add default option from param_range in validation curve #129
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autoreject/autoreject.py
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| @@ -84,7 +98,11 @@ def validation_curve(epochs, y, param_name, param_range, cv=None): | |||
| param_name="thresh", param_range=param_range, | |||
| cv=cv, n_jobs=1, verbose=0) | |||
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Since we're at it, perhaps let's expose the b_jobs param.
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probably the n_jobs parameter for the validation_curve function: Currently hardcoded to 1, see line 85(old)/99(new)
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@agramfort CIs are failing ... maybe because of your French keyboard |
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This looks like it could go into 0.2 easily. @agramfort are you done here? If so, I can help rebase and merge it. |
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yes. Can you take over though?
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jasmainak
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Codecov Report
@@ Coverage Diff @@
## master #129 +/- ##
==========================================
+ Coverage 92.02% 92.67% +0.65%
==========================================
Files 10 10
Lines 1178 1187 +9
==========================================
+ Hits 1084 1100 +16
+ Misses 94 87 -7 |
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Rebased, @agramfort anything else? |
| The values of the parameter that will be evaluated. | ||
| If None, 15 values between the min and the max threshold | ||
| will be tested. |
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The problem doing this is that you will have np.inf as the error when the candidate threshold is the min threshold. Even if you do something like min threshold + epsilon (so that at least one epoch is retained), you have the same problem as for some folds it could end up being the min threshold
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problem with None param or with a my custom grid?
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Your custom grid. It will give np.inf score when no epochs are kept.
On Sat 8 Jun 2019 at 13:12, Alexandre Gramfort ***@***.***> wrote:
***@***.**** commented on this pull request.
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In autoreject/autoreject.py
<#129 (comment)>:
> The values of the parameter that will be evaluated.
+ If None, 15 values between the min and the max threshold
+ will be tested.
problem with None param or with a my custom grid?
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can you make a test so I see if we catch this nicely?
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added a test for you that fails |
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if you get a loglik of -inf then it means the model is bad and to me it's not too much of a problem as you want to find the argmax of test_scores (so -inf will be ignored). do I miss something? |
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sure. But when you plot with np.inf then you have a ton of whitespace ... |
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if the plotting is done with your own matplotlib code is it our problem?
matplotlib just not plots the points as
if they were NaN? I can live with that
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this is all I needed to know ;-) |
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