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https://github.com/cdtools-developers/cdtools.git
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some horrible state but I need to stop developing on perlmutter
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@@ -10,6 +10,11 @@ import numpy as np
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__all__ = ['SimplePtycho']
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class complexWrapper(t.Tensor):
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def __new__(base_tensor):
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return t.view_as_complex(base_tensor)
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class SimplePtycho(CDIModel):
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"""A simple ptychography model for exploring ideas and extensions
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@@ -44,11 +49,14 @@ class SimplePtycho(CDIModel):
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# object
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self.register_buffer('probe_norm', t.max(t.abs(probe_guess)))
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self.probe_data = t.nn.Parameter(t.view_as_real(probe_guess / self.probe_norm))
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self.probe_data = complexParameter(probe_guess/self.probe_norm)
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#self.probe_data = t.nn.Parameter(t.view_as_real(probe_guess / self.probe_norm))
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self.obj_data = t.nn.Parameter(t.view_as_real(obj_guess))
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@property
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def probe(self):
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probe = t.view_as_complex(self.probe_data)
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return t.view_as_complex(self.probe_data)
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@property
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@@ -106,7 +114,6 @@ class SimplePtycho(CDIModel):
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def interaction(self, index, translations):
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pix_trans = tools.interactions.translations_to_pixel(self.probe_basis,
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translations,
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surface_normal=self.surface_normal)
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@@ -181,7 +188,7 @@ class SimplePtycho(CDIModel):
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('Object Phase',
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lambda self, fig: p.plot_phase(self.obj, fig=fig, basis=self.probe_basis))
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]
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def ePIE(self, iterations, dataset, beta = 1.0):
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"""Runs an ePIE reconstruction as described in `Maiden et al. (2017) <https://www.osapublishing.org/optica/abstract.cfm?uri=optica-4-7-736>`_.
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@@ -43,7 +43,6 @@ def translations_to_pixel(basis, translations, surface_normal=t.Tensor([0.,0.,1.
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pixel_translations : torch.Tensor
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A Jx2 stack of translations in internal (i,j) pixel-space, or a single translation
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"""
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projection_1 = t.as_tensor(np.array([[1,0,0],
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[0,1,0],
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[0,0,0]]),
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@@ -53,7 +52,8 @@ def translations_to_pixel(basis, translations, surface_normal=t.Tensor([0.,0.,1.
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projection_2[2] = t.as_tensor(-surface_normal / surface_normal[2],
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dtype=projection_2.dtype,
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device=projection_2.device)
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projection_2 = t.inverse(projection_2)
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projection_2 = t.linalg.inv(projection_2)
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basis_vectors_inv = t.pinverse(basis).to(device=translations.device,
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dtype=translations.dtype)
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