making Lidar - step 01 : basic dots

원래 프로그램에서 기초 점찍는 부분들만 뽑아낸 기둥.

(my local file name :  ~/py/pyqtgraph/l-01_basic_dots.py

 

# -*- coding: utf-8 -*-
"""
From main library's example, ScatterPlot.py, 
I will take out one of chart to make it for Lidar data display.
"""
from pyqtgraph.Qt import QtGui, QtCore
import pyqtgraph as pg
import numpy as np
from collections import namedtuple
from itertools import chain

app = QtGui.QApplication([])
mw = QtGui.QMainWindow()
mw.resize(500,800)
view = pg.GraphicsLayoutWidget()  ## GraphicsView with GraphicsLayout inserted by default
mw.setCentralWidget(view)
mw.show()
mw.setWindowTitle('Lidar Test')

## create four areas to add plots
w1 = view.addPlot()
view.nextRow()
w4 = view.addPlot()
print("Generating data, this takes a few seconds...")

## There are a few different ways we can draw scatter plots; each is optimized for different types of data:

## 1) All spots identical and transform-invariant (top-left plot).
## In this case we can get a huge performance boost by pre-rendering the spot
## image and just drawing that image repeatedly.

n = 360
s1 = pg.ScatterPlotItem(size=5, pen=pg.mkPen(None), brush=pg.mkBrush(255, 255, 255, 120))
pos = np.random.normal(size=(2,n), scale=1e-5)
spots = [{'pos': pos[:,i], 'data': 1} for i in range(n)] + [{'pos': [0,0], 'data': 1}]
s1.addPoints(spots)
w1.addItem(s1)

## Test performance of large scatterplots

s4 = pg.ScatterPlotItem(
    size=10,
    pen=pg.mkPen(None),
    brush=pg.mkBrush(255, 255, 255, 20),
    hoverable=True,
    hoverSymbol='s',
    hoverSize=15,
    hoverPen=pg.mkPen('r', width=2),
    hoverBrush=pg.mkBrush('g'),
)
n = 10000
pos = np.random.normal(size=(2, n), scale=1e-9)
s4.addPoints(
    x=pos[0],
    y=pos[1],
    #size=(np.random.random(n) * 20.).astype(int),
    #brush=[pg.mkBrush(x) for x in np.random.randint(0, 256, (n, 3))],
    data=np.arange(n)
)
w4.addItem(s4)

if __name__ == '__main__':
    import sys
    if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
        QtGui.QApplication.instance().exec_()