[+] Loading singularity  on cn3625 
[+] Setting proxy server to dtn05  for user dmoracze

/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/nilearn/image/resampling.py:510: UserWarning: Casting data from int32 to float32
  warnings.warn("Casting data from %s to %s" % (data.dtype.name, aux))
/usr/local/miniconda/lib/python3.7/site-packages/nilearn/image/resampling.py:510: UserWarning: Casting data from int32 to float32
  warnings.warn("Casting data from %s to %s" % (data.dtype.name, aux))
/usr/local/miniconda/lib/python3.7/site-packages/nilearn/image/resampling.py:510: UserWarning: Casting data from int32 to float32
  warnings.warn("Casting data from %s to %s" % (data.dtype.name, aux))
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/nipype/algorithms/confounds.py:1099: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.
  betas = np.linalg.lstsq(X, data.T)[0]
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range.
  warnings.warn("No contour levels were found"
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
/usr/local/miniconda/lib/python3.7/site-packages/scipy/fftpack/basic.py:160: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  z[index] = x
/usr/local/miniconda/lib/python3.7/site-packages/niworkflows/viz/utils.py:513: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  maximum_intensity_data = data[inds]
Preprocessing did not finish successfully. Errors occurred while processing data from participants: M16 (7). Check the HTML reports for details.
/spin1/swarm/dmoracze/mpN6Vnos9V/cmd.1: line 1:  STATUS=1: command not found
chown: cannot access ‘/scratch/dmoracze/derivatives’: No such file or directory