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trial.py
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from load_data import *
import numpy as np
import os
import sys
import json
from collections import defaultdict, OrderedDict
from matplotlib import pyplot as plt
def findPath(a,b):
pass
def generatePairs(P1, P2, d, ref):
for i in range(P1.shape[0]):
p1 = d[P1[i]]
p2 = d[P2[i]]
def calculateTheta(P1, P2):
arctan = lambda x,y: np.arctan2(x,y)
pi = np.pi
delta = P2-P1
theta = np.zeros((P1.shape[0],),dtype=P1.dtype)
# ind = np.where(np.isnan(delta))
# print(delta[ind])
ind_t = np.where((delta[:,0] < 0) & (delta[:,1] >= 0))[0]
ind_f = np.where(~((delta[:,0] < 0) & (delta[:,1] >= 0)))[0]
# ind_f = np.where((~((delta[:,0] < 0) & (delta[:,1] >= 0))) & (delta[:,0] != 0))[0]
theta[ind_t] = (2.5*pi - arctan(delta[ind_t,1],delta[ind_t,0])) * 180./pi
theta[ind_f] = (0.5*pi - arctan(delta[ind_f,1],delta[ind_f,0])) * 180./pi
# theta[ind_t] = (2.5*pi - arctan(delta[ind_t,1]/delta[ind_t,0])) * 180./pi
# theta[ind_f] = (0.5*pi - arctan(delta[ind_f,1]/delta[ind_f,0])) * 180./pi
# # ind = np.where(np.isnan(theta))[0]
# # # print(ind)
# ind_neg = np.where((delta[ind_f,0] == 0) & (delta[ind_f,1] < 0))[0]
# ind_pos = np.where((delta[ind_f,0] == 0) & (delta[ind_f,1] >= 0))[0]
# theta[ind_neg] = (0.5*pi + pi/2.) * 180./pi
# theta[ind_pos] = (0.5*pi - pi/2.) * 180./pi
# ind = np.where(theta > 360)[0]
# while ind.shape[0] > 0:
# theta[ind] -= 360
# ind = np.where(theta > 360)[0]
return theta
def calculatePD(P1, P2, P3):
# x1, y1 = P1
# x2, y2 = P2
x3, y3 = P3
ER = 6371.
# p1 = np.array([x1,y1])
# p2 = np.array([x2,y2])
p3 = np.array([x3,y3])
p1_p2 = np.sum(np.square(P2-P1),axis=1)
x = np.sum((p3-P1)*(P2-P1),axis=1)
ind = np.where(p1_p2 != 0)[0]
_mu = np.zeros(p1_p2.shape,dtype=p1_p2.dtype)
_mu[ind] = x[ind]/p1_p2[ind]
p = P1 + np.vstack((_mu,_mu)).T*(P2-P1)
# print(p[0])
pi = np.pi
R = p*(pi/180.)
R3 = p3*(pi/180.)
ab = R3-R
arcsin = lambda x: np.arcsin(x)
sin = lambda x: np.sin(x)
cos = lambda x: np.cos(x)
PD = 2 * ER * arcsin(np.sqrt( sin(ab[:,0]/2.)**2 + cos(R3[0])*cos(R[:,0])*(sin(ab[:,1]/2.)**2)) )
return PD, p
# return np.array([])
# def linkPairs()
if __name__ == '__main__':
dat = 'probe_data_map_matching'
l_id, dist = loadLinkLength(dat)
idref = loadLinkIdentifiers(dat)
lid, l_x, l_y = loadLinkLatLong(dat)
phead = loadProbeHeading(dat)
dot = loadLinkDOT(dat)
lid, P1, P2 = createP1P2(lid, l_x, l_y, dot)
print(P1.shape)
# for i, x in enumerate(idref.items()):
# if i == 10:
# break
# k,v = x
# print('{}: {}'.format(k,v))
# graph = loadLink(dat)[1]
# for x in graph:
# print(graph[x])
# break
# lID, ind, count = np.unique(l_id,return_index = True, return_counts=True)
# for i in range(lID.shape[0]):
# X = l_x[ind[i]: ind[i]+count[i]]
# Y = l_y[ind[i]: ind[i]+count[i]]
# # X = l_x[np.where(lid == l_id[i])]
# # Y = l_y[np.where(lid == l_id[i])]
# plt.plot(X,Y,c='green',linestyle='-',linewidth=2,marker='o',mfc='red',markersize=2)
pvid = set()
# fli = ['1199426401.0.json','1244811116.0.json','1244812317.0.json']
fli = ['1245061148.0.json']
for fl in fli:
slot = OrderedDict(json.load(open('slot_cand/{}'.format(fl),'r')))
# P = np.vstack((l_x,l_y))
# P = P.T
# # f = open('Link.csv','w')
# # for i in range(P.shape[0]):
# # f.write('{},{},{}\n'.format(lid[i],P[i,0],P[i,1]))
# # f.close()
# # np.savetxt(open(dat+'/Link.csv','wb'),P,fmt='%.10f', delimiter=',')
# P1 = P[:-1]
# l1 = lid[:-1]
# P2 = P[1:]
# l2 = lid[1:]
# ind = np.where(l1 == l2)
# print(ind[0].shape)
# lid = l1[ind]
# P1 = P1[ind]
# P2 = P2[ind]
for i,car in enumerate(slot):
