<html><head></head><body>How many cpu cores do you have? There is nproc parameter (and nblock?) to searchlight - try setting to some smaller number<br><br>Given the simplicity of the within searchlight function I wonder if there is something else which causes the blow up though<br><br><div class="gmail_quote">On May 14, 2020 7:03:00 PM EDT, Jacob Elder <jacobelder52@gmail.com> wrote:<blockquote class="gmail_quote" style="margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
<div dir="ltr">Hi,<div><br></div><div>I am trying to run a whole-brain searchlight RSA (on a cluster with a lot of processing cores available) but every time I do it returns a memoryError. However, when I split it into hemispheres or run as an ROI, it successfully runs without MemoryError. I have tried following some other suggestions I found online but nothing has resolved the issue. Memory shouldn't be an issue as the cluster has plenty of RAM available. We've also tried to run this on another cluster at a separate institution using a high mem option and it still didn't work. I am pretty stumped and was wondering if anyone can help or has any potential solutions in mind?</div><div><br></div><div>Here is what the code looks like:</div><div><br></div><div><blockquote style="margin:0px 0px 0px 40px;border:none;padding:0px"><div><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"> subject = subjectData(inputs.rootDir, inputs.ID)</p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0);min-height:14px"><br></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(83,101,121)"><span style="color:rgb(0,0,0)"> </span><i># load the trait similarity data</i></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"> traitData = subject.importSimilarity()</p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0);min-height:14px"><br></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(83,101,121)"><span style="color:rgb(0,0,0)"> </span><i># load the neural data</i></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"> neuralData = subject.importNeural()</p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0);min-height:14px"> </p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"> neuralData = remove_invariant_features(neuralData)</p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0);min-height:14px"><br></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(196,26,22)"><span style="color:rgb(0,0,0)"> </span><span style="color:rgb(155,35,147)"><b>print</b></span><span style="color:rgb(0,0,0)"> (</span>"Complete loading neural data"<span style="color:rgb(0,0,0)">)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0);min-height:14px"><br></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(83,101,121)"><span style="color:rgb(0,0,0)"> </span><i># create an object from the neuroCorrelation class</i></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"> matrixCorr = neuroCorrelation(traitData)</p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0);min-height:14px"><br></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(83,101,121)"><span style="color:rgb(0,0,0)"> </span><i># set up searchlight parameters</i></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(83,101,121)"><span style="color:rgb(0,0,0)"> </span><i># set the radius based on the input</i></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"> rad = inputs.rad</p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0);min-height:14px"><br></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(83,101,121)"><span style="color:rgb(0,0,0)"> </span><i># Fisher's z-transformation for correlation coefficient</i></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"> FisherTransform = FxMapper(<span style="color:rgb(28,0,207)">'features'</span>, <span style="color:rgb(155,35,147)"><b>lambda</b></span> r: <span style="color:rgb(28,0,207)">0.5</span> * np.log((<span style="color:rgb(28,0,207)">1</span> + r) / (<span style="color:rgb(28,0,207)">1</span> - r)))</p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0);min-height:14px"><br></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(83,101,121)"><span style="color:rgb(0,0,0)"> </span><i># create the search light</i></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"> sl = sphere_searchlight(matrixCorr.correlate, rad, results_backend=<span style="color:rgb(28,0,207)">'hdf5'</span>, postproc=FisherTransform)</p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0);min-height:14px"><br></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(196,26,22)"><span style="color:rgb(0,0,0)"> </span><span style="color:rgb(155,35,147)"><b>print</b></span><span style="color:rgb(0,0,0)"> (</span>"Complete search light set-up"<span style="color:rgb(0,0,0)">)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0);min-height:14px"><br></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(83,101,121)"><span style="color:rgb(0,0,0)"> </span><i># apply the search light function to the neural data</i></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"> sl_output = sl(neuralData)</p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0);min-height:14px"><br></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(196,26,22)"><span style="color:rgb(0,0,0)"> </span><span style="color:rgb(155,35,147)"><b>print</b></span><span style="color:rgb(0,0,0)"> (</span>"Search light completed"<span style="color:rgb(0,0,0)">)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0);min-height:14px"><br></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(83,101,121)"><span style="color:rgb(0,0,0)"> </span><i># transform the search light output to an image data</i></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"> sl_image = map2nifti(data=sl_output, dataset=neuralData)</p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0);min-height:14px"><br></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(83,101,121)"><span style="color:rgb(0,0,0)"> </span><i># save the output</i></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"> outputDir = os.path.join(inputs.rootDir, <span style="color:rgb(196,26,22)">"RSA"</span>, <span style="color:rgb(196,26,22)">"searchLightResult"</span>, <span style="color:rgb(196,26,22)">"Subject{n}"</span>.format(n=inputs.ID),</p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"> <span style="color:rgb(196,26,22)">"sub{n}_sl_results_{v}{h}_P_R{r}.nii.gz"</span>.format(n=inputs.ID, v=inputs.valence, h=inputs.hemisphere, r=inputs.rad))</p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"> sl_image.to_filename(outputDir)</p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0);min-height:14px"><br></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"> <span style="color:rgb(155,35,147)"><b>print</b></span> (<span style="color:rgb(196,26,22)">"Complete with subject{n}"</span>.format(n=inputs.ID))</p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:12px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><br></p></div></blockquote>Here is the error:</div><div><br></div><div><blockquote style="margin:0px 0px 0px 40px;border:none;padding:0px"><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures">/home/user/anaconda2/lib/python2.7/site-packages/numpy/lib/type_check.py:546: DeprecationWarning: np.asscalar(a) is deprecated since NumPy v1.16, use a.item() instead</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> 'a.item() instead', DeprecationWarning, stacklevel=1)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures">Traceback (most recent call last):</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "./script/RSA_rad_FB_test.py", line 54, in <module></span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> sl_output = sl(neuralData)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "/home/user/anaconda2/lib/python2.7/site-packages/mvpa2/base/learner.py", line 258, in __call__</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> return super(Learner, self).__call__(ds)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "/home/user/anaconda2/lib/python2.7/site-packages/mvpa2/base/node.py", line 138, in __call__</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> result = self._postcall(ds, result)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "/home/user/anaconda2/lib/python2.7/site-packages/mvpa2/measures/base.py", line 128, in _postcall</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> result = super(Measure, self)._postcall(dataset, result)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "/home/user/anaconda2/lib/python2.7/site-packages/mvpa2/base/node.py", line 179, in _postcall</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> result = self._apply_postproc(ds, result)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "/home/user/anaconda2/lib/python2.7/site-packages/mvpa2/base/node.py", line 253, in _apply_postproc</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> result = self.__postproc(result)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "/home/user/anaconda2/lib/python2.7/site-packages/mvpa2/base/learner.py", line 258, in __call__</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> return super(Learner, self).__call__(ds)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "/home/user/anaconda2/lib/python2.7/site-packages/mvpa2/base/node.py", line 137, in __call__</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> result = self._call(ds, **(_call_kwargs or self._get_call_kwargs(ds)))</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "/home/user/anaconda2/lib/python2.7/site-packages/mvpa2/mappers/base.py", line 291, in _call</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> return self.forward(ds)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "/home/user/anaconda2/lib/python2.7/site-packages/mvpa2/mappers/base.py", line 215, in forward</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> return self._forward_dataset(data)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "/home/user/anaconda2/lib/python2.7/site-packages/mvpa2/mappers/fx.py", line 204, in _forward_dataset</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> col[attr] = a</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "/home/user/anaconda2/lib/python2.7/site-packages/mvpa2/base/collections.py", line 590, in __setitem__</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> value = ArrayCollectable(value)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "/home/user/anaconda2/lib/python2.7/site-packages/mvpa2/base/collections.py", line 185, in __init__</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> Collectable.__init__(self, value=value, name=name, doc=doc)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "/home/user/anaconda2/lib/python2.7/site-packages/mvpa2/base/collections.py", line 67, in __init__</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> self._set(value)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "/home/user/anaconda2/lib/python2.7/site-packages/mvpa2/base/collections.py", line 291, in _set</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> val = np.asanyarray(val)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> File "/home/user/anaconda2/lib/python2.7/site-packages/numpy/core/numeric.py", line 591, in asanyarray</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures"> return array(a, dtype, copy=False, order=order, subok=True)</span></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"></p><p style="margin:0px;font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:11px;line-height:normal;font-family:Menlo;color:rgb(0,0,0)"><span style="font-variant-ligatures:no-common-ligatures">MemoryError</span></p></blockquote><div><br></div><div>Any help would be greatly appreciated! Thank you.</div></div><div><br></div>-- <br><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div style="color:rgb(0,0,0);font-size:12.8px">Jacob Elder</div><div style="color:rgb(0,0,0);font-size:12.8px">Ph.D. Student, Dept. of Psychology</div><div style="color:rgb(0,0,0);font-size:12.8px">University of California, Riverside</div><div style="color:rgb(0,0,0);font-size:12.8px"><a href="https://www.hugheslab.org/" target="_blank">The UCR Social Neuroscience Lab</a></div></div></div></div>
</blockquote></div><br>-- <br>Yaroslav O. Halchenko (mobile version)<br>Center for Open Neuroscience <a href="http://centerforopenneuroscience.org">http://centerforopenneuroscience.org</a><br>Dartmouth College, NH, USA<br></body></html>