uploading

basemap.py

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+from mpl_toolkits.basemap import Basemap
+from matplotlib import pyplot
+import numpy as np
+import CoreLocation
+
+manager = CoreLocation.CLLocationManager.alloc().init()
+manager.delegate()
+manager.startUpdatingLocation()
+loc = manager.location()
+if loc is None:
+ lat, lon = 0,0
+else:
+ coord = loc.coordinate()
+ lat, lon = coord.latitude, coord.longitude
+
+//def convert_to_decimal(degrees, arcminutes, arcseconds):
+// return float(degrees + arcminutes/60. + arcseconds/3600.)
+
+m = Basemap(projection='merc',llcrnrlat=-80,urcrnrlat=80,llcrnrlon=-180,urcrnrlon=180,lat_ts=20,resolution='c')
+
+m.drawcoastlines()
+m.drawstates()
+m.bluemarble()
+m.drawparallels(np.arange(-90.,91.,30.))
+m.drawmeridians(np.arange(-180.,181.,60.))
+m.drawmapboundary(fill_color='aqua')
+m.scatter(lon,lat,100,latlon=1,color='m',marker='.')
+
+pyplot.title("Mercator Projection | Latitude: " + str(lat) + ", Longitude: " + str(lon))
+pyplot.show()

finance.py

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+import math
+import csv
+import numpy
+import numpy as np
+import scipy as sp
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import scipy.fftpack
+import datetime
+import pandas as pd
+from scipy import stats
+
+def pv(fv,r):
+ return (fv/(1+r))
+
+def pvSum(c,r): //PV as a sum of cash flows c w/ interest rate 
+ sum=0
+ for n, ck in enumerate(c):
+  print n,ck,r
+  sum += ck/((1+r)**n)
+ return sum
+
+def annuity(A,r): //Annuity pays A forever
+ return A/r
+
+def annuityEnd(A,r,n)Annuity that pays A until n
+ return annuity(A,r)*(1-1/((1+r)**n)) 
+
+def discountRate(spotRate,t): 
+ return 1/((1+spotRate)**t)
+
+def fv(pv,r):
+ return (pv*(1+r))
+
+def p(f,i,n):
+ return (f/((1+i)**n))
+vec_p = np.vectorize(p)
+ptest = np.array([np.array([ 1.,  2.,  3.]), np.array(10), np.array(10)])
+vec_p(ptest[0],ptest[1],ptest[2])
+
+def f(p,i,n):
+ return (p*((1+i)**n))
+
+def fe(p,i,n):
+ return (p*(math.e**(i*n)))
+
+def pe(f,i,n):
+ return (f/(math.e**(i*n)))
+
+cpiv = []
+cpid = []
+with open('CPIAUCSL.csv', 'rb') as cpifile:
+ cpi = csv.reader(cpifile)
+ for row in cpi:
+  cpiv.append(row[1])
+  cpid.append(row[0])
+
+cpiv.pop(0)
+cpid.pop(0)
+
+cpidd = []
+for item in cpid:
+ cpidd.append(mpl.dates.date2num(datetime.datetime.strptime(item, "%Y-%m-%d")))
+
+plt.plot_date(x=cpidd,y=cpiv)
+plt.show()
+
+c = []
+b = 0
+for a in cpiv:
+  if b: c.append((float(a)-b)/float(a))
+  b = float(a)
+
+numpy.mean(c)*12
+
+x = np.poly1d([1,0])
+
+cpif = scipy.fftpack.fft(cpim)
+
+def ERi(Rf,Bi,ERm): //CAPM
+ return (Rf+Bi*(ERm-Rf))
+
+df = pd.read_csv('CPIAUCSL.csv')
+
+x = [5.05, 6.75, 3.21, 2.66]
+y = [1.65, 26.5, -5.93, 7.96]
+gradient, intercept, r_value, p_value, std_err = stats.linregress(x,y)
+t = np.arange([0.0, 10.0, 0.1])
+z = gradient*t+intercept
+plt.plot(t,z)
+plt.scatter(x,y)
+plt.show()

freq.py

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+import pandas as pd
+import matplotlib.pyplot as plt
+freq = pd.read_csv('frequency.csv', sep=',')
+freq['count'].plot()
+plt.show()

