pymaid.tiles.TileLoader

class pymaid.tiles.TileLoader(bbox, stack_id, zoom_level=0, coords='NM', image_mirror='auto', mem_lim=4000, remote_instance=None, **fetch_kwargs)[source]

Load tiles from CATMAID, stitch into image and render output.

Important

Loading lots of tiles is memory intensive. A single 100x100 pixel image already requires 80Kb, 1000x1000 8Mb and so on.

Parameters:

  • bbox (list | numpy.array) – Window to crop: left, right, top, bottom, z1, [z2, stepsize]. Can be single or list/array of bounding boxes. z2 can be omitted, in which case z2 = z1. Optionally you can provide a 7th stepsize parameter.

  • stack_id (int) – ID of EM image stack to use.

  • zoom_level (int, optional) – Zoom level

  • coords ('NM' | 'PIXEL', optional) – Dimension of bbox.

  • image_mirror (int | str | 'auto', optional) –

    Image mirror to use:

    • int is interpreted as mirror ID

    • str must be URL

    • 'auto' will automatically pick fastest

  • mem_lim (int, optional) – Memory limit in megabytes for loading tiles. This restricts the number of tiles that can be simultaneously loaded into memory.

Examples

>>> # Generate the job
>>> job = pymaid.tiles.TileLoader([119000, 124000,
...                               36000, 42000,
...                               4050],
...                               stack_id=5,
...                               coords='PIXEL')
>>> # Load, stitch and crop the required EM image tiles
>>> job.load_in_memory()
>>> # Render image
>>> ax = job.render_im(slider=False, figsize=(12, 12))
>>> # Add nodes
>>> job.render_nodes(ax, nodes=True, connectors=False)
>>> # Add scalebar
>>> job.scalebar(size=1000, ax=ax, label=False)
>>> # Show
>>> plt.show()

Initialise class.

__init__(bbox, stack_id, zoom_level=0, coords='NM', image_mirror='auto', mem_lim=4000, remote_instance=None, **fetch_kwargs)[source]

Initialise class.

Methods

__init__(bbox, stack_id[, zoom_level, ...])

Initialise class.

bboxes2imgcoords()

Convert bounding box(es) to coordinates for individual images.

estimate_memory()

Estimate memory [Mb] consumption of loading all tiles.

get_stack_info([image_mirror])

Retrieve basic info about image stack and mirrors.

load_and_save(filepath[, filename])

Download and stitch tiles, and save as images right away (memory efficient).

load_in_memory()

Download and stitch tiles, and keep images in memory.

render_im([slider, ax])

Draw image slices with a slider.

render_nodes(ax[, nodes, connectors, ...])

Render nodes onto image.

scalebar(ax[, size, pos, label, line_kws, ...])

Add scalebar to image.