def viaggi_to_json_txt(lista_viaggi, filename_output):
lout = []
cc = countries.CountryChecker("borders/TM_WORLD_BORDERS-0.3.shp")
for v in lista_viaggi:
lv = [v.id_, v.tempo_inizio, v.tempo_fine]
in_italy = True
for p in v.punti:
point = countries.Point(float(p.latitudine), float(p.longitudine))
if cc.getCountry(
point) == None or cc.getCountry(point).iso != "IT":
in_italy = False
break
lv.append([p.timestamp, p.latitudine, p.longitudine, p.velocita])
if in_italy:
lout.append(lv)
print len(lout)
if len(lout) > 0:
ftxtout = open(filename_output, "w")
json.dump(lout, ftxtout)
ftxtout.close()
print filename_output
def prod_sq():
file_path = './second_data.txt'
file_path1 = './geomap.txt'
file_path2 = './sq_data.txt'
with open(file_path2, 'w') as w:
with open(file_path, 'r') as f:
with open(file_path1, 'r') as g:
lst = f.readlines()
pos = g.readlines()[0].split()
for s in pos:
lat, lng = s.split(",")
cc = countries.CountryChecker('TM_WORLD_BORDERS-0.3.shp')
name = cc.getCountry(countries.Point(int(lat), int(lng)))
flag = True
for i in range(1, len(lst)):
data = lst[i].split("\n")[0].split(",")
if data[1] in str(name):
w.write(str(i) + " ")
flag = False
break
if flag:
w.write("0 ")
print("序列输出完成")
def getCountry(coord):
copyshapes.filter_file(
lambda x: x.GetField('REGION') == 150,
'TM_WORLD_BORDERS-0.3.shp', 'EUROPE.shp')
cc = countries.CountryChecker('TM_WORLD_BORDERS-0.3.shp')
country = cc.getCountry(countries.Point(coord[0], coord[1]))
return country
def __init__(self):
self.cc = countries.CountryChecker('geo-data/filtered.shp')
""" Filter out the bad ones """
self.bad_ids = set([203007243, 325160483, 186456725, 345423903, 169523312, 1211153959, 186456725])
self.bad_tokensRegEx = re.compile(
unicode(regex_or(
r'Yelp',
r'nowplaying',
r'happy-hours',
r'NowPlaying',
r'via',
r'4sq',
r'rt',
r'Goldmünzen',
r'Nahrungseinheiten',
r'gameinsight',
r'androidgames',
r'RT'
).decode('utf-8')), re.UNICODE)
def get_derived_covid_active_global():
"""
Reads the global active cases dataset into a pandas dataframe.
This is a derivative dataset. It is synthesized from confirmed and recovered cases.
Lat/Lon is converted into ISO country codes and shape data for easier country identification
Returns a pandas dataframe containing the sanitized data and timestep metadata
"""
cc = countries.CountryChecker('TM_WORLD_BORDERS-0.3.shp')
shapes = Reader('ne_50m_admin_0_countries.shp')
confirmed, timesteps_confirmed = get_covid_confirmed_global()
shape_data_confirmed = transform_to_shape_data(confirmed,
timesteps_confirmed, cc,
shapes)
recovered, timesteps_recovered = get_covid_recovered_global()
shape_data_recovered = transform_to_shape_data(recovered,
timesteps_recovered, cc,
shapes)
deaths, timesteps_deaths = get_covid_deaths_global()
shape_data_deaths = transform_to_shape_data(deaths, timesteps_deaths, cc,
shapes)
shape_data_confirmed_count = shape_data_confirmed[[*timesteps_confirmed]]
shape_data_recovered_count = shape_data_recovered[[*timesteps_recovered]]
shape_data_deaths_count = shape_data_deaths[[*timesteps_deaths]]
shape_data_con_min_rec = shape_data_confirmed_count.subtract(
shape_data_recovered_count)
shape_data_active_count = shape_data_con_min_rec.subtract(
shape_data_deaths_count)
shape_data_active_countries = shape_data_confirmed[['iso', 'shape']]
shape_data_active = pd.concat(
[shape_data_active_countries, shape_data_active_count], axis=1)
return shape_data_active, timesteps_confirmed
def detect_landmarks(user_id):
urls = []
response = vk_api.photos.get(owner_id=user_id,album_id="wall", rev=1, count=30)
for photo in response['items']:
for size in photo['sizes']:
if size['width'] > 600 and size['height'] > 600:
url = size['url']
urls.append(url)
break
result = {}
# urls = ["https://sun9-4.userapi.com/impf/c604625/v604625712/265c9/WwBwt2_6ygk.jpg?size=1280x960&quality=96&proxy=1&sign=a1649aba17c875e482fbe4e2c069efb3","https://sun9-12.userapi.com/impf/c623900/v623900048/2a2f1/ezedrrOTrno.jpg?size=816x1088&quality=96&proxy=1&sign=b9f44a4a1b515f4173fc845019eb340b","https://sun9-56.userapi.com/impf/c841138/v841138048/3aa38/TiBv8n5E7UU.jpg?size=744x744&quality=96&proxy=1&sign=b80d93be964e670e8e935a091a54f309"]
contents = ThreadPool(8).map(urlToContent, urls)
countryList = []
tags_weight = 0
tags_count = 1
for content in contents:
try:
client = vision.ImageAnnotatorClient()
# with io.open(path, 'rb') as image_file:
# content = image_file.read()
image = vision.Image(content=content)
landmarkResponse = client.landmark_detection(image=image)
landmarks = landmarkResponse.landmark_annotations
labelsResponse = client.label_detection(image=image)
labels = labelsResponse.label_annotations
# return str(labelsResponse)+";"+str(landmarks)
print('Labels:')
# Получение объектов на картинке
for label in labels:
label = label.description
if label in result:
result[label] = result[label] + 1
else:
result[label] = 1
try:
weight = weights_photo_tagsD[label]
print(weight)
if weight is not None:
tags_weight = tags_weight + weight
tags_count = tags_count + 1
except Exception as e:
pass
print(label)
print('Landmarks:')
# Получение координат и названий городов
for landmark in landmarks:
print(landmark.description)
for location in landmark.locations:
lat_lng = location.lat_lng
print('Latitude {}'.format(lat_lng.latitude))
print('Longitude {}'.format(lat_lng.longitude))
cc = countries.CountryChecker('/home/admin2/TM_WORLD_BORDERS-0.3.shp')
country = cc.getCountry(countries.Point(lat_lng.latitude, lat_lng.longitude)).iso
print(country)
countryList.append(country)
# print(country)
except Exception as e:
print("detect_landmarks error = " + str(e))
solvency = tags_weight / tags_count
sorted_result = {}
for key,value in reversed(sorted(result.items(), key=lambda kv: kv[1])):
sorted_result[key] = value
return str('{"tagsFromPhoto":' + str(sorted_result) + ', "countries": ' + str(countryList) + ', "solvency": ' + str(solvency) +'}').replace("'",'"');
import countries
cc = countries.CountryChecker('TM_WORLD_BORDERS-0.3.shp')
print(cc.getCountry(countries.Point(49.7821, 3.5708)).iso)
print('test working')
# we'll use url_for to get some URLs for the app on the templates
from flask import Flask, render_template, request, url_for, jsonify, send_file
from multiprocessing import Process
from make_map import make_map
import countries
# TODO Remove the following in production
from scan_product_links import urls
import os
import math
import wget
import urllib
import zipfile
import sys
app = Flask(__name__)
country_checker = countries.CountryChecker("TM_WORLD_BORDERS-0.3.shx")
# TODO Remove the following in production
us_urls = urls("elevationproductslinks/13secondplots.csv")
mx_ca_urls = urls("elevationproductslinks/1secondplots.csv")
# Define a route for the default URL, which loads the form
# TODO Remove the following route in production
@app.route('/', methods=['GET'])
def show_home():
return render_template('index.htm')
@app.route('/send_square/', methods=['POST'])
def respond():
data = request.get_json(force=True)
def in_switzerland(row):
longitude = row['longitude']
latitude = row['latitude']
cc = countries.CountryChecker('TM_WORLD_BORDERS/TM_WORLD_BORDERS-0.3.shp')
country = cc.getCountry(countries.Point(latitude, longitude)).iso
return country