Scan

Module for describing different types of scans.

class abtem.scan.AbstractScan[source]

Abstract class to describe scans.

abstract property calibrations

The measurement calibrations associated with the scan.

Return type

tuple

copy()[source]

Make a copy.

abstract get_positions()[source]

Get the scan positions as numpy array.

abstract insert_new_measurement(measurement, indices, new_values)[source]

Insert new measurement values into a Measurement object or HDF5 file.

Parameters

  • measurement (Measurement object) – The measurement to which new values are inserted.

  • start (int) – First index of slice.

  • end (int) – Last index of slice.

  • new_values (ndarray) – New measurement values to be inserted. Length should be (end - start).

abstract property shape

The shape the scan.

Return type

tuple

class abtem.scan.GridScan(start, end, gpts=None, sampling=None, endpoint=False, batch_partition='squares', measurement_shift=None)[source]

Grid scan object.

Defines a scan on a regular grid.

Parameters

  • start (two float) – Start corner of the scan [Å].

  • end (two float) – End corner of the scan [Å].

  • gpts (two int) – Number of scan positions in the x- and y-direction of the scan.

  • sampling (two float) – Sampling rate of scan positions [1 / Å].

  • endpoint (bool) – If True, end is the last position. Otherwise, it is not included. Default is False.

  • batch_partition ('squares' or 'lines') – Specify how to split the scan into batches. If ‘squares’, the scan position batches are divided into the best matching squares for the batch size. If ‘lines’, the batches are divided into lines of scan positions.

  • measurement_shift (two int) – The insertion indices of new measurements will be shifted by this amount in x and y. This is used for correctly inserting measurements collected from a partitioned scan.

add_to_mpl_plot(ax, alpha=0.33, facecolor='r', edgecolor='r', **kwargs)[source]

Add a visualization of the scan area to a matplotlib plot.

Parameters

  • ax (matplotlib Axes) – The axes of the matplotlib plot the visualization should be added to.

  • alpha (float, optional) – Transparency of the scan area visualization. Default is 0.33.

  • facecolor (str, optional) – Color of the scan area visualization.

  • edgecolor (str, optional) – Color of the edge of the scan area visualization.

  • kwargs – Additional options for matplotlib.patches.Rectangle used for scan area visualization as keyword arguments.

property calibrations

The measurement calibrations associated with the scan.

Return type

tuple

copy()

Make a copy.

property end

End corner of the scan [Å].

Return type

ndarray

property extent

Grid extent in each dimension [Å].

get_positions()[source]

Get the scan positions as numpy array.

Return type

ndarray

get_scan_area()[source]

Get the area of the scan.

Return type

float

property gpts

Number of grid points in each dimension.

insert_new_measurement(measurement, indices, new_measurement)[source]

Insert new measurement values into a Measurement object or HDF5 file.

Parameters

  • measurement (Measurement object) – The measurement to which new values are inserted.

  • start (int) – First index of slice.

  • end (int) – Last index of slice.

  • new_values (ndarray) – New measurement values to be inserted. Length should be (end - start).

partition_scan(partitions)[source]

Partition the scan into smaller grid scans

Parameters

partitions (two int) – The number of partitions to create in x and y.

Returns

Return type

List of GridScan objects

property sampling

Grid sampling in each dimension [1 / Å].

property shape

The shape the scan.

property start

Start corner of the scan [Å].

Return type

ndarray

class abtem.scan.LineScan(start, end=None, angle=0.0, gpts=None, sampling=None, margin=0.0, endpoint=True)[source]

Line scan object.

Defines a scan along a straight line.

Parameters

  • start (two float) – Start point of the scan [Å].

  • end (two float) – End point of the scan [Å].

  • gpts (int) – Number of scan positions.

  • sampling (float) – Sampling rate of scan positions [1 / Å].

  • endpoint (bool) – If True, end is the last position. Otherwise, it is not included. Default is True.

add_to_mpl_plot(ax, color='r', width=0.2, **kwargs)[source]

Add a visualization of a scan line to a matplotlib plot.

Parameters

  • ax (matplotlib Axes) – The axes of the matplotlib plot the visualization should be added to.

  • linestyle (str, optional) – Linestyle of scan line. Default is ‘-‘.

  • color (str, optional) – Color of the scan line. Default is ‘r’.

  • kwargs – Additional options for matplotlib.pyplot.plot as keyword arguments.

property angle

End point of the scan [Å].

Return type

float

property calibrations

The measurement calibrations associated with the scan.

Return type

Tuple[Calibration]

copy()

Make a copy.

property direction

Direction of the scan line.

Return type

Tuple[float, float]

property end

End point of the scan [Å].

Return type

Tuple[float, float]

property extent

Grid extent in each dimension [Å].

get_positions()[source]

Get the scan positions as numpy array.

Return type

ndarray

property gpts

Number of grid points in each dimension.

insert_new_measurement(measurement, indices, new_measurement_values)[source]

Insert new measurement values into a Measurement object or HDF5 file.

Parameters

  • measurement (Measurement object) – The measurement to which new values are inserted.

  • start (int) – First index of slice.

  • end (int) – Last index of slice.

  • new_values (ndarray) – New measurement values to be inserted. Length should be (end - start).

property sampling

Grid sampling in each dimension [1 / Å].

property shape

The shape the scan.

Return type

Tuple[int]

property start

Start point of the scan [Å].

Return type

Tuple[float, float]

class abtem.scan.PositionScan(positions)[source]

Position scan object.

Defines a scan based on user-provided positions.

Parameters

positions (list) – A list of xy scan positions [Å].

add_to_mpl_plot(ax, marker='o', color='r', **kwargs)[source]

Add a visualization of the scan positions to a matplotlib plot.

Parameters

  • ax (matplotlib Axes) – The axes of the matplotlib plot the visualization should be added to.

  • marker (str, optional) – Style of scan position markers. Default is ‘-‘.

  • color (str, optional) – Color of the scan position markers. Default is ‘r’.

  • kwargs – Additional options for matplotlib.pyplot.plot as keyword arguments.

property calibrations

The measurement calibrations associated with the scan.

Return type

tuple

copy()

Make a copy.

get_positions()[source]

Get the scan positions as numpy array.

insert_new_measurement(measurement, indices, new_measurement)[source]

Insert new measurement values into a Measurement object or HDF5 file.

Parameters

  • measurement (Measurement object) – The measurement to which new values are inserted.

  • start (int) – First index of slice.

  • end (int) – Last index of slice.

  • new_values (ndarray) – New measurement values to be inserted. Length should be (end - start).

property shape

The shape the scan.

Return type

tuple