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1 #!/usr/bin/python
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2 #
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3 # Copyright (C) Christian Thurau, 2010.
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4 # Licensed under the GNU General Public License (GPL).
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5 # http://www.gnu.org/licenses/gpl.txt
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6 """
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7 PyMF Compact Matrix Decomposition [1]
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8
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9 CMD(CUR): Class for Compact Matrix Decomposition
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10
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11 [1] Sun, J., Xie, Y., Zhang, H. and Faloutsos, C. (2007), Less is More: Compact Matrix Decomposition for Large
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12 Sparse Graphs, in Proc. SIAM Int. Conf. on Data Mining.
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13 """
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14
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15
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16 import numpy as np
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17 from cur import CUR
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18
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19 __all__ = ["CMD"]
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20
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21 class CMD(CUR):
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22 """
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23 CMD(data, rrank=0, crank=0)
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24
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25
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26 Compact Matrix Decomposition. Factorize a data matrix into three matrices s.t.
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27 F = | data - USV| is minimal. CMD randomly selects rows and columns from
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28 data for building U and V, respectively.
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29
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30 Parameters
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31 ----------
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32 data : array_like [data_dimension x num_samples]
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33 the input data
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34 rrank: int, optional
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35 Number of rows to sample from data. Double entries are eliminiated s.t.
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36 the resulting rank might be lower.
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37 4 (default)
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38 crank: int, optional
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39 Number of columns to sample from data. Double entries are eliminiated s.t.
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40 the resulting rank might be lower.
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41 4 (default)
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42
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43 Attributes
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44 ----------
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45 U,S,V : submatrices s.t. data = USV
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46
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47 Example
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48 -------
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49 >>> import numpy as np
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50 >>> from cmd import CMD
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51 >>> data = np.array([[1.0, 0.0, 2.0], [0.0, 1.0, 1.0]])
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52 >>> cmd_mdl = CMD(data, show_progress=False, rrank=1, crank=2)
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53 >>> cmd_mdl.factorize()
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54 """
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55
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56 def _cmdinit(self):
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57 nrids = np.unique(self._rid)
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58 ncids = np.unique(self._cid)
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59
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60 self._rcnt = np.zeros(len(nrids))
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61 self._ccnt = np.zeros(len(ncids))
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62
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63 for i,idx in enumerate(nrids):
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64 self._rcnt[i] = len(np.where(self._rid == idx)[0])
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65
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66 for i,idx in enumerate(ncids):
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67 self._ccnt[i] = len(np.where(self._cid == idx)[0])
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68
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69 self._rid = np.int32(list(nrids))
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70 self._cid = np.int32(list(ncids))
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71
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72 def factorize(self):
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73 """ Factorize s.t. CUR = data
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74
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75 Updated Values
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76 --------------
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77 .C : updated values for C.
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78 .U : updated values for U.
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79 .R : updated values for R.
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80 """
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81
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82 [prow, pcol] = self.sample_probability()
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83
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84 self._rid = self.sample(self._rrank, prow)
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85 self._cid = self.sample(self._crank, pcol)
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86
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87 self._cmdinit()
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88
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89 self.computeUCR()
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90
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91
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92 if __name__ == "__main__":
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93 import doctest
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94 doctest.testmod()
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