getFlows.py

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+from lxml import etree
+from cStringIO import StringIO
+import pycurl
+import pandas as pd
+import datetime
+
+start = datetime.datetime(2014,9,19)
+finish = datetime.datetime(2014,11,2)
+delta = datetime.timedelta(hours=1)
+times = []
+while start <= finish:
+ times.append(start)
+ start += delta
+
+for start in times:
+ print start.strftime("%Y-%m-%dT%H:%M:%SZ")
+ end = start + delta
+ request1 = '<?xml version="1.0" encoding="UTF-8"?><soapenc:Envelope xmlns:soapenc="http://schemas.xmlsoap.org/soap/envelope/"><soapenc:Body><getFlows><flow-filter max-rows="100000" domain-id="133" include-interface-data="false">'
+ request2 = '<date-selection><time-range-selection start="' + start.strftime("%Y-%m-%dT%H:%M:%SZ") + '" end="' + end.strftime("%Y-%m-%dT%H:%M:%SZ") + '" /></date-selection>'
+ request3 = '<applications>175,53</applications>'
+ request4 = '</flow-filter></getFlows></soapenc:Body></soapenc:Envelope>'
+ request = request1 + request2 + request3 + request4
+ buffer = StringIO()
+ co = pycurl.Curl()
+ co.setopt(co.UNRESTRICTED_AUTH,1)
+ co.setopt(co.URL,"https://lancope.example.com/smc/swsService/flows")
+ co.setopt(co.POST, 1)
+ co.setopt(co.INFILESIZE,len(request) + 1) 
+ co.setopt(co.WRITEFUNCTION, buffer.write)
+ co.setopt(co.POSTFIELDS, request)
+ co.setopt(co.SSL_VERIFYPEER, 0L) 
+ co.setopt(co.SSL_VERIFYHOST, 0L) 
+ co.setopt(co.USERPWD,"username:password")
+ try:
+  co.perform()
+ except:
+  print "POST failed"
+  exit(1)
+
+ co.close()
+ out = buffer.getvalue()
+ buffer.close()
+ doc = etree.fromstring(out)
+ netflows = [('client', 'clientHostName', 'clientPort', 'clientPackets', 'clientBytes', 'server', 'serverHostName', 'serverPort', 'serverPackets', 'serverBytes', 'startTime', 'lastTime', 'activeDuration')]
+ for elem in doc.getiterator('{http://www.lancope.com/sws/sws-service}flow'):
+  startTime = elem.get('start-time')
+  lastTime = elem.get('last-time')
+  activeDuration = elem.get('active-duration')
+  client = elem[0].get('ip-address')
+  clientHostName = elem[0].get('host-name')
+  clientPort = elem[0].get('port')
+  clientPackets = elem[0].get('packets')
+  clientBytes = elem[0].get('bytes')
+  server = elem[1].get('ip-address')
+  serverHostName = elem[1].get('host-name')
+  serverPort = elem[1].get('port')
+  serverPackets = elem[1].get('packets')
+  serverBytes = elem[1].get('bytes')
+  netflows.append((client, clientHostName, clientPort, clientPackets, clientBytes, server, serverHostName, serverPort, serverPackets, serverBytes, startTime, lastTime, activeDuration))
+
+ pd.DataFrame(netflows).to_csv(start.strftime("%Y-%m-%dT%H%M%SZ") + end.strftime("%Y-%m-%dT%H%M%SZ") + '.csv')

gis.py

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+import shapely.geometry
+import matplotlib.pyplot as plt
+import fiona.collection
+import descartes
+
+places = {'Los Angeles': (34.0204989,-118.4117325), 'Phoenix': (33.6054149,-112.125051), 'Albuquerque': (35.0824099,-106.6764794)}
+
+path = [(x, y) for y, x in places.values()]
+ls = shapely.geometry.LineString(path)
+
+with fiona.collection("tl_2014_us_state/tl_2014_us_state.shp") as features:
+    states = [shapely.geometry.shape(f['geometry']) for f in features]
+
+fig = plt.figure(figsize=(8,5), dpi=180)
+ax = fig.add_subplot(111)
+ax.axis([-125, -65, 25, 50])
+ax.axis('off')
+
+ax.plot(*ls.xy, color='#FFFFFF')
+
+for state in states:
+ if state.geom_type =='Polygon':
+  state = [state]
+ for poly in state:
+  poly_patch = descartes.PolygonPatch(poly, fc='#6699cc', ec='#000000')
+  ax.add_patch(poly_patch)
+
+for x, y in path:
+ buffered = shapely.geometry.Point(x, y).buffer(1)
+ ax.add_patch(descartes.PolygonPatch(buffered, fc='#EEEEEE', ec='#000000'))
+
+
+fig.show()

