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values | func_name stringlengths 1 134 | docstring stringlengths 1 46.9k | path stringlengths 4 223 | original_string stringlengths 75 104k | code stringlengths 75 104k | docstring_tokens listlengths 1 1.97k | repo stringlengths 7 55 | language stringclasses 1
value | url stringlengths 87 315 | code_tokens listlengths 19 28.4k | sha stringlengths 40 40 |
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train | hist_last_nonzero | Find the last nonzero index and mask the remaining entries.
Parameters
----------
hist : array_like, iterable
Input histogram with dimension at most 1.
return_index : bool, optional
If true, return the index.
copy : bool, optional
Whether to copy the input data (Tru... | pybar/analysis/plotting/plotting.py | def hist_last_nonzero(hist, return_index=False, copy=True):
'''Find the last nonzero index and mask the remaining entries.
Parameters
----------
hist : array_like, iterable
Input histogram with dimension at most 1.
return_index : bool, optional
If true, return the index.
... | def hist_last_nonzero(hist, return_index=False, copy=True):
'''Find the last nonzero index and mask the remaining entries.
Parameters
----------
hist : array_like, iterable
Input histogram with dimension at most 1.
return_index : bool, optional
If true, return the index.
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train | FifoReadout.readout | Readout thread continuously reading FIFO.
Readout thread, which uses read_raw_data_from_fifo() and appends data to self._fifo_data_deque (collection.deque). | pybar/daq/fifo_readout.py | def readout(self, fifo, no_data_timeout=None):
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time_last... | def readout(self, fifo, no_data_timeout=None):
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train | FifoReadout.worker | Worker thread continuously filtering and converting data when data becomes available. | pybar/daq/fifo_readout.py | def worker(self, fifo):
'''Worker thread continuously filtering and converting data when data becomes available.
'''
logging.debug('Starting worker thread for %s', fifo)
self._fifo_conditions[fifo].acquire()
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'''Worker thread continuously filtering and converting data when data becomes available.
'''
logging.debug('Starting worker thread for %s', fifo)
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train | FifoReadout.writer | Writer thread continuously calling callback function for writing data when data becomes available. | pybar/daq/fifo_readout.py | def writer(self, index, no_data_timeout=None):
'''Writer thread continuously calling callback function for writing data when data becomes available.
'''
is_fe_data_header = logical_and(is_fe_word, is_data_header)
logging.debug('Starting writer thread with index %d', index)
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'''Writer thread continuously calling callback function for writing data when data becomes available.
'''
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train | FifoReadout.get_data_from_buffer | Reads local data buffer and returns data and meta data list.
Returns
-------
data : list
List of data and meta data dicts. | pybar/daq/fifo_readout.py | def get_data_from_buffer(self, filter_func=None, converter_func=None):
'''Reads local data buffer and returns data and meta data list.
Returns
-------
data : list
List of data and meta data dicts.
'''
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'''Reads local data buffer and returns data and meta data list.
Returns
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data : list
List of data and meta data dicts.
'''
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train | FifoReadout.get_raw_data_from_buffer | Reads local data buffer and returns raw data array.
Returns
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data : np.array
An array containing data words from the local data buffer. | pybar/daq/fifo_readout.py | def get_raw_data_from_buffer(self, filter_func=None, converter_func=None):
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data : np.array
An array containing data words from the local data buffer.
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train | FifoReadout.read_raw_data_from_fifo | Reads FIFO data and returns raw data array.
Returns
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data : np.array
An array containing FIFO data words. | pybar/daq/fifo_readout.py | def read_raw_data_from_fifo(self, fifo, filter_func=None, converter_func=None):
'''Reads FIFO data and returns raw data array.
Returns
-------
data : np.array
An array containing FIFO data words.
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return convert_data_array(self.dut[fifo].get_data()... | def read_raw_data_from_fifo(self, fifo, filter_func=None, converter_func=None):
'''Reads FIFO data and returns raw data array.
Returns
-------
data : np.array
An array containing FIFO data words.
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train | get_item_from_queue | Attempts to retrieve an item from the queue Q. If Q is
empty, None is returned.
Blocks for 'timeout' seconds in case the queue is empty,
so don't use this method for speedy retrieval of multiple
items (use get_all_from_queue for that). | pybar/utils/utils.py | def get_item_from_queue(Q, timeout=0.01):
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""" Attempts to retrieve an item from the queue Q. If Q is
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train | argmin_list | Return a list of elements of seq[i] with the lowest
func(seq[i]) scores.
>>> argmin_list(['one', 'to', 'three', 'or'], len)
['to', 'or'] | pybar/utils/utils.py | def argmin_list(seq, func):
""" Return a list of elements of seq[i] with the lowest
func(seq[i]) scores.
>>> argmin_list(['one', 'to', 'three', 'or'], len)
['to', 'or']
"""
best_score, best = func(seq[0]), []
for x in seq:
x_score = func(x)
if x_score < b... | def argmin_list(seq, func):
""" Return a list of elements of seq[i] with the lowest
func(seq[i]) scores.
>>> argmin_list(['one', 'to', 'three', 'or'], len)
['to', 'or']
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train | flatten_iterable | flatten iterable, but leaves out strings
[[[1, 2, 3], [4, 5]], 6] -> [1, 2, 3, 4, 5, 6] | pybar/utils/utils.py | def flatten_iterable(iterable):
"""flatten iterable, but leaves out strings
[[[1, 2, 3], [4, 5]], 6] -> [1, 2, 3, 4, 5, 6]
"""
for item in iterable:
if isinstance(item, collections.Iterable) and not isinstance(item, basestring):
for sub in flatten_iterable(item):
... | def flatten_iterable(iterable):
"""flatten iterable, but leaves out strings
[[[1, 2, 3], [4, 5]], 6] -> [1, 2, 3, 4, 5, 6]
"""
for item in iterable:
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train | iterable | generate iterable from item, but leaves out strings | pybar/utils/utils.py | def iterable(item):
"""generate iterable from item, but leaves out strings
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if isinstance(item, collections.Iterable) and not isinstance(item, basestring):
return item
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return [item] | def iterable(item):
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train | natsorted | Returns a copy of seq, sorted by natural string sort. | pybar/utils/utils.py | def natsorted(seq, cmp=natcmp):
"Returns a copy of seq, sorted by natural string sort."
import copy
temp = copy.copy(seq)
natsort(temp, cmp)
return temp | def natsorted(seq, cmp=natcmp):
"Returns a copy of seq, sorted by natural string sort."
