Francis Tseng frnsys

## main.py
import numpy as np
from pyqtree import Index
from shapely import geometry
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
plt.style.use('ggplot')

# distance we expect the bus stop to be from the road
# will pad all bounding boxes accordingly
radius = 0.1

## index.html
<!doctype html>
<html lang="en">
  <head>
    <meta charset="utf-8"/>
    <meta name="viewport" content="width=device-width,initial-scale=1">
    <title>hello</title>
  </head>
  <body>
    <div id="root">Loading...</div>
    <script src="bundle.js"></script>

## gist:e669832a002c1f838baeb3465418de30
! Enabled modi
rofi.modi:                           window,run,ssh
! Window opacity
rofi.opacity:                        100
! Window width
rofi.width:                          50
! Number of lines
rofi.lines:                          15
! Number of columns
rofi.columns:                        1

## 2d_to_3d.py
import numpy as np

# the 2d array of our samples,
# each component is a category label
a = np.array([[1,2,3],[4,5,6]])

# the 3d array that will be the one-hot representation
# a.max() + 1 is the number of labels we have
b = np.zeros((a.shape[0], a.shape[1], a.max() + 1))

## keybase.md

      
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                frnsys
                / keybase.md
            
            
              Created
              January 13, 2016 16:59
            
          
    Keybase proof

I hereby claim:

I am frnsys on github.
I am frnsys (https://keybase.io/frnsys) on keybase.
I have a public key ASAvmZ40BDsDnDvSA1Gk5otOjOKmLmFe-tK1dGb3S18gjAo

To claim this, I am signing this object:

  
## optics.py
# Copyright (c) 2012, Ryan Gomba
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
#    list of conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright notice,
#    this list of conditions and the following disclaimer in the documentation

## train_doc2vec.py
import sys
import logging
import numpy
import gensim


logging.basicConfig(level=logging.INFO)

train_sentences = gensim.models.doc2vec.LabeledLineSentence(sys.argv[1])
model = gensim.models.Doc2Vec(train_sentences, size=400, window=8, min_count=2,

## contagion.py
import random
import networkx as nx

class Person():
    def __init__(self, name, stance=None):
        self.name = name

        if stance is None:
            self.stance = random.randrange(0, 2)
        else:

## hac.py
import operator
from itertools import combinations
from functools import reduce

import numpy as np

def hac(vecs, sim_func, threshold):
    """
    Hierarchical Agglomerative Clustering.
    """

## carray_test.py
# Adapted from
# http://pytables.github.io/usersguide/libref/homogenous_storage.html#the-carray-class

import os
import numpy
import tables
from itertools import groupby
from operator import itemgetter
from time import time
	import numpy as np
	from pyqtree import Index
	from shapely import geometry
	import matplotlib.pyplot as plt
	from matplotlib.patches import Polygon
	plt.style.use('ggplot')

	# distance we expect the bus stop to be from the road
	# will pad all bounding boxes accordingly
	radius = 0.1
	<!doctype html>
	<html lang="en">
	<head>
	<meta charset="utf-8"/>
	<meta name="viewport" content="width=device-width,initial-scale=1">
	<title>hello</title>
	</head>
	<body>
	<div id="root">Loading...</div>
	<script src="bundle.js"></script>
	! Enabled modi
	rofi.modi: window,run,ssh
	! Window opacity
	rofi.opacity: 100
	! Window width
	rofi.width: 50
	! Number of lines
	rofi.lines: 15
	! Number of columns
	rofi.columns: 1
	import numpy as np

	# the 2d array of our samples,
	# each component is a category label
	a = np.array([[1,2,3],[4,5,6]])

	# the 3d array that will be the one-hot representation
	# a.max() + 1 is the number of labels we have
	b = np.zeros((a.shape[0], a.shape[1], a.max() + 1))
	# Copyright (c) 2012, Ryan Gomba
	# All rights reserved.
	#
	# Redistribution and use in source and binary forms, with or without
	# modification, are permitted provided that the following conditions are met:
	#
	# 1. Redistributions of source code must retain the above copyright notice, this
	# list of conditions and the following disclaimer.
	# 2. Redistributions in binary form must reproduce the above copyright notice,
	# this list of conditions and the following disclaimer in the documentation
	import sys
	import logging
	import numpy
	import gensim


	logging.basicConfig(level=logging.INFO)

	train_sentences = gensim.models.doc2vec.LabeledLineSentence(sys.argv[1])
	model = gensim.models.Doc2Vec(train_sentences, size=400, window=8, min_count=2,
	import random
	import networkx as nx

	class Person():
	def __init__(self, name, stance=None):
	self.name = name

	if stance is None:
	self.stance = random.randrange(0, 2)
	else:
	import operator
	from itertools import combinations
	from functools import reduce

	import numpy as np

	def hac(vecs, sim_func, threshold):
	"""
	Hierarchical Agglomerative Clustering.
	"""
	# Adapted from
	# http://pytables.github.io/usersguide/libref/homogenous_storage.html#the-carray-class

	import os
	import numpy
	import tables
	from itertools import groupby
	from operator import itemgetter
	from time import time