Iguape package

Submodules

Iguape.Monitor module

This is Monitor Class. It was built to track and read a given Folder for new XRD Data. It’s dependent on the iguape_fileslist.txt text file. It was built to work only for Paineira XRD Data, but it can easily be adjusted for other situations.

class Iguape.Monitor.FolderMonitor(folder_path, fit_interval=None)

Bases: QThread

The Folder Monitor operates by tracking new or exiting data in a specified folder.

This class inherits the QThread class from PyQt. By reading the ‘iguape_filelist.txt’ file, it can track new or existing data files in the specified folder. Later, it reads the data and stores it in a pandas DataFrame. If a fitting interval is specified, it fits the data to a desired model and stores the fitting parameters in another DataFrame.

Parameters:

• (str) (folder_path)

• (list) (fit_interval)

__init__(folder_path, fit_interval=None)

The constructor for the FolderMonitor class. It defines all the flags necessary for the class to work, like the folder path, the fit interval, the fit model and the DataFrames.

Parameters:

• (str) (folder_path)

• (list (fit_interval)

• optional) (2theta interval selected to perform. Default is None)

new_data_signal

int = …, arguments: Sequence = …) -> PYQT_SIGNAL

types is normally a sequence of individual types. Each type is either a type object or a string that is the name of a C++ type. Alternatively each type could itself be a sequence of types each describing a different overloaded signal. name is the optional C++ name of the signal. If it is not specified then the name of the class attribute that is bound to the signal is used. revision is the optional revision of the signal that is exported to QML. If it is not specified then 0 is used. arguments is the optional sequence of the names of the signal’s arguments.

Type:

pyqtSignal(*types, name

Type:

str = …, revision

run()

The run method is the main method of the FolderMonitor class. It reads the ‘iguape_filelist.txt’ file tracking all the XRD data in the folder. Then it reads the data and stores it as DataFrames. I also performs the peak fit, if a fit interval is specified.

set_distance(distance)

Method for defining the minimum distance between the two peak centers. Only used when the model is Split PseduoVoigt.

Parameters:

(float) (distance)

set_fit_interval(interval)

Method for defining the fit interval.

Parameters:

(list) (interval)

set_fit_model(model)

Method for defining the fit model.

Parameters:

(str) (model)

set_height(height)

Method for defining the minimum height of the two peaks. Only used when the model is Split PseduoVoigt.

Parameters:

(float) (height)

Iguape.Monitor.calculate_q_vector(wavelength: float, two_theta: ndarray)

Converts 2theta values into Q vector (Scattering vector).

\[Q = \frac{4\pi}{\lambda} \sin{\theta}\]

Parameters:

• wavelength (float) – wavelength in Angstroms

• two_theta (np.ndarray) – 2theta values array

Returns:

Q-vector

Return type:

Q-vector values array

Iguape.Monitor.counter()

Counter function. It counts the number of XRD data and returns its index.

Returns:

_Index of the XRD data

Return type:

int

Iguape.Monitor.data_read(path)

Data reading function.

It reads the data from a given path and returns the 2theta and Intensity arrays, Temperature and Kelvin Signal tag.

Parameters:

(str) (path)

Returns:

• x (np.array) (2theta array.)

• y (np.array) (Intensity array.)

• temp (float) (Temperature.)

• kelvin_signal (bool) (Kelvin Signal tag.)

Iguape.Monitor.normalize_array(array: array)

Normalizes (by the maximum) and array

Parameters:

array (np.array) – Array to be normalized

Returns:

Normalized (by maximum) array

Return type:

np.array

Iguape.Monitor.peak_fit(theta, intensity, interval, id, bkg='Linear', pars=None)

Peak fitting function for the PseudoVoigt model. Given a set of 2theta and Intensity arrays, it fits the data to the PseudoVoigt model and 2theta interval selected. It returns the fitting parameters.

Parameters:

• (np.array) (intensity)

• (np.array)

• (list) (interval)

• (str (bkg)

• optional) (Background model. Default is 'Linear'.)

Returns:

• dois_theta_0 (float) (Peak center.)

• fwhm (float) (Full Width at Half Maximum.)

