Fluctuations at High Q values #70
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This contains the method for computing the average curvature of a given signal. This is serve as a helper function for representing the fluctuations at high Q for IQ data (to be implemented in QOI.py).
This contains the method for computing the average curvature of a given signal. This is serve as a helper function for representing the fluctuations at high Q for IQ data (to be implemented in QOI.py).
Codecov Report
@@ Coverage Diff @@
## master #70 +/- ##
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- Coverage 92.16% 91.29% -0.88%
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Files 19 19
Lines 919 942 +23
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+ Hits 847 860 +13
- Misses 72 82 +10
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This looks good, it needs a test |
This contains the method for computing the average curvature of a given signal. This is serve as a helper function for representing the fluctuations at high Q for IQ data. The QOI file is updated in this commit. A test for the avg_curvature function has also been added in this commit.
This contains the method for computing the average curvature of a given signal. This is serve as a helper function for representing the fluctuations at high Q for IQ data. The QOI file is updated in this commit. A test for the avg_curvature function has also been added in this commit.
This contains the method for computing the average curvature of a given signal. This is serve as a helper function for representing the fluctuations at high Q for IQ data. The QOI file is updated in this commit. A test for the avg_curvature function has also been added in this commit.
This contains the method for computing the average curvature of a given signal. This is serve as a helper function for representing the fluctuations at high Q for IQ data. The QOI file is updated in this commit. A test for the avg_curvature function has also been added in this commit.
This contains the method for computing the average curvature of a given signal. This is serve as a helper function for representing the fluctuations at high Q for IQ data. The QOI file is updated in this commit. A test for the avg_curvature function has also been added in this commit.
This contains the method for computing the average curvature of a given signal. This is serve as a helper function for representing the fluctuations at high Q for IQ data. The QOI file is updated in this commit. A test for the avg_curvature function has also been added in this commit.
sbillinge
reviewed
Jan 27, 2019
xpdtools/tools.py
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| def avg_curvature(y, x, high_val): | ||
| """Computes the average of the curvature of a given signal past a |
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| def avg_curvature(y, x, high_val): | ||
| """Computes the average of the curvature of a given signal past a | ||
| (currently) user provided high Q value, this will be used as the scalar |
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don't say what this will be used for. If it is just for that qoi it shouldn't be a separate function. If it has more broad application, it should be its own function but the docstring should just describe what it does.
This contains the method for computing the average curvature of a given signal. This is serve as a helper function for representing the fluctuations at high Q for IQ data. The QOI file is updated in this commit. A test for the avg_curvature function has also been added in this commit. Two methods for computing the pearsons correlation coefficient have been added in this commit as well as tests for both. Still need to implement them into the qoi file.
CJ-Wright
reviewed
Mar 8, 2019
| @@ -21,6 +21,13 @@ def max_gr_mean(pdf, **kwargs): | |||
| return locals() | |||
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| def fluc_high_q(iq_comp, high_q_val=45, **kwargs): | |||
CJ-Wright
reviewed
Mar 8, 2019
| def fluc_high_q(iq_comp, high_q_val=45, **kwargs): | ||
| q = iq_comp.pluck(0) | ||
| iq = iq_comp.pluck(1) | ||
| high_q_fluc = avg_curvature(iq, q, high_q_val) |
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You might use the q and mean and combine them, see: https://github.com/xpdAcq/xpdtools/blob/master/xpdtools/pipelines/raw_pipeline.py#L340
This needs to run through a starmap.
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This contains the method for computing the average curvature of a given signal. This will serve as a helper function for representing the fluctuations at high Q for IQ data (to be implemented in QOI.py).