def func(widths):
blu_width, ora_width, red_width, nir_width, seed = widths
t_exp = self.t_exp
if mode != "C":
# BLU
blu_center = seed - ora_width / 2 - blu_width / 2
blu_signal = self.signal(blu_center, blu_width, t_exp)
# ORA
ora_center = seed
ora_signal = self.signal(ora_center, ora_width, t_exp)
# RED
red_center = seed + ora_width / 2 + red_width / 2
red_signal = self.signal(red_center, red_width, t_exp)
# NIR
nir_center = seed + ora_width / 2 + red_width + nir_width / 2
nir_signal = self.signal(nir_center, nir_width, t_exp)
else:
# BLU
blu_center = seed - red_width / 2 - ora_width - blu_width / 2
blu_signal = self.signal(blu_center, blu_width, t_exp)
# ORA
ora_center = seed - red_width / 2 - ora_width / 2
ora_signal = self.signal(ora_center, ora_width, t_exp)
# RED
red_center = seed
red_signal = self.signal(red_center, red_width, t_exp)
# NIR
nir_center = seed + red_width / 2 + nir_width / 2
nir_signal = self.signal(nir_center, nir_width, t_exp)
snr_diff_blu = self.snr_target - snr(blu_signal * self.coca.G)
snr_diff_ora = self.snr_target - snr(ora_signal * self.coca.G)
snr_diff_red = self.snr_target - snr(red_signal * self.coca.G)
snr_diff_nir = self.snr_target - snr(nir_signal * self.coca.G)
print(
f"BLU snr = {snr(blu_signal * self.coca.G):.1f} width = {widths[0]:.1f}"
)
print(
f"ORA snr = {snr(ora_signal * self.coca.G):.1f} width = {widths[1]:.1f}"
)
print(
f"RED snr = {snr(red_signal * self.coca.G):.1f} width = {widths[2]:.1f}"
)
print(
f"NIR snr = {snr(nir_signal * self.coca.G):.1f} width = {widths[3]:.1f}"
)
print(f"total bandwidth = {np.sum(widths[:4]):.1f}")
widths_delta = (1100 - 400) - np.sum(widths[:4])
return np.max([
snr_diff_blu, snr_diff_ora, snr_diff_red, snr_diff_nir
]) + widths_delta**2
def func(widths):
blu_width, ora_width, red_width, nir_width = widths
# BLU
edge = seed - ora_width / 2
i = quad(self.integrand,
edge - blu_width,
edge,
args=(n, self.alpha))[0]
blu_signal = self.coca.A_Omega / self.coca.G * self.t_exp * i / (
const.h * const.c * self.coca.r_h**2) * 1e-9
# ORA
i = quad(self.integrand,
seed - ora_width / 2,
seed + ora_width / 2,
args=(n, self.alpha))[0]
ora_signal = self.coca.A_Omega / self.coca.G * self.t_exp * i / (
const.h * const.c * self.coca.r_h**2) * 1e-9
# RED
edge = seed + ora_width / 2
i = quad(self.integrand,
edge,
edge + red_width,
args=(n, self.alpha))[0]
red_signal = self.coca.A_Omega / self.coca.G * self.t_exp * i / (
const.h * const.c * self.coca.r_h**2) * 1e-9
# NIR
edge = seed + ora_width / 2 + red_width
i = quad(self.integrand,
edge,
edge + nir_width,
args=(n, self.alpha))[0]
nir_signal = self.coca.A_Omega / self.coca.G * self.t_exp * i / (
const.h * const.c * self.coca.r_h**2) * 1e-9
snr_diff_blu = self.snr_target - snr(blu_signal * self.coca.G)
snr_diff_ora = self.snr_target - snr(ora_signal * self.coca.G)
snr_diff_red = self.snr_target - snr(red_signal * self.coca.G)
snr_diff_nir = self.snr_target - snr(nir_signal * self.coca.G)
print(
f"BLU snr = {snr(blu_signal * self.coca.G):.1f} width = {widths[0]:.1f}"
)
print(
f"ORA snr = {snr(ora_signal * self.coca.G):.1f} width = {widths[1]:.1f}"
)
print(
f"RED snr = {snr(red_signal * self.coca.G):.1f} width = {widths[2]:.1f}"
)
print(
f"NIR snr = {snr(nir_signal * self.coca.G):.1f} width = {widths[3]:.1f}"
)
return snr_diff_blu + snr_diff_ora + snr_diff_red + snr_diff_nir
def plot_snr(r_h=1, mode="A", ice=False, alpha=0):
t_exps = np.linspace(0.22, 15, 10) / 1000
relative_velocities = [10, 30, 80]
CoCa = Camera()
CoCa.r_h = r_h
df = pd.read_csv("data/texp.csv")
t10 = interp1d(df.alpha, df["texp10"], fill_value="extrapolate")
df = pd.read_csv(f"data/filters_{mode}.csv")
