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# Copyright 2014 Diamond Light Source Ltd. |
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# |
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# Licensed under the Apache License, Version 2.0 (the "License"); |
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# you may not use this file except in compliance with the License. |
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# You may obtain a copy of the License at |
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# |
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# http://www.apache.org/licenses/LICENSE-2.0 |
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# |
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# Unless required by applicable law or agreed to in writing, software |
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# distributed under the License is distributed on an "AS IS" BASIS, |
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
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# See the License for the specific language governing permissions and |
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# limitations under the License. |
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# $Id: dezing_filter.py 467 2016-02-16 11:40:42Z kny48981 $ |
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""" |
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.. module:: dezinger_deprecated |
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:platform: Unix |
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:synopsis: A plugin to remove zingers |
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.. moduleauthor:: Mark Basham <[email protected]> |
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""" |
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import numpy as np |
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import dezing |
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from savu.plugins.filters.base_filter import BaseFilter |
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from savu.plugins.driver.cpu_plugin import CpuPlugin |
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from savu.plugins.utils import register_plugin |
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class DezingerDeprecated(BaseFilter, CpuPlugin): |
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def __init__(self): |
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super(DezingerDeprecated, self).__init__("DezingerDeprecated") |
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self.warnflag = 0 |
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self.errflag = 0 |
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def pre_process(self): |
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# Apply dezing to dark and flat images |
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inData = self.get_in_datasets()[0] |
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dark = inData.data.dark() |
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flat = inData.data.flat() |
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self.data_size = inData.get_shape() |
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pad_list = ((self.pad, self.pad), (0, 0), (0, 0)) |
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# dezing the dark field print "*****in data shape in base filter", in_dataset[0].get_shape() |
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if dark.size: |
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(retval, self.warnflag, self.errflag) = dezing.setup_size( |
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dark.shape, self.parameters['outlier_mu'], self.pad, |
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mode=self.parameters['mode']) |
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dark = self._dezing(np.pad(dark, pad_list, mode='edge')) |
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inData.data.update_dark(dark[self.pad:-self.pad]) |
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(retval, self.warnflag, self.errflag) = dezing.cleanup() |
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# dezing the flat field |
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if flat.size: |
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(retval, self.warnflag, self.errflag) = dezing.setup_size( |
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flat.shape, self.parameters['outlier_mu'], |
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self.pad, mode=self.parameters['mode']) |
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flat = self._dezing(np.pad(flat, pad_list, mode='edge')) |
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inData.data.update_flat(flat[self.pad:-self.pad]) |
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(retval, self.warnflag, self.errflag) = dezing.cleanup() |
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# setup dezing for data |
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self._dezing_setup(self.data_size) |
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def _dezing_setup(self, shape): |
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(retval, self.warnflag, self.errflag) = \ |
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dezing.setup_size(shape, self.parameters['outlier_mu'], |
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self.pad, mode=self.parameters['mode']) |
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def _process_calibration_frames(self, data): |
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nSlices = data.shape[self.proj_dim] - 2*self.pad |
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nSublists = int(np.ceil(nSlices/float(self.frame_limit))) |
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idx = np.array_split(np.arange(self.pad, nSlices+self.pad), nSublists) |
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idx = [np.arange(a[0]-self.pad, a[-1]+self.pad+1) for a in idx] |
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out_sl = np.tile([slice(None)]*3, [len(idx), 1]) |
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out_sl[:, self.proj_dim] = idx |
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result = np.empty_like(data) |
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for sl in out_sl: |
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result[tuple(sl)] = self._dezing(data[tuple(sl)]) |
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return result |
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def _dezing(self, data): |
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result = np.empty_like(data) |
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(retval, self.warnflag, self.errflag) = dezing.run(data, result) |
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return result |
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def process_frames(self, data): |
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return self._dezing(data[0]) |
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def post_process(self): |
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(retval, self.warnflag, self.errflag) = dezing.cleanup() |
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def get_max_frames(self): |
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return 'multiple' |
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def raw_data(self): |
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return True |
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def set_filter_padding(self, in_data, out_data): |
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in_data = in_data[0] |
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self.pad = (self.parameters['kernel_size'] - 1) / 2 |
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in_data.padding = {'pad_multi_frames': self.pad} |
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out_data[0].padding = {'pad_multi_frames': self.pad} |
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def executive_summary(self): |
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if self.errflag != 0: |
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return(["ERRORS detected in dezing plugin, Check the detailed \ |
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log messages."]) |
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if self.warnflag != 0: |
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return(["WARNINGS detected in dezing plugin, Check the detailed \ |
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log messages."]) |
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return ["Nothing to Report"] |
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DiamondLightSource /
Savu
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