GDEFReader 0.0.1a40

Tool to read/process *.gdf AFM measurement files

GDEFReader

Tool to read *.gdf files (DME AFM)

Features

• import measurements from *.gdf file into python

• create maps using matplotlib

• analyze nanoindents

• stich measurements

• create customizable output (e.g. *.png or power point presentations)

Table of Contents

• GDEFReader

  • Features

• API documentation

  • Module gdef_reader.gdef_importer

  • Module afm_tools.gdef_indent_analyzer

  • Module gdef_reader.gdef_measurement

    • class GDEFMeasurement

    • class GDEFSettings

  • Module afm_tools.gdef_sticher

  • Module afm_tools.background_correction

API documentation

Module gdef_reader.gdef_importer

class GDEFImporter

This class is used to read data from a *.gdf file (DME AFM) into python. This can be done like:

from gdef_reader.gdef_importer import GDEFImporter
impported_data = GDEFImporter(gdf_path)  # gdf_path should be a pathlib.Path to a *.gdf file

Methods:

• __init__

  __init__(self, filename: Optional[pathlib.Path] = None)

  filename:

  Path to *.gdf file. If it is None (default), a file has to be loaded via GDEFImporter.load().

• export_measurements

  export_measurements(self, path: pathlib.Path = None, create_images: bool = False) -> List[gdef_reader.gdef_measurement.GDEFMeasurement]

  Create a list of GDEFMeasurement-Objects from imported data. The optional parameter create_images can be used to show a matplotlib Figure for each GDEFMeasurement (default value is False).

  path:

  Save path for GDEFMeasurement-objects (and png’s if create_images). No saved files, if None.

  create_images:

  Show a matplotlib Figure for each GDEFMeasurement; used for debugging (default: False)

  return:

  list of GDEFMeasurement-Objects

• load

  load(self, filename: Union[str, pathlib.Path]) -> None

  Import data from a *.gdf file.

  filename:

  Path to *.gdf file.

  return:

  None

Instance Attributes:

• basename: Path.stem of the imported *.gdf file.

• bg_correction_type: BGCorrectionType for loaded measurements.

• keep_z_offset: If False (default), z-values for each imported measurement are corrected so that mean(z) == 0.

Module afm_tools.gdef_indent_analyzer

class GDEFIndentAnalyzer

Class to analyze a GDEFMeasurment with an indent.

Class Attributes:

• max_pixel_radius_value

• pixel_radius_distance_matrix

Methods:

• __init__

  __init__(self, measurement: gdef_reader.gdef_measurement.GDEFMeasurement)

  measurement:

  GDEFMeasurement with the indent to analyze.

• add_map_with_indent_pile_up_mask_to_axes

  add_map_with_indent_pile_up_mask_to_axes(self, ax: matplotlib.axes._axes.Axes, roughness_part=0.05) -> matplotlib.axes._axes.Axes

  Add a topography map with a color mask for pile-up to the given ax. Pile-up is determined as all pixels with z>0 + roughness_part * z_max

  ax:

  Axes object, to whitch the masked map should be added

  roughness_part:

  return:

  Axes

• get_summary_table_data

  get_summary_table_data(self) -> List[list]

  Returns a table (list of lists) with data of the indent. The result can be used directly to fill a pptx-table with python-ppxt-interface.

  return:

Module gdef_reader.gdef_measurement

class GDEFMeasurement

Class containing data of a single measurement from *.gdf file.

Methods:

• __init__

  __init__(self)

  Initialize self. See help(type(self)) for accurate signature.

• correct_background

  correct_background(self, correction_type: afm_tools.background_correction.BGCorrectionType = <BGCorrectionType.legendre_1: 3>, keep_offset: bool = False)

  Corrects background using the given correction_type on values_original and save the result in values. If keep_z_offset is True, the mean value of dataset is preserved. Otherwise the average value is set to zero. Right now only changes topographical data. Also, the original data can be obtained again via GDEFMeasurement.values_original.

  correction_type:

  select type of background correction

  keep_offset:

  If True (default) keeps average offset, otherwise average offset is reduced to 0.

  return:

  None

• create_plot

  create_plot(self, max_figure_size=(4, 4), dpi=96, add_id: bool = False, trim: bool = True) -> matplotlib.figure.Figure

  Returns a matplotlib figure of measurment data. If GDEFMeasurement.comment is not empty, the comment is used as title. Otherwise a default title with the type of measurement data is created.

  max_figure_size:

  Max. figure size. The actual figure size might be smaller.

  dpi:

  dpi value for Figure

  add_id:

  trim:

  return:

  Figure

• get_summary_table_data

  get_summary_table_data(self) -> List[list]

  Create table data (list of list) summary of the measurement. The result can be used directly to fill a pptx-table with python-ppxt-interface.

