diff --git a/test/Makefile b/test/Makefile
index db43480..a16cfb6 100644
--- a/test/Makefile
+++ b/test/Makefile
@@ -68,6 +68,8 @@ test: all
 	@echo "======timing test (type=$(DATATYPE))"
 	@./$(BENCHKISS) -x $(NUMFFTS) -n $(NFFT) 
 	@[ -x ./$(BENCHFFTW) ] && ./$(BENCHFFTW) -x $(NUMFFTS) -n $(NFFT) ||true
+	@echo "======higher dimensions type=$(DATATYPE))"
+	@for dim in 2 3 4 5 6 7 8 9; do ./testkiss.py $$dim ;done
 
 selftest.c:
 	./mk_test.py 10 12 14 > selftest.c
diff --git a/test/tailscrap.m b/test/tailscrap.m
index 51cd5fc..abf9046 100644
--- a/test/tailscrap.m
+++ b/test/tailscrap.m
@@ -1,4 +1,4 @@
-function diff=tailscrap()
+function maxabsdiff=tailscrap()
 % test code for circular convolution with the scrapped portion 
 % at the tail of the buffer, rather than the front
 %
@@ -8,19 +8,19 @@ function diff=tailscrap()
 nh=10;
 nfft=256;
 
-#h=ones(1,nh);
 h=rand(1,nh);
-
-#x=[1 zeros(1,nfft-1)];
 x=rand(1,nfft);
 
 hpad=[ h(nh) zeros(1,nfft-nh) h(1:nh-1) ]; 
 
-y = ifft( fft(hpad) .* fft(x) );
-yfilt = filter(h,1,x);
-yfilt_no_trans = yfilt(nh:nfft);
+% baseline comparison
+y1 = filter(h,1,x);
+y1_notrans = y1(nh:nfft);
+
+% fast convolution
+y2 = ifft( fft(hpad) .* fft(x) );
+y2_notrans=y2(1:nfft-nh+1);
+
+maxabsdiff = max(abs(y2_notrans - y1_notrans))
 
-#y2=y(nh:nfft);
-y2=y(1:nfft-nh+1);
-diff=y2 - yfilt_no_trans;
 end
diff --git a/test/testkiss.py b/test/testkiss.py
new file mode 100755
index 0000000..1ab722a
--- /dev/null
+++ b/test/testkiss.py
@@ -0,0 +1,146 @@
+#!/usr/local/bin/python2.3
+import math
+import sys
+import random
+import Numeric
+import struct
+
+pi=math.pi
+e=math.e
+j=complex(0,1)
+
+def dopack(x,fmt='f',cpx=1):
+    x = Numeric.reshape( x, ( Numeric.size(x),) )
+    if cpx:
+        s = ''.join( [ struct.pack(fmt*2,c.real,c.imag) for c in x ] )
+    else:
+        s = ''.join( [ struct.pack(fmt,c) for c in x ] )
+    return s
+
+def dounpack(x,fmt,cpx):
+    uf = fmt * ( len(x) / 4 )
+    s = struct.unpack(uf,x)
+    if cpx:
+        return Numeric.array(s[::2]) + Numeric.array( s[1::2] )*j
+    else:
+        return Numeric.array(s )
+
+
+def main():
+    #fft_func = fft
+    fft_func = real_fft
+
+    tvec = [0.309655,0.815653,0.768570,0.591841,0.404767,0.637617,0.007803,0.012665]
+    Ftvec = [ complex(r,i) for r,i in zip(
+                [3.548571,-0.378761,-0.061950,0.188537,-0.566981,0.188537,-0.061950,-0.378761],
+                [0.000000,-1.296198,-0.848764,0.225337,0.000000,-0.225337,0.848764,1.296198] ) ]
+
+    F = fft_func( tvec,0 )
+
+    nerrs= 0
+    for i in range(len(Ftvec)/2 + 1):
+        if abs( F[i] - Ftvec[i] )> 1e-5:
+            print 'F[%d]: %s != %s' % (i,F[i],Ftvec[i])
+            nerrs += 1
+
+    print '%d errors in forward fft' % nerrs
+    if nerrs:
+        return
+
+    trec = fft_func( F , 1 )
+
+    for i in range(len(trec) ):
+        trec[i] /= len(trec)
+
+    for i in range(len(tvec) ):
+        if abs( trec[i] - tvec[i] )> 1e-5:
+            print 't[%d]: %s != %s' % (i,tvec[i],trec[i])
+            nerrs += 1
+
+    print '%d errors in reverse fft' % nerrs
+
+
+def make_random(dims=[1]):
+    import Numeric 
+    res = []
+    for i in range(dims[0]):
+        if len(dims)==1:
+            r=random.uniform(-1,1)
+            i=random.uniform(-1,1)
+            res.append( complex(r,i) )
+        else:
+            res.append( make_random( dims[1:] ) )
+    return Numeric.array(res)
+
+def flatten(x):
+    import Numeric
+    ntotal = Numeric.product(Numeric.shape(x))
+    return Numeric.reshape(x,(ntotal,))
+
+def randmat( ndims ):
+    dims=[]
+    for i in range( ndims ):
+        curdim = int( random.uniform(2,4) )
+        dims.append( curdim )
+    return make_random(dims )
+
+def test_fftnd(ndims=3):
+    import FFT
+    import Numeric
+
+    x=randmat( ndims )
+    print 'dimensions=%s' % str( Numeric.shape(x) )
+    #print 'x=%s' %str(x)
+    xver = FFT.fftnd(x)
+    x2=myfftnd(x)
+    err = xver - x2
+    errf = flatten(err)
+    xverf = flatten(xver)
+    errpow = Numeric.vdot(errf,errf)+1e-10
+    sigpow = Numeric.vdot(xverf,xverf)+1e-10
+    snr = 10*math.log10(abs(sigpow/errpow) )
+    print 'SNR(compared to Python FFT module) =%sdB' % str( snr )
+    if snr<80:
+        print xver
+        print x2
+        sys.exit(1)
+ 
+def myfftnd(x):
+    import Numeric
+    xf = flatten(x)
+    Xf = fftndwork( xf , Numeric.shape(x) )
+    return Numeric.reshape(Xf,Numeric.shape(x) )
+
+def fftndwork(x,dims):
+    import popen2
+
+    cmd = '../tools/fft -n '
+    cmd += ','.join([str(d) for d in dims])
+    p = popen2.Popen3(cmd )
+    p.tochild.write( dopack( x , 'f' ,1 ) )
+    p.tochild.close()
+    res = dounpack( p.fromchild.read() , 'f' ,1 )
+    p.wait()
+    return res
+
+    #import Numeric
+    #dimprod=Numeric.product( dims )
+#
+    #for k in range( len(dims) ):
+        #cur_dim=dims[ k ]
+        #stride=dimprod/cur_dim
+        #next_x = [complex(0,0)]*len(x)
+        #for i in range(stride):
+            #next_x[i*cur_dim:(i+1)*cur_dim] = fft(x[i:(i+cur_dim)*stride:stride],0)
+        #x = next_x
+    #return x
+
+if __name__ == "__main__":
+    try:
+        nd = int(sys.argv[1])
+    except:
+        nd=None
+    if nd:    
+        test_fftnd( nd )
+    else:    
+        sys.exit(0)