colors = [BLUE, ORANGE, RED, BLACK]
centers = df.centers
widths = df.widths
for filter_center, filter_width, color in zip(centers, widths, colors):
snrs = []
for t_exp in t_exps:
i = quad(integrand, filter_center - filter_width / 2, filter_center + filter_width / 2,
args=(alpha, ice))[0]
signal = CoCa.A_Omega / CoCa.G * t_exp * i / (const.h * const.c * CoCa.r_h ** 2) * 1e-9
snrs.append(snr(signal * CoCa.G))
print(snrs)
t_func = interp1d(snrs,t_exps, fill_value="extrapolate", kind="quadratic")
snr_cont = np.linspace(0, 180, 100)
plt.plot(snr_cont, t_func(snr_cont)*1000, color=color, ls="-")
plt.ylabel("t_exp [ms]")
plt.xlabel("SNR")
plt.savefig(f"plots/snr_vs_t_{r_h}au_{mode}_ice={ice}_{alpha}deg.pdf")
plt.show()
def func(width):
i = quad(integrand_low,
filter_center - width / 2,
filter_center + width / 2,
args=(N, alpha))[0]
signal = coca.A_Omega / coca.G * coca.t_exp * i / (
const.h * const.c * coca.r_h**2) * 1e-9
return snr(signal * coca.G) - 100
def plot_snr(r_h=1, mode="A", ice=False):
relative_velocities = [10, 30, 80]
CoCa = Camera()
CoCa.r_h = r_h
phase_angles = np.arange(0, 90, 10)
df = pd.read_csv("data/texp.csv")
t10 = interp1d(df.alpha, df["texp10"], fill_value="extrapolate")
df = pd.read_csv(f"data/filters_{mode}.csv")
colors = [BLUE, ORANGE, RED, BLACK]
centers = df.centers
widths = df.widths
for v, ls in zip(relative_velocities, ["-", "-.", "--"]):
print(f"calculating for v = {v} km/s")
for filter_center, filter_width, color in zip(centers, widths, colors):
snrs = []
t_exp = t10(11) / 1000 / (v / 10)
i = quad(integrand,
filter_center - filter_width / 2,
filter_center + filter_width / 2,
args=(11, ice))[0]
signal = CoCa.A_Omega / CoCa.G * t_exp * i / (const.h * const.c *
CoCa.r_h**2) * 1e-9
print(
f"v = {v}, center = {filter_center:.2f}, SNR = {snr(signal * CoCa.G):.2f}"
)
for alpha in phase_angles:
t_exp = t10(alpha) / 1000 / (v / 10)
i = quad(integrand,
filter_center - filter_width / 2,
filter_center + filter_width / 2,
args=(alpha, ice))[0]
signal = CoCa.A_Omega / CoCa.G * t_exp * i / (
const.h * const.c * CoCa.r_h**2) * 1e-9
snrs.append(snr(signal * CoCa.G))
snrs_func = interp1d(phase_angles,
snrs,
fill_value="extrapolate",
kind="quadratic")
phase_angles_cont = np.linspace(0, 90, 200)
plt.plot(phase_angles_cont,
snrs_func(phase_angles_cont),
color=color,
ls=ls)
l1 = lines.Line2D([], [], color='black', ls="-")
l2 = lines.Line2D([], [], color='black', ls="-.")
l3 = lines.Line2D([], [], color='black', ls="--")
plt.legend(handles=[l1, l2, l3],
labels=["v = 10 km/s", "v = 30 km/s", "v = 80 km/s"],
fancybox=True,
framealpha=1,
shadow=True,
borderpad=1)
plt.xlabel("phase angle [°]")
plt.ylabel("SNR")
plt.savefig(f"plots/snrs_{r_h}au_{mode}_ice={ice}_new_new.pdf")
plt.show()
def func(t_exp):
i = quad(integrand, filter_center - filter_width / 2, filter_center + filter_width / 2,
args=(N, alpha))[0]
signal = CoCa.A_Omega / CoCa.G * t_exp * i / (const.h * const.c * CoCa.r_h ** 2) * 1e-9
return snr(signal * CoCa.G) - 100
def run(self, mode="A"):
def func(widths):
blu_width, ora_width, red_width, nir_width, seed = widths
t_exp = self.t_exp
if mode != "C":
# BLU
blu_center = seed - ora_width / 2 - blu_width / 2
blu_signal = self.signal(blu_center, blu_width, t_exp)
# ORA
ora_center = seed
ora_signal = self.signal(ora_center, ora_width, t_exp)
# RED
red_center = seed + ora_width / 2 + red_width / 2
red_signal = self.signal(red_center, red_width, t_exp)
# NIR
nir_center = seed + ora_width / 2 + red_width + nir_width / 2
nir_signal = self.signal(nir_center, nir_width, t_exp)
else:
# BLU
blu_center = seed - red_width / 2 - ora_width - blu_width / 2
