[+] Loading singularity on cn1932 [+] Setting proxy server to dtn04 for user sahad3 Option "--use-aroma" requires functional images to be resampled to MNI152NLin6Asym space. The argument "MNI152NLin6Asym:res-2" has been automatically added to the list of output spaces (option ``--output-spaces``). /usr/local/miniconda/lib/python3.7/site-packages/bids/layout/layout.py:62: UserWarning: Accessing entities as attributes is deprecated as of 0.7. Please use the .entities dictionary instead (i.e., .entities['suffix'] instead of .suffix. % (attr, attr)) /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/nilearn/image/resampling.py:510: UserWarning: Casting data from int16 to float32 warnings.warn("Casting data from %s to %s" % (data.dtype.name, aux)) /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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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] Error in atexit._run_exitfuncs: Traceback (most recent call last): File "/usr/local/miniconda/lib/python3.7/concurrent/futures/process.py", line 101, in _python_exit thread_wakeup.wakeup() File "/usr/local/miniconda/lib/python3.7/concurrent/futures/process.py", line 89, in wakeup self._writer.send_bytes(b"") File "/usr/local/miniconda/lib/python3.7/multiprocessing/connection.py", line 183, in send_bytes self._check_closed() File "/usr/local/miniconda/lib/python3.7/multiprocessing/connection.py", line 136, in _check_closed raise OSError("handle is closed") OSError: handle is closed