evaluation

Classes:

Evaluation(source)

Main class for evaluating data.

class pyEvalData.evaluation.Evaluation(source)[source]

Bases: object

Main class for evaluating data. The raw data is accessed via a Source object. The evaluation allows to bin data, calculate errors and propagate them. There is also an interface to lmfit for easy batch-fitting.

Parameters

source (Source) – raw data source.

Attributes
  • log (logging.logger) – logger instance from logging.

  • clist (list[str]) – list of counter names to evaluate.

  • cdef (dict{str – str}): dict of predefined counter names and definitions.

  • xcol (str) – counter or motor for x-axis.

  • t0 (float) – approx. time zero for delay scans to determine the unpumped region of the data for normalization.

  • custom_counters (list[str]) – list of custom counters - default is []

  • math_keys (list[str]) – list of keywords which are evaluated as numpy functions

  • statistic_type (str) – ‘gauss’ for normal averaging, ‘poisson’ for counting statistics

  • propagate_errors (bool) – propagate errors for dpendent counters.

Methods:

get_clist()

Returns a list of counters as defined by the user.

traverse_counters(clist[, source_cols])

Traverse all counters and replace all predefined counter definitions.

resolve_counter_name(col_name[, source_cols])

Replace all predefined counter definitions in a given counter name.

col_string_to_eval_string(col_string[, ...])

Use regular expressions in order to generate an evaluateable string from the counter string in order to append the new counter to the spec data.

add_custom_counters(spec_data, scan_num, ...)

Add custom counters to the spec data array.

filter_data(data)

param data

DESCRIPTION.

get_scan_data(scan_num)

param scan_num

DESCRIPTION.

get_scan_list_data(scan_list)

param scan_num

DESCRIPTION.

avg_N_bin_scans(scan_list[, xgrid, binning])

Averages data defined by the counter list, clist, onto an optional xgrid.

plot_scans(scan_list[, ylims, xlims, ...])

Plot a list of scans from the spec file.

plot_mesh_scan(scan_num[, skip_plot, ...])

Plot a single mesh scan from the spec file.

plot_scan_sequence(scan_sequence[, ylims, ...])

Plot a list of scans from the spec file.

export_scan_sequence(scan_sequence, path, ...)

Exports spec data for each scan list in the sequence as individual file.

fit_scans(scans, mod, pars[, ylims, xlims, ...])

Fit, plot, and return the data of scans.

fit_scan_sequence(scan_sequence, mod, pars)

Fit, plot, and return the data of a scan sequence.

get_last_fig_number()

Return the last figure number of all opened figures for plotting data in the same figure during for-loops.

get_next_fig_number()

Return the number of the next available figure.

get_clist()[source]

Returns a list of counters as defined by the user. If the counters where defined in a dict it will be converted to a list for backwards compatibility.

Returns

clist (list[str]) – list of counter names to evaluate.

traverse_counters(clist, source_cols='')[source]

Traverse all counters and replace all predefined counter definitions. Returns also a list of the included source counters for error propagation.

Parameters
  • clist (list[str]) – Initial counter list.

  • source_cols (list[str], optional) – counters in the raw source data.

Returns

(tuple)

  • resolved_counters (list[str]) - resolved counters.

  • source_counters (list[str]) - all source counters in the resolved counters.

resolve_counter_name(col_name, source_cols='')[source]

Replace all predefined counter definitions in a given counter name. The function works recursively.

Parameters
  • col_name (str) – initial counter string.

  • source_cols (list[str], optional) – columns in the source data.

Returns

(tuple)

  • col_string (str) - resolved counter string.

  • source_counters (list[str]) - source counters in the col_string

col_string_to_eval_string(col_string, array_name='spec_data')[source]

Use regular expressions in order to generate an evaluateable string from the counter string in order to append the new counter to the spec data.

Parameters
  • col_string (str) – Definition of the counter.

  • mode (int) – Flag for different modes

Returns

eval_string (str)

Evaluateable string to add the new counter

to the spec data.

add_custom_counters(spec_data, scan_num, source_counters)[source]

Add custom counters to the spec data array. This is a stub for child classes.

Parameters
  • spec_data (ndarray) – Data array from the spec scan.

  • scan_num (int) – Scan number of the spec scan.

  • list (source_counters) – List of the source counters and custom counters from the clist and xcol.

Returns

spec_data (ndarray) – Updated data array from the spec scan.

filter_data(data)[source]
Parameters

data (TYPE) – DESCRIPTION.

Returns

TYPE – DESCRIPTION.

get_scan_data(scan_num)[source]
Parameters

scan_num (TYPE) – DESCRIPTION.

Returns

TYPE – DESCRIPTION.

get_scan_list_data(scan_list)[source]
Parameters

scan_num (TYPE) – DESCRIPTION.

