[feat][METEOR-1128] TDCT Odemis Wrapper #2999
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| # get the point of interest coordinate (in microscope coordinates, in metres) | ||
| poi_coord = correlation_results["output"]["poi"][0]["px_um"] | ||
| poi_coord = (poi_coord[0] * 1e-6, poi_coord[1] * 1e-6) | ||
| return poi_coord |
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It is confusing that some coordinates are saved in pixels and some in m, while all of them are called as coords? I am not sure why poi_coord is in m and not in pixels
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this is the final output for the milling patterns, which have coordinates in metres. They are all coordinates, not sure if you have a better name?
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Maybe if most of the coordinates are in pixels, by default the coords can represent pixels and for m it can be represented by pos , while the function name can explicitly tell i.e. in meters ? For e.g. get_poi_pos() or get_poi_coords_in_meters().
With that I would rename the function description and definitions to make the difference clear.
| :param das: the data arrays (CTZYX, ZYX, or YX), all arrays must have the same shape | ||
| :param x: the x-coordinate | ||
| :param y: the y-coordinate | ||
| :param z: the z-coordinate (initial guess) |
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So this argument is only present in case of failure, in which case it will be returned without manipulation. To me it makes more sense to not make it an arg/return but just throw the error (or return None, since no optimal z was found) and handle the failure case outside of this function.
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I understand your point but disagree, almost always the handling will be to use the initial value. If it becomes an issue it can be changed later
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|
Just a quick question, how would the refractive index correction be handled? I am not sure if I have seen that code. |
That isn't implemented yet, it will come a bit later on |
Implementation of the 3DCT wrapper to allow running multi-point correlation from odemis. Includes a parser to read correlated position from file, and z-targeting utility for multi-channel images.
3DCT package now only has two dependencies for the core workflow (excluding user interface and image readers), which are already included in odemis (numpy, scipy). Packaging will be done later. Source Repository
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