ljwolf

{
 "metadata": {
  "name": "",
  "signature": "sha256:757bae3d1c46461b74ec91af4b14ba7c0b8aa312faf196602171864e35bfed90"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [

ljwolf

import pysal as ps

#Lots of reload for dev.
try:
    reload(network)
except:
    import network
    
try:
    reload(analysis)

ljwolf

#!/bin/python
##ljw
##./$GIT_ROOT/pysal/network/fw.py
from collections import defaultdict
import pysal as ps
import numpy as np

ntw = ps.network.network.Network(ps.examples.get_path('geodanet/streets.shp'))

def floyd_warshall(ntw, cost = None, directed = False):

ljwolf

................F...
======================================================================
FAIL: test_assuncao_rate (__main__.TestUtils)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "pysal/esda/tests/test_smoothing.py", line 236, in test_assuncao_rate
    exp_assuncao, sm.assuncao_rate(e, b)[:4])
  File "/usr/lib/python3.4/site-packages/numpy/testing/utils.py", line 842, in assert_array_almost_equal
    precision=decimal)
  File "/usr/lib/python3.4/site-packages/numpy/testing/utils.py", line 665, in assert_array_compare

ljwolf

import pysal as ps
import numpy as np

df = ps.pdio.read_files(ps.examples.get_path('columbus.shp'))
W = ps.queen_from_shapefile(ps.examples.get_path('columbus.shp'))

y = df['HOVAL'].values
y.reshape(W.n,1)
X = df[['CRIME', 'INC']].values

ljwolf

ljwolf

Notes from ljwolf's GSOC call, 5/23

• Blog posts proceeding fine, should be simple to continue making them on schedule, at the pace at which I blog normally.
• Questions about Request for Comment:
  • What should I prioritize? NOGR or Labeled Array Interface?
    • Labeled Array. This is critical to get correct, and will make NOGR need and scope clearer.
• How deep into PySAL should the Labeled Array interface go?

ljwolf

ljwolf

import pandas as pd
import string 

df = pd.DataFrame([[*string.ascii_letters[0:26:2]],
                    *string.ascii_letters[1:26:2]])
rolled = df.rolling(window=2, center=False, axis=1).apply(lambda x: ''.join(x))

#expected: [['ac', 'ce', 'eg', 'gi', 'ik', 'km', 'mo', 'oq', 'qs', 'su', 'uw', 'wy'],
#            'bd', 'df', 'fh', 'hj', 'jl', 'ln', 'np', 'pr', 'rt', 'tv', 'vx', 'xz']]
print(rolled.values)

ljwolf