• area (float) (Area under the peak.)

• r_squared (float) (R-squared value of the fit.)

• out (lmfit.ModelResult) (ModelResult. Inherited from the lmfit package.)

• comps (dict) (Fitting components such as the backgroud and model function. Inherited from the lmfit package.)

• theta_fit (np.array) (2theta array for the fitting interval.)

Iguape.Monitor.peak_fit_split_gaussian(theta, intensity, interval, id, bkg='Linear', height=1000000000.0, distance=35, prominence=50, pars=None)

Peak fitting function for the Split PseudoVoigt model. Given a set of 2theta and Intensity arrays, it fits the data to the Split PseudoVoigt model and 2theta interval selected. It returns the fitting parameters.

Parameters:

• theta (np.array) – 2theta array.

• intensity (np.array) – Intensity array.

• interval (list) – 2theta interval for the peak fitting

• id (str) – String with the index and temperature of the XRD data.

• bkg (str, optional) – Background Model, defaults to ‘Linear’

• height (float, optional) – Minimum height of the peaks, defaults to 1e+09

• distance (int, optional) – Minimum distance bewtween the peaks, defaults to 35

• prominence (int, optional) – Minimum prominence of the peaks, defaults to 50

• pars (dict, optional) – Parameters dictionary (as described by lmfit), defaults to None

Returns:

tuple with fit results

Return type:

tuple

Iguape.Monitor.pseudo_voigt(x, amplitude, center, sigma, eta)

PseudoVoigt function, a linear combination of a Gaussian and a Lorentzian function.

Parameters:

• (np.array) (x)

• (float) (eta)

• (float)

• (float)

• (float)

Returns:

np.array

Return type:

PseudoVoigt function.

Notes

The PseudoVoigt function is defined as:

\[PV(x; A, \mu, \sigma, \eta) = \eta L(x; A, \mu, \sigma) + (1 - \eta) G(x; A, \mu, \sigma)\]

\[L(x; A, \mu, \sigma) = \frac{A}{\pi} \left[ \frac{\sigma}{(x-\mu)^2 + \sigma^{2}} \right]\]

\[G(x; A, \mu, \sigma) = \frac{A}{\sigma\sqrt{2\pi}}e^{\left[ \frac{-(x - \mu)^{2}}{2\sigma^{2}} \right]}\]

Iguape.Monitor.split_pseudo_voigt(x, amp1, cen1, sigma1, eta1, amp2, cen2, sigma2, eta2)

Split PseudoVoigt function, a linear combination of two PseudoVoigt functions.

Parameters:

• x (np.array) – 2theta array

• amp1 (np.array) – Peak amplitude for the first peak

• cen1 (float) – Peak center for the first peak.

• sigma1 (float) – Sigma value or standard deviation for the first peak.

• eta1 (float) – Eta value for the first peak (mixing parameter).

• amp2 (float) – Peak amplitude for the second peak.

• cen2 (float) – Peak center for the second peak.

• sigma2 (float) – Sigma value or standard deviation for the second peak.

• eta2 (float) – Eta value for the second peak (mixing parameter).

Returns:

Split PseudoVoigt function

Return type:

np.array

Notes

The Split PseudoVoigt function is defined as:

\[SPV(x; A1, \mu1, \sigma1, \eta1, A2, \mu2, \sigma2, \eta2) = PV1(x; A1, \mu1, \sigma1, \eta1) + PV2(x; A2, \mu2, \sigma2, \eta2)\]

Iguape.iguape module

This is the main script for the excution of the Paineira Graphical User Interface, a GUI for visualization and data processing during in situ experiments at Paineira. In this script, both GUIs used by the program are called and all of the backend functions and processes are defined.

class Iguape.iguape.CustomListViewModel(data=None, unit=None)

Bases: QAbstractListModel

Custom QListView made to display the data correctly.

Parameters:

QAbstractListModel (QAbstractListModel) – QAbstractListModel from PyQt5

__init__(data=None, unit=None)

Constructor

Parameters:

• data (pd.DataFrame, optional) – pandas DataFrame containing the names of the XRD data files. Defaults to None.. Defaults to None.

