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Splitting to handle multiple frames per plane #500
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Our hypothesis is that ScanImage records some fields in the metadata which will help us disambiguate how may frames per plane are being taken. One promising option is
which is 4 for Note to self: we should also be looking at
which appears to be |
First part of last paragraph makes perfect sense ( However, whatever the structure of I'll try to start a document with definitions which ScanImage parameters are set and to what for each data modalities, and I think we should add a column there for metadata field where this is recorded. |
@nataliaorlova Your explanation of |
Types of outputs:
|
While piloting high resolution stacks and also axonal imaging, we discovered the need to acquire multiple frames per plane in all data modalities for experiments on MesoScopes (surface_average, depth_average, timeseries, local and cortical stacks).
We acquired first session (SID 1178748400) with frames per plane number != 1, and it caused splitting module to fail - see this lims job data log
The code failed on splitting surface_average, but we anticipate it to fail on other modes where we change frames per plane as well. For surface, the splitting code expects N pairs of FastZ actuator values for N ROIs in a session, i.e. if the session has 2 ROIs and their surfaces are at -160 and -155, it expects the fast Z actuators to be
[[-160, 0], [-155,0]]
, while when averaging is set to M, the value array with have M repeats of each pair, i.e. for M=4, the fastz values array will be[[-160, 0], [-160, 0], [-160, 0], [-160, 0], [-155, 0], [-155, 0], [-155, 0], [-155, 0]]
To optimize data quality in both phase 4 projects and OpenScope, we have to change this parameter (number of frames per plane) and we would like to request the splitting code to be able to handle this situation.
We acquired the sample test data, it's located here : /allen/programs/braintv/workgroups/multiphoton/Natalia/05242022_sample_data_splitting_for_Scott
Test data consists of the following:
For each data modality (surface, depth, local stack and cortical stack - we skipped timeseries because of it's size, and since depth_average represents a sub-sample of timeseries data):
Additionally, for cortical z stack, we acquired a stack in a slightly different mode (so called slow stack in ScanImage):
This is because cortical stacks are larger (more planes) and ScanImage has a limitation on number of repeats for large stacks and doesn't allow us to stick the same "fast Stack" mode.
Related to issue 495, whenever the stack comes off the rig unaveraged, we'd like the splitting code to average all planes at the same depth for both local and cortical stacks.
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