[pysal] 01/02: Add patch to fix TabErrors.

Bas Couwenberg sebastic at debian.org
Sat Jul 30 23:27:05 UTC 2016


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sebastic pushed a commit to branch master
in repository pysal.

commit 600c7d1c2760af4abfca3dfd31c2f9c5104e3b00
Author: Bas Couwenberg <sebastic at xs4all.nl>
Date:   Sun Jul 31 01:08:44 2016 +0200

    Add patch to fix TabErrors.
---
 debian/changelog              |   1 +
 debian/patches/series         |   1 +
 debian/patches/taberror.patch | 130 ++++++++++++++++++++++++++++++++++++++++++
 3 files changed, 132 insertions(+)

diff --git a/debian/changelog b/debian/changelog
index 270dcc7..3312f42 100644
--- a/debian/changelog
+++ b/debian/changelog
@@ -2,6 +2,7 @@ pysal (1.11.2-3) UNRELEASED; urgency=medium
 
   * Team upload.
   * Remove unneeded conditional in reproducible-build-and-output.patch.
+  * Add patch to fix TabErrors.
 
  -- Bas Couwenberg <sebastic at debian.org>  Sat, 30 Jul 2016 20:00:20 +0200
 
diff --git a/debian/patches/series b/debian/patches/series
index 2c793e3..8600986 100644
--- a/debian/patches/series
+++ b/debian/patches/series
@@ -1,2 +1,3 @@
 unusual-interpreter.patch
 reproducible-build-and-output.patch
+taberror.patch
diff --git a/debian/patches/taberror.patch b/debian/patches/taberror.patch
new file mode 100644
index 0000000..2e87d79
--- /dev/null
+++ b/debian/patches/taberror.patch
@@ -0,0 +1,130 @@
+Description: Fix TabErrors.
+ Sorry: TabError: inconsistent use of tabs and spaces in indentation (klincs.py, line 34)
+ Sorry: TabError: inconsistent use of tabs and spaces in indentation (lincs.py, line 287)
+Author: Bas Couwenberg <sebastic at debian.org>
+
+--- a/pysal/contrib/network/klincs.py
++++ b/pysal/contrib/network/klincs.py
+@@ -31,11 +31,11 @@ class WeightedRandomSampleGenerator(obje
+     """
+ 
+     def __init__(self, weights, population, n):
+-	"""
+-	weights: an iterable with m numeric elements
+-	population: a numpy array with m elements
+-	n: an integer representing sample size
+-	"""
++        """
++        weights: an iterable with m numeric elements
++        population: a numpy array with m elements
++        n: an integer representing sample size
++        """
+         self.totals = np.cumsum(weights)
+         self.population = population
+         self.n = n
+@@ -57,10 +57,10 @@ class RandomSampleGenerator(object):
+     from a population group
+     """
+     def __init__(self, population, n):
+-	"""
+-	population: a numpy array with m elements
+-	n: an integer representing sample size
+-	"""
++        """
++        population: a numpy array with m elements
++        n: an integer representing sample size
++        """
+         self.population = population
+         self.n = n
+ 
+--- a/pysal/contrib/network/lincs.py
++++ b/pysal/contrib/network/lincs.py
+@@ -284,11 +284,11 @@ def lincs(network, event, base, weight,
+     w, edges, e, b, edges_geom = None, None, None, None, []
+     if weight == 'Node-based':
+         w, edges = node_weights(network, attribute=True)
+-	n = len(edges)
+-	e, b = np.zeros(n), np.zeros(n)
+-	for edge in edges:
++        n = len(edges)
++        e, b = np.zeros(n), np.zeros(n)
++        for edge in edges:
+             edges_geom.append(edges[edge][0])
+-	    e[edge] = edges[edge][event]
