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FIX: Edge case where a resampled column was too-long-by-one #365

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Feb 1, 2019
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FIX: Edge case where a resampled column was too-long-by-one #365

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8cfba06
BUG: Demonstrate resampling bug
effigies Jan 27, 2019
c44fedc
FIX: revert to length of self.Index when dimensions differ slightly, …
adswa Jan 29, 2019
319f81c
rely exclusively on self.index length during resampling
adswa Feb 1, 2019
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28 changes: 28 additions & 0 deletions bids/variables/tests/test_variables.py
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Original file line number Diff line number Diff line change
@@ -1,13 +1,16 @@
from bids.layout import BIDSLayout
import pytest
import os
from os.path import join
from bids.tests import get_test_data_path
from bids.variables import (merge_variables, DenseRunVariable, SimpleVariable,
load_variables)
from bids.variables.entities import RunInfo
import numpy as np
import pandas as pd
import nibabel as nb
import uuid
import json


def generate_DEV(name='test', sr=20, duration=480):
Expand Down Expand Up @@ -174,3 +177,28 @@ def test_filter_simple_variable(layout2):
assert merged.filter({'nonexistent': 2}, strict=True) is None
merged.filter({'acquisition': 'fullbrain'}, inplace=True)
assert merged.to_df().shape == (40, 9)


@pytest.mark.parametrize(
"TR, nvols",
[(2.00000, 251),
(2.000001, 251)])
def test_resampling_edge_case(tmpdir, TR, nvols):
tmpdir.chdir()
os.makedirs('sub-01/func')
with open('sub-01/func/sub-01_task-task_events.tsv', 'w') as fobj:
fobj.write('onset\tduration\tval\n1\t0.1\t1\n')
with open('sub-01/func/sub-01_task-task_bold.json', 'w') as fobj:
json.dump({'RepetitionTime': TR}, fobj)

dataobj = np.zeros((5, 5, 5, nvols), dtype=np.int16)
affine = np.diag((2.5, 2.5, 2.5, 1))
img = nb.Nifti1Image(dataobj, affine)
img.header.set_zooms((2.5, 2.5, 2.5, TR))
img.to_filename('sub-01/func/sub-01_task-task_bold.nii.gz')

layout = BIDSLayout('.', validate=False)
coll = load_variables(layout).get_collections('run')[0]
dense_var = coll.variables['val'].to_dense(coll.sampling_rate)
regressor = dense_var.resample(1.0 / TR).values
assert regressor.shape == (nvols, 1)
3 changes: 2 additions & 1 deletion bids/variables/variables.py
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Original file line number Diff line number Diff line change
Expand Up @@ -448,12 +448,13 @@ def resample(self, sampling_rate, inplace=False, kind='linear'):
self.index = self._build_entity_index(self.run_info, sampling_rate)

x = np.arange(n)
num = int(np.ceil(n * sampling_rate / old_sr))
num = len(self.index)
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I worry that this will hide other potential edge cases where there's a bigger mismatch... I suggest checking for a discrepancy and issuing a warning either if any is found, or if a large one is found (like you did in one of the other PRs).

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I think that was an earlier version of this PR. I'm curious what kind of edge case you're talking about?

As I understand it, we have a run duration, which is the original TR * nvols.

For a given sampling rate, we find the nearest n such that n / sampling_rate == duration. So this line was a way of taking from duration ~= n_old / sr_old ~= n_new / sr_new, and calculating n_new from n_old, sr_old, and sr_new. Index instead calculates directly from duration and sr_new. So the discrepancy we were finding is when you get an off-by-one between the two ways of calculating n_new.

So it's not really clear where another discrepancy can arise.


from scipy.interpolate import interp1d
f = interp1d(x, self.values.values.ravel(), kind=kind)
x_new = np.linspace(0, n - 1, num=num)
self.values = pd.DataFrame(f(x_new))
assert len(self.values) == len(self.index)

self.sampling_rate = sampling_rate

Expand Down