"""
Computing a camera image with custom emissivity
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
This tutorial defines an emissivity that varies in space and computes the
signal received by a camera using this emissivity.
"""
###############################################################################
# We start by loading a built-in `tofu` configuration and define a 2D camera.
import matplotlib.pyplot as plt
import numpy as np
import tofu as tf
configB2 = tf.load_config("B2")
cam2d = tf.geom.utils.create_CamLOS2D(
config=configB2,
pinhole=[3.4, 0, 0],
sensor_nb=100,
focal=0.1,
sensor_size=0.1,
orientation=[np.pi, np.pi/6, 0],
Name="",
Exp="",
Diag="",
)
###############################################################################
# Now, we define an emissivity function that depends on r and z coordinates.
# We can plot its profile in the (0, X, Z) plane.
[docs]def emissivity(pts, t=None, vect=None):
"""Custom emissivity as a function of geometry.
:param pts: ndarray of shape (3, npts) (each column is a xyz coordinate)
:param t: optional, time parameter to add a time dependency to the
emissivity function
:param vect: optional, ndarray of shape (3, npts), if anisotropic
emissivity, unit direction vectors (X,Y,Z)
:return:
- emissivity -- 2D array holding the emissivity for each point in the
input grid
"""
r, z = np.hypot(pts[0, :], pts[1, :]), pts[2, :]
e = np.exp(-(r - 2.4) ** 2 / 0.2 ** 2 - z ** 2 / 0.4 ** 2)
if t is not None:
e = np.cos(np.atleast_1d(t))[:, None] * e[None, :]
else:
# as stated in documentation of calc_signal, e.ndim must be 2
e = np.reshape(e, (1, -1))
return e
y = np.linspace(2, 3, num=90)
z = np.linspace(-0.5, 0.5, num=100)
Y, Z = np.meshgrid(y, z)
X = np.zeros_like(Y)
pts = np.c_[X.ravel(), Y.ravel(), Z.ravel()].T
emissivity_vals = emissivity(pts)
emissivity_vals = emissivity_vals.reshape(X.shape)
[docs]def project_to_2D(xyz):
"""Projection to (0, X, Z) plane."""
return xyz[0], xyz[2]
fig, ax = plt.subplots()
ax.pcolormesh(Y, Z, emissivity_vals)
ax.set_xlabel('y')
ax.set_ylabel('z')
configB2.plot(lax=ax, proj='cross')
cam_center, = ax.plot(*project_to_2D(cam2d._dgeom['pinhole']), '*', ms=20)
ax.set_aspect("equal")
ax.legend(handles=[cam_center], labels=['camera pinhole'], loc='upper right')
###############################################################################
# Finally, we compute an image using the 2D camera and this emissivity.
# If we provide a time vector, the field will vary in a cosinusoidal fashion
# (see above definition) across time.
time_vector = np.linspace(0, 2 * np.pi, num=100)
sig, units = cam2d.calc_signal(emissivity,
res=0.01,
reflections=False,
minimize="hybrid",
method="sum",
newcalc=True,
plot=False,
ani=False,
t=time_vector)
sig.plot(ntMax=1)
plt.show(block=False)