[LINUX] Draw graphs in Julia ... Leave the graphs to Python

"Draw a graph in the programming language Julia" I succeeded in moving the sample for the time being, but the data created by my own program (in Julia language) I decided to find out how to draw a graph using. Well, I wanted to use 3D graphs (OpenGL), and I thought it would be difficult to port all the sample code of PyQtGraph to Julia. ** Okay, change policy ... Let's leave all the graphs to Python! ** **

As a result, it became the source code at the end of the sentence.

• Plotting.jl (Julia source code) just passes the array to a function called Plotting.my_graph_set () (although the array is actually calculated in advance). After passing it, call Plotting.my_graph_run () to draw the graph. Let Python draw the graph for you.
• In Plotting.py (Python source code), the array passed from Julia is stored in a global variable called plot_data_1. Store the array passed from Julia in a global variable called plot_data_1 when my_graph_set () is called. When my_graph_run () is called, ** only the upper left graph ** is drawn using the array data passed from Julia.
• When calling Python code using PyCall, C: \ julia-0.2.1-win32 \ bin is included in the load path, so both Plotting.jl and Plotting.py should be C: \ julia- I decided to save it under 0.2.1-win32 \ bin (for the time being).

By leaving the processing of graphs ** to the Python code **, development has become super easy! After that, if there is a sample that performs such calculation processing on the Julia side ... ** Next, let's try a 3D graph using OpenGL! ** **

Note: Please refer to "Drawing a graph in the programming language Julia" for environment construction.

text:Plotting.jl(C:\julia-0.2.1-win32\Save to bin)

using PyCall

@pyimport Plotting
Plotting.my_graph_set([1, 2, 3, 4, 5, 10, 20, 5])
Plotting.my_graph_run()

python:Plotting.py(C:\julia-0.2.1-win32\Save to bin)

# -*- 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

plot_data_1 = []

def my_graph_set(plot_data):
	global plot_data_1
	plot_data_1 = plot_data

def my_graph_run():
	global plot_data_1

	app = QtGui.QApplication([])

	win = pg.GraphicsWindow(title="Basic plotting examples")
	win.resize(800,600)
	win.setWindowTitle('pyqtgraph example: Plotting')

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

	p1 = win.addPlot(title="Basic array plotting", y=plot_data_1)

	p2 = win.addPlot(title="Multiple curves")
	p2.plot(np.random.normal(size=100), pen=(255,0,0))
	p2.plot(np.random.normal(size=100)+5, pen=(0,255,0))
	p2.plot(np.random.normal(size=100)+10, pen=(0,0,255))

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

	win.nextRow()

	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)

	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)

	global curve, data, ptr, p6
	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)

	win.nextRow()

	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)

	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)

	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()

	QtGui.QApplication.instance().exec_()