• load_from_pickle

  load_from_pickle(filename: pathlib.Path) -> 'GDEFMeasurement'

  Static method to load and return a measurement object using pickle. Take note, that pickle is not a save module to load data. Make sure to only use files from trustworthy sources.

  filename:

  return:

  GDEFMeasurement

• save_as_pickle

  save_as_pickle(self, filename)

  Save the measurement object using pickle. This is useful for example, if the corresponding *.gdf file contains a lot of measurements, but only a few of them are needed. Take note, that pickle is not a save module to load data. Make sure to only use files from trustworthy sources.

  filename:

  return:

  None

• save_png

  save_png(self, filename, max_figure_size=(4, 4), dpi: int = 300, transparent: bool = False)

  Save a matplotlib.Figure of the measurement as a *.png.

  filename:

  max_figure_size:

  Max size of the Figure. The final size might be smaller in x or y.

  dpi:

  (default 300)

  transparent:

  Set background transparent (default False).

  return:

• set_topography_to_axes

  set_topography_to_axes(self, ax: matplotlib.axes._axes.Axes, add_id: bool = False)

  Sets the measurement data as diagram to a matplotlib Axes. If GDEFMeasurement.comment is not empty, the comment is used as title. Otherwise a default title with the type of measurement data is created.

  ax:

  Axes object to witch the topography is written.

  add_id:

  Adds block_id before title text (default False)

  return:

  None

Instance Attributes:

• background_correction_type

• comment: Comment text given for the measurement.

• gdf_basename: Path.stem of the imported *.gdf file.

• gdf_block_id: Block ID in original *.gdf file. Might be used to filter measurements.

• name: Returns a name of the measurement created from original *.gdf filename and the gdf_block_id

• pixel_width

• preview

• pygdf_filename

• settings: GDEFSettings object

• values_original: Original measurement data (read-only property)

• values_original: Original measurement data (read-only property)

class GDEFSettings

Stores all the settings used during measurement.

Methods:

• __init__

  __init__(self)

  Initialize self. See help(type(self)) for accurate signature.

• pixel_area

  pixel_area(self) -> float

  Return pixel-area [m^2]

• shape

  shape(self) -> Tuple[int, int]

  Returns the shape of the scanned area (columns, lines). In case of aborted measurements, lines is reduced by the number of missing lines.

• size_in_um_for_plot

  size_in_um_for_plot(self) -> Tuple[float, float, float, float]

  Returns the size of the scanned area as a tuple for use with matplotlib.

Instance Attributes:

• aux_gain

• bias_voltage

• calculated

• columns

• digital_loop

• direct_ac

• fft_type

• fixed_max

• fixed_min

• fixed_palette

• frequency_offset

• id

• invert_line_mean

• invert_plane_corr

• line_mean_order

• line_mean_order

• lines: total number of scan lines (including missing lines)

• loop_filter

• loop_gain

• loop_int

• max_height: scan area height [m]

• max_width: scan area width [m]

• measured_amplitude

• missing_lines: number of missing lines (e.g. due to aborted measurement)

• offset_pos

• offset_x

• offset_y

• phase_shift

• pixel_blend

• pixel_height: Pixel-height [m] (read-only property)

• pixel_width: Pixel-width [m] (read-only property)

• q_boost

• q_factor

• retrace_type

• retrace_type

• scan_direction

• scan_mode

• scan_speed: [�m/s]

• scanner_range

• set_point

• source_channel

• x_calib

• xy_linearized

• y_calib

• z_calib

• z_linearized

• z_unit

• zero_scan

Module afm_tools.gdef_sticher

class GDEFSticher

GDEFSticher combines/stiches several AFM area-measurements using cross-corelation to find the best fit. To reduce calculation time, the best overlap position is only searched in a fraction of the measurement area (defined by parameter initial_x_offset_fraction), and each measutrement is added to the right side. Make sure the given list of measurements is ordered from left to right, otherwise wrong results are to be expected. To evaluate the stiching, show_control_figures can be set to True. This creates a summary image for each stiching step (using matplotlib plt.show()).

Methods:

• __init__

  __init__(self, measurements: List[gdef_reader.gdef_measurement.GDEFMeasurement], initial_x_offset_fraction: float = 0.35, show_control_figures: bool = False)

  measurements:

  initial_x_offset_fraction:

  used to specify max. overlap area, thus increasing speed and reducing risk of wrong stiching

  show_control_figures:

• stich

  stich(self, initial_x_offset_fraction: float = 0.35, show_control_figures: bool = False) -> numpy.ndarray

  Stiches a list of GDEFMeasurement.values using cross-correlation.

  initial_x_offset_fraction:

  used to specify max. overlap area, thus increasing speed and reducing risk of wrong stiching

  return:

  stiched np.ndarray

Module afm_tools.background_correction

class BGCorrectionType

Class Attributes:

• gradient

• legendre_0

• legendre_1

• legendre_2

• legendre_3

• raw_data