def main():
palette.configure(False)
print("Good target: center on %d%d%d" % (47 % 7, (47 // 7) % 7, 47 // 49))
plot_dev(0)
plot_dev(1)
plot_dev(2)
plt.show()
def main():
palette.configure(False)
all_ids, mvir, rvir, mpeak, x, y, z = np.loadtxt(
"halo_data.txt", usecols=(0, 1, 2, 3, 6, 7, 8)
).T
vec = np.array([x, y, z]).T
unique_ids = np.unique(all_ids) # array of booleans for uniqueness
# i.e. a new host halo id == True
for j in range(5):
plt.figure(j)
ok = all_ids == unique_ids[j] # SUPER HELPFUL LINE FOR CONDENSING
plot_subhaloes(mpeak[ok], 1e12, rvir[ok], vec[ok])
plt.show()
"""
def main():
palette.configure(False)
d_indiv, n_indiv = np.loadtxt("indiv_dx_min.txt").T
d_global, n_global = np.loadtxt("global_dx_min.txt").T
d_rot_global, n_rot_global = np.loadtxt("global_rotation.txt").T
d_window_indiv, n_window_indiv = np.loadtxt("rotate_window_indiv.txt").T
d_mean_indiv, n_mean_indiv = np.loadtxt("rotate_mean_indiv.txt").T
d_mode_indiv, n_mode_indiv = np.loadtxt("rotate_mode_indiv.txt").T
plt.plot(d_indiv, n_indiv, color=pc("k"),
label=r"${\rm individual\ (\Delta x)_{\rm min}}$")
plt.plot(d_global, n_global, color=pc("r"),
label=r"${\rm global\ (\Delta x)_{\rm min}}$")
plt.plot(d_rot_global, n_rot_global, color=pc("o"),
label=r"${\rm global\ rotation}$")
plt.plot(d_rot_global - 2**16, n_rot_global, color=pc("o"))
plt.plot(d_window_indiv, n_window_indiv, color=pc("g"),
label=r"${\rm individual\ rotation\ (window)}$")
plt.plot(d_window_indiv - 2**16, n_window_indiv, color=pc("g"))
plt.plot(d_mean_indiv, n_mean_indiv, color=pc("b"),
label=r"${\rm individual\ rotation\ (mean)}$")
plt.plot(d_mean_indiv - 2**16, n_mean_indiv, color=pc("b"))
plt.plot(d_mode_indiv, n_mode_indiv, color=pc("p"),
label=r"${\rm individual\ rotation\ (mode)}$")
plt.plot(d_mode_indiv - 2**16, n_mode_indiv, color=pc("p"))
plt.legend(loc="upper left", frameon=True, fontsize=16)
xlo, xhi = plt.xlim(-400, 2000)
ylo, yhi = plt.ylim()
plt.ylim(ylo, yhi)
plt.xlabel(r"$\Delta x$")
plt.ylabel(r"$N(\Delta x)$")
n = -512
while n < xhi:
plt.plot([n, n], [ylo, yhi], ":", lw=1, c="k")
n += 256
plt.show()
def main():
palette.configure(True)
file_names = [
"profiles/phi_pts/phi_pts_4_1.25.txt",
"profiles/phi_pts/phi_pts_4_2.5.txt",
"profiles/phi_pts/phi_pts_4_5.txt",
"profiles/phi_pts/phi_pts_4_10.txt",
"profiles/phi_pts/phi_pts_4_20.txt"
]
log_r, phi = np.loadtxt(file_names[0]).T
log_r_2, phi_2 = np.loadtxt(file_names[-1]).T
mvir = 5.112e+09
vvir = mvir_to_vvir(mvir)
rvir = mvir_to_rvir(mvir)
log_r -= np.log10(rvir)
log_r_2 -= np.log10(rvir)
phi /= vvir**2
phi_2 /= vvir**2
plt.plot([-12, 5], [-12, 5], "--", lw=2, c=pc("a"))
plt.plot(phi, phi_2, ".", c="k")
plt.xlim(-12, 5)
plt.ylim(-12, 5)
plt.xlabel(r"$\Phi_{\rm true}/V_{\rm vir}^2$")
plt.ylabel(r"$\Phi(\delta_v = 0.8 V_{\rm vir})/V_{\rm vir}^2$")
plt.fill_between([0, 5], [0, 0], [-12, -12], color=pc("b"), alpha=0.2)
plt.fill_between([-12, 0], [5, 5], [0, 0], color=pc("r"), alpha=0.2)
plt.savefig("plots/fig4_vvir_boundedness.png")
import matplotlib.pyplot as plt
import numpy as np
import palette
from palette import pc
import string
ls = "-"
lw = 3
palette.configure()
def gaussian(mu, sigma, x):
return np.exp(-(x - mu)**2 /
(2 * sigma**2)) / np.sqrt(2 * np.pi * sigma**2)
x = np.linspace(0, 1, 100)
for c in palette.colors[:0:-1]:
plt.figure()
for sigma in np.linspace(0.2, 1.0, 10):
plt.plot(x, gaussian(sigma, sigma, x), ls, lw=lw, c=pc(c, sigma))
if c == "red":
plt.savefig("README_images/color_range.png")
plt.figure()
x = np.linspace(-1, 1, 100)
plt.figure()
acc = np.array(accuracies[0])
plt.plot(np.log10(acc), dv_means, c=pc("b"), label=r"$\vec{v}$")
plt.plot(np.log10(acc), dv_means, "o", c=pc("b"))
plt.xlabel(r"$\log_{10}(\delta v)\ ({\rm km\,s^{-1}})$", color=pc("b"))
plt.ylabel(r"${\rm Compression\ ratio}$")
plt.tick_params(axis="x", colors=pc("b"))
plt.twiny()
plt.plot(np.log10(acc / spacing / 1e3),
dx_means,
c=pc("r"),
label=r"$\vec{x}$")
plt.plot(np.log10(acc / spacing / 1e3), dx_means, "o", c=pc("r"))
plt.xlabel(r"$\log_{10}(\delta x / l)$", color=pc("r"))
plt.ylabel(r"${\rm Compression\ ratio}$")
plt.tick_params(axis="x", colors=pc("r"))
plt.savefig("plots/fig_2b_ratio_vs_accuracy.png")
if __name__ == "__main__":
palette.configure(True)
main()
#plt.show()
import sys
sys.path.append("../python")
import matplotlib
matplotlib.use("PDF")
import numpy as np
import matplotlib.pyplot as plt
import palette
from palette import pc
import minh
import time
palette.configure(False)
def main():
fname = sys.argv[1]
f = minh.open(fname)
for b in range(f.blocks):
x, vx, mvir, vmax = f.block(b, ["x", "vx", "mvir", "vmax"])
print("X", x[:3])
print("Y", vx[:3])
print("mvir", mvir[:3])
print("vmax", vmax[:3])
break
"""