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Improvements all over the place, now input is controlled by files in regions and tracks, algorithm has to improve to get better performance, it is too slow as it currently stands to manage all geometry checks currently done.

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This commit is contained in:
masiv
2026-02-10 22:44:09 -03:00
parent 683f21be20
commit 2b7fc154ee
24 changed files with 21738 additions and 47 deletions
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2
.gitignore vendored
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@@ -1,6 +1,4 @@
*.gpkg
*.gpx *.gpx
.venv/ .venv/
.vscode/ .vscode/
conf.py
__pycache__ __pycache__

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regions/Canelones.csv Normal file
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admlnm,vertex_index,long,lat
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274
regions/Montevideo.csv Normal file
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admlnm,vertex_index,long,lat
Montevideo,0,-56.324388325337,-34.7021412342176
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274 Montevideo 272 -56.324388325337 -34.7021412342176

625
regions/San Jose.csv Normal file
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admlnm,vertex_index,long,lat
San Jose,0,-56.3575348885738,-34.7825370908262
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624 San Jose 622 -56.3569981331205 -34.782312904605
625 San Jose 623 -56.3575348885738 -34.7825370908262

1180
regions_unused/Artigas.csv Normal file
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1406
regions_unused/Cerro Largo.csv Normal file
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regions_unused/Colonia.csv Normal file
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@@ -0,0 +1,651 @@
admlnm,vertex_index,long,lat
Colonia,0,-58.4158286374833,-33.8410419565103
Colonia,1,-58.412021499874,-33.8406493454443
Colonia,2,-58.4050853710421,-33.8484658748484
Colonia,3,-58.4037290782687,-33.8487633074741
Colonia,4,-58.4013020280428,-33.8477996257667
Colonia,5,-58.3967810521317,-33.8489298697446
Colonia,6,-58.3955913216288,-33.8500244218072
Colonia,7,-58.3879312564005,-33.8549742811167
Colonia,8,-58.3799694762682,-33.8551128258724
Colonia,9,-58.3718193034592,-33.8548353499882
Colonia,10,-58.3639466192511,-33.854431654298
Colonia,11,-58.3559159383564,-33.851961773774
Colonia,12,-58.347963779675,-33.8552168764299
Colonia,13,-58.3420888904515,-33.8483640287332
Colonia,14,-58.3411769590975,-33.8403279001131
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@@ -0,0 +1,745 @@
admlnm,vertex_index,long,lat
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regions_unused/Simplified_Canelones.csv Normal file
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@@ -0,0 +1,12 @@
long,lat
-56.5220862058439,-34.6744179248431
-56.1621031676395,-34.7151781174471
-56.0156414972386,-34.8692422990367
-55.7013248787378,-34.8516881207115
-55.3689062560302,-34.8408836874841
-55.4363773626194,-34.5757324920648
-55.5943584902428,-34.1900292931707
-55.9958938562857,-34.2199711485487
-56.3019822910561,-34.3233247705037
-56.4402157777266,-34.399398730309
-56.5027499740775,-34.5919906512877
1 long lat
2 -56.5220862058439 -34.6744179248431
3 -56.1621031676395 -34.7151781174471
4 -56.0156414972386 -34.8692422990367
5 -55.7013248787378 -34.8516881207115
6 -55.3689062560302 -34.8408836874841
7 -55.4363773626194 -34.5757324920648
8 -55.5943584902428 -34.1900292931707
9 -55.9958938562857 -34.2199711485487
10 -56.3019822910561 -34.3233247705037
11 -56.4402157777266 -34.399398730309
12 -56.5027499740775 -34.5919906512877

12
regions_unused/Simplified_Montevideo.csv Normal file
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@@ -0,0 +1,12 @@
long,lat
-56.3720568712232,-34.7925892655551
-56.3446655970443,-34.743837118297
-56.3264047475917,-34.7110069627891
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-56.2586874308716,-34.932123330225
-56.3865133770399,-34.9052962445149
-56.4648828559407,-34.8484937385346
1 long lat
2 -56.3720568712232 -34.7925892655551
3 -56.3446655970443 -34.743837118297
4 -56.3264047475917 -34.7110069627891
5 -56.2830352301417 -34.7347710453663
6 -56.1689049210629 -34.7378973897825
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9 -56.1232527974314 -34.9570708850476
10 -56.2586874308716 -34.932123330225
11 -56.3865133770399 -34.9052962445149
12 -56.4648828559407 -34.8484937385346