• unit (str, optional) – Temperature unit. Defaults to None.

data(index, role=0)

Parameters:

• index (QModelIndex) – PyQt5 index for each item

• role (Qt.DisplayRolde, optional) – PyQt5 Display Role for each item

Return type:

QVariant

flags(index)

Defines the properties of each item

Parameters:

index (QIndexModel) – PyQt5 index for each item

Returns:

_description_

Return type:

_type_

rowCount(parent=<PyQt5.QtCore.QModelIndex object>)

Return the length of the pandas DataFrame, i.e. the number of columns.

Parameters:

parent (_type_, optional) – _description_. Defaults to QModelIndex().

Returns:

_description_

Return type:

_type_

setData(index, value, role=2)

Changes the status of an item

Parameters:

• index (QIndexModel) – PyQt5 index for each item

• value (Qt.CheckState) – PyQt5 CheckState of the item

• role (Qt.EditRole, optional) – Defaults to Qt.EditRole.

Return type:

Bool

class Iguape.iguape.ExportWindow(figure: Figure, parent=None)

Bases: QDialog, Ui_Export_Figure

Custom QDialog for managing Figure export.

Parameters:

• QDialog (QDialog) – QDialog class from PyQt5

• Ui_Export_Figure (_type_) – Custom QDialog mode with QDesigner

__init__(figure: Figure, parent=None)

Constructor

Parameters:

• figure (matplotlib.figure.Figure) – matplotlib Figure class

• parent (_type_, optional) – Defaults to None.

get_color()

Gets the color selected with QColorDialog and sets the button color to it.

on_change_font_comboBox(font)

Changes the label and tick font.

Parameters:

font (str) – Font for label and ticks

on_change_label_size_spinBox(value)

Changes the label font size

Parameters:

value (int) – Font size

on_change_label_style_comboBox(style)

Changes the label style

Parameters:

style (str) – Label style (italic/bold/normal)

on_change_tick_size_spinBox(value)

Changes the tick font size

Parameters:

value (int) – Font size

on_change_tick_style_comboBox(style)

Changes the tick style

Parameters:

style (str) – Tick style (italic/bold/normal)

redraw_fig()

Redraws the Figure according to the changes made by the user.

save_fig()

Saves the Figure according to the chosen format.

class Iguape.iguape.FilterWindow(data=None, kelvin_signal=None, parent=None)

Bases: QDialog, Ui_Filter_Dialog

_summary_

Parameters:

• QDialog (QDialog) – QDialog class from PyQt5

• Ui_Filter_Dialog (QDialog) – Custom QDialog class made from QtDesigner

__init__(data=None, kelvin_signal=None, parent=None)

Constructor This method will initialize the QDialog and render a QListView() in the QDialog Window.

Parameters:

• data (pd.DataFrame, optional) – pandas DataFrame containing the names of the XRD data files. Defaults to None.

• kelvin_signal (Bool, optional) – Defines if the temperature unit is K or °C. Defaults to None.

• parent (_type_, optional) – _description_. Defaults to None.

apply()

Send the maks to IGUAPE’s main Window

mask

int = …, arguments: Sequence = …) -> PYQT_SIGNAL

types is normally a sequence of individual types. Each type is either a type object or a string that is the name of a C++ type. Alternatively each type could itself be a sequence of types each describing a different overloaded signal. name is the optional C++ name of the signal. If it is not specified then the name of the class attribute that is bound to the signal is used. revision is the optional revision of the signal that is exported to QML. If it is not specified then 0 is used. arguments is the optional sequence of the names of the signal’s arguments.

Type:

pyqtSignal(*types, name

Type:

str = …, revision

set_state_checked()

Sets the state of a given item as checked

set_state_selected()

Sets the state of a given item as selected

set_state_unchecked()

Sets the state of a given item as unchecked

setup_df()

Initializes the data as unchecked

class Iguape.iguape.FitWindow(parent=None)

Bases: QDialog, Ui_pk_window

QDialog Window to manage the Peak Fitting options.

