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filter_selector.py
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filter_selector.py
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import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from unibe import *
from make_filters import make_filter
from scipy.interpolate import interp1d
from comet import ref_rock
from scipy.integrate import quad
from camera import Camera
import scipy.constants as const
from SNR import snr
def get_mirror():
df_mirror = pd.read_csv("data/mirrors_transmission.txt", delimiter="\s")
M = interp1d(df_mirror.wavelength, df_mirror.transmission, fill_value="extrapolate")
# percent
return M
def get_detector():
df_qe = pd.read_csv("data/qe.txt", delimiter=",")
Q = interp1d(df_qe.Wavelength, df_qe.QE / 100, fill_value="extrapolate")
# electrons per photons
return Q
def get_solar():
df_solar = pd.read_csv("data/solar.csv", delimiter=";", skiprows=1)
S = interp1d(df_solar["Wavelength (nm)"], df_solar["Extraterrestrial W*m-2*nm-1"], fill_value="extrapolate")
# W per meter squared per nanometer
return S
class DraggableScatter():
epsilon = 10
def __init__(self, scatter, filters, fig, v, mode):
df = pd.read_csv(f"data/widths.csv")
self.width = interp1d(df.c, df.widths * 2, kind="linear", fill_value="extrapolate")
self.scatter = scatter
self.filters = filters
self._ind = None
self.ax = scatter.axes
self.canvas = self.ax.figure.canvas
self.filter_data = [
{"center": self.scatter.get_offsets()[0][0],
"width": self.scatter.get_offsets()[0][1]},
{"center": self.scatter.get_offsets()[1][0],
"width": self.scatter.get_offsets()[1][1]},
{"center": self.scatter.get_offsets()[2][0],
"width": self.scatter.get_offsets()[2][1]},
{"center": self.scatter.get_offsets()[3][0],
"width": self.scatter.get_offsets()[3][1]},
]
self.canvas.mpl_connect('button_press_event', self.button_press_callback)
self.canvas.mpl_connect('button_release_event', self.button_release_callback)
self.canvas.mpl_connect('motion_notify_event', self.motion_notify_callback)
plt.tight_layout()
plt.show()
fig.savefig(f"plots/selected_filters_v{v}_mode_{mode}.pdf")
for filter in self.filter_data:
print(filter)
def get_ind_under_point(self, event):
xy = np.asarray(self.scatter.get_offsets())
xyt = self.ax.transData.transform(xy)
xt, yt = xyt[:, 0], xyt[:, 1]
d = np.sqrt((xt - event.x) ** 2 + (yt - event.y) ** 2)
ind = d.argmin()
if d[ind] >= self.epsilon:
ind = None
return ind
def button_press_callback(self, event):
if event.inaxes is None:
return
if event.button != 1:
return
self._ind = self.get_ind_under_point(event)
def button_release_callback(self, event):
if event.button != 1:
return
self._ind = None
def motion_notify_callback(self, event):
if self._ind is None:
return
if event.inaxes is None:
return
if event.button != 1:
return
x, y = event.xdata, event.ydata
if x > 1000: x = 1000
if x < 400: x = 400
wavelengths = np.linspace(300, 1100, 1000)
filter = make_filter(x, y)
self.filter_data[self._ind]["center"] = x
self.filter_data[self._ind]["width"] = y # float(self.width(x))
# y = self.width(x)
self.filters[self._ind].set_ydata(100 * filter(wavelengths))
xy = np.asarray(self.scatter.get_offsets())
xy[self._ind] = np.array([x, y])
self.scatter.set_offsets(xy)
self.canvas.draw_idle()
def main(mode, v=30, alpha=11):
fig, axes = plt.subplots(nrows=2, sharex=True)
if mode != "C":
wavelengths = np.linspace(300, 1100, 1000)
else:
wavelengths = np.linspace(200, 1100, 1000)
df = pd.read_csv(f"data/widths_snr.csv")
widths100_avg = df.widths_100
widths80_avg = df.widths_80
widths60_avg = df.widths_60
centers = df.c
width100 = interp1d(centers, widths100_avg, kind="quadratic", fill_value="extrapolate")
width80 = interp1d(centers, widths80_avg, kind="quadratic", fill_value="extrapolate")
width60 = interp1d(centers, widths60_avg, kind="quadratic", fill_value="extrapolate")
axes[0].plot(np.linspace(380, 1000, 100), width100(np.linspace(380, 1000, 100)), color=BLACK, zorder=-1,
label="SNR 100")
axes[0].plot(np.linspace(380, 1000, 100), width80(np.linspace(380, 1000, 100)), ls="-.", color=BLACK, zorder=-1,
label="SNR 80")
axes[0].plot(np.linspace(380, 1000, 100), width60(np.linspace(380, 1000, 100)), ls="--", color=BLACK, zorder=-1,
label="SNR 60")
axes[0].legend()
if mode != "C":
axes[0].set_ylim(0.8 * min(df.widths_60), max(df.widths_80))
else:
axes[0].set_xticks(np.arange(200,1101,100))
axes[0].set_xticklabels(np.arange(200, 1101, 100))
axes[0].set_ylabel("width [nm]")
axes[0].set_xlabel("center [nm]")
axes[1].set_xlabel("wavelength [nm]")
axes[1].set_ylabel("transmission [%]")
c1 = 460
c2 = 650
c3 = 764
c4 = 900
df = pd.read_csv(f"data/filters_{mode}.csv")
c1, c2, c3, c4 = df.centers
w1, w2, w3, w4 = df.widths
F0 = make_filter(c1, w1)
F1 = make_filter(c2, w2)
F2 = make_filter(c3, w3)
F3 = make_filter(c4, w4)
if mode == "C":
f0, = axes[1].plot(wavelengths, 100 * F0(wavelengths), color=BLUE)
f1, = axes[1].plot(wavelengths, 100 * F1(wavelengths), color=GREEN)
f2, = axes[1].plot(wavelengths, 100 * F2(wavelengths), color=ORANGE)
f3, = axes[1].plot(wavelengths, 100 * F3(wavelengths), color=RED)
else:
f0, = axes[1].plot(wavelengths, 100 * F0(wavelengths), color=BLUE)
f1, = axes[1].plot(wavelengths, 100 * F1(wavelengths), color=ORANGE)
f2, = axes[1].plot(wavelengths, 100 * F2(wavelengths), color=RED)
f3, = axes[1].plot(wavelengths, 100 * F3(wavelengths), color=BLACK)
axes[1].plot(wavelengths, np.zeros(wavelengths.shape), color=BLACK)
M = get_mirror()
Q = get_detector()
S = get_solar()
signal = M(wavelengths) * Q(wavelengths) * ref_rock(wavelengths,alpha) * S(wavelengths)
signal = signal / np.max(signal) * 100
# axes[1].plot(wavelengths, signal.T, color=BLACK)
df = pd.read_csv("data/texp.csv")
t = interp1d(df.alpha, df["texp10"], fill_value="extrapolate")
t_exp = t(alpha) / (v / 10) / 1000
# axes[0].set_title(f"phase angle = {alpha}°")
if mode == "C":
scatter = axes[0].scatter([c1, c2, c3, c4], [w1, w2, w3, w4],
color=[BLUE, GREEN, ORANGE, RED], edgecolor=BLACK)
else:
scatter = axes[0].scatter([c1, c2, c3, c4], [w1, w2, w3, w4],
color=[BLUE, ORANGE, RED, BLACK], edgecolor=BLACK)
DraggableScatter(scatter, [f0, f1, f2, f3], fig, v, mode)
if __name__ == "__main__":
# main("A", alpha=11)
main("D", alpha=11)