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‎.gitattributes

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# Auto detect text files and perform LF normalization
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* text=auto
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# Custom for Visual Studio
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*.cs diff=csharp
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# Standard to msysgit
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*.doc diff=astextplain
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*.DOC diff=astextplain
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*.docx diff=astextplain
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*.DOCX diff=astextplain
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*.dot diff=astextplain
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*.DOT diff=astextplain
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*.pdf diff=astextplain
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*.PDF diff=astextplain
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*.rtf diff=astextplain
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*.RTF diff=astextplain

‎.gitignore

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# Windows image file caches
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Thumbs.db
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ehthumbs.db
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# Folder config file
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Desktop.ini
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# Recycle Bin used on file shares
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$RECYCLE.BIN/
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# Windows Installer files
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*.cab
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*.msi
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*.msm
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*.msp
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# Windows shortcuts
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*.lnk
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# =========================
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# Operating System Files
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# =========================
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# OSX
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# =========================
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.DS_Store
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.AppleDouble
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.LSOverride
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# Thumbnails
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._*
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# Files that might appear in the root of a volume
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.DocumentRevisions-V100
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.fseventsd
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.Spotlight-V100
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.TemporaryItems
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.Trashes
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.VolumeIcon.icns
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# Directories potentially created on remote AFP share
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.AppleDB
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.AppleDesktop
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Network Trash Folder
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Temporary Items
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.apdisk

‎Chapter01/simul.py

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from matplotlib import pyplot as plt
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from matplotlib import animation
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from random import uniform
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import timeit
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class Particle:
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__slots__ = ('x', 'y', 'ang_speed')
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def __init__(self, x, y, ang_speed):
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self.x = x
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self.y = y
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self.ang_speed = ang_speed
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class ParticleSimulator:
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def __init__(self, particles):
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self.particles = particles
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def evolve(self, dt):
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timestep = 0.00001
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nsteps = int(dt/timestep)
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for i in range(nsteps):
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for p in self.particles:
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norm = (p.x**2 + p.y**2)**0.5
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v_x = (-p.y)/norm
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v_y = p.x/norm
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d_x = timestep * p.ang_speed * v_x
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d_y = timestep * p.ang_speed * v_y
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p.x += d_x
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p.y += d_y
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# def evolve(self, dt):
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# timestep = 0.00001
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# nsteps = int(dt/timestep)
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# # First, change the loop order
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# for p in self.particles:
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# t_x_ang = timestep * p.ang_speed
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# for i in range(nsteps):
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# norm = (p.x**2 + p.y**2)**0.5
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# p.x, p.y = p.x - t_x_ang*p.y/norm, p.y + t_x_ang * p.x/norm
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def visualize(simulator):
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X = [p.x for p in simulator.particles]
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Y = [p.y for p in simulator.particles]
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fig = plt.figure()
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ax = plt.subplot(111, aspect='equal')
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line, = ax.plot(X, Y, 'ro')
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# Axis limits
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plt.xlim(-1, 1)
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plt.ylim(-1, 1)
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# It will be run when the animation starts
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def init():
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line.set_data([], [])
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return line,
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def animate(i):
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# We let the particle evolve for 0.1 time units
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simulator.evolve(0.01)
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X = [p.x for p in simulator.particles]
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Y = [p.y for p in simulator.particles]
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line.set_data(X, Y)
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return line,
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# Call the animate function each 10 ms
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anim = animation.FuncAnimation(fig,
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animate,
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init_func=init,
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blit=True,
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interval=10)
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plt.show()
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def test_visualize():
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particles = [Particle( 0.3, 0.5, +1),
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Particle( 0.0, -0.5, -1),
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Particle(-0.1, -0.4, +3)]
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simulator = ParticleSimulator(particles)
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visualize(simulator)
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def test_evolve():
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particles = [Particle( 0.3, 0.5, +1),
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Particle( 0.0, -0.5, -1),
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Particle(-0.1, -0.4, +3)]
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simulator = ParticleSimulator(particles)
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simulator.evolve(0.1)
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p0, p1, p2 = particles
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def fequal(a, b):
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return abs(a - b) < 1e-5
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assert fequal(p0.x, 0.2102698450356825)
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assert fequal(p0.y, 0.5438635787296997)
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assert fequal(p1.x, -0.0993347660567358)
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assert fequal(p1.y, -0.4900342888538049)
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assert fequal(p2.x, 0.1913585038252641)
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assert fequal(p2.y, -0.3652272210744360)
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def benchmark():
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particles = [Particle(uniform(-1.0, 1.0),
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uniform(-1.0, 1.0),
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uniform(-1.0, 1.0))
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for i in range(100)]
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simulator = ParticleSimulator(particles)
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simulator.evolve(0.1)
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def timing():
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result = timeit.timeit('benchmark()',
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setup='from __main__ import benchmark',
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number=10)
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# Result is the time it takes to run the whole loop
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print(result)
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result = timeit.repeat('benchmark()',
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setup='from __main__ import benchmark',
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number=10,
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repeat=3)
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# Result is a list of times
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print(result)
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def benchmark_memory():
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particles = [Particle(uniform(-1.0, 1.0),
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uniform(-1.0, 1.0),
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uniform(-1.0, 1.0))
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for i in range(100000)]
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simulator = ParticleSimulator(particles)
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simulator.evolve(0.001)
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if __name__ == '__main__':
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benchmark()

‎Chapter01/taylor.py

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def factorial(n):
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if n == 0:
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return 1.0
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else:
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return float(n) * factorial(n-1)
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def taylor_exp(n):
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return [1.0/factorial(i) for i in range(n)]
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def taylor_sin(n):
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res = []
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for i in range(n):
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if i % 2 == 1:
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res.append((-1)**((i-1)/2)/float(factorial(i)))
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else:
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res.append(0.0)
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return res
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def benchmark():
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taylor_exp(500)
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taylor_sin(500)
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if __name__ == '__main__':
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benchmark()

‎Chapter01/test_simul.py

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from simul import Particle, ParticleSimulator
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def test_evolve(benchmark):
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particles = [Particle( 0.3, 0.5, +1),
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Particle( 0.0, -0.5, -1),
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Particle(-0.1, -0.4, +3)]
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simulator = ParticleSimulator(particles)
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simulator.evolve(0.1)
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p0, p1, p2 = particles
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def fequal(a, b):
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return abs(a - b) < 1e-5
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assert fequal(p0.x, 0.2102698450356825)
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assert fequal(p0.y, 0.5438635787296997)
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assert fequal(p1.x, -0.0993347660567358)
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assert fequal(p1.y, -0.4900342888538049)
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assert fequal(p2.x, 0.1913585038252641)
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assert fequal(p2.y, -0.3652272210744360)
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benchmark(simulator.evolve, 0.1)

‎Chapter02/.cache/v/cache/lastfailed

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{}

‎Chapter02/.cache/v/cache/lastfailed (2)

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{}

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