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2
requirements.txt
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@@ -2,4 +2,4 @@ matplotlib
gpxpy gpxpy
python-dateutil python-dateutil
datetime datetime
geopandas csv

73
script.py
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@@ -1,12 +1,7 @@
from matplotlib.path import Path from matplotlib.path import Path
from datetime import datetime from datetime import datetime
import gpxpy import gpxpy, gpxpy.gpx, sys, csv, os, os.path
import gpxpy.gpx
import geopandas as gpd
import sys
class Region: class Region:
def __init__(self, boundary, name, timeSpent=0): def __init__(self, boundary, name, timeSpent=0):
@@ -22,39 +17,21 @@ class Region:
self.timeSpent += timeSpent self.timeSpent += timeSpent
class Point: class Point:
def __init__(self, coordinates, date, name='', region=0): def __init__(self, coordinates, date):
self.coordinates = coordinates self.coordinates = coordinates
self.date = date self.date = date
self.name = name
self.region = region
def importGPX(): def importGPX():
gpx_file = open('thisyear.gpx', 'r') def tracksFileImport(filePath):
global gpx gpx_file = open(filePath, 'r')
gpx = gpxpy.parse(gpx_file) global gpx
gpx = gpxpy.parse(gpx_file)
def importRegions(): for files in os.listdir('tracks'):
areas = gpd.read_file('regions.gpkg') tracksFileImport(''.join(['tracks/',files]))
areas.head()
def initVariables():
#importRegions()
importGPX()
# temp import for regions, have to implement gpx eventually, such file currenly contains a series of polygons
from conf import Regions
initRegions = Regions
global regions
global points global points
regions = []
points = [] points = []
for boundary, name in initRegions:
region = Region(boundary, name)
regions.append(region)
for track in gpx.tracks: for track in gpx.tracks:
for segment in track.segments: for segment in track.segments:
@@ -62,12 +39,25 @@ def initVariables():
point = Point((point.longitude, point.latitude), point.time.timestamp()) point = Point((point.longitude, point.latitude), point.time.timestamp())
points.append(point) points.append(point)
#for coordinates, date in initPoints: def importRegions():
# point = Point(coordinates, date) global regions
# points.append(point) regions = []
def addTimeToRegion(region, time=0): def regionFileImport(filePath, name):
region.timeSpent += time with open(filePath, mode ='r') as file:
csvFile = csv.reader(file)
next(csvFile, None) # Skip header
boundary = []
for row in csvFile:
# must be long, lat
boundary.extend([[row[2],row[3]]])
region = Region(boundary, name)
regions.append(region)
for files in os.listdir('regions'):
regionFileImport(''.join(['regions/',files]), files[:-4]) # Import every file, and get name from splice filename
def calcTimePerRegion(): def calcTimePerRegion():
# The idea is to iterate through every point, if the point is inside a given region, # The idea is to iterate through every point, if the point is inside a given region,
@@ -77,23 +67,18 @@ def calcTimePerRegion():
for point in points: for point in points:
for region in regions: for region in regions:
if region._checkBoundary(point.coordinates): if region._checkBoundary(point.coordinates):
addTimeToRegion(region, (point.date - lastPointDate)) region.timeSpent += (point.date - lastPointDate)
lastPointDate = point.date lastPointDate = point.date
def printResults(): def printResults():
for region in regions: for region in regions:
print("Time spent on ", region.name, ":", round(region.timeSpent / 60), "minutes") print("Time spent on ", region.name, ":", round(region.timeSpent / 60), "minutes")
def main(): def main():
initVariables() importRegions()
importGPX()
calcTimePerRegion() calcTimePerRegion()
printResults() printResults()
main() main()
# print(a._checkBoundary(point.coordinates))