Parameters:

• QDialog (QDialog) – QDialog from PyQt5

• Ui_pk_window (QDialog) – Custom QDialog made with QDesigner

__init__(parent=None)

Constructor

Parameters:

parent (optional) – Defaults to None.

clear_plot()

Clears the Figure

fit()

Performs the fit, with the model, interval and data selected in the XRD Data Tab.

onChanged_bkg_combo_box(text)

Changes the Background model. Currently only Linear model is applied.

Parameters:

text (_type_) – _description_

onChanged_distance_spinbox(value)

Sets the distance to value. Only valid for Spli PseudoVoigt model

Parameters:

value (int) – Minimum distance (in experimental points) between peaks.

onChanged_height_spinbox(value)

Sets the height to value (x1e09). Only valid for Spli PseudoVoigt model

Parameters:

value (float) – Minimum height of peaks. This float is multiplied by 1e09.

onChanged_pk_combo_box(text)

Routine for selecting the Peak Fitting Model via the ComboBox.

Parameters:

(str) (text)

onChanged_prominence_spinbox(value)

Sets the prominence to value. Only valid for Spli PseudoVoigt model

Parameters:

value (int) – Prominence of peaks. Prominence is the difference between the maximum value of the peak and the background of the measure.

onChanged_xrd_combo_box(text)

Adds a new XRD difractogram to the Figure. If there’s already two plotted, it will ask to user to clear the canvas.

Parameters:

text (str) – Text from the QComboBox. It identifies the XRD data.

onselect(xmin, xmax)

Sets the selected fit interval as [xmin, xmax]. It also draws a rectangle spaning the interval (axvspan)

Parameters:

• xmin (float) – Lower bound of the interval

• xmax (flat) – Upper bound of the interval

peak_fitting_error(error_message)

Shows QMessageBox if there’s been an error during peak fitting.

Parameters:

error_message (str) – Error message

peak_fitting_finished(time)

Shows QMessageBox when Peak Fitting is done.

Parameters:

time (float) – Time spent during Peak Fit

preview()

Displays a preview of the Peak Fit in the Figure.

setup_layout()

Setup the figures layout and connects the widgets to its functions.

update_progress(value)

Updates the QProgressDialog with a percentage progress

Parameters:

value (int) – Progress percentage

class Iguape.iguape.GarbageCollector

Bases: QThread

Garbage Collector class. Inherits a QThread and calls, every 3 seconds, the collect method of python’s garbage collector. The matpltolib Figures are updated using for loops. This consumes a lot of RAM memory. This method frees up some memory space.

Parameters:

QThread (QThread) – QThread class from PyQt5

__init__()

Constructor

run()

Calls the collect method from python’s Garbage Collector every 3 seconds.

class Iguape.iguape.Window(parent=None)

Bases: QMainWindow, Ui_MainWindow

Class for IGUAPE main window. It inherits QMainWindow from PyQt5 and Ui_MainWindow from GUI.iguape_GUI

Parameters:

• QMainWindow (QMainWindow) – QMainWindow from PyQt5

• Ui_MainWindow (QMainWindow) – Ui_MainWindow from GUI.iguape_GUI

__init__(parent=None)

Constructor for Window class

Parameters:

parent (optional) – Defaults to None.

_create_double_peak_dataframe()

Method for creating a DataFrame with the results of a Split-PseudoVoigt peak fitting. :returns: pandas DataFrame with fitting parameters from a Split-PseudoVoigt peak fit. :rtype: pd.DataFrame

_create_single_peak_dataframe()

Method for creating a DataFrame with the results of a PseudoVoigt peak fitting. :returns: pandas DataFrame with fitting parameters from a PseudoVoigt single peak fit. :rtype: pd.DataFrame

_get_mask(i: int)

Method for getting the \(2\theta\) mask, given the selection of interval by SpanSelector in the XRD Data tab.

Parameters:

i (int) – index of the XRD pattern

Returns:

slice object as a mask.

Return type:

slice

_open_url(url: str)

Uses QDesktopServices to open URL from logos.

Parameters:

url (str) – url to websites (as strings)

_plot_double_peak()

Hidden method to call Window._plot_parameter() in order to plot fitting parameters of a double peak.

_plot_fitting_parameters()

This method calls Window._plot_single_peak() or Window._plot_double_peak(), according to the profile model selected.