Returns

TYPE – DESCRIPTION.

avg_N_bin_scans(scan_list, xgrid=array([], dtype=float64), binning=True)[source]

Averages data defined by the counter list, clist, onto an optional xgrid. If no xgrid is given the x-axis data of the first scan in the list is used instead.

Parameters
  • scan_list (List[int]) – List of scan numbers.

  • xgrid (Optional[ndarray]) – Grid to bin the data to - default in empty so use the x-axis of the first scan.

Returns

avg_data (ndarray) – Averaged data for the scan list. std_data (ndarray) : Standart derivation of the data for the scan list. err_data (ndarray) : Error of the data for the scan list. name (str) : Name of the data set.

plot_scans(scan_list, ylims=[], xlims=[], fig_size=[], xgrid=[], yerr='std', xerr='std', norm2one=False, binning=True, label_text='', title_text='', skip_plot=False, grid_on=True, ytext='', xtext='', fmt='-o')[source]

Plot a list of scans from the spec file. Various plot parameters are provided. The plotted data are returned.

Parameters
  • scan_list (List[int]) – List of scan numbers.

  • ylims (Optional[ndarray]) – ylim for the plot.

  • xlims (Optional[ndarray]) – xlim for the plot.

  • fig_size (Optional[ndarray]) – Figure size of the figure.

  • xgrid (Optional[ndarray]) – Grid to bin the data to - default in empty so use the x-axis of the first scan.

  • yerr (Optional[ndarray]) – Type of the errors in y: [err, std, none] default is ‘std’.

  • xerr (Optional[ndarray]) – Type of the errors in x: [err, std, none] default is ‘std’.

  • norm2one (Optional[bool]) – Norm transient data to 1 for t < t0 default is False.

  • label_text (Optional[str]) – Label of the plot - default is none.

  • title_text (Optional[str]) – Title of the figure - default is none.

  • skip_plot (Optional[bool]) – Skip plotting, just return data default is False.

  • grid_on (Optional[bool]) – Add grid to plot - default is True.

  • ytext (Optional[str]) – y-Label of the plot - defaults is none.

  • xtext (Optional[str]) – x-Label of the plot - defaults is none.

  • fmt (Optional[str]) – format string of the plot - defaults is -o.

Returns

y2plot (OrderedDict) – y-data which was plotted. x2plot (ndarray) : x-data which was plotted. yerr2plot (OrderedDict) : y-error which was plotted. xerr2plot (ndarray) : x-error which was plotted. name (str) : Name of the data set.

plot_mesh_scan(scan_num, skip_plot=False, grid_on=False, ytext='', xtext='', levels=20, cbar=True)[source]

Plot a single mesh scan from the spec file. Various plot parameters are provided. The plotted data are returned.

Parameters
  • scan_num (int) – Scan number of the spec scan.

  • skip_plot (Optional[bool]) – Skip plotting, just return data default is False.

  • grid_on (Optional[bool]) – Add grid to plot - default is False.

  • ytext (Optional[str]) – y-Label of the plot - defaults is none.

  • xtext (Optional[str]) – x-Label of the plot - defaults is none.

  • levels (Optional[int]) – levels of contour plot - defaults is 20.

  • cbar (Optional[bool]) – Add colorbar to plot - default is True.

Returns

xx, yy, zz – x,y,z data which was plotted

plot_scan_sequence(scan_sequence, ylims=[], xlims=[], fig_size=[], xgrid=[], yerr='std', xerr='std', norm2one=False, binning=True, sequence_type='', label_text='', title_text='', skip_plot=False, grid_on=True, ytext='', xtext='', fmt='-o')[source]

Plot a list of scans from the spec file. Various plot parameters are provided. The plotted data are returned.

Parameters
  • (List[ (scan_sequence) – List/Tuple[List[int], int/str]]) : Sequence of scan lists and parameters.

  • ylims (Optional[ndarray]) – ylim for the plot.

  • xlims (Optional[ndarray]) – xlim for the plot.

  • fig_size (Optional[ndarray]) – Figure size of the figure.

  • xgrid (Optional[ndarray]) – Grid to bin the data to - default in empty so use the x-axis of the first scan.

  • yerr (Optional[ndarray]) – Type of the errors in y: [err, std, none] default is ‘std’.

  • xerr (Optional[ndarray]) – Type of the errors in x: [err, std, none] default is ‘std’.

  • norm2one (Optional[bool]) – Norm transient data to 1 for t < t0 default is False.

  • sequence_type (Optional[str]) – Type of the sequence: [fluence, delay, energy, theta, position, voltage, none, text] - default is enumeration.

  • label_text (Optional[str]) – Label of the plot - default is none.

  • title_text (Optional[str]) – Title of the figure - default is none.

  • skip_plot (Optional[bool]) – Skip plotting, just return data default is False.

  • grid_on (Optional[bool]) – Add grid to plot - default is True.

  • ytext (Optional[str]) – y-Label of the plot - defaults is none.

  • xtext (Optional[str]) – x-Label of the plot - defaults is none.

