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| def __init__(self, data, noise_map, exposure_time_map=None, name=None): | ||
| def __init__( | ||
| self, data, noise_map, exposure_time_map=None, name=None, metadata=None |
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Add type hints and put arguments over new lines
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| self.preload_transform = preload_transform | ||
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| if preload_transform: |
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This kind of thing might be better done using lazy instantiation
| class TransformerFFT(object): | ||
| def __init__(self, uv_wavelengths, grid): | ||
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| super(TransformerFFT, self).__init__() |
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You can just call super().init() in python3
| return [real_transformed_mapping_matrix, imag_transformed_mapping_matrix] | ||
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| class TransformerFFT(object): |
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No need to inherit from object in python 3
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| self.u_fft = np.fft.fftshift( | ||
| np.fft.fftfreq( | ||
| grid.shape_2d[0], grid.pixel_scales[0] * units.arcsec.to(units.rad) |
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self.u_fft, self.v_fft = [... for i in (1, 2)]
| * 1j | ||
| * ( | ||
| self.grid.pixel_scales[0] | ||
| / 2.0 |
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Maybe break this equation up?
| ) | ||
| ) | ||
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| self.uv = np.array( |
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I wonder if array is happy to accept an iterable meaning you don't need to cast to list?
| list(zip(self.uv_wavelengths[:, 0], self.uv_wavelengths[:, 1])) | ||
| ) | ||
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| def visibilities_from_image(self, image): |
| # ... | ||
| z_fft_shifted = z_fft * self.shift | ||
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| # ... |
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| def transformed_mapping_matrices_from_mapping_matrix(self, mapping_matrix): | ||
| """ | ||
| ... |
| class TransformerNUFFT(NUFFT_cpu): | ||
| def __init__(self, uv_wavelengths, grid): | ||
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| super(TransformerNUFFT, self).__init__() |
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Docs, no need to pass super args
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| def initialize_plan(self, ratio=2, interpolation_kernel=(6, 6)): | ||
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| if not isinstance(ratio, int): |
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You're supposed to fix the issues before you merge it! |
Ah, the thing at the bottom said approved, never saw it does it on a commit by commit basis. This transformer stuff is scientifically untested so I dont want to spend too much time on documenting / cleaning the code currently. We could be using a completely different library in a months time. |
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