Difference between revisions of "mrcImageNormalizing"
From EosPedia
(Created page with "'''mrcImageNormalizing''' is Eos's Command that performs normalizing the value of image. == List of option == === Main option === <table border="1"> <tr> <...") |
(→-m details) |
||
| Line 106: | Line 106: | ||
data = A*data + B </td> | data = A*data + B </td> | ||
</tr> | </tr> | ||
| − | </table> | + | <tr> |
| − | + | <td>5</td> | |
| + | <td>Assume the density as Gaussian<br> | ||
| + | data = A*Normalized(data) + B<br> | ||
| + | where normalized means (average=0, SD=1)</td> | ||
| + | </tr> | ||
| + | </table> | ||
== Execution example == | == Execution example == | ||
Revision as of 04:52, 3 October 2014
mrcImageNormalizing is Eos's Command that performs normalizing the value of image.
Contents
List of option
Main option
| Option | Essential/Optional | Description | Default |
|---|---|---|---|
| -i | Essential | Input: mrcImage | NULL |
| -o | Essential | Output: mrcImage | NULL |
| -A | Optional | A | 1.0 |
| -B | Optional | B | 0.0 |
| -ContourMin | Optional | ContourMin | 0.0 |
| -ContourMax | Optional | ContourMax | 1.0 |
| -ContourSolvent | Optional | ContourSolvent | 0.0 |
| -c | Optional | ConfigurationFile | NULL |
| -m | Optional | Mode | 0 |
| -h | Optional | Help |
-m details
| Value | Description |
|---|---|
| 0 | Double Exponential: Solvent and Object Fitting histgram to double exponentials as Solvent and Object |
| 1 | Min-Max: Background and Object data = A*(data-Min)/(Max-Min) + B |
| 2 | Contour data = A*(data-ContourMin)/(ContourMax-ContourMin) + B |
| 3 | Contour and Solvent if data < ContourSolvent, data = ContourSolvent. After this, calculate the below. |
| 4 | No Estimation data = A*data + B |
| 5 | Assume the density as Gaussian data = A*Normalized(data) + B |
Execution example
Input file image
 |
Min Max |
-18651.7 (10, 1, 0) 52942.7 (24, 39, 0) |
Example of options only essential
 |
Min Max |
-0.00221962 (10, 1, 0) 0.00448009 (24, 39, 0) |
Option -A, -B
Case: A=1000, B=3
 |
Min Max |
0.780381 (10, 1, 0) 7.48009 (24, 39, 0) |
