In [1]:

    

import sys, os
import urllib2, httplib

%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib.image as mpimg

import numpy as np
import pandas as pd

from IPython.display import clear_output


    

In [75]:

    

def construct_googlemaps_url_request(center=None, zoom=None, imgsize=(500,500), \
                                     maptype="roadmap", apiKey="", imgformat="jpeg"):
    request =  "http://maps.google.com/maps/api/staticmap?" # base URL, append query params, separated by &
    if center is not None:
        request += "center=%s&"%center.replace(" ","+")
    if zoom is not None:
        request += "zoom=%d&"%zoom  # zoom 0 (all of the world scale ) to 22 (single buildings scale)
    if apiKey is not None:
        request += "key=%s&"%apiKey
    request += "size=%dx%d&"%imgsize  # tuple of ints, up to 640 by 640
    request += "format=%s&"%imgformat
    request += "maptype=%s&sensor=false"%maptype  # roadmap, satellite, hybrid, terrain
    return request


    

In [48]:

    

url = construct_googlemaps_url_request(center="Berkeley, CA")
url


    

    
Out[48]:





'http://maps.google.com/maps/api/staticmap?center=Berkeley,+CA&size=500x500&format=jpeg&maptype=roadmap&sensor=false'

In [78]:

    

import urllib
import cStringIO 
import Image

def get_static_google_map(request, filename=None):  
    if filename is not None:
        urllib.urlretrieve(request, filename) 
    else:
        web_sock = urllib.urlopen(request)
        imgdata = cStringIO.StringIO(web_sock.read()) # constructs a StringIO holding the image
        try:
            img = Image.open(imgdata)
        except IOError:
            print "IOError:", imgdata.read() # print error (or it may return a image showing the error"
            return None
        else:
            return np.asarray(img.convert("RGB"))


    

In [95]:

    

url = construct_googlemaps_url_request(center="Berkeley, CA", maptype="satellite", zoom=19)
img = get_static_google_map(url)


    

In [96]:

    

plt.figure(figsize=(7,7))
plt.imshow(img)


    

    
Out[96]:





<matplotlib.image.AxesImage at 0x7f93f8817990>






    

In [66]:

    

sites_df = pd.read_csv("/home/ubuntu/data/prop39/site_information.csv", \
                       converters={'Site CDS Code':str, 'Site ZIP Code':str})
sites_df.head()


    

    
Out[66]:






  

    

      

      
Site CDS Code
      
Site Name
      
Site City
      
Site Mailing Address
      
Site ZIP Code
      
lat
      
lon
    
  
  

    

      
0
      
1100170000000
      
Burke Center
      
Hayward
      
313 W.Winton Ave, Hayward, CA 94544
      
94544
      
37.658469
      
-122.098358
    
    

      
1
      
1611196090054
      
Lincoln Middle School
      
Alameda
      
1250 Fernside , Alameda, CA 94501
      
94501
      
37.751768
      
-122.232073
    
    

      
2
      
1611190132878
      
Encinal High School
      
Alameda
      
210 Cental Ave, Alameda, CA 94501
      
94501
      
37.772765
      
-122.289009
    
    

      
3
      
1611196110779
      
Bay Farm Elementary School
      
Alameda
      
200 Aughinbaugh Way , Alameda, CA 94502
      
94502
      
37.744121
      
-122.251922
    
    

      
4
      
1611196090005
      
Donald Lum Elemenary School
      
Alameda
      
1801 Sandcreek Way, Alameda, CA 94501
      
94501
      
37.761699
      
-122.260174
    
  

In [84]:

    

locations = dict(zip(sites_df['Site CDS Code'].values,
                 map(lambda x, y: "%2.6f,%2.6f"%(x,y), sites_df['lat'].values, sites_df['lon'].values)))


    

In [97]:

    

myAPIKey   = "AIzaSyAmgXPgd-Db8HD_juxtPf_4nricPBdcOrw"
myOutPath  = "/home/ubuntu/data/prop39/images/"
zoomLevels = [17, 18, 19]


    

In [90]:

    

url = construct_googlemaps_url_request(center=locations.values()[0], maptype="satellite", zoom=18, apiKey=myAPIKey)
img = get_static_google_map(url)
plt.figure(figsize=(7,7))
plt.imshow(img)


    

    
Out[90]:





<matplotlib.image.AxesImage at 0x7f93f8a8af50>






    

In [100]:

    

url = construct_googlemaps_url_request(center=locations.values()[0], maptype="satellite", zoom=18, apiKey=myAPIKey)
img = get_static_google_map(url, filename=myOutPath+"/%s.jpg"%locations.keys()[0])


    

In [102]:

    

if not os.path.exists(myOutPath):
    os.makedirs(myOutPath)
for zoom in zoomLevels:
    curDir = myOutPath + "/zoom%s/"%zoom
    if not os.path.exists(curDir):
        os.makedirs(curDir)


    

In [117]:

    

for i,row in sites_df.iloc[2837:].iterrows():
    clear_output(wait=True)
    siteId   = row['Site CDS Code']
    siteName = row['Site Name']
    if type(siteName) == str:
        siteName = siteName.replace(" ", "").replace(" ", "").replace(".","").replace("/","")
    else:
        siteName = "NONE"
    loc = "%2.6f,%2.6f"%(row['lat'], row['lon'])
    for zoom in zoomLevels:
        filename = filename=myOutPath + "/zoom%s/%s_%s_z%d.jpg"%(zoom, siteId, siteName, zoom)
        url = construct_googlemaps_url_request(center=loc, maptype="satellite", zoom=zoom, apiKey=myAPIKey)
        get_static_google_map(url, filename)
        print "%d/%d : %s (zoom: %d)"%(i, len(sites_df), siteName, zoom)


    

    




3151/3152 : ProvisionalAcceleratedLearningAcademy (zoom: 17)
3151/3152 : ProvisionalAcceleratedLearningAcademy (zoom: 18)
3151/3152 : ProvisionalAcceleratedLearningAcademy (zoom: 19)

In [115]:

    

i


    

    
Out[115]:





2837

In [116]:

    

row['Site Name']


    

    
Out[116]:





nan

In [ ]: