<html><head><meta http-equiv="Content-Type" content="text/html charset=us-ascii"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div dir="auto" style="font-family: Helvetica-Light; word-wrap: break-word;" class=""><span style="font-family: helvetica-light;" class="">Hi, this is my first time working with PyMVPA and I'm looking to build one fmri dataset from 10 individual fmri runs. I was wondering how I would go about this? As a brute force approach, I was thinking to import the first run, then looping through the rest of the runs and appending the data. However, how would I go about adding the attribute targets and chunks to it?? Below is an attempt to do this....</span></div><div dir="auto" style="font-family: Helvetica-Light; word-wrap: break-word;" class=""><span style="font-family: helvetica-light;" class=""><br class=""></span></div><div dir="auto" style="font-family: Helvetica-Light; word-wrap: break-word;" class=""><div style="font-family: helvetica-light;" class="">Any help would be much appreciated! </div><div style="font-family: helvetica-light;" class=""><br class=""></div><div style="font-family: helvetica-light;" class="">******************************<wbr class="">******************</div><div class=""><div class=""><div class=""><div class=""><font face="Helvetica-Light" class="">def loadData():</font></div><div class=""><font face="Helvetica-Light" class=""> </font></div><div class=""><font face="Helvetica-Light" class=""> data_path = "/Users/..."</font></div><div class=""><font face="Helvetica-Light" class=""> </font></div><div class=""><font face="Helvetica-Light" class=""> #start with run1 and append runs 2-10</font></div><div class=""><font face="Helvetica-Light" class=""> </font></div><div class=""><font face="Helvetica-Light" class=""> bold_fname = os.path.join(data_path, 'run1_mask+orig.nii.gz')</font></div><div class=""><font face="Helvetica-Light" class=""><br class=""></font></div><div class=""><font face="Helvetica-Light" class=""> #upload BOLD data with its mask</font></div><div class=""><font face="Helvetica-Light" class=""> ds = fmri_dataset(samples = bold_fname)</font></div><div class=""><font face="Helvetica-Light" class=""><br class=""></font></div><div class=""><font face="Helvetica-Light" class=""> #iterate through runs 2-10 and append each fmri dataset to ds</font></div><div class=""><font face="Helvetica-Light" class=""> for i in range(2,11):</font></div><div class=""><font face="Helvetica-Light" class=""> path = 'run'+str(i)+'_mask+orig.nii.gz'</font></div><div class=""><font face="Helvetica-Light" class=""> bold_fname = os.path.join(data_path, path)</font></div><div class=""><font face="Helvetica-Light" class=""> sub = fmri_dataset(samples = bold_fname)</font></div><div class=""><font face="Helvetica-Light" class=""><br class=""></font></div><div class=""><font face="Helvetica-Light" class=""> ds = vstack((ds,sub))</font></div><div class=""><font face="Helvetica-Light" class=""><br class=""></font></div><div class=""><font face="Helvetica-Light" class=""> </font></div><div class=""><font face="Helvetica-Light" class=""> #add the attribute targets/chunks to the data</font></div><div class=""><font face="Helvetica-Light" class=""> ds.sa.targets = attr.targets</font></div><div class=""><font face="Helvetica-Light" class=""> ds.sa.chunks = np.array(attr.chunks)</font></div><div class=""><font face="Helvetica-Light" class=""><br class=""></font></div><div class=""><font face="Helvetica-Light" class=""> print ds.shape</font></div><div class=""><font face="Helvetica-Light" class=""><br class=""></font></div><div class=""><font face="Helvetica-Light" class=""> print ds.summary()</font></div><div class=""><font face="Helvetica-Light" class=""> </font></div><div class=""><font face="Helvetica-Light" class=""> return ds</font></div></div><div class=""><br class=""></div></div><div style="font-family: helvetica-light;" class="">******************************<wbr class="">******************<br class=""></div><font face="Helvetica-Light" class="">Thanks!</font></div><div style="font-family: helvetica-light;" class=""><br class=""></div><div style="font-family: helvetica-light;" class="">Elia</div></div></body></html>