# if i == 1:
# break
# print(slot[car])
# P1 = np.array(list(slot[car].keys()))
# P2 = P1.copy()
# print(P1.shape)
# P2 = P1[1:]
# P1 = P1[:-1]
# print(P1, P2)
# generatePairs(P1,P2,slot[car], idref)
# pvid = set()
for j,coor in enumerate(slot[car]):
# print(len(slot[car][coor]))
# if j == 10:
# break
x,y = coor.split(',')
x = float(x)
y = float(y)
rxMin = x - 0.0001
rxMax = x + 0.0001
ryMin = y - 0.0001
ryMax = y + 0.0001
ind = np.where((P1[:,0] >= rxMin) & (P1[:,0] <= rxMax) & (P1[:,1] >= ryMin) & (P1[:,1] <= ryMax))[0]
P1_f = P1[ind,:]
P2_f = P2[ind,:]
lid_f = lid[ind]
temp, ps = calculatePD(P1_f,P2_f,(x,y))
ind = temp.argsort()
temp = temp[ind]
l = lid_f[ind]
p1 = P1_f[ind,:]
p2 = P2_f[ind,:]
ps = ps[ind]
# if temp.shape[0] > 0:
# pvid.add(l[0])
# print('({},{}); {}; PVID:{}, Ppoint:({},{}), {},{}'.format(x,y,temp[0],l[0],ps[0,0],ps[0,1],p1[0,:],p2[0,:]))
# print('{},{}: PVID: {}, Distance: {:.4f}, {},{}'.format(x,y, l[0], temp[0], P1[0], P2[0]))
# print(x, y)
plt.figure(1)
plt.plot(x,y,marker='^', color='blue',markersize=5)
for m,k in enumerate(slot[car][coor]):
print(k[0])
pvid.add(k[0])
# if m == 1:
# break
# if l.shape[0] > 0:
# id = l[0]
# X = l_x[np.where(lid == id)[0]]
# Y = l_y[np.where(lid == id)[0]]
# plt.figure(2)
# plt.plot(X,Y, color='green',marker='o',mfc='red',linestyle='-',linewidth=2)
f = open('file.csv','w')
for x in pvid:
f.write('{}\n'.format(x))
f.close()
# # # plt.axes([51.1718, 10.9567, 0.02, 0.043])
plt.xlabel('Latitude')
plt.ylabel('Longitude')
# plt.figure(2)
# plt.xlabel('Latitude')
# plt.ylabel('Longitude')
plt.show()
# # print()
# # print()
# # # pass
# # path = findPath(graph,[])
# # l_id, l_x, l_y = loadLinkLatLong(dat)
# # lid = lid[:-1]
# # P1 = np.array([[4,8],
# # [10,1],
# # [3,9]], dtype=np.float64)
# # P2 = np.array([[10,1],
# # [3,9],
# # [5,2]],dtype=np.float64)
# ER = 6371.
# x3, y3 = 51.1724748183,10.9884865489
# p3 = np.array([x3,y3])
# dLat = (0.05/ER)*(180/np.pi)
# dLong = (0.05/ER)*(180/np.pi)/np.cos(x3*np.pi/180)
# # print(dLat, dLong)
# rxMin = x3 - dLat
# rxMax = x3 + dLat
# ryMin = y3 - dLong
# ryMax = y3 + dLong
# print(rxMin, rxMax, ryMin, ryMax)
# print()
# # ind = np.where(((P1[:,0] >= (p3[0]-dLat)) & (P1[:,0] <= (p3[0]+dLat))) & ((P1[:,1] >= (p3[1]-dLong)) & (P1[:,1] <= (p3[1]+dLong))))
# ind = np.where((P1[:,0] >= rxMin) & (P1[:,0] <= rxMax) & (P1[:,1] >= ryMin) & (P1[:,1] <= ryMax))[0]
# print(ind.shape)
# p1_f = P1[ind,:]
# p2_f = P2[ind,:]
# lid_f = lid[ind]
# # print(p1_)
# # ind = np.where((P1[:,1] >= ryMin) & (P1[:,1] <= ryMax))
# # print(ind[0].shape)
# x,p = calculatePD(p1_f,p2_f,(x3,y3))
# # print(x, p)
# ind = x.argsort()
# x = x[ind]
# l = lid_f[ind]
# p1 = p1_f[ind]
# p2 = p2_f[ind]
# p = p[ind]
# print('{}; PVID:{}, Ppoint:({},{}), {},{}'.format(x[0],l[0],p[0,0],p[0,1],P1[0,:],P2[0,:]))
# for i in range(10):
# print('{}; PVID:{}, Ppoint:({},{}), {},{}'.format(x[i],l[i],p[i,0],p[i,1],P1[i,:],P2[i,:]))
# print('Dist: {}, PVID: {}, p1: {}, p2: {}'.format(x[i], l[i], P1[i], P2[i]))
# p1 = np.array([[51.1728399, 10.98829]])
# p2 = np.array([[51.1730854, 10.9881512]])
# t1 = calculateTheta(P1,P2)
# # # print(t)
# ind = np.where(t1 > 360)[0]
# print(ind.shape)
# # p2 = np.array([[51.1728399, 10.98829]])
# # p1 = np.array([[51.1730854, 10.9881512]])
# t2 = calculateTheta(P2,P1)
# # print(t)
# ind = np.where(t2 < 0)[0]
# print(ind.shape)
# ind = np.where(t1 == t2)[0]
# print(ind.shape)
# print(dot[str(762466209)])