def main(fname):
collision_data = CollisionData.data_from_file(fname)
t1 = collision_data.type1s
t2 = collision_data.type2s
deltaVs = collision_data.deltaVs
distances = collision_data.distances
low = np.min(deltaVs)
high = np.max(deltaVs)
#diff_indices = np.where(t1 != t2)
#diff_deltaVs = deltaVs[diff_indices]
#diff_hist = gaussian_kde(diff_deltaVs)
#diff_xs = np.linspace(low, high, 200)
#he_indices = np.where(np.logical_and(t1 == 0, t2 == 0))
#he_deltaVs = deltaVs[he_indices]
#he_hist = gaussian_kde(he_deltaVs)
#he_xs = np.linspace(low, high, 200)
#he_dist = distances[he_indices]
xe_indices = np.where(np.logical_and(t1 == 7, t2 == 7))
xe_deltaVs = deltaVs[xe_indices]
xe_xs = np.linspace(low, high, 200)
xe_dist = distances[xe_indices]
#print np.mean(xe_dist), np.median(xe_dist), np.mean(distances), np.median(distances)
print mquantiles(distances, prob=[0.8, 0.85, 0.9, 0.95, 0.975, 0.99])
if len(xe_deltaVs) <= 1:
return
xe_hist = gaussian_kde(xe_deltaVs)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
# print np.mean(xe_dist)
# update the view limits
#ax.plot(diff_xs, diff_hist(diff_xs), c='r', marker='.', label='He-Xe')
#ax.plot(he_xs, he_hist(he_xs), c='g', marker='.', label='He-He')
ax.plot(xe_xs, xe_hist(xe_xs), c='b', marker='.', label='Xe-Xe')
ax.set_xlim(0, high)
ax.set_title("Collision Radius vs Difference in Velocity")
ax.set_xlabel("Delta V (m/s)")
ax.set_ylabel("Relative Density")
ax.legend()
fig.savefig(os.path.splitext(fname)[0] + ".png", dpi=250)
plt.close()
fig = None
ax = None
def main(fname):
collision_data = CollisionData.data_from_file(fname)
t1 = collision_data.type1s
t2 = collision_data.type2s
deltaVs = collision_data.deltaVs
distances = collision_data.distances
low = np.min(deltaVs)
high = np.max(deltaVs)
#diff_indices = np.where(t1 != t2)
#diff_deltaVs = deltaVs[diff_indices]
#diff_hist = gaussian_kde(diff_deltaVs)
#diff_xs = np.linspace(low, high, 200)
#he_indices = np.where(np.logical_and(t1 == 0, t2 == 0))
#he_deltaVs = deltaVs[he_indices]
#he_hist = gaussian_kde(he_deltaVs)
#he_xs = np.linspace(low, high, 200)
#he_dist = distances[he_indices]
xe_indices = np.where(np.logical_and(t1 == 7, t2 == 7))
xe_deltaVs = deltaVs[xe_indices]
xe_xs = np.linspace(low, high, 200)
xe_dist = distances[xe_indices]
#print np.mean(xe_dist), np.median(xe_dist), np.mean(distances), np.median(distances)
print mquantiles(distances, prob=[0.8, 0.85, 0.9, 0.95, 0.975, 0.99])
if len(xe_deltaVs) <= 1:
return
xe_hist = gaussian_kde(xe_deltaVs)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
# print np.mean(xe_dist)
# update the view limits
#ax.plot(diff_xs, diff_hist(diff_xs), c='r', marker='.', label='He-Xe')
#ax.plot(he_xs, he_hist(he_xs), c='g', marker='.', label='He-He')
ax.plot(xe_xs, xe_hist(xe_xs), c='b', marker='.', label='Xe-Xe')
ax.set_xlim(0, high)
ax.set_title("Collision Radius vs Difference in Velocity")
ax.set_xlabel("Delta V (m/s)")
ax.set_ylabel("Relative Density")
ax.legend()
fig.savefig(os.path.splitext(fname)[0] + ".png", dpi=250)
plt.close()
fig = None
ax = None
def main(fname):
collision_data = CollisionData.data_from_file(fname)
if collision_data is None:
return
energies = collision_data.energies * 6.24150934e15
distances = collision_data.distances
if len(energies) < 100:
return
for d, e in zip(distances, energies):
print d, ',', e
#energies.sort()
low = np.min(energies)
high = np.max(energies)
print fname, np.max(energies)
hist = gaussian_kde(energies)
n, bins = np.histogram(energies, bins=100)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
# print np.mean(xe_dist)
# update the view limits
#ax.plot(diff_xs, diff_hist(diff_xs), c='r', marker='.', label='He-Xe')
#ax.plot(he_xs, he_hist(he_xs), c='g', marker='.', label='He-He')
#ax.plot(bins[:-1], n, c='b', marker='.')
