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Fixed small data discrepancy between Xee and pure computePixels(). #105
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LGTM.
x_size = int(np.ceil((x_max - x_min) / np.abs(self.store.scale_x))) | ||
y_size = int(np.ceil((y_max - y_min) / np.abs(self.store.scale_y))) | ||
x_size = int(np.round((x_max - x_min) / np.abs(self.store.scale_x))) | ||
y_size = int(np.round((y_max - y_min) / np.abs(self.store.scale_y))) |
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Did Sai’s modulus trick not work?
I have an internal only test where we want to substitute Xee for computePixels. Does that test pass with this change?
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I think @shoyer would be good to consult, too.
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No @alxmrs sai's modulus trick is not working on all the images.
And Yes, that internal test was passed with this change.
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Then this sounds good to me!
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LGTM. Can you get the checks to pass?
Yes @alxmrs all the CI/CD test-cases were passed locally and once this PR will merged I will update the internal test-case too. |
By incorporating the following code into the main branch, i successfully addressed and resolved issue #40 mentioned internal test case was passed when utilizing the current solution.)