daplis.functions.fits module

Module for fitting timestamp differences with Gaussian function.

This file can also be imported as a module and contains the following functions:

fit_with_gaussian - fit timestamp differences of a pair of pixels

with a Gaussian function and plot a histogram of timestamp differences and the fit in a single figure.

fit_with_gaussian_combine - combine timestamp differences for the

requested pixels before fitting them with a Gaussian function. Then, plot a histogram together with the fit.

fit_with_gaussian_all - find all peaks above the given threshold

and fit them individually with a Gaussian function.

fit_with_gaussian_full_sensor - fit timestamp differences of a

pair of pixels (one from each half of the sensor) with a Gaussian function and plot a histogram of timestamp differences and the fit in a single figure.

fit_with_gaussian_fancy - fit timestamp diferences of a pair of

pixels using the lmfit library. The main parameters reported are the standard deviation, mean value, and contrast, together with residuals and signal-to-noise ratio (SNR) defined as a ratio of peak height to standard deviation of background.

unpickle_fit - unpickle the ‘.pkl’ file, show the plot, and

return the plot data for each line found (histogram, fit 1, fit 2, etc.).

daplis.functions.fits.fit_with_gaussian(path: str, pixels: List[int] | List[List[int]], ft_file: str | None = None, range_left: float = -5000.0, range_right: float = 5000.0, multiplier: int = 1, normalize: bool = False, color_data: str | None = None, color_fit: str | None = None, title_on: bool = True, correct_pix_address: bool = False, return_fit_params: bool = False, pickle_figure: bool = False, file_offset_abs: str | None = None) → DataFrame[source]

Fit with Gaussian function and plot it.

Fits timestamp differences of a pair of pixels with Gaussian function and plots it next to the histogram of the differences. Timestamp differences are collected from a ‘.feather’ file if it exists.

Parameters:

path (str) – Path to the folder with ‘.dat’ data files or where the ‘.feather’ file with timestamp differences is located.
pixels (List[int] | List[List[int]]) – List of pixel numbers for which the timestamp differences should be calculated and saved or list of two lists with pixel numbers for peak vs. peak calculations.
ft_file (str, optional) – Name of the ‘.feather’ file to use for plotting. Can be used when the raw ‘.dat’ data is not available. The default is None.
range_left (float, optional) – Left limit for the signal window. The default is -5e3.
range_right (float, optional) – Right limit for the signal window. The default is 5e3.
multiplier (int, optional) – Bins of delta t histogram should be in units of 17.857 (average LinoSPAD2 TDC bin width), this parameter helps with changing the bin size while maintaining that rule. Default is 1.
normalize (bool, optional) – Switch for normalizing the plot to median. The default is False.
color_data (str, optional) – For changing the color of the data. The default is “rebeccapurple”.
color_fit (str, optional) – For changing the color of the fit. The default is “darkorange”.
title_on (bool, optional) – Switch for turning on/off the title of the plot, the title shows the pixels for which the fit is done. The default is True.
correct_pix_address (bool, optional) – Correct pixel address for the FPGA board on side 23. The default is False.
return_fit_params (bool, optional) – Switch for returning the fit parameters for further analysis. The default is False.
pickle_figure (bool, optional) – Switch for pickling the plot. Can be used to extract the plot data. The default is False.
file_offset_abs (str, optional) – Absolute path to the ‘.npy’ file with the offset calibration for the particular board. The default is None.

Raises:

FileNotFoundError – Raised if no ‘.dat’ data files are found.
FileNotFoundError – Raised if no ‘.feather’ file with timestamp differences is found.
ValueError – Raised if no data for the requested pair of pixels is found in the ‘.feather’ file.

Returns:

A dataframe with fit parameters and their standard errors. Returned only if the “return_fit_params” is set to True.

Return type:

DataFrame.

daplis.functions.fits.fit_with_gaussian_all(path: str, pixels: List[int] | List[List[int]], ft_file: str | None = None, threshold_multiplier: float = 1.2, range_left: float = -5000.0, range_right: float = 5000.0, multiplier: int = 1, normalize: bool = False, color_d: str | None = None, color_f: str | None = None, title_on: bool = True, correct_pix_address: bool = False, return_fit_params: bool = False, pickle_figure: bool = False) → DataFrame[source]

Find all peaks above threshold and fit each with Gaussian.

Finds all peaks above the given threshold (uses the ‘threshold_multiplier’ parameter as a multiplier of the median) and fits each with a Gaussian function.