import copy
temp = copy.copy(seq)
natsort(temp, cmp)
return temp | [
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train | get_iso_time | returns time as ISO string, mapping to and from datetime in ugly way
convert to string with str() | pybar/utils/utils.py | def get_iso_time():
'''returns time as ISO string, mapping to and from datetime in ugly way
convert to string with str()
'''
t1 = time.time()
t2 = datetime.datetime.fromtimestamp(t1)
t4 = t2.__str__()
try:
t4a, t4b = t4.split(".", 1)
except ValueError:
t4a = t... | def get_iso_time():
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t2 = datetime.datetime.fromtimestamp(t1)
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train | get_float_time | returns time as double precision floats - Time64 in pytables - mapping to and from python datetime's | pybar/utils/utils.py | def get_float_time():
'''returns time as double precision floats - Time64 in pytables - mapping to and from python datetime's
'''
t1 = time.time()
t2 = datetime.datetime.fromtimestamp(t1)
return time.mktime(t2.timetuple()) + 1e-6 * t2.microsecond | def get_float_time():
'''returns time as double precision floats - Time64 in pytables - mapping to and from python datetime's
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t1 = time.time()
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return time.mktime(t2.timetuple()) + 1e-6 * t2.microsecond | [
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train | groupby_dict | Group dict of dicts by key. | pybar/utils/utils.py | def groupby_dict(dictionary, key):
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train | zip_nofill | Zipping iterables without fillvalue.
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Note: https://stackoverflow.com/questions/38054593/zip-longest-without-fillvalue
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train | find_file_dir_up | Finding file in directory upwards. | pybar/utils/utils.py | def find_file_dir_up(filename, path=None, n=None):
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train | load_configuration_from_text_file | Loading configuration from text files to register object
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configuration_file : string
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register : pybar.fei4.register object
configuration_file : string
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train | load_configuration_from_hdf5 | Loading configuration from HDF5 file to register object
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Filename of the HDF5 configuration file or file object.
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train | save_configuration_to_text_file | Saving configuration to text files from register object
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register : pybar.fei4.register object
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Filename of the configuration file.
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register : pybar.fei4.register object
configuration_file : string
Filename of the configuration file.
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train | save_configuration_to_hdf5 | Saving configuration to HDF5 file from register object
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configuration_file : string, file
Filename of the HDF5 configuration file or file object.
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Parameters
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register : pybar.fei4.register object
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Filename of the HDF5 configuration file or file object.
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register : pybar.fei4.register object
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Filename of the HDF5 configuration file or file object.
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train | FEI4Register.load_configuration | Loading configuration
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configuration_file : string
Path to the configuration file (text or HDF5 file).
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train | FEI4Register.save_configuration | Saving configuration
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train | FEI4Register.get_commands | get fe_command from command name and keyword arguments
wrapper for build_commands()
implements FEI4 specific behavior | pybar/fei4/register.py | def get_commands(self, command_name, **kwargs):
"""get fe_command from command name and keyword arguments
wrapper for build_commands()
implements FEI4 specific behavior
"""
chip_id = kwargs.pop("ChipID", self.chip_id_bitarray)
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train | FEI4Register.build_command | build command from command_name and keyword values
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command_bitvector : list
List of bitarrays.
Usage
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Receives: command name as defined inside xml file, key-value-pairs as defined inside bit stream filed for each command | pybar/fei4/register.py | def build_command(self, command_name, **kwargs):
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train | FEI4Register.get_global_register_attributes | Calculating register numbers from register names.
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Receives: attribute name to be returned, dictionaries (kwargs) of register attributes and values for making cuts
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train | FEI4Register.get_global_register_objects | Generate register objects (list) from register name list
Usage: get_global_register_objects(name = ["Amp2Vbn", "GateHitOr", "DisableColumnCnfg"], address = [2, 3])
Receives: keyword lists of register names, addresses,... for making cuts
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train | FEI4Register.get_global_register_bitsets | Calculating register bitsets from register addresses.
Usage: get_global_register_bitsets([regaddress_1, regaddress_2, ...])
Receives: list of register addresses
Returns: list of register bitsets | pybar/fei4/register.py | def get_global_register_bitsets(self, register_addresses): # TOTO: add sorting
"""Calculating register bitsets from register addresses.
Usage: get_global_register_bitsets([regaddress_1, regaddress_2, ...])
Receives: list of register addresses
Returns: list of register bitsets
... | def get_global_register_bitsets(self, register_addresses): # TOTO: add sorting
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Usage: get_global_register_bitsets([regaddress_1, regaddress_2, ...])
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train | FEI4Register.get_pixel_register_objects | Generate register objects (list) from register name list
Usage: get_pixel_register_objects(name = ["TDAC", "FDAC"])
Receives: keyword lists of register names, addresses,...
Returns: list of register objects | pybar/fei4/register.py | def get_pixel_register_objects(self, do_sort=None, reverse=False, **kwargs):
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Usage: get_pixel_register_objects(name = ["TDAC", "FDAC"])
Receives: keyword lists of register names, addresses,...
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Usage: get_pixel_register_objects(name = ["TDAC", "FDAC"])
Receives: keyword lists of register names, addresses,...
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train | FEI4Register.get_pixel_register_bitset | Calculating pixel register bitsets from pixel register addresses.
Usage: get_pixel_register_bitset(object, bit_number, double_column_number)
Receives: register object, bit number, double column number
Returns: double column bitset | pybar/fei4/register.py | def get_pixel_register_bitset(self, register_object, bit_no, dc_no):
"""Calculating pixel register bitsets from pixel register addresses.
Usage: get_pixel_register_bitset(object, bit_number, double_column_number)
Receives: register object, bit number, double column number
Returns: ... | def get_pixel_register_bitset(self, register_object, bit_no, dc_no):
"""Calculating pixel register bitsets from pixel register addresses.
Usage: get_pixel_register_bitset(object, bit_number, double_column_number)
Receives: register object, bit number, double column number
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train | FEI4Register.create_restore_point | Creating a configuration restore point.
Parameters
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'''Creating a configuration restore point.
Parameters
----------
name : str
Name of the restore point. If not given, a md5 hash will be generated.
'''
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'''Creating a configuration restore point.
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name : str
Name of the restore point. If not given, a md5 hash will be generated.
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train | FEI4Register.restore | Restoring a configuration restore point.
