Low-level Control with MMCore

Pycro-Manager provides access to the Micro-Manager core via the mmpycorex library. The behavior of the Core object depends on whether the Python or Java backend is in use (see Headless Mode):

  • Java backend: Returns an automatically Python-converted version of the Java core object

  • Python backend: Returns a direct reference to a pymmcore object

While both wrap the same underlying object, there may be slight differences in their APIs.

Receiving Core callbacks (Java backend)

The Core.get_core_callback(callback_fn) is used with the Java backend Core object to set up a callback function that triggers whenever the Core emits a signal (such as when the state of hardware has changed). The callback function should be defined with the following signature:

def callback_fn(name, *args):
    pass

Where name is the name of the signal emitted by the Core, and args are the arguments passed by the signal.

For more information, see here

Discovering Available Functions

To explore available functions:

  1. In IPython, type core. and press Tab for autocomplete suggestions.

  2. Refer to the Java version of the core API documentation.

Note

Function names are automatically translated from Java’s camelCase to Python’s snake_case (e.g., setExposure becomes set_exposure).

# This example shows how to use pycromanager to interact with the micro-manager core.
# Aside from the setup section, each following section can be run independently

from pycromanager import Core
import numpy as np
import matplotlib.pyplot as plt

#Setup
# get object representing MMCore
core = Core()

#### Calling core functions ###
exposure = core.get_exposure()


#### Setting and getting properties ####
# Here we set a property of the core itself, but same code works for device properties
auto_shutter = core.get_property('Core', 'AutoShutter')
core.set_property('Core', 'AutoShutter', 0)


#### Acquiring images ####
# The micro-manager core exposes several mechanisms foor acquiring images. In order to
# not interfere with other pycromanager functionality, this is the one that should be used
core.snap_image()
tagged_image = core.get_tagged_image()

# If using micro-manager multi-camera adapter, use core.getTaggedImage(i), where i is
# the camera index

# pixels by default come out as a 1D array. We can reshape them into an image
pixels = np.reshape(tagged_image.pix,
                        newshape=[tagged_image.tags['Height'], tagged_image.tags['Width']])
# plot it
plt.imshow(pixels, cmap='gray')
plt.show()