def rsmplInHighRes(aryBoxCarConv,<EOL>tplPngSize,<EOL>tplVslSpcHighSze,<EOL>varNumMtDrctn,<EOL>varNumVol):
<EOL>aryBoxCarConvHigh = np.zeros((tplVslSpcHighSze[<NUM_LIT:0>],<EOL>tplVslSpcHighSze[<NUM_LIT:1>],<EOL>varNumMtDrctn,<EOL>varNumVol))<EOL>for idxMtn in range(<NUM_LIT:0>, varNumMtDrctn):<EOL><INDENT>for idxVol in range(<NUM_LIT:0>, varNumVol):<EOL><INDENT>vecRange = np.arange(<NUM_LIT:0>, tplPngSize[<NUM_LIT:0>])<EOL>crd2, crd1 = np.meshgrid(vecRange, vecRange)<EOL>aryOrixPixCoo = np.column_stack((crd1.flatten(), crd2.flatten()))<EOL>vecOrigPixVal = aryBoxCarConv[:, :, idxMtn, idxVol]<EOL>vecOrigPixVal = vecOrigPixVal.flatten()<EOL>varStpSzeX = np.complex(tplVslSpcHighSze[<NUM_LIT:0>])<EOL>varStpSzeY = np.complex(tplVslSpcHighSze[<NUM_LIT:1>])<EOL>aryPixGridX, aryPixGridY = np.mgrid[<NUM_LIT:0>:tplPngSize[<NUM_LIT:0>]:varStpSzeX,<EOL><NUM_LIT:0>:tplPngSize[<NUM_LIT:1>]:varStpSzeY]<EOL>aryResampled = griddata(aryOrixPixCoo,<EOL>vecOrigPixVal,<EOL>(aryPixGridX, aryPixGridY),<EOL>method='<STR_LIT>')<EOL>aryBoxCarConvHigh[:, :, idxMtn, idxVol] = aryResampled<EOL><DEDENT><DEDENT>return aryBoxCarConvHigh<EOL>
Resample pixel-time courses in high-res visual space.

    Parameters
    ----------
    input1 : 2d numpy array, shape [n_samples, n_measurements]
        Description of input 1.
    input2 : float, positive
      Description of input 2.
    Returns
    -------
    data : 2d numpy array, shape [n_samples, n_measurements]
        Closed data.
    Reference
    ---------
    [1]