lumicks.pylake.correlated_stack.CorrelatedStack¶

class CorrelatedStack(image_name, align=True)¶

CorrelatedStack acquired with Bluelake. Bluelake can export stacks of images to various formats. These can be opened and correlated to timeline data using CorrelatedStack.

Parameters:	image_name : str Filename for the image stack. Typically a TIFF file recorded from a camera in Bluelake. align : bool If enabled, multi-channel images will be reconstructed from the image alignment metadata from Bluelake. The default value is `True`.

Examples

from lumicks import pylake

# Loading a stack.
stack = pylake.CorrelatedStack("example.tiff")

# Making a plot where force is correlated to images in the stack.
file = pylake.File("example.h5")
stack.plot_correlated(file.force1x)

# Determine the force trace averaged over frame 2...9.
file.force1x.downsampled_over(stack[2:10].frame_timestamp_ranges)

__init__(image_name, align=True)¶: Initialize self. See help(type(self)) for accurate signature.

Methods

`__init__`(image_name[, align])	Initialize self.
`crop_and_rotate`([frame, channel, show_title])	Open a widget to interactively edit the image stack.
`crop_by_pixels`(x_min, x_max, y_min, y_max)	Crop the image stack by pixel values.
`define_tether`(point1, point2)	Returns a copy of the stack rotated such that the tether defined by `point_1` and `point_2` is horizontal.
`export_tiff`(file_name[, roi])	Export a video of a particular scan plot
`from_data`(data[, name, start_idx, stop_idx])	Deprecated since version 0.10.1.
`from_dataset`(data[, name, start_idx, stop_idx])	Construct CorrelatedStack from image stack object
`get_image`([channel])	Get image data for the full stack as an `np.ndarray`.
`plot`([frame, channel, show_title])	Plot image from image stack
`plot_correlated`(channel_slice[, frame, …])	Downsample channel on a frame by frame basis and plot the results.
`plot_tether`(**kwargs)	Plot a line at the tether position.

Attributes

`frame_timestamp_ranges`	List of time stamps.
`num_frames`	Number of frames in the stack.
`raw`	Raw frame data.
`start`	Starting time stamp of the stack.
`stop`	Final time stamp of the stack.
`timestamps`	Deprecated since version 0.11.1.

__getitem__(item)¶: All indexing is in frames

crop_and_rotate(frame=0, channel='rgb', show_title=True, **kwargs)¶

Open a widget to interactively edit the image stack.

Actions include:

scrolling through frames using the mouse wheel
left-click to define the location of the tether

Parameters:	frame : int, optional Index of the frame to plot. channel : ‘rgb’, ‘red’, ‘green’, ‘blue’, None; optional Channel to plot for RGB images (None defaults to ‘rgb’) Not used for grayscale images show_title : bool, optional Controls display of auto-generated plot title **kwargs Forwarded to `matplotlib.pyplot.imshow()`.

Examples

from lumicks import pylake import matplotlib.pyplot as plt

# Loading a stack. stack = pylake.CorrelatedStack(“example.tiff”) widget = stack.crop_and_rotate() plt.show()

# Select cropping ROI by right-click drag # Select tether ends by left-click

# Grab the updated image stack new_stack = widget.image

crop_by_pixels(x_min, x_max, y_min, y_max)¶

Crop the image stack by pixel values.

Parameters:	x_min : int minimum x pixel (inclusive) x_max : int maximum x pixel (exclusive) y_min : int minimum y pixel (inclusive) y_max : int maximum y pixel (exclusive)

define_tether(point1, point2)¶

Returns a copy of the stack rotated such that the tether defined by point_1 and point_2 is horizontal.

Parameters:	point_1 : (float, float) (x, y) coordinates of the tether start point point_2 : (float, float) (x, y) coordinates of the tether end point

export_tiff(file_name, roi=None)¶

Export a video of a particular scan plot

Parameters:	file_name : str File name to export to. roi : list_like region of interest in pixel values [xmin, xmax, ymin, ymax] Deprecated since v0.10.1 Instead, use `CorrelatedStack.crop_by_pixels()` to select the ROI before exporting.”

classmethod from_data(data, name=None, start_idx=0, stop_idx=None)¶: Deprecated since version 0.10.1: Renamed to from_dataset() for consistency with Kymo and Scan.

classmethod from_dataset(data, name=None, start_idx=0, stop_idx=None)¶

Construct CorrelatedStack from image stack object

Parameters:	data : TiffStack TiffStack object. name : str Plot label of the correlated stack start_idx : int Index at the first frame. stop_idx: int Index beyond the last frame.

get_image(channel='rgb')¶

Get image data for the full stack as an np.ndarray.

Parameters:	channel : {‘red’, ‘green’, ‘blue’, ‘rgb’} The color channel of the requested data. For single-color data, this argument is ignored.

plot(frame=0, channel='rgb', show_title=True, **kwargs)¶

Plot image from image stack

Parameters:	frame : int, optional Index of the frame to plot. channel : ‘rgb’, ‘red’, ‘green’, ‘blue’, None; optional Channel to plot for RGB images (None defaults to ‘rgb’) Not used for grayscale images show_title : bool, optional Controls display of auto-generated plot title **kwargs Forwarded to `matplotlib.pyplot.imshow()`.

plot_correlated(channel_slice, frame=0, reduce=<function mean>, channel='rgb', figure_scale=0.75)¶

Downsample channel on a frame by frame basis and plot the results. The downsampling function (e.g. np.mean) is evaluated for the time between a start and end time of a frame. Note: In environments which support interactive figures (e.g. jupyter notebook with ipywidgets or interactive python) this plot will be interactive.

Parameters:

channel_slice : pylake.channel.Slice: Data slice that we with to downsample.
frame : int: Frame to show.
reduce : callable: The function which is going to reduce multiple samples into one. The default is numpy.mean(), but numpy.sum() could also be appropriate for some cases e.g. photon counts.
channel : ‘rgb’, ‘red’, ‘green’, ‘blue’, None; optional: Channel to plot for RGB images (None defaults to ‘rgb’) Not used for grayscale images
figure_scale : float: Scaling of the figure width and height. Values greater than one increase the size of the figure.

Examples

from lumicks import pylake

file = pylake.File("example.h5")
stack = pylake.CorrelatedStack("example.tiff")
stack.plot_correlated(file.force1x, frame=5)

plot_tether(**kwargs)¶

Plot a line at the tether position.

Parameters:	**kwargs Forwarded to :fun:`matplotlib.pyplot.plot`.

frame_timestamp_ranges¶: List of time stamps.

num_frames¶: Number of frames in the stack.

raw¶: Raw frame data.

Deprecated since version 0.10.1: Access to raw frame instances will be removed in a future release. All operations on these objects should be handled through the CorrelatedStack public API. For example, to retrieve the image data as an np.ndarray please use CorrelatedStack.get_image().

start¶: Starting time stamp of the stack.

stop¶: Final time stamp of the stack.

timestamps¶: Deprecated since version 0.11.1: For camera based images only the integration start/stop timestamps are defined. Use CorrelatedStack.frame_timestamp_ranges instead.