Difference between revisions of "CamCASP/Bugs/7"
import>Ajs1 |
import>Ajs1 |
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Line 4: | Line 4: | ||
11.43900000 11.41700000 7.41600000 2.64700000 +++ |
11.43900000 11.41700000 7.41600000 2.64700000 +++ |
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0.42400000 0.01400000 |
0.42400000 0.01400000 |
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− | with similar behaviour for C 11c 20, C 22c 22s and O 11c 20, but none of the other cases |
+ | with similar behaviour for C 11c 20, C 22c 22s and O 11c 20, but none of the other cases. Removing the "options tests" line from the data to get the standard grid makes things even worse: |
20 20 |
20 20 |
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-9.88200000 -9.52700000 -7.58300000 -2.61900000 +++ |
-9.88200000 -9.52700000 -7.58300000 -2.61900000 +++ |
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Line 13: | Line 13: | ||
25.60290131 18.22199084 10.00593354 3.58000511 +++ |
25.60290131 18.22199084 10.00593354 3.58000511 +++ |
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0.63051681 0.02341723 |
0.63051681 0.02341723 |
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+ | Weight 5 improves matters, but weight 6 is needed to get sensible results: |
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+ | 20 20 |
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+ | 20.80100000 20.83700000 20.99700000 21.01100000 +++ |
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+ | 19.14900000 14.68600000 8.43300000 2.77400000 +++ |
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+ | 0.39500000 0.01400000 |
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+ | The fit is still pretty good: r.m.s. error 0.073% for weight 6 compared with 0.042% for weight 4. Even with weight 6 there are some anomalous cases, especially O 20 20, but the absolute values are small. |
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+ | |||
+ | Ideally we should force the monotonic decrease in magnitude, but I don't see how to do it, even if we fitted all frequencies together. |
Revision as of 11:12, 9 June 2009
Most of the polarizabilities generated by CamCASP show the expected monotonic decrease with increasing imaginary frequency. A few, however, depart wildly from this behaviour. In the example case of formamide, we get, for C,
20 20 3.74300000 3.98200000 5.26700000 8.33300000 +++ 11.43900000 11.41700000 7.41600000 2.64700000 +++ 0.42400000 0.01400000
with similar behaviour for C 11c 20, C 22c 22s and O 11c 20, but none of the other cases. Removing the "options tests" line from the data to get the standard grid makes things even worse:
20 20 -9.88200000 -9.52700000 -7.58300000 -2.61900000 +++ 3.70900000 7.16600000 5.79900000 2.32900000 +++ 0.39500000 0.01400000
This is a problem with pfit; the anchor values are
33.27220340 33.16682559 32.53705396 30.41159247 +++ 25.60290131 18.22199084 10.00593354 3.58000511 +++ 0.63051681 0.02341723
Weight 5 improves matters, but weight 6 is needed to get sensible results: 20 20
20.80100000 20.83700000 20.99700000 21.01100000 +++ 19.14900000 14.68600000 8.43300000 2.77400000 +++ 0.39500000 0.01400000
The fit is still pretty good: r.m.s. error 0.073% for weight 6 compared with 0.042% for weight 4. Even with weight 6 there are some anomalous cases, especially O 20 20, but the absolute values are small.
Ideally we should force the monotonic decrease in magnitude, but I don't see how to do it, even if we fitted all frequencies together.