add relative import and change 'print' function to be compatible with python3

README.md

@@ -1,5 +1,7 @@
 ## GLRM
 
+### The original repo is out of maintained from the original author. This repo has several updates, including README, glrm.py, setup.py etc. It still has some instability issue.
+
 GLRM is a python package for exploratory data analysis using Generalized Low
 Rank Models (GLRMs). 
 
@@ -63,8 +65,8 @@ For example, if a 4x4 block of data is missing from the center of A,
 this corresponds to rows 24-27 and columns 49-50 of submatrix 1,
 and rows 24-27 and columns 1-2 of submatrix 2. (Python is 0-indexed.)
 
-    missing1     = [(23, 48), (23, 49), (24, 48), (24, 49), \
-                    (25, 48), (25, 49), (26, 48), (26, 49)]
+    missing1     = [(48, 23), (49, 23), (48, 24), (49, 24), \
+                    (48, 22), (49, 21), (48, 21), (49, 22)]
     missing2     = [(23, 0), (23, 1), (24, 0), (24, 1), \
                     (25, 0), (25, 1), (26, 0), (26, 1)]
     missing_list = [missing1, missing2]

glrm/__init__.py

@@ -1 +1 @@
-from glrm import GLRM
+from .glrm import GLRM

glrm/convergence.py

@@ -15,7 +15,7 @@ def d(self): # if converge.d == True:
         # return True if converged
         if len(self) < 2: return False
         if len(self) > self.max_iters: 
-            print "hit max iters for convergence object"
+            print( "hit max iters for convergence object")
             return True
         return abs(self.obj[-1] - self.obj[-2])/self.obj[-2] < self.TOL
 

glrm/glrm.py

@@ -1,4 +1,4 @@
-from convergence import Convergence
+from .convergence import Convergence
 from numpy import sqrt, repeat, tile, hstack, array, zeros, ones, sqrt, diag, asarray, hstack, vstack, split, cumsum
 from numpy.random import randn
 from copy import copy
@@ -161,7 +161,7 @@ def _initialize_XY(self, B, k, missing_list):
 
     def _finalize_XY(self, Xv, Yv):
         """ Multiply by std, offset by mean """
-        m, k = Xv.shape.size
+        m, k = Xv.size
         self.X = asarray(hstack((Xv.value, ones((m,1)))))
         self.Y = [asarray(yj.value)*tile(mask[0,:],(k+1,1)) \
                 for yj, mask in zip(Yv, self.masks)]

glrm/reg.py

@@ -1,6 +1,6 @@
 from numpy.linalg import norm
 from numpy import sign, Inf
-from util import shrinkage
+from .util import shrinkage
 import cvxpy as cp
 
 """

setup.py

@@ -10,5 +10,7 @@
         url="http://github.com/cehorn/GLRM/",
         license="MIT",
         install_requires=[  "numpy >= 1.8",
-                            "scipy >= 0.13"]
+                            "scipy >= 0.13"
+			    "cvxpy >= 0.4.11"
+			    "matplotlib >= 2.1.2"]
 )