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Name of the restore point. If not given, a md5 hash will be generated.
keep : bool
Keeping restore point for later use.
last : bool
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Parameters
----------
name : str
Name of the restore point. If not given, a md5 hash will be generated.
keep : bool
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Parameters
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name : str
Name of the restore point. If not given, a md5 hash will be generated.
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train | FEI4Register.clear_restore_points | Deleting all/a configuration restore points/point.
Parameters
----------
name : str
Name of the restore point to be deleted. If not given, all restore points will be deleted. | pybar/fei4/register.py | def clear_restore_points(self, name=None):
'''Deleting all/a configuration restore points/point.
Parameters
----------
name : str
Name of the restore point to be deleted. If not given, all restore points will be deleted.
'''
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... | def clear_restore_points(self, name=None):
'''Deleting all/a configuration restore points/point.
Parameters
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name : str
Name of the restore point to be deleted. If not given, all restore points will be deleted.
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train | save_configuration_dict | Stores any configuration dictionary to HDF5 file.
Parameters
----------
h5_file : string, file
Filename of the HDF5 configuration file or file object.
configuation_name : str
Configuration name. Will be used for table name.
configuration : dict
Configuration diction... | pybar/daq/readout_utils.py | def save_configuration_dict(h5_file, configuation_name, configuration, **kwargs):
'''Stores any configuration dictionary to HDF5 file.
Parameters
----------
h5_file : string, file
Filename of the HDF5 configuration file or file object.
configuation_name : str
Configuration n... | def save_configuration_dict(h5_file, configuation_name, configuration, **kwargs):
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Parameters
----------
h5_file : string, file
Filename of the HDF5 configuration file or file object.
configuation_name : str
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train | convert_data_array | Filter and convert raw data numpy array (numpy.ndarray).
Parameters
----------
array : numpy.array
Raw data array.
filter_func : function
Function that takes array and returns true or false for each item in array.
converter_func : function
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Parameters
----------
array : numpy.array
Raw data array.
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Raw data array.
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train | convert_data_iterable | Convert raw data in data iterable.
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data_iterable : iterable
Iterable where each element is a tuple with following content: (raw data, timestamp_start, timestamp_stop, status).
filter_func : function
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data_iterable : iterable
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train | data_array_from_data_iterable | Convert data iterable to raw data numpy array.
Parameters
----------
data_iterable : iterable
Iterable where each element is a tuple with following content: (raw data, timestamp_start, timestamp_stop, status).
Returns
-------
data_array : numpy.array
concatenated data... | pybar/daq/readout_utils.py | def data_array_from_data_iterable(data_iterable):
'''Convert data iterable to raw data numpy array.
Parameters
----------
data_iterable : iterable
Iterable where each element is a tuple with following content: (raw data, timestamp_start, timestamp_stop, status).
Returns
------... | def data_array_from_data_iterable(data_iterable):
'''Convert data iterable to raw data numpy array.
Parameters
----------
data_iterable : iterable
Iterable where each element is a tuple with following content: (raw data, timestamp_start, timestamp_stop, status).
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train | convert_tdc_to_channel | Converts TDC words at a given channel to common TDC header (0x4). | pybar/daq/readout_utils.py | def convert_tdc_to_channel(channel):
''' Converts TDC words at a given channel to common TDC header (0x4).
'''
def f(value):
filter_func = logical_and(is_tdc_word, is_tdc_from_channel(channel))
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value[select] = np.bitwise_and(value[select], 0x0FFFFFFF... | def convert_tdc_to_channel(channel):
''' Converts TDC words at a given channel to common TDC header (0x4).
'''
def f(value):
filter_func = logical_and(is_tdc_word, is_tdc_from_channel(channel))
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train | is_data_from_channel | Selecting FE data from given channel.
Parameters
----------
channel : int
Channel number (4 is default channel on Single Chip Card).
Returns
-------
Function.
Usage:
1 Selecting FE data from channel 4 (combine with is_fe_word):
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'''Selecting FE data from given channel.
Parameters
----------
channel : int
Channel number (4 is default channel on Single Chip Card).
Returns
-------
Function.
Usage:
1 Selecting FE data from channel 4... | def is_data_from_channel(channel=4): # function factory
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Parameters
----------
channel : int
Channel number (4 is default channel on Single Chip Card).
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train | logical_and | Logical and from functions.
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f1, f2 : function
Function that takes array and returns true or false for each item in array.
Returns
-------
Function.
Usage:
filter_func=logical_and(is_data_record, is_data_from_channel(4)) # new filter function
... | pybar/daq/readout_utils.py | def logical_and(f1, f2): # function factory
'''Logical and from functions.
Parameters
----------
f1, f2 : function
Function that takes array and returns true or false for each item in array.
Returns
-------
Function.
Usage:
filter_func=logical_and(is_data_rec... | def logical_and(f1, f2): # function factory
'''Logical and from functions.
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f1, f2 : function
Function that takes array and returns true or false for each item in array.
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Function.
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train | logical_or | Logical or from functions.
Parameters
----------
f1, f2 : function
Function that takes array and returns true or false for each item in array.
Returns
-------
Function. | pybar/daq/readout_utils.py | def logical_or(f1, f2): # function factory
'''Logical or from functions.
Parameters
----------
f1, f2 : function
Function that takes array and returns true or false for each item in array.
Returns
-------
Function.
'''
def f(value):
return np.logical_o... | def logical_or(f1, f2): # function factory
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Parameters
----------
f1, f2 : function
Function that takes array and returns true or false for each item in array.
Returns
-------
Function.
'''
def f(value):
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train | logical_not | Logical not from functions.
Parameters
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f1, f2 : function
Function that takes array and returns true or false for each item in array.
Returns
-------
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'''Logical not from functions.
Parameters
----------
f1, f2 : function
Function that takes array and returns true or false for each item in array.
Returns
-------
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f1, f2 : function
Function that takes array and returns true or false for each item in array.
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train | logical_xor | Logical xor from functions.
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f1, f2 : function
Function that takes array and returns true or false for each item in array.
Returns
-------
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f1, f2 : function
Function that takes array and returns true or false for each item in array.
