def exp_jiao_environment():
map = ExpSetting.getBasicMap()
fig = MapFigure(map)
fig.drawMapByFeatures()
fig.setXYLabel(u'距离/mm', u'距离/mm')
fig.setXYLim(0, 2500, 0, 3200)
fig.showFigure()
def getRadarData(start, end, step, r_idx):
# 创建地图、增加两个货包块
map = ExpSetting.getBasicMap()
radar = ExpSetting.getBasicRadar()
ret = []
ret.append(getGroupData(radar, map, [0, 0, 0], r_idx))
for i in range(start, end, step):
ret.append(getGroupData(radar, map, [500, i, 0], 1))
return ret
def exp_jiao_drawEstimate(p1, p2, p3, y1, y2):
xs = np.arange(1, 11)
map = ExpSetting.getBasicMap()
fig = MapFigure(map)
l1 = fig.drawRadarPoints(xs, p3, 'ro-')
l2 = fig.drawRadarPoints(xs, p1, 'g--<')
l3 = fig.drawRadarPoints(xs, p2, 'm:d')
plt.legend([l1, l2, l3], [u'AAAAA', u'B', 'C'], loc='upper right')
fig.setXYLabel(u'数据编号', u'距离/mm')
fig.setXYLim(0, 11, y1, y2)
fig.showFigure()
def exp_jiao_radardata(radar_pos):
map = ExpSetting.getBasicMap()
fig = MapFigure(map)
radar = ExpSetting.getBasicRadar()
radar_data = radar.getMeasureData(map, radar_pos)
rag = DBSCAN.getFeatureRange(radar_data, radar_pos)
colors = ['b.', 'r.', 'g.']
xs = [x[0] for x in radar_data]
ys = [x[1] for x in radar_data]
for i in range(len(rag)):
s = rag[i][0]
e = rag[i][1]
fig.drawRadarPoints(xs[s:e], ys[s:e], colors[i])
fig.setXYLabel(u'距离/mm', u'距离/mm')
fig.setXYLim(0, 2500, 0, 3200)
fig.showFigure()
def exp_jiao_drawErrRange():
dats = [[1977, 2007], [1982, 2012], [1993, 2002], [1979,
2006], [1994, 2023],
[1992, 2016], [1992, 2015], [1996, 2017], [1983, 2003],
[1996, 2014]]
x = np.arange(1, 11, 1)
y = []
e = []
for i in range(len(dats)):
y.append((dats[i][0] + dats[i][1]) / 2.0)
e.append(dats[i][1] - y[i])
map = ExpSetting.getBasicMap()
fig = MapFigure(map)
fig.drawErrorBar(x, y, e, 'k-o')
fig.drawRadarPoints(np.arange(0, 12), [2000] * 12, 'r--')
fig.setXYLabel(u'数据编号', u'距离/mm')
fig.setXYLim(0, 11, 1950, 2050)
fig.showFigure()
def estimateLine2():
# 创建地图、增加两个货包块
map = ExpSetting.getBasicMap()
# 创建激光雷达、设置位置、扫描数据
radar = ExpSetting.getBasicRadar()
radar_pos = [0, 0, 0]
radar_data = radar.getMeasureData(map, radar_pos)
# 获取
rag = DBSCAN.getFeatureRange(radar_data, radar_pos)
mid = Split.getSingleSplitPoint(radar_data, rag[1])
theta, p_val = LeastSquare.normalCal(radar_data, rag[1][0], mid - 2)
ls = LeastSquare(theta, p_val)
for i in range(1000, 2000, 100):
radar_pos = [500, i, 0]
radar_data = radar.getMeasureData(map, radar_pos)
rag = DBSCAN.getFeatureRange(radar_data, radar_pos)
print rag
mid = Split.getSingleSplitPoint(radar_data, rag[1])
print ls.recursiveCal(radar_data, rag[1][0], mid - 5, 0.98)
draw3Dsurface(np.arange(0, h, 1), np.arange(0, w, 1), prob_map.s_grid)
'''
xs = [[25, 825], [975, 1575]]
ys = [[25, 85], [235, 285], [435, 465], [615, 665], [815, 885]]
def genRandPos(x, y, w, h, num):
ran1 = RandomNum.createRandom(num) * w + x
ran2 = RandomNum.createRandom(num) * h + y
return ran1, ran2
w = 1600
h = 900
map = ExpSetting.getBasicMap(w, h, Feas.fea2)
fig = MapFigure(map)
fig.drawMapByFeatures()
# 主通道
#ran1, ran2 = genRandPos(825, 25, 150, 850, 300)
# 搜索c
#ran1, ran2 = genRandPos(825, 210, 150, 100, 50)
#
ran1, ran2 = genRandPos(825, 690, 150, 80, 50)
fig.drawRadarPoints(ran1, ran2, 'b.')
'''
for i in range (len(xs)):
for j in range(len(ys)):
ran1, ran2 = genRandPos(xs[i][0], ys[j][0], xs[i][1] - xs[i][0], ys[j][1] - ys[j][0], 120)
fig.drawRadarPoints(ran1, ran2, 'b.')
'''