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CC1/2: Difference between revisions
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==CC<sub>1/2</sub> calculation== | ==CC<sub>1/2</sub> calculation== | ||
CC<sub>1/2</sub> can be calculated with the so-called σ-τ method ([https:// | CC<sub>1/2</sub> can be calculated with the so-called σ-τ method ([https://doi.org/10.1107/S1600576716005471 Assmann, G., Brehm, W. and Diederichs, K. (2016) Identification of rogue datasets in serial crystallography. J. Appl. Cryst. 49, 1021-1028.]) by: | ||
: <math>CC_{1/2}=\frac{\sigma^2_{\tau}}{\sigma^2_{\tau}+\sigma^2_{\epsilon}} =\frac{\sigma^2_{y}- \frac{1}{2}\sigma^2_{\epsilon}}{\sigma^2_{y}+ \frac{1}{2}\sigma^2_{\epsilon}} </math> | : <math>CC_{1/2}=\frac{\sigma^2_{\tau}}{\sigma^2_{\tau}+\sigma^2_{\epsilon}} =\frac{\sigma^2_{y}- \frac{1}{2}\sigma^2_{\epsilon}}{\sigma^2_{y}+ \frac{1}{2}\sigma^2_{\epsilon}} </math> | ||
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===calculating ''' <math>\sigma^2_{y} </math>'''=== | ===calculating ''' <math>\sigma^2_{y} </math>'''=== | ||
Let N be the number of reflections in a resolution shell. With <math>\overline{x}_{ | Let N be the number of reflections in a resolution shell. With <math>\overline{x}_{i}= \frac{1} {n} \sum^n_{j} x_{j,i}</math> , the unbiased sample variance from all averaged intensities of all unique reflections is calculated by: | ||
<math>s^2_{y} = \frac{1}{N-1} \cdot \left (\sum^N_{i} \overline{x}_{i}^2 - \frac{\left ( \sum^N_{i} \overline{x}_{i} \right )^2}{ N} \right ) </math> | <math>s^2_{y} = \frac{1}{N-1} \cdot \left (\sum^N_{i} \overline{x}_{i}^2 - \frac{\left ( \sum^N_{i} \overline{x}_{i} \right )^2}{ N} \right ) </math> | ||
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== See also == | == See also == | ||
[https://www.youtube.com/watch?v=LirxJIcQ6T0 CC* - Linking crystallographic model and data quality.] Video recorded at SBGrid/NE-CAT workshop 2014; the PDF is [https:// | [https://www.youtube.com/watch?v=LirxJIcQ6T0 CC* - Linking crystallographic model and data quality.] Video recorded at SBGrid/NE-CAT workshop 2014; the PDF is [https://wiki.uni-konstanz.de/pub/CC%20-%20Linking%20crystallographic%20model%20and%20data%20quality.pdf here]. The sound is poor. | ||