gpx.py

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+import gpxpy
+
+gpx_file = open("file", 'r')
+gpx = gpxpy.parse(gpx_file)
+
+points = []
+for point in gpx.tracks[0].segments[0].points:
+ points.append((point.latitude,point.longitude,point.elevation,point.time))

map.py

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+import overpy
+import numpy
+from matplotlib import pyplot
+from shapely.geometry import LineString
+from shapely.geometry import shape
+from shapely.ops import polygonize_full
+from descartes import PolygonPatch
+from fiona import collection
+from geopandas import GeoSeries
+from geopandas import GeoDataFrame
+
+api = overpy.Overpass()
+
+countyRelation = api.query("rel(396479);(._;>;);out;")
+primaryHighwaysInBoundingBox = api.query("way(33.5277,-119.3500,34.9895,-117.1115)[highway=primary];(._;>);out;")
+
+countyWaysAboveIslands = []
+for way in countyRelation.ways:
+ above = 1
+ for node in way.nodes:
+  if (node.lat < 33.6078):
+   above = 0
+ if (above):
+  countyWaysAboveIslands.append(way)
+
+countyLineStrings = []
+for way in countyWaysAboveIslands:
+ lineString = []
+ for node in way.nodes:
+  lineString.append((node.lat,node.lon))
+ countyLineStrings.append(LineString(lineString))
+
+polygons, dangles, cuts, invalids = polygonize_full(countyLineStrings)
+countyPolygon = polygons.geoms[0]
+
+highwayLineStrings = []
+for way in primaryHighwaysInBoundingBox.ways:
+ line = []
+ for node in way.nodes:
+  line.append((node.lat,node.lon))
+ wayLineString = LineString(line)
+ if countyPolygon.contains(wayLineString): highwayLineStrings.append(wayLineString)
+
+fig = pyplot.figure(figsize=(100,100))
+ax = fig.add_subplot(111)
+
+for line in highwayLineStrings:
+ x, y = line.xy
+ ax.plot(x, y, color='#999999', linewidth=1, zorder=1)
+
+patch = PolygonPatch(countyPolygon, fc='#6699cc', ec='#6699cc', alpha=0.5, zorder=2)
+ax.add_patch(patch)
+
+fig.savefig('test.png')
+
+// debug info
+
+from shapely.geometry import MultiLineString
+test = MultiLineString(highwayLineStrings)
+patch = PolygonPatch(countyPolygon, fc='#6699cc', ec='#6699cc', alpha=0.5, zorder=2)
+ax.add_patch(patch)
+
+object.__dict__
+result.nodes
+result.nodes.[0].lat
+result.ways
+result.ways[0]._node_ids[0]
+result.relations
+result.relations[0].members[0].ref
+
+len(streetsInBB.ways[0].get_nodes(resolve_missing=True))
+
+for way in aboveIslands:
+ gray = gray + .025
+ for node in way.nodes:
+  ax.scatter(node.lon, node.lat, color=[gray,gray,gray], s=100, zorder=1)
+
+states = [shapely.geometry.shape(f['geometry']) for f in features]
+
+http://overpass.osm.rambler.ru/cgi/interpreter?data=%5Bout:json%5D;relation(396479);out;
+

risk.py

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+import numpy as np
+//from pylab import *
+import matplotlib.pyplot as plot
+import math
+
+top = np.array([[0,1,2],[2,2,1]])
+mid = np.array([[0,1,2],[2,1,0]])
+bot = np.array([[0,1,2],[2,0,0]])
+
+plot.plot(top[0],top[1])
+plot.plot(mid[0],mid[1])
+plot.plot(bot[0],bot[1])
+
+t = np.arange(0.0, 10.0, 0.1)
+top2 = 10-np.arange(0.0, 1.0, 0.01)
+top = 10-(.3*t)**2
+mid = -t + 10
+bot = 10-np.sqrt(t)
+bot2 = 1/(t)
+
+plot.plot(t,top2)
+plot.plot(t,top)
+plot.plot(t,mid)
+plot.plot(t,bot)
+plot.plot(t,bot2)
+
+plot.scatter(2,6)
+plot.scatter(2,5)
+plot.scatter(9,1)
+
+plot.xlabel('Cost')
+plot.ylabel('Risk')
+plot.title('Risk vs. Cost')
+plot.grid(True)
+plot.show()
+
+
+\\Risk = Money * Time
+\\ Time = constant * Money
+\\ Outsource Time = constant1 * Time + constant2 * Money