Parameters:

path (str) – Path to the folder with ‘.dat’ data files or where the ‘.feather’ file with timestamp differences is located.
pixels (List[int] | List[List[int]]) – List of pixel numbers for which the timestamp differences should be calculated and saved or list of two lists with pixel numbers for peak vs. peak calculations.
ft_file (str, optional) – Name of the ‘.feather’ file to use for plotting. Can be used when the raw ‘.dat’ data is not available. The default is None.
threshold_multiplier (float, optional) – Multiplier for the median of the histogram counts. Used for setting a threshold for the peak discovery in the histogram. The default is 1.2, or 20% above the median.
range_left (float, optional) – Left limit for the signal window. The default is -5e3.
range_right (float, optional) – Right limit for the signal window. The default is 5e3.
multiplier (int, optional) – Bins of delta t histogram should be in units of 17.857 (average LinoSPAD2 TDC bin width). Default is 1.
normalize (bool, optional) – Switch for normalizing the plot to median. The default is False.
color_d (str, optional) – Color for the histogram. The default is “rebeccapurple”.
color_f (str, optional) – Color for the fit with Gaussian. The default is “darkorange”.
title_on (bool, optional) – Switch for showing the plot title. The default is “True”.
correct_pix_address (bool, optional) – Correct pixel address for the FPGA board on side 23. The default is False.
return_fit_params (bool, optional) – Switch for returning the fit parameters for further analysis. The default is False.
pickle_figure (bool, optional) – Switch for pickling the plot. Can be used to extract the plot data. The default is False.

Raises:

FileNotFoundError – Raised when no ‘.dat’ data files are found.
FileNotFoundError – Raised when no ‘.feather’ file with timestamp differences is found.
ValueError – Raised when no data for the requested pair of pixels was found in the ‘.feather’ file.

Returns:

A dataframe with fit parameters and their standard errors. Returned only if the “return_fit_params” is set to True.

Return type:

DataFrame.

daplis.functions.fits.fit_with_gaussian_combine(path: str, pixels: List[int] | List[List[int]], ft_file: str | None = None, range_left: float = -5000.0, range_right: float = 5000.0, multiplier: int = 1, normalize: bool = False, color_data: str | None = None, color_fit: str | None = None, title_on: bool = True, correct_pix_address: bool = False, return_fit_params: bool = False, pickle_figure: bool = False, file_offset_abs: str | None = None) → DataFrame[source]

Fit with Gaussian function and plot it, merging the pixels.

Fits timestamp differences of a pair of pixels with Gaussian function and plots it next to the histogram of the differences. Timestamp differences are collected from a ‘.feather’ file if it exists. Merges the data from all pixel pairs requested into a single peak.

Parameters:

path (str) – Path to the folder with ‘.dat’ data files or where the ‘.feather’ file with timestamp differences is located.
pixels (List[int] | List[List[int]]) – List of pixel numbers for which the timestamp differences should be calculated and saved or list of two lists with pixel numbers for peak vs. peak calculations.
ft_file (str, optional) – Name of the ‘.feather’ file to use for plotting. Can be used when the raw ‘.dat’ data is not available. The default is None.
range_left (float, optional) – Left limit for the signal window. The default is -5e3.
range_right (float, optional) – Right limit for the signal window. The default is 5e3.
multiplier (int, optional) – Bins of delta t histogram should be in units of 17.857 (average LinoSPAD2 TDC bin width), this parameter helps with changing the bin size while maintaining that rule. Default is 1.
normalize (bool, optional) – Switch for normalizing the plot to median. The default is False.
color_data (str, optional) – For changing the color of the data. The default is “rebeccapurple”.
color_fit (str, optional) – For changing the color of the fit. The default is “darkorange”.
title_on (bool, optional) – Switch for turning on/off the title of the plot, the title shows the pixels for which the fit is done. The default is True.
correct_pix_address (bool, optional) – Correct pixel address for the FPGA board on side 23. The default is False.
return_fit_params (bool, optional) – Switch for returning the fit parameters for further analysis. The default is False.
pickle_figure (bool, optional) – Switch for pickling the plot. Can be used to extract the plot data. The default is False.
file_offset_abs (str, optional) – Absolute path to the ‘.npy’ file with the offset calibration for the particular board. The default is None.

Raises:

FileNotFoundError – Raised if no ‘.dat’ data files are found.
FileNotFoundError – Raised if no ‘.feather’ file with timestamp differences is found.
ValueError – Raised if no data for the requested pair of pixels is found in the ‘.feather’ file.