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train | get_trigger_data | Returns 31bit trigger counter (mode=0), 31bit timestamp (mode=1), 15bit timestamp and 16bit trigger counter (mode=2) | pybar/daq/readout_utils.py | def get_trigger_data(value, mode=0):
'''Returns 31bit trigger counter (mode=0), 31bit timestamp (mode=1), 15bit timestamp and 16bit trigger counter (mode=2)
'''
if mode == 2:
return np.right_shift(np.bitwise_and(value, 0x7FFF0000), 16), np.bitwise_and(value, 0x0000FFFF)
else:
retur... | def get_trigger_data(value, mode=0):
'''Returns 31bit trigger counter (mode=0), 31bit timestamp (mode=1), 15bit timestamp and 16bit trigger counter (mode=2)
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return np.right_shift(np.bitwise_and(value, 0x7FFF0000), 16), np.bitwise_and(value, 0x0000FFFF)
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train | get_col_row_tot_array_from_data_record_array | Convert raw data array to column, row, and ToT array.
Parameters
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array : numpy.array
Raw data array.
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-------
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Parameters
----------
array : numpy.array
Raw data array.
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-------
Tuple of arrays.
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def get_col_row_tot_1_array_from_dat... | def get_col_row_tot_array_from_data_record_array(array): # TODO: max ToT
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train | interpret_pixel_data | Takes the pixel raw data and interprets them. This includes consistency checks and pixel/data matching.
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Parameters
----------
data : numpy.ndarray
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... | pybar/daq/readout_utils.py | def interpret_pixel_data(data, dc, pixel_array, invert=True):
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The data has to come from one double column only but can have more than one pixel bit (e.g. TDAC = 5 bit).
Parameters
----------
... | def interpret_pixel_data(data, dc, pixel_array, invert=True):
'''Takes the pixel raw data and interprets them. This includes consistency checks and pixel/data matching.
The data has to come from one double column only but can have more than one pixel bit (e.g. TDAC = 5 bit).
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train | AnalyzeRawData.set_standard_settings | Set all settings to their standard values. | pybar/analysis/analyze_raw_data.py | def set_standard_settings(self):
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train | AnalyzeRawData.trig_count | Set the numbers of BCIDs (usually 16) of one event. | pybar/analysis/analyze_raw_data.py | def trig_count(self, value):
"""Set the numbers of BCIDs (usually 16) of one event."""
self._trig_count = 16 if value == 0 else value
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train | AnalyzeRawData.max_tot_value | Set maximum ToT value that is considered to be a hit | pybar/analysis/analyze_raw_data.py | def max_tot_value(self, value):
"""Set maximum ToT value that is considered to be a hit"""
self._max_tot_value = value
self.interpreter.set_max_tot(self._max_tot_value)
self.histogram.set_max_tot(self._max_tot_value)
self.clusterizer.set_max_hit_charge(self._max_tot_value) | def max_tot_value(self, value):
"""Set maximum ToT value that is considered to be a hit"""
self._max_tot_value = value
self.interpreter.set_max_tot(self._max_tot_value)
self.histogram.set_max_tot(self._max_tot_value)
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train | AnalyzeRawData.interpret_word_table | Interprets the raw data word table of all given raw data files with the c++ library.
Creates the h5 output file and PDF plots.
Parameters
----------
analyzed_data_file : string
The file name of the output analyzed data file. If None, the output analyzed data file
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'''Interprets the raw data word table of all given raw data files with the c++ library.
Creates the h5 output file and PDF plots.
Parameters
----------
analyzed_data_file : string
... | def interpret_word_table(self, analyzed_data_file=None, use_settings_from_file=True, fei4b=None):
'''Interprets the raw data word table of all given raw data files with the c++ library.
Creates the h5 output file and PDF plots.
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analyzed_data_file : string
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train | AnalyzeRawData.analyze_hit_table | Analyzes a hit table with the c++ histogrammming/clusterizer.
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----------
analyzed_data_file : string
The filename of the analyzed data file. If None, the analyzed data file
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Filename extension (.h5) does not... | pybar/analysis/analyze_raw_data.py | def analyze_hit_table(self, analyzed_data_file=None, analyzed_data_out_file=None):
'''Analyzes a hit table with the c++ histogrammming/clusterizer.
Parameters
----------
analyzed_data_file : string
The filename of the analyzed data file. If None, the analyzed data file
... | def analyze_hit_table(self, analyzed_data_file=None, analyzed_data_out_file=None):
'''Analyzes a hit table with the c++ histogrammming/clusterizer.
Parameters
----------
analyzed_data_file : string
The filename of the analyzed data file. If None, the analyzed data file
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train | AnalyzeRawData._deduce_settings_from_file | Tries to get the scan parameters needed for analysis from the raw data file | pybar/analysis/analyze_raw_data.py | def _deduce_settings_from_file(self, opened_raw_data_file): # TODO: parse better
'''Tries to get the scan parameters needed for analysis from the raw data file
'''
try: # take infos raw data files (not avalable in old files)
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train | AnalyzeRawData._get_plsr_dac_charge | Takes the PlsrDAC calibration and the stored C-high/C-low mask to calculate the charge from the PlsrDAC array on a pixel basis | pybar/analysis/analyze_raw_data.py | def _get_plsr_dac_charge(self, plsr_dac_array, no_offset=False):
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'''
charge = np.zeros_like(self.c_low_mask, dtype=np.float16) # charge in electrons
if self.... | def _get_plsr_dac_charge(self, plsr_dac_array, no_offset=False):
'''Takes the PlsrDAC calibration and the stored C-high/C-low mask to calculate the charge from the PlsrDAC array on a pixel basis
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charge = np.zeros_like(self.c_low_mask, dtype=np.float16) # charge in electrons
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train | DocManager._parse_fields | If Schema access, parse fields and build respective lists | mongo_connector/doc_managers/solr_doc_manager.py | def _parse_fields(self, result, field_name):
""" If Schema access, parse fields and build respective lists
"""
field_list = []
for key, value in result.get('schema', {}).get(field_name, {}).items():
if key not in field_list:
field_list.append(key)
retu... | def _parse_fields(self, result, field_name):
""" If Schema access, parse fields and build respective lists
"""
field_list = []
for key, value in result.get('schema', {}).get(field_name, {}).items():
if key not in field_list:
field_list.append(key)
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train | DocManager._build_fields | Builds a list of valid fields | mongo_connector/doc_managers/solr_doc_manager.py | def _build_fields(self):
""" Builds a list of valid fields
"""
declared_fields = self.solr._send_request('get', ADMIN_URL)
result = decoder.decode(declared_fields)
self.field_list = self._parse_fields(result, 'fields')
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""" Builds a list of valid fields
"""
declared_fields = self.solr._send_request('get', ADMIN_URL)
result = decoder.decode(declared_fields)
self.field_list = self._parse_fields(result, 'fields')
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train | DocManager._clean_doc | Reformats the given document before insertion into Solr.