ax.scatter(energies, distances)
ax.set_xlim(low, high)
ax.set_ylim(0.0, np.max(distances))
ax.set_title("Collision Energy Histogram")
ax.set_xlabel("Collision Energy (keV)")
ax.set_ylabel("Relative Density")
ax.legend()
fig.savefig(os.path.splitext(fname)[0] + ".png", dpi=250)
plt.close()
fig = None
ax = None
def main(fname):
collision_data = CollisionData.data_from_file(fname)
time = collision_data.times
pos = collision_data.positions
ene = collision_data.energies
ene_min = np.min(ene)
ene_max = np.max(ene)
jet = plt.get_cmap('jet')
cNorm = colo.Normalize(vmin=0, vmax=ene_max)
scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet)
ep = np.zeros((len(ene), 3))
for i in range(len(ene)):
ep[i, :] = scalarMap.to_rgba(ene[i])[0:3]
x_min = np.min(pos[:, 0])
x_max = np.max(pos[:, 0])
z_min = np.min(pos[:, 2])
z_max = np.max(pos[:, 2])
x_range = x_max - x_min
z_range = z_max - z_min
X = np.zeros((GRID_WIDTH, GRID_HEIGHT, 3))
grid_x = ((pos[:, 0] - x_min) / x_range * GRID_WIDTH).astype(int) - 1
grid_y = ((pos[:, 2] - z_min) / z_range * GRID_HEIGHT).astype(int) - 1
X[grid_y, grid_x] = ep
xs = np.arange(0, GRID_WIDTH) * x_range / GRID_WIDTH + x_min
ys = np.arange(0, GRID_HEIGHT) * z_range / GRID_HEIGHT + z_min
extents = (x_min, x_max, z_min, z_max)
plt.imshow(X, origin='lower', cmap=cmx.jet, aspect='auto', extent=extents)
plt.savefig(fname + ".png", dpi=150)
plt.clf()
def main(fname):
collision_data = CollisionData.data_from_file(fname)
fig, ax = plt.subplots()
t1 = collision_data.type1s
t2 = collision_data.type2s
deltaVs = collision_data.deltaVs
distances = collision_data.distances
del collision_data
diff_indices = np.where(t1 != t2)[::10]
diff_deltaVs = deltaVs[diff_indices]
diff_distances = distances[diff_indices]
he_indices = np.where(np.logical_and(t1 == 0, t2 == 0))[::10]
he_deltaVs = deltaVs[he_indices]
he_distances = distances[he_indices]
xe_indices = np.where(np.logical_and(t1 == 7, t2 == 7))[::10]
xe_deltaVs = deltaVs[xe_indices]
xe_distances = distances[xe_indices]
print np.mean(xe_distances)
ax.scatter(diff_deltaVs, diff_distances, c='r', marker='.', label='He-Xe')
ax.scatter(he_deltaVs, he_distances, c='g', marker='.', label='He-He')
ax.scatter(xe_deltaVs, xe_distances, c='b', marker='.', label='Xe-Xe')
ax.set_xlim(0, np.max(deltaVs))
ax.set_ylim(np.min(distances), np.max(distances))
ax.set_title("Collision Radius vs Difference in Velocity")
ax.set_xlabel("Delta V (m/s)")
ax.set_ylabel("Collision Radius (m)")
ax.legend()
fig.savefig(fname + ".png", dpi=250)
plt.clf()
def main(fname):
collision_data = CollisionData.data_from_file(fname)
fig, ax = plt.subplots()
t1 = collision_data.type1s
t2 = collision_data.type2s
deltaVs = collision_data.deltaVs
distances = collision_data.distances
del collision_data
diff_indices = np.where(t1 != t2)[::10]
diff_deltaVs = deltaVs[diff_indices]
diff_distances = distances[diff_indices]
he_indices = np.where(np.logical_and(t1 == 0, t2 == 0))[::10]
he_deltaVs = deltaVs[he_indices]
he_distances = distances[he_indices]
xe_indices = np.where(np.logical_and(t1 == 7, t2 == 7))[::10]
xe_deltaVs = deltaVs[xe_indices]
xe_distances = distances[xe_indices]
print np.mean(xe_distances)
ax.scatter(diff_deltaVs, diff_distances, c="r", marker=".", label="He-Xe")
ax.scatter(he_deltaVs, he_distances, c="g", marker=".", label="He-He")
ax.scatter(xe_deltaVs, xe_distances, c="b", marker=".", label="Xe-Xe")
ax.set_xlim(0, np.max(deltaVs))
ax.set_ylim(np.min(distances), np.max(distances))
ax.set_title("Collision Radius vs Difference in Velocity")
ax.set_xlabel("Delta V (m/s)")
ax.set_ylabel("Collision Radius (m)")
ax.legend()
fig.savefig(fname + ".png", dpi=250)
plt.clf()
middle = 0.5 * (right + left)
return (middle, ene / n)
def make_histogram(data, fname):
middle, ene = histogram_from_data(data)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
# update the view limits
ax.set_xlim(middle[0], middle[-1])
#ax.set_ylim(0.0, 10.0)
ax.set_xlabel("Radius")
ax.set_ylabel("Density")
ax.plot(middle, ene, c='r')
fig.savefig(os.path.splitext(fname)[0] + ".png", dpi=150)
plt.close()
fig = None
ax = None
for fname in sys.argv[1:]:
print fname
data = CollisionData.data_from_file(fname)
make_histogram(data, fname)
middle = 0.5 * (right + left)
return (middle, ene / n)
def make_histogram(data, fname):
middle, ene = histogram_from_data(data)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
# update the view limits
ax.set_xlim(middle[0], middle[-1])
#ax.set_ylim(0.0, 10.0)
ax.set_xlabel("Radius")
ax.set_ylabel("Density")
ax.plot(middle, ene, c='r')
fig.savefig(os.path.splitext(fname)[0] + ".png", dpi=150)
plt.close()
fig = None
ax = None
for fname in sys.argv[1:]:
print fname
data = CollisionData.data_from_file(fname)
make_histogram(data, fname)