_plot_parameter(ax, x, y, ylabel, xlabel, label=None, color=None, marker='o', yerr=None)

Generic routine to plot xy data in a given axes. :param ax: A matplotlib Axes object :type ax: matplotlib.axes.Axes :param x: x-axis data :type x: list :param y: y-axis data :type y: list :param ylabel: y-axis label :type ylabel: str :param xlabel: x-axis label :type xlabel: str :param label: Displays label. Accepts True or False. Defaults to None. :type label: bool, optional :param color: matplotlib color. Defaults to None. :type color: str, optional :param marker: matplotlib marker. Defaults to ‘o’. :type marker: str, optional :param yerr: y-axis error. Defaults to None. :type yerr: list, optional

_plot_single_peak()

Hidden method to call Window._plot_parameter() in order to plot fitting parameters of a single peak.

_update_main_figure()

Routine to update XRD Data Tab graph. This calls other methods such as update_colormap and plots the selected XRD measures in the main figure.

about()

Initializes a QMessageBox with some info on IGUAPE.

apply_filter()

Initializes the FilterWindow class.

apply_temp_mask(mask)

Method for applying a temperature mask in the XRD measures. Recieves an array of booleans. The array has a length equal to the number of XRD data read by the Iguape.Monitor.FolderMonitor. :param mask: numpy array with booleans as entries :type mask: np.array

contour()

Draws a contour plot at the Contour Plot Tab graph.

create_graphs_layout()

Routine to initialize and connect UI elements. All parameters and flags are initiated and UI element’s signals are connected to its functions.

eventFilter(source: QLabel, event: QEvent)

eventFilter method for logo QLabel. It tracks a mouse press event and calls the Window._open_url()

Parameters:

• source (QLabel) – Object name of logo in IGUAPE UI (QLabel)

• event (QEvent) – QEvent to track mouse click

Returns:

Boolean value that determines the excution of Window._open_url()

Return type:

Bool

export_figure()

Method for initializing the ExportWindow class. This Window has the elements that control the fitting parameters.

handle_new_data(new_data)

This method is connected to the signal emited by Iguape.Monitor.FolderMonitor, which delivers a pd.DataFrame containing the XDR data.

Parameters:

new_data (pd.DataFrame) – pandas DataFrame to be concatenated with the existing one

measure_order_index(checked)

Method connected to the measure order QCheckBox. This method will change the colormaps that identify the XRD data. All of the Figures are updated accordingly.

Parameters:

checked (bool) – True or False

normalize()

Draws an intensities normalized plot at the Normalization Plot Tab graph.

on_change_color_pallete(index)

Sets the current item in the QComboBox.

Parameters:

index (int) – Integer representing the index of item in the Color pallete QComboBox.

on_change_vline_checkbox()

This method enables a Vertical Line cursor in the XRD Data Tab Figure.

on_mouse_move(event)

This method is connected to the canvas in the XRD Data Tab graph. It shows the temperature/index of the closest XRD difractogram.

Parameters:

event (str) – matplotlib FigureCanvas event.

on_toggle_2theta_action()

This is triggred when the 2theta visualization option is selected by the user. This is the default visualization mode. The method updates the graphs to plot as function of 2theta.

on_toggle_Q_vector_action()

This is triggred when the Q vector visualization option is selected by the user. This renders a QDialog for user input of the wavelength and than updates the graphs to plot as function of Q.

onselect(xmin, xmax)

This method is passed as argument for the SpanSelector in the XRD Data Tab Graph. It sets the selected interval for visualization based on the min/max value received for 2theta.

Parameters:

• xmin (float) – minimum 2theta value of the interval selected in the XRD Data graph

• xmax (float) – maximum 2theta value of the interval selected in the XRD Data graph

read_data(path, normalize=False, Q=False)

Reads the XRD data using pandas read_csv function. Comments are identified by “#” and the header is identified by the first line.

Parameters:

• path (str)

• normalize (bool, optional) – If True the XRD intensities will be normalized. Defaults to False.

• Q (bool, optional) – If True the XRD x-axis will be converted from 2theta to the scattering vector Q. Defaults to False.

Returns:

2theta and Intensity numpy arrays read from the XRD data.