This method reformats the document in the following ways:
- removes extraneous fields that aren't defined in schema.xml
- unwinds arrays in order to find and later flatten sub-documents
- flattens the document so that there ... | mongo_connector/doc_managers/solr_doc_manager.py | def _clean_doc(self, doc, namespace, timestamp):
"""Reformats the given document before insertion into Solr.
This method reformats the document in the following ways:
- removes extraneous fields that aren't defined in schema.xml
- unwinds arrays in order to find and later flatten su... | def _clean_doc(self, doc, namespace, timestamp):
"""Reformats the given document before insertion into Solr.
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train | DocManager.apply_update | Override DocManagerBase.apply_update to have flat documents. | mongo_connector/doc_managers/solr_doc_manager.py | def apply_update(self, doc, update_spec):
"""Override DocManagerBase.apply_update to have flat documents."""
# Replace a whole document
if not '$set' in update_spec and not '$unset' in update_spec:
# update_spec contains the new document.
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train | DocManager.update | Apply updates given in update_spec to the document whose id
matches that of doc. | mongo_connector/doc_managers/solr_doc_manager.py | def update(self, document_id, update_spec, namespace, timestamp):
"""Apply updates given in update_spec to the document whose id
matches that of doc.
"""
# Commit outstanding changes so that the document to be updated is the
# same version to which the changes apply.
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"""Apply updates given in update_spec to the document whose id
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"""
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# same version to which the changes apply.
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train | DocManager.upsert | Update or insert a document into Solr
This method should call whatever add/insert/update method exists for
the backend engine and add the document in there. The input will
always be one mongo document, represented as a Python dictionary. | mongo_connector/doc_managers/solr_doc_manager.py | def upsert(self, doc, namespace, timestamp):
"""Update or insert a document into Solr
This method should call whatever add/insert/update method exists for
the backend engine and add the document in there. The input will
always be one mongo document, represented as a Python dictionary.
... | def upsert(self, doc, namespace, timestamp):
"""Update or insert a document into Solr
This method should call whatever add/insert/update method exists for
the backend engine and add the document in there. The input will
always be one mongo document, represented as a Python dictionary.
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train | DocManager.bulk_upsert | Update or insert multiple documents into Solr
docs may be any iterable | mongo_connector/doc_managers/solr_doc_manager.py | def bulk_upsert(self, docs, namespace, timestamp):
"""Update or insert multiple documents into Solr
docs may be any iterable
"""
if self.auto_commit_interval is not None:
add_kwargs = {
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"""Update or insert multiple documents into Solr
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train | DocManager.remove | Removes documents from Solr
The input is a python dictionary that represents a mongo document. | mongo_connector/doc_managers/solr_doc_manager.py | def remove(self, document_id, namespace, timestamp):
"""Removes documents from Solr
The input is a python dictionary that represents a mongo document.
"""
self.solr.delete(id=u(document_id),
commit=(self.auto_commit_interval == 0)) | def remove(self, document_id, namespace, timestamp):
"""Removes documents from Solr
The input is a python dictionary that represents a mongo document.
"""
self.solr.delete(id=u(document_id),
commit=(self.auto_commit_interval == 0)) | [
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train | DocManager._stream_search | Helper method for iterating over Solr search results. | mongo_connector/doc_managers/solr_doc_manager.py | def _stream_search(self, query):
"""Helper method for iterating over Solr search results."""
for doc in self.solr.search(query, rows=100000000):
if self.unique_key != "_id":
doc["_id"] = doc.pop(self.unique_key)
yield doc | def _stream_search(self, query):
"""Helper method for iterating over Solr search results."""
for doc in self.solr.search(query, rows=100000000):
if self.unique_key != "_id":
doc["_id"] = doc.pop(self.unique_key)
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train | DocManager.search | Called to query Solr for documents in a time range. | mongo_connector/doc_managers/solr_doc_manager.py | def search(self, start_ts, end_ts):
"""Called to query Solr for documents in a time range."""
query = '_ts: [%s TO %s]' % (start_ts, end_ts)
return self._stream_search(query) | def search(self, start_ts, end_ts):
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query = '_ts: [%s TO %s]' % (start_ts, end_ts)
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train | DocManager.get_last_doc | Returns the last document stored in the Solr engine. | mongo_connector/doc_managers/solr_doc_manager.py | def get_last_doc(self):
"""Returns the last document stored in the Solr engine.
"""
#search everything, sort by descending timestamp, return 1 row
try:
result = self.solr.search('*:*', sort='_ts desc', rows=1)
except ValueError:
return None
for r ... | def get_last_doc(self):
"""Returns the last document stored in the Solr engine.
"""
#search everything, sort by descending timestamp, return 1 row
try:
result = self.solr.search('*:*', sort='_ts desc', rows=1)
except ValueError:
return None
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train | pbkdf2_single | Returns the result of the Password-Based Key Derivation Function 2 with
a single iteration (i.e. count = 1).
prf - a psuedorandom function
See http://en.wikipedia.org/wiki/PBKDF2 | pyscrypt/hash.py | def pbkdf2_single(password, salt, key_length, prf):
'''Returns the result of the Password-Based Key Derivation Function 2 with
a single iteration (i.e. count = 1).
prf - a psuedorandom function
See http://en.wikipedia.org/wiki/PBKDF2
'''
block_number = 0
result = b''
# The i... | def pbkdf2_single(password, salt, key_length, prf):
'''Returns the result of the Password-Based Key Derivation Function 2 with
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prf - a psuedorandom function
See http://en.wikipedia.org/wiki/PBKDF2
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train | salsa20_8 | Salsa 20/8 stream cypher; Used by BlockMix. See http://en.wikipedia.org/wiki/Salsa20 | pyscrypt/hash.py | def salsa20_8(B):
'''Salsa 20/8 stream cypher; Used by BlockMix. See http://en.wikipedia.org/wiki/Salsa20'''
# Create a working copy
x = B[:]
# Expanded form of this code. The expansion is significantly faster but
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# ROUNDS = (
# (4, 0, 12, 7), (8, ... | def salsa20_8(B):
'''Salsa 20/8 stream cypher; Used by BlockMix. See http://en.wikipedia.org/wiki/Salsa20'''
# Create a working copy
x = B[:]
# Expanded form of this code. The expansion is significantly faster but
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train | blockmix_salsa8 | Blockmix; Used by SMix. | pyscrypt/hash.py | def blockmix_salsa8(BY, Yi, r):
'''Blockmix; Used by SMix.'''
start = (2 * r - 1) * 16
X = BY[start:start + 16] # BlockMix - 1
for i in xrange(0, 2 * r): # BlockMix - 2
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train | smix | SMix; a specific case of ROMix. See scrypt.pdf in the links above. | pyscrypt/hash.py | def smix(B, Bi, r, N, V, X):
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train | hash | Returns the result of the scrypt password-based key derivation function.
