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OptimizeReferences
This logic aligns the class averages so that they are in the same direction. After classification step different classes might contain the same view, but rotated in the image plane, so alignment is needed for the same views to look identical.
Usage
The quality of the output heavily depends on the quality of the first class average chosen - preferrably, it should show enough details of the molecule or complex and be surronded by a black rim. The optimal values for radius parameter are around 0.8-0.9.
Example
Process
Parameters | Description |
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Correlation Function | The correlation function that is optimized during the image alignment |
Fraction | The maximal fraction of the image that will be shifted relative to reference image during the alignment |
Interpolation | Defines the interpolation function used to get the value between two neighbouring pixels |
Radius | The value of Circular Mask Fraction (this fraction of image dimension will be used as diameter of the circle cut from the image for cf calculations) |
Sampling | The maximal fraction of the image shifted during the alignment relative to the reference image |
Input | Description |
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Input | A set of class averages |
Output | Description |
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Output | A set of aligned class averages |
Written Header Values | Description |
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resolutionAt0.143 | Estimated resolution for FSC cut off at 0.143 |
resolutionAt0.3 | Estimated resolution for FSC cut off at 0.3 |
resolutionAt0.5 | Estimated resolution for FSC cut off at 0.5 |
resolutionAt0.9 | Estimated resolution for FSC cut off at 0.9 |
resolutionAt3Sigma | Estimated resolution for FSC cut off at 3 Sigma |
resolution | Estimated resolution at the user chosen cut off value |
maxResolution | Maximum resolution in the local map |
meanResolution | Mean resolution in the local map |
minResolution | Minimum resolution in the local map |
resolutionVariance | Variance of the resolution in the local map |
abscissaIsLogarithmical , abscissaMin, abscissaMax | For internal 1D viewer use only, to be hidden |
Concept
A Paper about FSC theory and applications can be found here