6. Miscellaneous (processor.utilities.misc)
- processor.utilities.misc.EnergyDensity400(Diode, Diameter=600)[source]
Calculate the pulse energy density of 400nm laser in uJ/cm^2. The units are um for beam diameter, uJ/cm^2 for energy density.
- Parameters:
- Diode: numeric
Measured value from photodiode (arb. units)
- Diameter: numeric | 600
Beam diameter.
- processor.utilities.misc.EnergyDensity800(Diode, Diameter=600)[source]
Calculate the pulse energy density of 800nm laser in uJ/cm^2. The units are um for beam diameter, uJ/cm^2 for energy density.
- Parameters:
- Diode: numeric
Measured value from photodiode (arb. units)
- Diameter: numeric | 600
Beam diameter.
- processor.utilities.misc.PulseEnergy400(Diode)[source]
Calculate the pulse energy of 400nm laser in uJ. The unit is um for beam diameter.
- Parameter:
- Diode: numeric
Measured value from photodiode (arb. units)
- processor.utilities.misc.PulseEnergy800(Diode)[source]
Calculate the pulse energy of 800nm laser in uJ. The unit is um for beam diameter.
- Parameter:
- Diode: numeric
Meausred value from photodiode (arb. units)
- processor.utilities.misc.argnearest(array, val, rettype='vectorized')[source]
Find the coordinates of the nD array element nearest to a specified value.
- Args:
array (np.array): Numeric data array val (int or float) : Look-up value rettype (
str,optional): return type specification‘vectorized’ (default) denotes vectorized coordinates (integer) ‘coordinates’ denotes multidimensional coordinates (tuple)
- Returns:
argval (int): coordinate position
- processor.utilities.misc.create_dataframes(runNumbers, *args)[source]
Creates a parquet dataframe for each run passed. Returns:
fails: dictionary of runs and error which broke the dataframe generation
- processor.utilities.misc.get_available_runs(rootpath)[source]
Collects the filepaths to the available experimental run data.
- Parameters:
- rootpath: str
path where to look for data (recursive in subdirectories)
- Return:
- available_runs: dict
dict with run numbers as keys (e.g. ‘run12345’) and path where to load data from as str.
- processor.utilities.misc.get_path_to_run(runNumber, rootpath)[source]
Returns the path to the data of a given run number
- Parameters:
- runNumber: str or int
run number as integer or string.
- rootpath: str
path where to look for data (recursive in subdirectories)
- Return:
- path: str
path to where the raw data of the given run number is stored.
- processor.utilities.misc.load_binned_h5(file_name, mode='r', ret_type='list')[source]
Load an HDF5 file saved with
save_binned()method.- Args:
file_name (str): name of the file to load, including full path mode (
str, optional): Read mode of h5 file (‘r’ = read). ret_type (str, optional): output format for axes and histograms:‘list’ generates a list of arrays, ordered as the corresponding dimensions in data. ‘dict’ generates a dictionary with the names of each axis.
- Returns:
data np.array: Multidimensional data read from h5 file. axes np.array: The axes values associated with the read data. hist np.array: Histogram values associated with the read data.
- processor.utilities.misc.parse_category(category, settings_file='default')[source]
parse setting file and return desired value
- Args:
category (str): title of the category setting_file (str): path to setting file. If set to ‘default’ it takes
a file called SETTINGS.ini in the main folder of the repo.
- Returns:
dictionary containing name and value of all entries present in this category.
- Notes:
Author: Steinn Ymir Agustsson <sagustss@uni-mainz.de>
- processor.utilities.misc.parse_logbook(log_text)[source]
Parse a log book entry to read out metadata.
- Args:
log_text (str or file): file or plain text of the log book, in the “correct” format TODO: add example of log entry
- Returns:
logDict (dict): Dictionary with the relevant metadata
- Notes:
Author: Steinn Ymir Agustsson <sagustss@uni-mainz.de>
- processor.utilities.misc.parse_setting(category, name, settings_file='default')[source]
parse setting file and return desired value
- Args:
- category: str
title of the category
- name: str
name of the parameter
- setting_file: str | ‘default’
path to setting file. If set to ‘default’ it takes a file called SETTINGS.ini in the main folder of the repo.
- Returns:
value of the parameter, None if parameter cannot be found.
- Notes:
Author: Steinn Ymir Agustsson <sagustss@uni-mainz.de>
- processor.utilities.misc.plot_lines(data, normalization='None', range=None, color_range=(0, 1), x_label='', y_label='', xlim=None, ylim=None, savefig=False, save_dir='E:/data/FLASH/', save_name='fig', static_curve=None)[source]
function to fit a series of curves with nice colorplot.
- processor.utilities.misc.repr_byte_size(size_bytes)[source]
Represent in a string the size in Bytes in a compact format.
Adapted from https://stackoverflow.com/questions/5194057/better-way-to-convert-file-sizes-in-python Follows same notation as Windows does for files. See: https://en.wikipedia.org/wiki/Mebibyte
- processor.utilities.misc.save_H5_hyperstack(data_array, filename, path=None, overwrite=True)[source]
Saves an hdf5 file with 4D (Kx,Ky,E,Time) images for import in FIJI
- Parameters:
- data_array: numpy array
4D data array, order must be Kx,Ky,Energy,Time.
- filename: str
The name of the file to save
- path: str
The path to where to save hdf5 file. If None, uses the “results” folder from SETTINGS.ini.
- overwrite: str
If true, it overwrites existing file with the same name. Otherwise raises and error.
- processor.utilities.misc.write_setting(value, category, name, settings_file='default')[source]
Write enrty in the settings file
- Args:
category (str): title of the category name (str): name of the parameter setting_file (str): path to setting file. If set to ‘default’ it takes
a file called SETTINGS.ini in the main folder of the repo.
- Returns:
value of the parameter, None if parameter cannot be found.
- Notes:
Author: Steinn Ymir Agustsson <sagustss@uni-mainz.de>