Constraints:
r * p < (2 ** 30)
dkLen <= (((2 ** 32) - 1) * 32
N must be a power of 2 greater than 1 (eg. 2, 4, 8, 16, 32...)
N, r, p must be positive | pyscrypt/hash.py | def hash(password, salt, N, r, p, dkLen):
"""Returns the result of the scrypt password-based key derivation function.
Constraints:
r * p < (2 ** 30)
dkLen <= (((2 ** 32) - 1) * 32
N must be a power of 2 greater than 1 (eg. 2, 4, 8, 16, 32...)
N, r, p must be positive
... | def hash(password, salt, N, r, p, dkLen):
"""Returns the result of the scrypt password-based key derivation function.
Constraints:
r * p < (2 ** 30)
dkLen <= (((2 ** 32) - 1) * 32
N must be a power of 2 greater than 1 (eg. 2, 4, 8, 16, 32...)
N, r, p must be positive
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train | ScryptFile._load_get_attr | Return an internal attribute after ensuring the headers is loaded if necessary. | pyscrypt/file.py | def _load_get_attr(self, name):
'Return an internal attribute after ensuring the headers is loaded if necessary.'
if self._mode in _allowed_read and self._N is None:
self._read_header()
return getattr(self, name) | def _load_get_attr(self, name):
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self._read_header()
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train | ScryptFile.close | Close the underlying file.
Sets data attribute .closed to True. A closed file cannot be used for
further I/O operations. close() may be called more than once without
error. Some kinds of file objects (for example, opened by popen())
may return an exit status upon closing. | pyscrypt/file.py | def close(self):
'''Close the underlying file.
Sets data attribute .closed to True. A closed file cannot be used for
further I/O operations. close() may be called more than once without
error. Some kinds of file objects (for example, opened by popen())
may return an exit status ... | def close(self):
'''Close the underlying file.
Sets data attribute .closed to True. A closed file cannot be used for
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error. Some kinds of file objects (for example, opened by popen())
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train | ScryptFile.verify_file | Returns whether a scrypt encrypted file is valid. | pyscrypt/file.py | def verify_file(fp, password):
'Returns whether a scrypt encrypted file is valid.'
sf = ScryptFile(fp = fp, password = password)
for line in sf: pass
sf.close()
return sf.valid | def verify_file(fp, password):
'Returns whether a scrypt encrypted file is valid.'
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sf.close()
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train | ScryptFile.readline | Next line from the decrypted file, as a string.
Retain newline. A non-negative size argument limits the maximum
number of bytes to return (an incomplete line may be returned then).
Return an empty string at EOF. | pyscrypt/file.py | def readline(self, size = None):
'''Next line from the decrypted file, as a string.
Retain newline. A non-negative size argument limits the maximum
number of bytes to return (an incomplete line may be returned then).
Return an empty string at EOF.'''
if self.closed: raise Valu... | def readline(self, size = None):
'''Next line from the decrypted file, as a string.
Retain newline. A non-negative size argument limits the maximum
number of bytes to return (an incomplete line may be returned then).
Return an empty string at EOF.'''
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train | ScryptFile._read_header | Read and parse the header and calculate derived keys. | pyscrypt/file.py | def _read_header(self):
'''Read and parse the header and calculate derived keys.'''
try:
# Read the entire header
header = self._fp.read(96)
if len(header) != 96:
raise InvalidScryptFileFormat("Incomplete header")
# Magic number
... | def _read_header(self):
'''Read and parse the header and calculate derived keys.'''
try:
# Read the entire header
header = self._fp.read(96)
if len(header) != 96:
raise InvalidScryptFileFormat("Incomplete header")
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train | ScryptFile.read | Read at most size bytes, returned as a string.
If the size argument is negative or omitted, read until EOF is reached.
Notice that when in non-blocking mode, less data than what was requested
may be returned, even if no size parameter was given. | pyscrypt/file.py | def read(self, size = None):
'''Read at most size bytes, returned as a string.
If the size argument is negative or omitted, read until EOF is reached.
Notice that when in non-blocking mode, less data than what was requested
may be returned, even if no size parameter was given.'''
... | def read(self, size = None):
'''Read at most size bytes, returned as a string.
If the size argument is negative or omitted, read until EOF is reached.
Notice that when in non-blocking mode, less data than what was requested
may be returned, even if no size parameter was given.'''
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train | ScryptFile._write_header | Writes the header to the underlying file object. | pyscrypt/file.py | def _write_header(self):
'Writes the header to the underlying file object.'
header = b'scrypt' + CHR0 + struct.pack('>BII', int(math.log(self.N, 2)), self.r, self.p) + self.salt
# Add the header checksum to the header
checksum = hashlib.sha256(header).digest()[:16]
header += ch... | def _write_header(self):
'Writes the header to the underlying file object.'
header = b'scrypt' + CHR0 + struct.pack('>BII', int(math.log(self.N, 2)), self.r, self.p) + self.salt
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train | ScryptFile._finalize_write | Finishes any unencrypted bytes and writes the final checksum. | pyscrypt/file.py | def _finalize_write(self):
'Finishes any unencrypted bytes and writes the final checksum.'
# Make sure we have written the header
if not self._done_header:
self._write_header()
# Write the remaining decrypted part to disk
block = self._crypto.encrypt(self._decrypted... | def _finalize_write(self):
'Finishes any unencrypted bytes and writes the final checksum.'
# Make sure we have written the header
if not self._done_header:
self._write_header()
# Write the remaining decrypted part to disk
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train | ScryptFile.write | Write string str to the underlying file.
Note that due to buffering, flush() or close() may be needed before
the file on disk reflects the data written. | pyscrypt/file.py | def write(self, str):
'''Write string str to the underlying file.
Note that due to buffering, flush() or close() may be needed before
the file on disk reflects the data written.'''
if self.closed: raise ValueError('File closed')
if self._mode in _allowed_read:
raise... | def write(self, str):
'''Write string str to the underlying file.