blu_signal = self.signal(blu_center, blu_width, t_exp)
# ORA
ora_center = seed - red_width / 2 - ora_width / 2
ora_signal = self.signal(ora_center, ora_width, t_exp)
# RED
red_center = seed
red_signal = self.signal(red_center, red_width, t_exp)
# NIR
nir_center = seed + red_width / 2 + nir_width / 2
nir_signal = self.signal(nir_center, nir_width, t_exp)
snr_diff_blu = self.snr_target - snr(blu_signal * self.coca.G)
snr_diff_ora = self.snr_target - snr(ora_signal * self.coca.G)
snr_diff_red = self.snr_target - snr(red_signal * self.coca.G)
snr_diff_nir = self.snr_target - snr(nir_signal * self.coca.G)
print(
f"BLU snr = {snr(blu_signal * self.coca.G):.1f} width = {widths[0]:.1f}"
)
print(
f"ORA snr = {snr(ora_signal * self.coca.G):.1f} width = {widths[1]:.1f}"
)
print(
f"RED snr = {snr(red_signal * self.coca.G):.1f} width = {widths[2]:.1f}"
)
print(
f"NIR snr = {snr(nir_signal * self.coca.G):.1f} width = {widths[3]:.1f}"
)
print(f"total bandwidth = {np.sum(widths[:4]):.1f}")
widths_delta = (1100 - 400) - np.sum(widths[:4])
return np.max([
snr_diff_blu, snr_diff_ora, snr_diff_red, snr_diff_nir
]) + widths_delta**2
if mode == "A":
bounds = ((0, 250), (0, 250), (0, 250), (0, 250), (650, 651))
seed = 650
elif mode == "B":
bounds = ((0, 250), (0, 250), (0, 250), (0, 250), (500, 650))
seed = 650
else:
bounds = ((0, 250), (0, 250), (0, 250), (0, 250), (650, 650.1))
seed = 650
sol = minimize(func, (150, 100, 100, 150, seed), bounds=bounds)
blu_width = sol.x[0]
ora_width = sol.x[1]
red_width = sol.x[2]
nir_width = sol.x[3]
seed = sol.x[4]
if mode != "C":
blu_center = seed - ora_width / 2 - blu_width / 2
ora_center = seed
red_center = seed + ora_width / 2 + red_width / 2
nir_center = seed + ora_width / 2 + red_width + nir_width / 2
else:
blu_center = seed - red_width / 2 - ora_width - blu_width / 2
ora_center = seed - red_width / 2 - ora_width / 2
red_center = seed
nir_center = seed + red_width / 2 + nir_width / 2
print(f"BLUE: center = {blu_center:4.2f}, width = {blu_width:4.2f}")
print(f"ORA: center = {ora_center:4.2f}, width = {ora_width:4.2f}")
print(f"RED: center = {red_center:4.2f}, width = {red_width:4.2f}")
print(f"NIR: center = {nir_center:4.2f}, width = {nir_width:4.2f}")
print(f"t_exp = {self.t_exp * 1000:.2f} ms")
centers = [blu_center, ora_center, red_center, nir_center]
widths = [blu_width, ora_width, red_width, nir_width]
d = {"centers": centers, "widths": widths}
df = pd.DataFrame(data=d)
df.to_csv(f"data/filters_{mode}.csv", index=False)
return
phase_angles = np.arange(1, 90, 10)
snrs = np.zeros((len(phase_angles), 4))
k = 0
df = pd.read_csv("data/texp.csv")
t = interp1d(df.alpha, df["texp10"], fill_value="extrapolate")
for alpha in phase_angles:
t_exp = t(alpha) / (self.v / 10) / 1000
j = 0
for c, w in zip(centers, widths):
i = quad(integrand, c - w / 2, c + w / 2, args=(alpha))[0]
signal = coca.A_Omega / coca.G * t_exp * i / (
const.h * const.c * coca.r_h**2) * 1e-9
snrs[k, j] = snr(signal * coca.G)
j += 1
k += 1
plt.plot(phase_angles, snrs[:, 0], label="BLU", color=BLUE)
plt.plot(phase_angles, snrs[:, 1], label="ORA", color=ORANGE)
plt.plot(phase_angles, snrs[:, 2], label="RED", color=RED)
plt.plot(phase_angles, snrs[:, 3], label="NIR", color=BLACK)
plt.legend()
plt.title(rf"$v$={self.v} km/s")
plt.ylabel("SNR [-]")
plt.xlabel(r"$\alpha$ [°]")
plt.savefig("plots/snrs.pdf")
plt.show()
def func(width):
i = quad(integrand, filter_center - width / 2, filter_center + width / 2, args=(alpha))[
0]
signal = coca.A_Omega / coca.G * coca.t_exp * i / (const.h * const.c * coca.r_h ** 2) * 1e-9
print(f"snr: {snr(signal * coca.G):4.2f}")
return 60 - snr(signal * coca.G)