useq-schema 0.3.2

Schema for multi-dimensional microscopy experiments

useq-schema

An implementation agnostic schema for describing a sequence of events during a multi-dimensional imaging acquisition.

Documentation: https://pymmcore-plus.github.io/useq-schema/

The goal of this repo is to provide a specification (and some python utilities) for generating event objects that can be consumed by microscope acquisition engines. The hope is that this will encourage inter-operability between various efforts to drive automated image acquisition.

The schema tries to remain agnostic to the specific acquisition engine, though it was designed based on the Micro-Manager acquisition engine. One hope is to solicit feedback from interested parties regarding limitations and/or potential extensions to the schema. Similarly, while the "ideal" schema will support arbitrary dimensions (i.e. more than the conventional position, time, channel, z, ...), it also hard to avoid hard-coding some assumptions about dimensionality in certain places. Any and all feedback (even minor stuff, such as parameter naming, etc...) is welcome!

MDAEvent

The primary "event" object is useq.MDAEvent. This captures a single event that a microscope should perform, including preparation of the hardware, and execution of the event (such as an image acquisition).

• For micro-manager, this object is most similar (though not that similar) to the events generated by generate-acq-sequence in the clojure acquisition engine.
• For pycro-manager, this object is similar to an individual acquisition event dict generated by multi_d_acquisition_events, (and, useq.MDAEvent provides a to_pycromanager() method that returns a single pycro-manager event dict)
• your object here?...

# simplified, and possibly outdated.  See useq.MDAEvent in codebase

# where `None` generally means "make no change"
class MDAEvent:
    metadata: Dict[str, Any] = {}  # user-specific data
    index: Dict[str, int] = {}  # {'axis'->index} for this event
    channel: Optional[Channel]  # optical config
    exposure: Optional[PositiveFloat]  # will likely expand for camera
    min_start_time: Optional[int]  # min time delta for beginning event
    x_pos: Optional[float]  # stage x
    y_pos: Optional[float]  # stage y
    z_pos: Optional[float]  # stage z
    properties: Optional[Sequence[PropertyTuple]]  # set arbitrary device props
    # TBD
    # action: Action ... such as "acquire", etc...

class Channel:
    config: str
    group: str = "Channel"

class PropertyTuple(NamedTuple):
    device_name: str
    property_name: str
    property_value: Any

useq-schema uses pydantic to define models, so you can retrieve the json schema for the MDAEvent object with MDAEvent.schema_json()

MDASequence

useq.MDASequence represents a sequence of events (as might be generated by the multidimensional acquisition GUI in most microscope software). A useq.MDASequence object is itself iterable, and yields MDAEvent objects.

• For micro-manager, this object is most similar to org.micromanager.acquisition.SequenceSettings, (generated by clicking the "Acquire!" button in the Multi-D Acquisition GUI)
• For pycro-manager, this object is similar to the multi_d_acquisition_events convenience function, (and useq.MDASequence provides a to_pycromanager() method that returns a list of pycro-manager events)
• your object here?...

# simplified, and possibly outdated.  See useq.MDASequence in codebase

class MDASequence(BaseModel):
    metadata: Dict[str, Any] = {}  # user-specific data
    axis_order: str  # e.g. 'tpcz'
    stage_positions: Tuple[Position]
    channels: Tuple[Channel, ...]
    time_plan: AnyTimePlan  # see details below
    z_plan: AnyZPlan  # see details below

class Position(BaseModel):
    # if None, implies 'do not move this axis'
    x: Optional[float]
    y: Optional[float]
    z: Optional[float]
    name: Optional[str]
    z_plan: Optional[AnyZPlan]


class Channel(BaseModel):
    config: str
    group: str
    exposure: Optional[PositiveFloat]
    do_stack: bool = True
    z_offset: float = 0.0
    acquire_every: PositiveInt = 1  # acquire every n frames
    camera: Optional[str]

useq-schema uses pydantic to define models, so you can retrieve the json schema for the MDASequence object with MDASequence.schema_json()

TimePlan and ZPlan are each iterable objects that allow for various ways to describe time and Z series. These are each rather configurable and will be documented more later.

TimePlans:

• TIntervalDuration - specify interval and duration
• TIntervalLoops - specify interval and number of timepoints
• TDurationLoops - specify duration and number of timepoints

ZPlans:

• ZTopBottom - specify absolute top, bottom, and step
• ZRangeAround - specify symmetric range and step
• ZAboveBelow - specify asymmetric range above and below reference, with step
• ZRelativePositions - directly specify a sequence of relative z positions
• ZAbsolutePositions - directly specify a sequence of absolute z positions

example MDASequence usage:

from useq import MDASequence

mda = MDASequence(
    stage_positions=[(100, 100, 30), (200, 150, 35)],
    channels=["DAPI", "FITC"],
    time_plan={'interval': 1, 'loops': 20},
    z_plan={"range": 4, "step": 0.5},
    axis_order='tpcz',
)

len(mda)
# 720

list(mda)
# [
#     MDAEvent(index={'t': 0, 'p': 0, 'c': 0, 'z': 0}, ... z_pos=28.0),
#     MDAEvent(index={'t': 0, 'p': 0, 'c': 0, 'z': 1}, ... z_pos=28.5),
#     ...
# ]

mda.to_pycromanager()

# [
#  {'axes': {'position': 0, 'time': 0, 'z': 0},
#   'z': 28.0,
#   'x': 100.0,
#   'y': 100.0,
#   'min_start_time': 0,
#   'channel': {'config': 'DAPI', 'group': 'Channel'}},
#  {'axes': {'position': 0, 'time': 0, 'z': 1},
#   'z': 28.5,
#   'x': 100.0,
#   'y': 100.0,
#   'min_start_time': 0,
#   'channel': {'config': 'DAPI', 'group': 'Channel'}},
#   ...
# ]