Note that due to buffering, flush() or close() may be needed before
the file on disk reflects the data written.'''
if self.closed: raise ValueError('File closed')
if self._mode in _allowed_read:
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train | get_logger | Return a logger with the specified name, creating it if necessary. | logone/__init__.py | def get_logger(logger_name):
"""
Return a logger with the specified name, creating it if necessary.
"""
# Use default global logger
if logger_name is None:
return __instance
assert isinstance(logger_name, str), 'Logger name must be a string!'
with __lock:
if logger_name in... | def get_logger(logger_name):
"""
Return a logger with the specified name, creating it if necessary.
"""
# Use default global logger
if logger_name is None:
return __instance
assert isinstance(logger_name, str), 'Logger name must be a string!'
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train | removeFile | remove a file | hallie/modules/files.py | def removeFile(file):
"""remove a file"""
if "y" in speech.question("Are you sure you want to remove " + file + "? (Y/N): "):
speech.speak("Removing " + file + " with the 'rm' command.")
subprocess.call(["rm", "-r", file])
else:
speech.speak("Okay, I won't remove " + file + ".") | def removeFile(file):
"""remove a file"""
if "y" in speech.question("Are you sure you want to remove " + file + "? (Y/N): "):
speech.speak("Removing " + file + " with the 'rm' command.")
subprocess.call(["rm", "-r", file])
else:
speech.speak("Okay, I won't remove " + file + ".") | [
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train | copy | copy file or directory at a given location; can be pasted later | hallie/modules/files.py | def copy(location):
"""copy file or directory at a given location; can be pasted later"""
copyData = settings.getDataFile()
copyFileLocation = os.path.abspath(location)
copy = {"copyLocation": copyFileLocation}
dataFile = open(copyData, "wb")
pickle.dump(copy, dataFile)
speech.speak(location + " copied successfu... | def copy(location):
"""copy file or directory at a given location; can be pasted later"""
copyData = settings.getDataFile()
copyFileLocation = os.path.abspath(location)
copy = {"copyLocation": copyFileLocation}
dataFile = open(copyData, "wb")
pickle.dump(copy, dataFile)
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train | paste | paste a file or directory that has been previously copied | hallie/modules/files.py | def paste(location):
"""paste a file or directory that has been previously copied"""
copyData = settings.getDataFile()
if not location:
location = "."
try:
data = pickle.load(open(copyData, "rb"))
speech.speak("Pasting " + data["copyLocation"] + " to current directory.")
except:
speech.fail("It doesn't loo... | def paste(location):
"""paste a file or directory that has been previously copied"""
copyData = settings.getDataFile()
if not location:
location = "."
try:
data = pickle.load(open(copyData, "rb"))
speech.speak("Pasting " + data["copyLocation"] + " to current directory.")
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train | add_zfs_apt_repository | adds the ZFS repository | bookshelf/api_v2/pkg.py | def add_zfs_apt_repository():
""" adds the ZFS repository """
with settings(hide('warnings', 'running', 'stdout'),
warn_only=False, capture=True):
sudo('DEBIAN_FRONTEND=noninteractive /usr/bin/apt-get update')
install_ubuntu_development_tools()
apt_install(packages=['so... | def add_zfs_apt_repository():
""" adds the ZFS repository """
with settings(hide('warnings', 'running', 'stdout'),
warn_only=False, capture=True):
sudo('DEBIAN_FRONTEND=noninteractive /usr/bin/apt-get update')
install_ubuntu_development_tools()
apt_install(packages=['so... | [
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train | apt_install | installs a apt package | bookshelf/api_v2/pkg.py | def apt_install(**kwargs):
"""
installs a apt package
"""
for pkg in list(kwargs['packages']):
if is_package_installed(distribution='ubuntu', pkg=pkg) is False:
sudo("DEBIAN_FRONTEND=noninteractive /usr/bin/apt-get install -y %s" % pkg)
# if we didn't abort above, we shou... | def apt_install(**kwargs):
"""
installs a apt package
"""
for pkg in list(kwargs['packages']):
if is_package_installed(distribution='ubuntu', pkg=pkg) is False:
sudo("DEBIAN_FRONTEND=noninteractive /usr/bin/apt-get install -y %s" % pkg)
# if we didn't abort above, we shou... | [
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train | apt_install_from_url | installs a pkg from a url
p pkg_name: the name of the package to install
p url: the full URL for the rpm package | bookshelf/api_v2/pkg.py | def apt_install_from_url(pkg_name, url, log=False):
""" installs a pkg from a url
p pkg_name: the name of the package to install
p url: the full URL for the rpm package
"""
if is_package_installed(distribution='ubuntu', pkg=pkg_name) is False:
if log:
log_green(
... | def apt_install_from_url(pkg_name, url, log=False):
""" installs a pkg from a url
p pkg_name: the name of the package to install
p url: the full URL for the rpm package
"""
if is_package_installed(distribution='ubuntu', pkg=pkg_name) is False:
if log:
log_green(
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train | apt_add_key | trust a new PGP key related to a apt-repository | bookshelf/api_v2/pkg.py | def apt_add_key(keyid, keyserver='keyserver.ubuntu.com', log=False):
""" trust a new PGP key related to a apt-repository """
if log:
log_green(
'trusting keyid %s from %s' % (keyid, keyserver)
)
with settings(hide('warnings', 'running', 'stdout')):
sudo('apt-key adv --key... | def apt_add_key(keyid, keyserver='keyserver.ubuntu.com', log=False):
""" trust a new PGP key related to a apt-repository """
if log:
log_green(
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with settings(hide('warnings', 'running', 'stdout')):
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train | enable_apt_repositories | adds an apt repository | bookshelf/api_v2/pkg.py | def enable_apt_repositories(prefix, url, version, repositories):
""" adds an apt repository """
with settings(hide('warnings', 'running', 'stdout'),
warn_only=False, capture=True):
sudo('apt-add-repository "%s %s %s %s"' % (prefix,
url... | def enable_apt_repositories(prefix, url, version, repositories):
""" adds an apt repository """
with settings(hide('warnings', 'running', 'stdout'),
warn_only=False, capture=True):
sudo('apt-add-repository "%s %s %s %s"' % (prefix,
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train | install_gem | install a particular gem | bookshelf/api_v2/pkg.py | def install_gem(gem):
""" install a particular gem """
with settings(hide('warnings', 'running', 'stdout', 'stderr'),
warn_only=False, capture=True):
# convert 0 into True, any errors will always raise an exception
return not bool(
run("gem install %s --no-rdoc --no... | def install_gem(gem):
""" install a particular gem """
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# convert 0 into True, any errors will always raise an exception
