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epicyon
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Code Issues 14 Releases Wiki Activity

Move city functions to their own module

merge-requests/30/head
Bob Mottram 2021-05-10 19:53:20 +01:00
parent 0b5574369c
commit 79e1633ebc
3 changed files with 149 additions and 137 deletions
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147
city.py 100644
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@ -0,0 +1,147 @@
__filename__ = "city.py"
__author__ = "Bob Mottram"
__license__ = "AGPL3+"
__version__ = "1.2.0"
__maintainer__ = "Bob Mottram"
__email__ = "bob@freedombone.net"
__status__ = "Production"
import os
import datetime
import random
import math
from random import randint
def _getCityPulse(currTimeOfDay, decoySeed: int) -> (float, float):
"""The data decoy
This simulates expected average patterns of movement in a city.
Jane or Joe average lives and works in the city, commuting in
and out of the central district for work. They have a unique
life pattern, which machine learning can latch onto.
This returns a polar coordinate:
Distance from the city centre is in the range 0.0 - 1.0
Angle is in radians
"""
randgen = random.Random(decoySeed)
variance = 3
busyStates = ("work", "shop", "play", "party")
dataDecoyState = "sleep"
dataDecoyIndex = 0
weekday = currTimeOfDay.weekday()
minHour = 7 + randint(0, variance)
maxHour = 17 + randint(0, variance)
if currTimeOfDay.hour > minHour:
if currTimeOfDay.hour <= maxHour:
if weekday < 5:
dataDecoyState = "work"
dataDecoyIndex = 1
elif weekday == 5:
dataDecoyState = "shop"
dataDecoyIndex = 2
else:
dataDecoyState = "play"
dataDecoyIndex = 3
else:
if weekday < 5:
dataDecoyState = "evening"
dataDecoyIndex = 4
else:
dataDecoyState = "party"
dataDecoyIndex = 5
randgen2 = random.Random(decoySeed + dataDecoyIndex)
angleRadians = \
(randgen2.randint(0, 100000) / 100000) * 2 * math.pi
# some people are quite random, others have more predictable habits
decoyRandomness = randgen.randint(1, 3)
# occasionally throw in a wildcard to keep the machine learning guessing
if randint(0, 100) < decoyRandomness:
distanceFromCityCenter = (randint(0, 100000) / 100000)
angleRadians = (randint(0, 100000) / 100000) * 2 * math.pi
else:
# what consitutes the central district is fuzzy
centralDistrictFuzz = (randgen.randint(0, 100000) / 100000) * 0.1
busyRadius = 0.3 + centralDistrictFuzz
if dataDecoyState in busyStates:
# if we are busy then we're somewhere in the city center
distanceFromCityCenter = \
(randgen.randint(0, 100000) / 100000) * busyRadius
else:
# otherwise we're in the burbs
distanceFromCityCenter = busyRadius + \
((1.0 - busyRadius) * (randgen.randint(0, 100000) / 100000))
return distanceFromCityCenter, angleRadians
def spoofGeolocation(baseDir: str,
city: str, currTime, decoySeed: int,
citiesList: []) -> (float, float, str, str):
"""Given a city and the current time spoofs the location
for an image
returns latitude, longitude, N/S, E/W
"""
locationsFilename = baseDir + '/custom_locations.txt'
if not os.path.isfile(locationsFilename):
locationsFilename = baseDir + '/locations.txt'
cityRadius = 0.1
variance = 0.001
default_latitude = 51.8744
default_longitude = 0.368333
default_latdirection = 'N'
default_longdirection = 'W'
if citiesList:
cities = citiesList
else:
if not os.path.isfile(locationsFilename):
return (default_latitude, default_longitude,
default_latdirection, default_longdirection)
cities = []
with open(locationsFilename, "r") as f:
cities = f.readlines()
city = city.lower()
for cityName in cities:
if city in cityName.lower():
latitude = cityName.split(':')[1]
longitude = cityName.split(':')[2]
latdirection = 'N'
longdirection = 'E'
if 'S' in latitude:
latdirection = 'S'
latitude = latitude.replace('S', '')
if 'W' in longitude:
longdirection = 'W'
longitude = longitude.replace('W', '')
latitude = float(latitude)
longitude = float(longitude)
# get the time of day at the city
approxTimeZone = int(longitude / 15.0)
if longdirection == 'E':
approxTimeZone = -approxTimeZone
currTimeAdjusted = currTime - \
datetime.timedelta(hours=approxTimeZone)
# patterns of activity change in the city over time
(distanceFromCityCenter, angleRadians) = \
_getCityPulse(currTimeAdjusted, decoySeed)
# Get the position within the city, with some randomness added
latitude += \
distanceFromCityCenter * cityRadius * math.cos(angleRadians)
# add a small amount of variance around the location
fraction = randint(0, 100000) / 100000
latitude += (fraction * fraction * variance) - (variance / 2.0)
longitude += \
distanceFromCityCenter * cityRadius * math.sin(angleRadians)
# add a small amount of variance around the location
fraction = randint(0, 100000) / 100000
longitude += (fraction * fraction * variance) - (variance / 2.0)
# gps locations aren't transcendental, so round to a fixed
# number of decimal places
latitude = int(latitude * 10000) / 10000.0
longitude = int(longitude * 10000) / 10000.0
return latitude, longitude, latdirection, longdirection
return (default_latitude, default_longitude,
default_latdirection, default_longdirection)

