| Re: clustering [message #54895 is a reply to message #54850] |
Thu, 19 July 2007 09:12   |
nivedita.raghunath
Messages: 15
Registered: July 2006
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Junior Member |
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Here is a subset of my data.
IDL> help,pos1
POS1 FLOAT = Array[7, 53]
IDL> print,pos1
0.910300 0.413400 -0.0221000 0.00300000 -150.250
129.510 -13.0400
0.910200 0.413400 -0.0223000 0.00370000 -150.280
129.460 -13.0200
0.910200 0.413500 -0.0228000 0.00360000 -150.300
129.400 -13.1300
0.910200 0.413400 -0.0231000 0.00310000 -150.190
129.520 -13.0700
0.910200 0.413400 -0.0226000 0.00320000 -150.220
129.580 -13.0800
0.910200 0.413600 -0.0224000 0.00460000 -150.510
129.040 -13.1000
0.910200 0.413500 -0.0221000 0.00250000 -150.210
129.560 -13.0000
0.910200 0.413500 -0.0223000 0.00340000 -150.310
129.420 -13.1000
0.910200 0.413500 -0.0225000 0.00350000 -150.160
129.620 -13.0900
0.910200 0.413500 -0.0224000 0.00240000 -150.090
129.720 -13.0100
0.930600 0.365500 -0.0216000 0.00170000 -147.800
125.760 -16.7500
0.930500 0.365600 -0.0220000 0.000900000 -147.650
125.160 -16.6800
0.930500 0.365700 -0.0222000 0.00230000 -147.930
125.370 -16.8100
0.930500 0.365700 -0.0217000 0.00280000 -148.090
125.750 -16.8600
0.930400 0.365800 -0.0225000 0.00240000 -147.800
125.400 -16.8200
0.930400 0.365800 -0.0213000 0.00430000 -148.490
124.950 -16.7800
0.930400 0.365800 -0.0220000 0.00210000 -147.910
126.000 -16.7200
0.930400 0.365800 -0.0220000 0.00200000 -147.830
125.560 -16.6900
0.930400 0.365900 -0.0216000 0.00250000 -148.080
125.490 -16.7700
0.930400 0.365800 -0.0224000 0.00230000 -147.870
125.980 -16.6200
0.897600 0.439600 -0.0331000 0.00790000 -147.060
130.970 -6.02000
0.897600 0.439500 -0.0334000 0.00720000 -146.790
130.520 -6.13000
0.897500 0.439600 -0.0337000 0.00770000 -146.820
130.660 -6.13000
0.897500 0.439600 -0.0328000 0.00750000 -147.160
130.790 -6.13000
0.897600 0.439600 -0.0331000 0.00680000 -146.860
130.570 -6.07000
0.897600 0.439600 -0.0335000 0.00700000 -146.830
130.660 -6.12000
0.897600 0.439500 -0.0326000 0.00750000 -147.090
130.870 -6.08000
0.897600 0.439600 -0.0327000 0.00750000 -146.880
130.610 -6.14000
0.897600 0.439500 -0.0336000 0.00810000 -146.980
130.560 -6.25000
0.897600 0.439500 -0.0331000 0.00800000 -147.130
130.820 -6.19000
0.897500 0.439600 -0.0332000 0.00800000 -147.000
130.600 -6.25000
0.871700 0.488800 -0.0332000 0.0102000 -146.260
133.480 -1.14000
0.871600 0.488900 -0.0330000 0.0111000 -146.390
133.540 -1.29000
0.871600 0.488900 -0.0347000 0.00920000 -145.690
132.630 -1.26000
0.871700 0.488800 -0.0337000 0.0103000 -146.100
133.330 -1.44000
0.871700 0.488700 -0.0336000 0.0104000 -146.310
133.610 -1.58000
0.871700 0.488800 -0.0340000 0.00950000 -145.820
132.840 -1.33000
0.872000 0.488200 -0.0335000 0.00960000 -146.040
133.140 -1.95000
0.872000 0.488200 -0.0330000 0.00820000 -145.910
133.210 -1.83000
0.872000 0.488300 -0.0333000 0.0100000 -146.040
133.110 -1.82000
0.872100 0.488200 -0.0330000 0.00880000 -146.000
133.150 -1.83000
0.872000 0.488200 -0.0335000 0.00900000 -145.910
133.210 -1.85000
0.873000 0.487300 -0.0227000 0.000700000 -143.720
132.260 -6.08000
0.872900 0.487300 -0.0230000 0.000100000 -143.630
132.350 -6.07000
0.872900 0.487300 -0.0235000 0.000500000 -143.560
132.370 -6.14000
0.872900 0.487300 -0.0234000 -0.000300000 -143.430
132.520 -6.15000
0.872900 0.487300 -0.0231000 0.000700000 -143.670
132.280 -6.15000
0.872900 0.487300 -0.0237000 0.000200000 -143.480
132.430 -6.07000
0.872900 0.487300 -0.0231000 0.000500000 -143.550
132.450 -6.03000
0.872900 0.487300 -0.0241000 -0.000200000 -143.440
132.450 -6.11000
0.872900 0.487300 -0.0237000 0.000400000 -143.470
132.490 -6.05000
0.873000 0.487300 -0.0228000 0.000600000 -143.700
132.270 -6.03000
0.872900 0.487300 -0.0235000 -0.000200000 -143.430
132.450 -6.10000
IDL> weights=clust_wts(pos1,n_clusters=5)
IDL> print,weights
0.159265 0.119451 0.113155 0.180601 0.0680267
0.243488 0.116014
0.874568 0.483835 -0.0256644 0.00231699 -144.219
132.388 -5.40240
0.113501 0.127323 0.0985566 0.247231 0.225678
0.0779656 0.109745
0.238006 0.236222 0.127174 0.0261984 0.266028
0.0180832 0.0882878
0.0301962 0.232814 0.209770 0.146116 0.235975
0.134589 0.0105386
IDL> result=cluster(pos1,weights,n_clusters=5)
IDL> print,result(uniq(result))
1
The 5 clusters are pretty distinct but "cluster" does a hopeless job
identifying them. I tried scaling the data but that too finds 3
clusters in the end. Any ideas?
On Jul 18, 3:07 pm, Conor <cmanc...@gmail.com> wrote:
> On Jul 17, 11:36 am, nivedita.raghun...@gmail.com wrote:
>
>> Hi all,
>
>> I am trying to cluster a (7 x n) array with n_clusters=5. Visually I
>> can see 5 distinct clusters, but when I do clust_wts the cluster
>> centroids don't end up right. No matter what options I give, clust_wts
>> refuses to find the clusters.
>
>> Any idea on whats going on ?
>
>> Thanks,
>> Nivedita
>
> No idea. More information might be helpful. It's quite possible
> though that the the clust_wts algorithm just doesn't work for your
> particular data set, at least not as well as you apparently want it to.
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