return not bool(
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train | install_python_module_locally | instals a python module using pip | bookshelf/api_v2/pkg.py | def install_python_module_locally(name):
""" instals a python module using pip """
with settings(hide('everything'),
warn_only=False, capture=True):
# convert 0 into True, any errors will always raise an exception
print(not bool(local('pip --quiet install %s' % name).return_cod... | def install_python_module_locally(name):
""" instals a python module using pip """
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train | is_package_installed | checks if a particular package is installed | bookshelf/api_v2/pkg.py | def is_package_installed(distribution, pkg):
""" checks if a particular package is installed """
if ('centos' in distribution or
'el' in distribution or
'redhat' in distribution):
return(is_rpm_package_installed(pkg))
if ('ubuntu' in distribution or
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""" checks if a particular package is installed """
if ('centos' in distribution or
'el' in distribution or
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return(is_rpm_package_installed(pkg))
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train | is_rpm_package_installed | checks if a particular rpm package is installed | bookshelf/api_v2/pkg.py | def is_rpm_package_installed(pkg):
""" checks if a particular rpm package is installed """
with settings(hide('warnings', 'running', 'stdout', 'stderr'),
warn_only=True, capture=True):
result = sudo("rpm -q %s" % pkg)
if result.return_code == 0:
return True
... | def is_rpm_package_installed(pkg):
""" checks if a particular rpm package is installed """
with settings(hide('warnings', 'running', 'stdout', 'stderr'),
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result = sudo("rpm -q %s" % pkg)
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train | yum_install | installs a yum package | bookshelf/api_v2/pkg.py | def yum_install(**kwargs):
"""
installs a yum package
"""
if 'repo' in kwargs:
repo = kwargs['repo']
for pkg in list(kwargs['packages']):
if is_package_installed(distribution='el', pkg=pkg) is False:
if 'repo' in locals():
log_green(
... | def yum_install(**kwargs):
"""
installs a yum package
"""
if 'repo' in kwargs:
repo = kwargs['repo']
for pkg in list(kwargs['packages']):
if is_package_installed(distribution='el', pkg=pkg) is False:
if 'repo' in locals():
log_green(
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train | yum_group_install | instals a yum group | bookshelf/api_v2/pkg.py | def yum_group_install(**kwargs):
""" instals a yum group """
for grp in list(kwargs['groups']):
log_green("installing %s ..." % grp)
if 'repo' in kwargs:
repo = kwargs['repo']
sudo("yum groupinstall -y --quiet "
"--enablerepo=%s '%s'" % (repo, grp))
... | def yum_group_install(**kwargs):
""" instals a yum group """
for grp in list(kwargs['groups']):
log_green("installing %s ..." % grp)
if 'repo' in kwargs:
repo = kwargs['repo']
sudo("yum groupinstall -y --quiet "
"--enablerepo=%s '%s'" % (repo, grp))
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train | yum_install_from_url | installs a pkg from a url
p pkg_name: the name of the package to install
p url: the full URL for the rpm package | bookshelf/api_v2/pkg.py | def yum_install_from_url(pkg_name, url):
""" installs a pkg from a url
p pkg_name: the name of the package to install
p url: the full URL for the rpm package
"""
if is_package_installed(distribution='el', pkg=pkg_name) is False:
log_green(
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""" installs a pkg from a url
p pkg_name: the name of the package to install
p url: the full URL for the rpm package
"""
if is_package_installed(distribution='el', pkg=pkg_name) is False:
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train | abstractInterface.recherche | abstractSearch in fields of collection and reset rendering.
Returns number of results.
If in_all is True, call get_all before doing the search. | pyDLib/Core/controller.py | def recherche(self, pattern, entete, in_all=False):
"""abstractSearch in fields of collection and reset rendering.
Returns number of results.
If in_all is True, call get_all before doing the search."""
if in_all:
self.collection = self.get_all()
self.collection.recher... | def recherche(self, pattern, entete, in_all=False):
"""abstractSearch in fields of collection and reset rendering.
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If in_all is True, call get_all before doing the search."""
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train | abstractInterface.launch_background_job | Launch the callable job in background thread.
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train | abstractInterface.filtre | Return a filter list, bases on criteres
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:param criteres: Criteria { `attribut`:[valeurs,...] }
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def choisi(ac):
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On failure, raise :class:`~.Core.exceptions.StructureError`, :class:`~.Core.exceptions.ConnexionError`
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train | abstractInterInterfaces._load_users | Default implentation requires users from DB.
Should setup `users` attribute | pyDLib/Core/controller.py | def _load_users(self):
"""Default implentation requires users from DB.
Should setup `users` attribute"""
r = sql.abstractRequetesSQL.get_users()()
self.users = {d["id"]: dict(d) for d in r} | def _load_users(self):
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"}"
] | 16be28e99837e40287a63803bbfdf67ac1806b7b |
train | abstractInterInterfaces.load_modules | Should instance interfaces and set them to interface, following `modules` | pyDLib/Core/controller.py | def load_modules(self):
"""Should instance interfaces and set them to interface, following `modules`"""
if self.INTERFACES_MODULE is None:
raise NotImplementedError("A module containing interfaces modules "
"should be setup in INTERFACES_MODULE !")
... | def load_modules(self):
"""Should instance interfaces and set them to interface, following `modules`"""
if self.INTERFACES_MODULE is None:
raise NotImplementedError("A module containing interfaces modules "
"should be setup in INTERFACES_MODULE !")
... | [
"Should",
"instance",
"interfaces",
"and",
"set",
"them",
"to",
"interface",
"following",
"modules"
] | benoitkugler/abstractDataLibrary | python | https://github.com/benoitkugler/abstractDataLibrary/blob/16be28e99837e40287a63803bbfdf67ac1806b7b/pyDLib/Core/controller.py#L273-L282 | [
"def",
"load_modules",
"(",
"self",
")",
":",
"if",
"self",
".",
"INTERFACES_MODULE",
"is",
"None",
":",
"raise",
"NotImplementedError",
"(",
"\"A module containing interfaces modules \"",
"\"should be setup in INTERFACES_MODULE !\"",
")",
"else",
":",
"for",
"module",
... | 16be28e99837e40287a63803bbfdf67ac1806b7b |
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