to be given. Parameters ---------- gdacs : array like The GDAC settings where the threshold should be determined from the calibr...

Calculates the number of cluster in every event. Parameters ---------- cluster_table : pytables.table Returns ------- numpy.Histogram def get_n_cluster_per_event_hist(cluster_table): '''Calculates the number of cluster in every event. Parameters ---------- cluster_table : pyt...

Finds contiguous True regions of the boolean array "condition". Returns a 2D array where the first column is the start index of the region and the second column is the end index. http://stackoverflow.com/questions/4494404/find-large-number-of-consecutive-values-fulfilling-condition-in-a-numpy-array def con...

Checking FEI4 raw data array for corrupted data. def check_bad_data(raw_data, prepend_data_headers=None, trig_count=None): """Checking FEI4 raw data array for corrupted data. """ consecutive_triggers = 16 if trig_count == 0 else trig_count is_fe_data_header = logical_and(is_fe_word, is_data_header) ...

Converts array into chunks with consecutive elements of given step size. http://stackoverflow.com/questions/7352684/how-to-find-the-groups-of-consecutive-elements-from-an-array-in-numpy def consecutive(data, stepsize=1): """Converts array into chunks with consecutive elements of given step size. http://sta...

Printing FEI4 data from raw data file for debugging. def print_raw_data_file(input_file, start_index=0, limit=200, flavor='fei4b', select=None, tdc_trig_dist=False, trigger_data_mode=0, meta_data_v2=True): """Printing FEI4 data from raw data file for debugging. """ with tb.open_file(input_file + '.h5', mod...

Printing FEI4 raw data array for debugging. def print_raw_data(raw_data, start_index=0, limit=200, flavor='fei4b', index_offset=0, select=None, tdc_trig_dist=False, trigger_data_mode=0): """Printing FEI4 raw data array for debugging. """ if not select: select = ['DH', 'TW', "AR", "VR", "SR", "DR", ...

Updates the widget to show the ETA or total time when finished. def update(self, pbar): 'Updates the widget to show the ETA or total time when finished.' self.n_refresh += 1 if pbar.currval == 0: return 'ETA: --:--:--' elif pbar.finished: return 'Time: %s' % sel...

Fit spline to the profile histogramed data, differentiate, determine MPV and plot. Parameters ---------- x_p, y_p : array like data points (x,y) y_p_e : array like error bars in y def plot_result(x_p, y_p, y_p_e, smoothed_data, smoothed_data_diff, filename=None): ''...

Generating HitOr calibration file (_calibration.h5) from raw data file and plotting of calibration data. Parameters ---------- output_filename : string Input raw data file name. plot_pixel_calibrations : bool, iterable If True, genearating additional pixel calibration plots. If l...

Interval timer decorator. Taken from: http://stackoverflow.com/questions/12435211/python-threading-timer-repeat-function-every-n-seconds/12435256 def interval_timed(interval): '''Interval timer decorator. Taken from: http://stackoverflow.com/questions/12435211/python-threading-timer-repeat-function-every...

Interval timer function. Taken from: http://stackoverflow.com/questions/22498038/improvement-on-interval-python/22498708 def interval_timer(interval, func, *args, **kwargs): '''Interval timer function. Taken from: http://stackoverflow.com/questions/22498038/improvement-on-interval-python/22498708 '''...

Sends a run status mail with the traceback to a specified E-Mail address if a run crashes. def send_mail(subject, body, smtp_server, user, password, from_addr, to_addrs): ''' Sends a run status mail with the traceback to a specified E-Mail address if a run crashes. ''' logging.info('Send status E-Mail (' +...

Extracts the configuration of the modules. def _parse_module_cfgs(self): ''' Extracts the configuration of the modules. ''' # Adding here default run config parameters. if "dut" not in self._conf or self._conf["dut"] is None: raise ValueError('Parameter "dut" not defined.') ...

Sets the default parameters if they are not specified. def _set_default_cfg(self): ''' Sets the default parameters if they are not specified. ''' # adding special conf for accessing all DUT drivers self._module_cfgs[None] = { 'flavor': None, 'chip_address': None,...

Initialize all modules consecutively def init_modules(self): ''' Initialize all modules consecutively''' for module_id, module_cfg in self._module_cfgs.items(): if module_id in self._modules or module_id in self._tx_module_groups: if module_id in self._modules: ...

Start runs on all modules sequentially. Sets properties to access current module properties. def do_run(self): ''' Start runs on all modules sequentially. Sets properties to access current module properties. ''' if self.broadcast_commands: # Broadcast FE commands ...

Releasing hardware resources. def close(self): '''Releasing hardware resources. ''' try: self.dut.close() except Exception: logging.warning('Closing DUT was not successful') else: logging.debug('Closed DUT')

Handling of the data. Parameters ---------- data : list, tuple Data tuple of the format (data (np.array), last_time (float), curr_time (float), status (int)) def handle_data(self, data, new_file=False, flush=True): '''Handling of the data. Parameters ------...