  • fmt (Optional[str]) – format string of the plot - defaults is -o.

Returns

sequence_data (OrderedDict) – Dictionary of the averaged scan data. parameters (List[str, float]) : Parameters of the sequence. names (List[str]) : List of names of each data set. label_texts (List[str]) : List of labels for each data set.

export_scan_sequence(scan_sequence, path, fileName, yerr='std', xerr='std', xgrid=[], norm2one=False, binning=True)[source]

Exports spec data for each scan list in the sequence as individual file.

Parameters
  • (List[ (scan_sequence) – List/Tuple[List[int], int/str]]) : Sequence of scan lists and parameters.

  • path (str) – Path of the file to export to.

  • fileName (str) – Name of the file to export to.

  • yerr (Optional[ndarray]) – Type of the errors in y: [err, std, none] default is ‘std’.

  • xerr (Optional[ndarray]) – Type of the errors in x: [err, std, none] default is ‘std’.

  • xgrid (Optional[ndarray]) – Grid to bin the data to - default in empty so use the x-axis of the first scan.

  • norm2one (Optional[bool]) – Norm transient data to 1 for t < t0 default is False.

fit_scans(scans, mod, pars, ylims=[], xlims=[], fig_size=[], xgrid=[], yerr='std', xerr='std', norm2one=False, binning=True, sequence_type='text', label_text='', title_text='', ytext='', xtext='', select='', fit_report=0, show_single=False, weights=False, fit_method='leastsq', offset_t0=False, plot_separate=False, grid_on=True, fmt='o')[source]

Fit, plot, and return the data of scans.

This is just a wrapper for the fit_scan_sequence method

fit_scan_sequence(scan_sequence, mod, pars, ylims=[], xlims=[], fig_size=[], xgrid=[], yerr='std', xerr='std', norm2one=False, binning=True, sequence_type='', label_text='', title_text='', ytext='', xtext='', select='', fit_report=0, show_single=False, weights=False, fit_method='leastsq', offset_t0=False, plot_separate=False, grid_on=True, last_res_as_par=False, sequence_data=[], fmt='o')[source]

Fit, plot, and return the data of a scan sequence.

Parameters
  • (List[ (scan_sequence) – List/Tuple[List[int], int/str]]) : Sequence of scan lists and parameters.

  • mod (Model[lmfit]) – lmfit model for fitting the data.

  • pars (Parameters[lmfit]) – lmfit parameters for fitting the data.

  • ylims (Optional[ndarray]) – ylim for the plot.

  • xlims (Optional[ndarray]) – xlim for the plot.

  • fig_size (Optional[ndarray]) – Figure size of the figure.

  • xgrid (Optional[ndarray]) – Grid to bin the data to - default in empty so use the x-axis of the first scan.

  • yerr (Optional[ndarray]) – Type of the errors in y: [err, std, none] default is ‘std’.

  • xerr (Optional[ndarray]) – Type of the errors in x: [err, std, none] default is ‘std’.

  • norm2one (Optional[bool]) – Norm transient data to 1 for t < t0 default is False.

  • sequence_type (Optional[str]) – Type of the sequence: [fluence, delay, energy, theta] - default is fluence.

  • label_text (Optional[str]) – Label of the plot - default is none.

  • title_text (Optional[str]) – Title of the figure - default is none.

  • ytext (Optional[str]) – y-Label of the plot - defaults is none.

  • xtext (Optional[str]) – x-Label of the plot - defaults is none.

  • select (Optional[str]) – String to evaluate as select statement for the fit region - default is none

  • fit_report (Optional[int]) – Set the fit reporting level: [0: none, 1: basic, 2: full] default 0.

  • show_single (Optional[bool]) – Plot each fit seperately - default False.

  • weights (Optional[bool]) – Use weights for fitting - default False.

  • fit_method (Optional[str]) – Method to use for fitting; refer to lmfit - default is ‘leastsq’.

  • offset_t0 (Optional[bool]) – Offset time scans by the fitted t0 parameter - default False.

  • plot_separate (Optional[bool]) – A single plot for each counter default False.

  • grid_on (Optional[bool]) – Add grid to plot - default is True.

  • last_res_as_par (Optional[bool]) – Use the last fit result as start values for next fit - default is False.

  • sequence_data (Optional[ndarray]) – actual exp. data are externally given. default is empty

  • fmt (Optional[str]) – format string of the plot - defaults is -o.

Returns

res (Dict[ndarray]) – Fit results. parameters (ndarray) : Parameters of the sequence. sequence_data (OrderedDict) : Dictionary of the averaged scan data.equenceData

get_last_fig_number()[source]

Return the last figure number of all opened figures for plotting data in the same figure during for-loops.

Returns

fig_number (int) – last figure number of all opened figures.

get_next_fig_number()[source]

Return the number of the next available figure.

Returns

next_fig_number (int) – next figure number of all opened figures.