Returns:

A dataframe with fit parameters and their standard errors. Returned only if the “return_fit_params” is set to True.

Return type:

DataFrame.

daplis.functions.fits.fit_with_gaussian_fancy(path: str, pixels: List[int] | List[List[int]], ft_file: str | None = None, range_left: float = -5000.0, range_right: float = 5000.0, multiplier: int | None = None, normalize: bool = False, return_fit_params: bool = False, interpolate_fit: bool = True, correct_pix_address: bool = False, pickle_figure: bool = False)[source]

Fit with Gaussian function and plot it, using lmfit library.

Fits timestamp differences of a pair of pixels with Gaussian function and plots it over to the histogram of the differences. Timestamp differences are collected from a ‘.feather’ file. Additionally, the residuals are calculated and plotted below the data and fit, together with a normal distribution of them.

Parameters:

path (str) – Path to the folder with ‘.dat’ data files or where the ‘.feather’ file with timestamp differences is located.
pixels (List[int] | List[List[int]]) – List of pixel numbers for which the timestamp differences should be calculated and saved or list of two lists with pixel numbers for peak vs. peak calculations.
ft_file (str, optional) – Name of the ‘.feather’ file with the timestamp differences. Should be provided when the data files are not available. The default is None.
range_left (float, optional) – Left limit for the signal window. The default is -5e3.
range_right (float, optional) – Right limit for the signal window. The default is 5e3.
multiplier (int, optional) – Bins of delta t histogram should be in units of 17.857 (average LinoSPAD2 TDC bin width), this parameter helps with changing the bin size while maintaining that rule. Default is 1.
normalize (bool, optional) – Switch for normalizing the plot to median. The default is False.
return_fit_parameters (bool, optional) – Switch for returning the fit parameters as they are returned by the lmfit library. The default is False.
interpolate_fit (bool, optional) – Switch for an interpolated fit. The default is True.
correct_pix_address (bool, optional) – Correct pixel address for the FPGA board on side 23. The default is False.
pickle_figure (bool, optional) – Switch for pickling the plot. Can be used to extract the plot data. The default is False.

Returns:

Parameters of the fit as returned by the lmfit library. Returned only if the “return_fit_params” is set to True.

Return type:

lmfit.parameter.Parameters

Raises:

FileNotFoundError – Raised if the ‘delta_ts_data’ folder was not found.

daplis.functions.fits.fit_with_gaussian_full_sensor(path, pix_pair: List[int], window: float = 5000.0, multiplier: int = 1, color_data: str | None = None, color_fit: str | None = None, title_on: bool = True)[source]

Fit with Gaussian function and plot it.

Fits timestamp differences of a pair of pixels with Gaussian function and plots it next to the histogram of the differences. Timestamp differences are collected from a ‘.feather’ file with those if such exists.

Parameters:

path (str) – Path to the folder with ‘.dat’ data files.
pix_pair (list) – Two pixel numbers for which fit is done.
window (float, optional) – Time range in which timestamp differences are fitted. The default is 5e3.
multiplier (int, optional) – Bins of delta t histogram should be in units of 17.857 (average LinoSPAD2 TDC bin width), this parameter helps with changing the bin size while maintaining that rule. Default is 1.
color_data (str, optional) – For changing the color of the data. The default is “rebeccapurple”.
color_fit (str, optional) – For changing the color of the fit. The default is “darkorange”.
title_on (bool, optional) – Switch for turning on/off the title of the plot, the title shows the pixels for which the fit is done. The default is True.

Raises:

FileNotFoundError – Raised when no ‘.dat’ data files are found.
FileNotFoundError – Raised when no ‘.feather’ file with timestamp differences is found.
ValueError – Raised when no data for the requested pair of pixels was found in the ‘.feather’ file.

Return type:

None.

daplis.functions.fits.unpickle_fit(fit_pickle_file: str) → dict[source]

Unpickle a saved figure and return plot data.

Load a pickled figure, extract and return the histogram and fit data.

Parameters:: fit_pickle_file (str) – The absolute path to the pickle file with the fit plot.
Returns:: A tuple containing: - fig (matplotlib.figure.Figure): The unpickled figure object. - plot_data (dict): A dictionary with keys “Histogram” and “Fit_{i}” (for i >= 1), where each value is a tuple of x and y data for the corresponding line plot. - params_df (pandas.DataFrame): A DataFrame containing fit parameters extracted from the legend. Columns represent each fit.
Return type:: tuple
Raises:: FileNotFoundError – If the specified pickle file does not exist, a FileNotFoundError is raised and an error message is printed.