137
media.py
View File

@ -8,8 +8,6 @@ __status__ = "Production"
import os
import datetime
import random
import math
from random import randint
from hashlib import sha1
from auth import createPassword
@ -21,6 +19,7 @@ from utils import getMediaExtensions
from shutil import copyfile
from shutil import rmtree
from shutil import move
from city import spoofGeolocation
def replaceYouTube(postJsonObject: {}, replacementDomain: str) -> None:
@ -56,140 +55,6 @@ def _removeMetaData(imageFilename: str, outputFilename: str) -> None:
os.system('/usr/bin/mogrify -strip ' + outputFilename) # nosec
def _getCityPulse(currTimeOfDay, decoySeed: int) -> (float, float):
"""The data decoy
This simulates expected average patterns of movement in a city.
Jane or Joe average lives and works in the city, commuting in
and out of the central district for work. They have a unique
life pattern, which machine learning can latch onto.
This returns a polar coordinate:
Distance from the city centre is in the range 0.0 - 1.0
Angle is in radians
"""
randgen = random.Random(decoySeed)
variance = 3
busyStates = ("work", "shop", "play", "party")
dataDecoyState = "sleep"
dataDecoyIndex = 0
weekday = currTimeOfDay.weekday()
minHour = 7 + randint(0, variance)
maxHour = 17 + randint(0, variance)
if currTimeOfDay.hour > minHour:
if currTimeOfDay.hour <= maxHour:
if weekday < 5:
dataDecoyState = "work"
dataDecoyIndex = 1
elif weekday == 5:
dataDecoyState = "shop"
dataDecoyIndex = 2
else:
dataDecoyState = "play"
dataDecoyIndex = 3
else:
if weekday < 5:
dataDecoyState = "evening"
dataDecoyIndex = 4
else:
dataDecoyState = "party"
dataDecoyIndex = 5
randgen2 = random.Random(decoySeed + dataDecoyIndex)
angleRadians = \
(randgen2.randint(0, 100000) / 100000) * 2 * math.pi
# some people are quite random, others have more predictable habits
decoyRandomness = randgen.randint(1, 3)
# occasionally throw in a wildcard to keep the machine learning guessing
if randint(0, 100) < decoyRandomness:
distanceFromCityCenter = (randint(0, 100000) / 100000)
angleRadians = (randint(0, 100000) / 100000) * 2 * math.pi
else:
# what consitutes the central district is fuzzy
centralDistrictFuzz = (randgen.randint(0, 100000) / 100000) * 0.1
busyRadius = 0.3 + centralDistrictFuzz
if dataDecoyState in busyStates:
# if we are busy then we're somewhere in the city center
distanceFromCityCenter = \
(randgen.randint(0, 100000) / 100000) * busyRadius
else:
# otherwise we're in the burbs
distanceFromCityCenter = busyRadius + \
((1.0 - busyRadius) * (randgen.randint(0, 100000) / 100000))
return distanceFromCityCenter, angleRadians
def spoofGeolocation(baseDir: str,
city: str, currTime, decoySeed: int,
citiesList: []) -> (float, float, str, str):
"""Given a city and the current time spoofs the location
for an image
returns latitude, longitude, N/S, E/W
"""
locationsFilename = baseDir + '/custom_locations.txt'
if not os.path.isfile(locationsFilename):
locationsFilename = baseDir + '/locations.txt'
cityRadius = 0.1
variance = 0.001
default_latitude = 51.8744
default_longitude = 0.368333
default_latdirection = 'N'
default_longdirection = 'W'
if citiesList:
cities = citiesList
else:
if not os.path.isfile(locationsFilename):
return (default_latitude, default_longitude,
default_latdirection, default_longdirection)
cities = []
with open(locationsFilename, "r") as f:
cities = f.readlines()
city = city.lower()
for cityName in cities:
if city in cityName.lower():
latitude = cityName.split(':')[1]
longitude = cityName.split(':')[2]
latdirection = 'N'
longdirection = 'E'
if 'S' in latitude:
latdirection = 'S'
latitude = latitude.replace('S', '')
if 'W' in longitude:
longdirection = 'W'
longitude = longitude.replace('W', '')
latitude = float(latitude)
longitude = float(longitude)
# get the time of day at the city
approxTimeZone = int(longitude / 15.0)
if longdirection == 'E':
approxTimeZone = -approxTimeZone
currTimeAdjusted = currTime - \
datetime.timedelta(hours=approxTimeZone)
# patterns of activity change in the city over time
(distanceFromCityCenter, angleRadians) = \
_getCityPulse(currTimeAdjusted, decoySeed)
# Get the position within the city, with some randomness added
latitude += \
distanceFromCityCenter * cityRadius * math.cos(angleRadians)
# add a small amount of variance around the location
fraction = randint(0, 100000) / 100000
latitude += (fraction * fraction * variance) - (variance / 2.0)
longitude += \
distanceFromCityCenter * cityRadius * math.sin(angleRadians)
# add a small amount of variance around the location
fraction = randint(0, 100000) / 100000
longitude += (fraction * fraction * variance) - (variance / 2.0)
# gps locations aren't transcendental, so round to a fixed
# number of decimal places
latitude = int(latitude * 10000) / 10000.0
longitude = int(longitude * 10000) / 10000.0
return latitude, longitude, latdirection, longdirection
return (default_latitude, default_longitude,
default_latdirection, default_longdirection)
def _spoofMetaData(baseDir: str, nickname: str, domain: str,
outputFilename: str, spoofCity: str) -> None:
"""Spoof image metadata using a decoy model for a given city

2
tests.py
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@ -77,7 +77,7 @@ from like import likePost
from like import sendLikeViaServer
from announce import announcePublic
from announce import sendAnnounceViaServer
from media import spoofGeolocation
from city import spoofGeolocation
from media import getMediaPath
from media import getAttachmentMediaType
from delete import sendDeleteViaServer