라이트터치

 
# -*- coding: utf-8 -*-
"""
This example demonstrates many of the 2D plotting capabilities
in pyqtgraph. All of the plots may be panned/scaled by dragging with
the left/right mouse buttons. Right click on any plot to show a context menu.
"""
from pyqtgraph.Qt import QtGui, QtCore
import numpy as np
import pyqtgraph as pg


#QtGui.QApplication.setGraphicsSystem('raster')
app = QtGui.QApplication([])
#mw = QtGui.QMainWindow()
#mw.resize(800,800)


win = pg.GraphicsWindow(title="Basic plotting examples")    # PyQtGraph grahical window
win.resize(1000,600)
win.setWindowTitle('pyqtgraph example: Plotting')           # Title of python window


# Enable antialiasing for prettier plots
pg.setConfigOptions(antialias=True)

# Basic Array Plotting
p1 = win.addPlot(title="Basic array plotting", y=np.random.normal(size=100))

# Multiple Curves
p2 = win.addPlot(title="Multiple curves")
p2.plot(np.random.normal(size=100), pen=(255,0,0), name="Red curve")
p2.plot(np.random.normal(size=110)+5, pen=(0,255,0), name="Green curve")
p2.plot(np.random.normal(size=120)+10, pen=(0,0,255), name="Blue curve")

# Drawing with Points
p3 = win.addPlot(title="Drawing with points")
p3.plot(np.random.normal(size=100), pen=(200,200,200), symbolBrush=(255,0,0), symbolPen='w')

# Next Row
win.nextRow()

# Parametric, Grid Enabled
p4 = win.addPlot(title="Parametric, grid enabled")
x = np.cos(np.linspace(0, 2*np.pi, 1000))
y = np.sin(np.linspace(0, 4*np.pi, 1000))
p4.plot(x, y)
p4.showGrid(x=True, y=True)

# Scatter Plot, Axis Labels, Log Scale
p5 = win.addPlot(title="Scatter plot, axis labels, log scale")
x = np.random.normal(size=1000) * 1e-5
y = x*1000 + 0.005 * np.random.normal(size=1000)
y -= y.min()-1.0
mask = x > 1e-15
x = x[mask]
y = y[mask]
p5.plot(x, y, pen=None, symbol='t', symbolPen=None, symbolSize=10, symbolBrush=(100, 100, 255, 50))
p5.setLabel('left', "Y Axis", units='A')
p5.setLabel('bottom', "Y Axis", units='s')
p5.setLogMode(x=True, y=False)

# Updating Plot
p6 = win.addPlot(title="Updating plot")
curve = p6.plot(pen='y')
data = np.random.normal(size=(10,1000))
ptr = 0
def update():
    global curve, data, ptr, p6
    curve.setData(data[ptr%10])
    if ptr == 0:
        p6.enableAutoRange('xy', False)  ## stop auto-scaling after the first data set is plotted
    ptr += 1
timer = QtCore.QTimer()
timer.timeout.connect(update)
timer.start(50)

# Next Row
win.nextRow()

# Filled Plot, Axis Disabled
p7 = win.addPlot(title="Filled plot, axis disabled")
y = np.sin(np.linspace(0, 10, 1000)) + np.random.normal(size=1000, scale=0.1)
p7.plot(y, fillLevel=-0.3, brush=(50,50,200,100))
p7.showAxis('bottom', False)

# Region Selection
x2 = np.linspace(-100, 100, 1000)
data2 = np.sin(x2) / x2
p8 = win.addPlot(title="Region Selection")
p8.plot(data2, pen=(255,255,255,200))
lr = pg.LinearRegionItem([400,700])
lr.setZValue(-10)
p8.addItem(lr)

# Zoom on Selected Region
p9 = win.addPlot(title="Zoom on selected region")
p9.plot(data2)
def updatePlot():
    p9.setXRange(*lr.getRegion(), padding=0)
def updateRegion():
    lr.setRegion(p9.getViewBox().viewRange()[0])
lr.sigRegionChanged.connect(updatePlot)
p9.sigXRangeChanged.connect(updateRegion)
updatePlot()

## Start Qt event loop unless running in interactive mode or using pyside.
if __name__ == '__main__':
    import sys
    if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
        QtGui.QApplication.instance().exec_()

일반적으로 Python 환경에서 matplotlib를 가장 많이 사용하는데

실시간으로 업데이트 되는 그래프를 표시하기에 너무 느립니다.

찾아보니 PyQtGraph라는 라이브러리가 속도도 빠르고 수학적인 표현을 할 때

좋은 그래프가 많다고 하네요.

다만, 홈페이지의 문서가 상당히 불친절하게 되어 있어서 정보를 찾기가 쉽지 않습니다.

잘 사용만 한다면 쓸만한 그래픽 툴인 것 같습니다.

라이브러리의 각종 사용법 및 명령어들을 알 수 있음.

Numpy

https://docs.scipy.org/doc/

Pandas

https://pandas.pydata.org/pandas-docs/stable/index.html