Merge pull request #645 from jlaura/master

Update to weights module documentation for PySAL-REST
pysal · Jun 27, 2015 · 057016f · 057016f
2 parents 47899f8 + dc3efcd
commit 057016f
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Showing 5 changed files with 43 additions and 21 deletions.
diff --git a/pysal/spatial_dynamics/ergodic.py b/pysal/spatial_dynamics/ergodic.py
@@ -21,7 +21,7 @@ def steady_state(P):
 
     Returns
     -------
-    matrix 
+    	     : matrix 
                (k, 1), steady state distribution.
 
     Examples
@@ -125,12 +125,12 @@ def var_fmpt(P):
 
     Parameters
     ----------
-    P      : matrix 
+    P      : matrix
              (k, k), an ergodic Markov transition probability matrix.
 
     Returns
     -------
-    matrix 
+    	   : matrix 
              (k, k), elements are the variances for the number of intervals
              required for a chain starting in state i to first enter state j.
 

diff --git a/pysal/spatial_dynamics/markov.py b/pysal/spatial_dynamics/markov.py
@@ -574,7 +574,7 @@ def chi2(T1, T2):
  
     Returns
     -------
-    tuple 
+    	  : tuple 
             (3 elements).
             (chi2 value, pvalue, degrees of freedom).
 
@@ -1288,7 +1288,7 @@ def homogeneity(transition_matrices, regime_names=[], class_names=[], \
 
     Returns
     -------     
-    implicit            
+    			: implicit            
                           an instance of Homogeneity_Results.
     """
 
@@ -1314,6 +1314,9 @@ class Homogeneity_Results:
     title               : string
                           Title of the table.
 
+    Attributes
+    -----------
+
     Notes
     -----
     Degrees of freedom adjustment follow the approach in Bickenbach and Bode (2003) [3]_.
@@ -1506,4 +1509,4 @@ def summary(self, file_name=None, title="Markov Homogeneity Test"):
                 c.append("\\hline\n")
                 c.append("\\end{tabular}")
                 s2 = "".join(c)
-                f.write(s1+s2)
+                f.write(s1+s2)
diff --git a/pysal/spatial_dynamics/rank.py b/pysal/spatial_dynamics/rank.py
@@ -269,7 +269,7 @@ def _calc(self, x, y):
         return tau, pval, Concordant, Discordant, ExtraX, ExtraY
 
 
-class SpatialTau:
+class SpatialTau(object):
     """
     Spatial version of Kendall's rank correlation statistic.
 
@@ -333,13 +333,16 @@ class SpatialTau:
     ----------
     .. [3] Christensen, D. (2005) "Fast algorithms for the calculation of
        Kendall's tau." Computational Statistics, 20: 51-62.
+  
     .. [4] Press, W.H, S. A Teukolsky, W.T. Vetterling and B. P. Flannery (2007).
        Numerical Recipes: The Art of Scientific Computing. Cambridge. Pg 752.
+    
     .. [5] Rey, S.J. (2004) "Spatial dependence in the evolution of regional income
        distributions," in A. Getis, J. Mur and H.Zoeller (eds). Spatial
        Econometrics and Spatial Statistics. Palgrave, London, pp. 194-213.
+
     .. [6] Rey, S.J. (2014) "Fast algorithms for calculation of a space-time
-       concordance measure." Computational Statistics, 29(3-4):799–811.
+       concordance measure." Computational Statistics, 29(3-4): 799-811.
 
     Examples
     --------

diff --git a/pysal/weights/Distance.py b/pysal/weights/Distance.py
@@ -217,6 +217,17 @@ class Kernel(W):
                   adjustment to ensure knn distance range is closed on the
                   knnth observations
 
+    Attributes
+    ----------
+    weights : dict
+	      Dictionary keyed by id with a list of weights for each neighbor
+
+    neighbors : dict
+		of lists of neighbors keyed by observation id
+
+    bandwidth : array
+ 		array of bandwidths
+
     Examples
     --------
 
@@ -428,6 +439,14 @@ class DistanceBand(W):
     ids         : list
                   values to use for keys of the neighbors and weights dicts
 
+    Attributes
+    ----------
+    weights : dict
+	      of neighbor weights keyed by observation id
+
+    neighbors : dict
+		of neighbors keyed by observation id
+    
     Examples
     --------
 

diff --git a/pysal/weights/util.py b/pysal/weights/util.py
@@ -456,15 +456,15 @@ def higher_order_sp(w, k=2, shortest_path=True, diagonal=False):
     Contiguity weights for either a sparse W or pysal.weights.W  for order k.
 
     Parameters
-    ==========
+    ----------
 
-    w           :   W, sparse_matrix
-                    spatial weights object or scipy.sparse.csr.csr_instance
+    w           :   W
+		    sparse_matrix, spatial weights object or scipy.sparse.csr.csr_instance
 
     k           :   int
                     Order of contiguity
 
-    shortest_path:  boolean
+    shortest_path :  boolean
                     True: i,j and k-order neighbors if the
                     shortest path for i,j is k
                     False: i,j are k-order neighbors if there
@@ -476,10 +476,8 @@ def higher_order_sp(w, k=2, shortest_path=True, diagonal=False):
 
     Returns
     -------
-
-    wk: W, WSP
-        type matches type of w argument
-
+    wk : W
+	 WSP, type matches type of w argument
 
     Notes
     -----
@@ -679,10 +677,9 @@ def full(w):
 
     Returns
     -------
-
-    tuple
-               first element being the full numpy array and second element
-               keys being the ids associated with each row in the array.
+    (fullw, keys) : tuple
+                    first element being the full numpy array and second element
+                    keys being the ids associated with each row in the array.
 
     Examples
     --------
@@ -714,7 +711,6 @@ def full(w):
 def full2W(m, ids=None):
     '''
     Create a PySAL W object from a full array.
-    ...
 
     Parameters
     ----------
@@ -781,6 +777,7 @@ def full2W(m, ids=None):
 
 
 def WSP2W(wsp, silent_island_warning=False):
+
     """
     Convert a pysal WSP object (thin weights matrix) to a pysal W object.