added a nice way to tweak the simulation
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2475186d79
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23
coefficients.py
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23
coefficients.py
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@ -0,0 +1,23 @@
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import numpy as np
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c = np.array(
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[ 15 # (x**0
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, 1 # x**1
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, -6 # x**2
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, 0 # x**3
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, 0 # x**4
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, 0 # x**5
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, 0 # x**6)
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, 1 # *c*exp(
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, -1 # c
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, 0 # (r - c))
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, -1 # + c*exp(
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, -.1 # c
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, 2 # (r - c))
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, -4 # + c*exp(
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, -0.05 # c
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, 40 # (r - c)**2)
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, 10 # + c*exp(
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, -0.05 # c
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, 20] # (r - c)**2)
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, dtype=np.float16)
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11
force.py
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force.py
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@ -0,0 +1,11 @@
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from brown.interaction import UFuncWrapper
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import numpy as np
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import matplotlib.pyplot as plt
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from coefficients import c
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force_function = UFuncWrapper(0, c)
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r = np.arange(0, 100, 0.02, dtype=np.float16)
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plt.plot(r, force_function(r))
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plt.show()
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12
particles.py
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particles.py
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@ -6,17 +6,19 @@ from copy import copy
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import matplotlib.pyplot as plt
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import matplotlib.animation as ani
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c = np.array([5, 10, 20, 30, 0, 0, 0, 1, -20, 0, -2, -0.1, 2, 0, 0, 0, 0, 0, 0], dtype=np.float16)
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from coefficients import c
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#force_function = UFuncWrapper(0, c)
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#interaction2D = UFuncWrapper(1, c)
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borders_x = [-100, 100]
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borders_y = [-100, 100]
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n_particles = 6
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n_particles = 600
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frames = 1000
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spawn_restriction = 1.1
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x_coords = np.random.uniform(borders_x[0] / 2, borders_x[1] / 2, n_particles).astype(np.float16)
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y_coords = np.random.uniform(borders_y[0] / 2, borders_y[1] / 2, n_particles).astype(np.float16)
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x_coords = np.random.uniform(borders_x[0] / spawn_restriction, borders_x[1] / spawn_restriction, n_particles).astype(np.float16)
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y_coords = np.random.uniform(borders_y[0] / spawn_restriction, borders_y[1] / spawn_restriction, n_particles).astype(np.float16)
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x_momenta = np.zeros(n_particles, dtype=np.float16)
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@ -41,7 +43,7 @@ brown = BrownIterator(-1, c
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, y_momenta, y_momenta
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, borders_x, borders_y
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, border_dampening=1
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, dt=0.001)
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, dt=0.0001)
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u = iter(brown)
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