++            e[edge] = edges[edge][event]
+             b[edge] = getBase(edges, edge, base)
+         w.id_order = edges.keys()
+     elif dist is not None:
+@@ -298,50 +298,50 @@ def lincs(network, event, base, weight,
+                 network[n1][n2] = network[n1][n2][0]
+         w, edges = dist_weights(network, id2edgepoints, edge2id, dist)
+         n = len(id2attr)
+-	e, b = np.zeros(n), np.zeros(n)
++        e, b = np.zeros(n), np.zeros(n)
+         if base:
+             base -= 1
+-	for edge in id2attr:
++        for edge in id2attr:
+             edges_geom.append(edges[edge])
+-	    e[edge] = id2attr[edge][event - 1]
++            e[edge] = id2attr[edge][event - 1]
+             b[edge] = getBase(id2attr, edge, base)
+         w.id_order = id2attr.keys()
+ 
+     Is, p_sim, Zs = None,None, None
+     if sim_method == 'permutation':
+         if lisa_func == pysal.esda.moran.Moran_Local:
+-	    lisa_i = lisa_func(e*1.0/b,w,transformation="r",permutations=sim_num)
++            lisa_i = lisa_func(e*1.0/b,w,transformation="r",permutations=sim_num)
+             Is = lisa_i.Is
+             Zs = lisa_i.q
+         else:
+-	    lisa_i = lisa_func(e*1.0/b,w,transform="R",permutations=sim_num,star=star)
++            lisa_i = lisa_func(e*1.0/b,w,transform="R",permutations=sim_num,star=star)
+             Is = lisa_i.Gs
+             Zs = lisa_i.Zs
+         p_sim = lisa_i.p_sim
+     else:
+-	sims = None
++        sims = None
+         if lisa_func == pysal.esda.moran.Moran_Local:
+-	    lisa_i = lisa_func(e*1.0/b,w,transformation="r",permutations=0)
++            lisa_i = lisa_func(e*1.0/b,w,transformation="r",permutations=0)
+             Is = lisa_i.Is
+             Zs = lisa_i.q
+         else:
+-	    lisa_i = lisa_func(e*1.0/b,w,transform="R",permutations=0,star=star)
+-	    Is = lisa_i.Gs
+-	    Zs = lisa_i.Zs
+-	if sim_method == 'binomial':
+-	    sims = unconditional_sim(e, b, sim_num)
+-	elif sim_method == 'poisson':
+-	    sims = unconditional_sim_poisson(e, b, sim_num)
+-	else:
+-	    sims = conditional_multinomial(e, b, sim_num)
++            lisa_i = lisa_func(e*1.0/b,w,transform="R",permutations=0,star=star)
++            Is = lisa_i.Gs
++            Zs = lisa_i.Zs
++        if sim_method == 'binomial':
++            sims = unconditional_sim(e, b, sim_num)
++        elif sim_method == 'poisson':
++            sims = unconditional_sim_poisson(e, b, sim_num)
++        else:
++            sims = conditional_multinomial(e, b, sim_num)
+         if lisa_func == pysal.esda.moran.Moran_Local:
+-	    for i in range(sim_num):
+-		sims[:,i] = lisa_func(sims[:,i]*1.0/b,w,transformation="r",permutations=0).Is
++            for i in range(sim_num):
++                sims[:,i] = lisa_func(sims[:,i]*1.0/b,w,transformation="r",permutations=0).Is
+         else:
+-	    for i in range(sim_num):
+-		sims[:,i] = lisa_func(sims[:,i]*1.0/b,w,permutations=0,star=star).Gs
+-	sim_res = pseudo_pvalues(Is, sims)
+-	p_sim = sim_res[0]
++            for i in range(sim_num):
++                sims[:,i] = lisa_func(sims[:,i]*1.0/b,w,permutations=0,star=star).Gs
++        sim_res = pseudo_pvalues(Is, sims)
++        p_sim = sim_res[0]
+ 
+     w.transform = 'O'
+     return zip(edges_geom, e, b, Is, Zs, p_sim), w

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