Return type:

(theta, intensity)

reset_interval()

Method for resetting the 2theta interval in the XRD Data graph to None

save_data_frame()

This method calls two hidden method that generates the DataFrame to be saved. It also writes comments (“#”) on the top of the csv file.

select_fit_interval()

Method for initializing the FitWindow class. This Window has the elements that control the fitting parameters.

select_folder()

Method for selecting a folder conatining the XRD data. In order for IGUAPE to read and monitor the folder, the file iguape_filelist.txt must be present.

temp_index(checked)

Method connected to the measure order QCheckBox. This method will change the colormaps that identify the XRD data. All of the Figures are updated accordingly.

Parameters:

checked (bool) – True or False

update_colormap(color_map_type: str, label: str)

Routine for updating the colormaps and norm used in the XRD Data and PeakFit tabs.

Parameters:

• color_map_type (str) – Column label of XRD patterns DataFrame. It can be temp or file_index

• label (str) – _description_

update_graphs()

Method to update Main Figure (XRD Data tab) and Plotting Parameters Figure (Peak Fitting tab).

validate_temp(min_value, max_value)

Method for validating the temperature value entered in the temperature QDoubleSpinBox. It returns the closest available temperature from the Monitor’s DataFrame

Parameters:

• min_value (float) – Minimum temperature

• max_value (float) – Maximum temperature

Returns:

(min_temp, max_temp) tuple with the closest min/max available temperature

Return type:

tuple

class Iguape.iguape.Worker(interval)

Bases: QThread

QThread that performs peak fitting in the selected XRD data. :param QThread: QThread class from PyQt5 :type QThread: QThread

__init__(interval)

Constructor for the peak fitting thread.

Parameters:

• interval (list) – List in the form [\(2\theta_{i}\), \(2\theta_{f}\)] where \(2\theta_{i}\) and \(2\theta_{f}\) are, respectively,

• fitting. (the initial and final values of the 2theta interval selected to perfor peak)

error

int = …, arguments: Sequence = …) -> PYQT_SIGNAL

types is normally a sequence of individual types. Each type is either a type object or a string that is the name of a C++ type. Alternatively each type could itself be a sequence of types each describing a different overloaded signal. name is the optional C++ name of the signal. If it is not specified then the name of the class attribute that is bound to the signal is used. revision is the optional revision of the signal that is exported to QML. If it is not specified then 0 is used. arguments is the optional sequence of the names of the signal’s arguments.

Type:

pyqtSignal(*types, name

Type:

str = …, revision

finished

int = …, arguments: Sequence = …) -> PYQT_SIGNAL

types is normally a sequence of individual types. Each type is either a type object or a string that is the name of a C++ type. Alternatively each type could itself be a sequence of types each describing a different overloaded signal. name is the optional C++ name of the signal. If it is not specified then the name of the class attribute that is bound to the signal is used. revision is the optional revision of the signal that is exported to QML. If it is not specified then 0 is used. arguments is the optional sequence of the names of the signal’s arguments.

Type:

pyqtSignal(*types, name

Type:

str = …, revision

progress

int = …, arguments: Sequence = …) -> PYQT_SIGNAL

types is normally a sequence of individual types. Each type is either a type object or a string that is the name of a C++ type. Alternatively each type could itself be a sequence of types each describing a different overloaded signal. name is the optional C++ name of the signal. If it is not specified then the name of the class attribute that is bound to the signal is used. revision is the optional revision of the signal that is exported to QML. If it is not specified then 0 is used. arguments is the optional sequence of the names of the signal’s arguments.

Type:

pyqtSignal(*types, name

Type:

str = …, revision

run()

Performs peak fitting in the selected XRD data in the selected 2theta interval [\(2\theta_{i}\), \(2\theta_{f}\)]

Iguape.launcher module

Execution script. It goes to the directory where Iguape is installed and it executes the program (iguape.py)

Iguape.launcher.main()

_summary_

Module contents

This is the main script for the excution of the Paineira Graphical User Interface, a GUI for visualization and data processing during in situ experiments at Paineira. In this script, both GUIs used by the program are called and all of the backend functions and processes are defined.