-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathviz_tools.py
187 lines (158 loc) · 8.32 KB
/
viz_tools.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation
from mpl_toolkits.mplot3d import Axes3D
def fourier_transform(signal, N, T):
"""Function for computing the Fourier ransform of <signal>
consisting of <N> data points and an upper sample time <T>"""
N_half = int(round(N/2))
A = np.zeros(N_half)
B = np.zeros(N_half)
A[0] = signal.mean()
q = np.arange(1, N+1)
for n in range(1, N_half):
A[n-1] = np.sum(2/N*signal*np.cos((2*np.pi*q*n)/N))
B[n-1] = np.sum(2/N*signal*np.sin((2*np.pi*q*n)/N))
A[N_half-1] = np.sum(1/N*signal*np.cos(np.pi*q))
B[N_half-1] = 0
freq = np.zeros(N_half)
for n in range(1, N_half+1):
freq[n-1] = n/T
E = A**2 + B**2
return freq, E
#plt.style.use("seaborn")
def eta_animation(X, Y, eta_list, frame_interval, filename):
fig, ax = plt.subplots(1, 1)
plt.xlabel("x [m]", fontname="serif", fontsize=12)
plt.ylabel("y [m]", fontname="serif", fontsize=12)
pmesh = plt.pcolormesh(X, Y, eta_list[0], cmap=plt.cm.RdBu_r)
plt.colorbar(pmesh, orientation="vertical")
def update_eta(num):
# We directly work with the Z array suitable for the expected dimensions.
Z = eta_list[num][:-1, :-1] # Adjust Z to match X, Y dimensions for pcolormesh
# Flatten Z and remove the last column of the last row to fit the expected array size
pmesh.set_array(Z[:-1, :-1].ravel())
ax.set_title(f"Surface elevation $\\eta$ after t = {num*frame_interval/3600:.2f} hours", fontname="serif", fontsize=16)
return pmesh,
anim = animation.FuncAnimation(fig, update_eta, frames=len(eta_list), interval=10, blit=False)
mpeg_writer = animation.FFMpegWriter(fps=24, bitrate=10000, codec="libx264", extra_args=["-pix_fmt", "yuv420p"])
anim.save(f"{filename}.mp4", writer=mpeg_writer)
return anim
# Need to return anim object to see the animation
def velocity_animation(X, Y, u_list, v_list, frame_interval, filename):
"""Function that takes in the domain x, y (2D meshgrids) and a lists of 2D arrays
u_list, v_list and creates an quiver animation of the velocity field (u, v). To get
updating title one also need specify time step dt between each frame in the simulation,
the number of time steps between each eta in eta_list and finally, a filename for video."""
fig, ax = plt.subplots(figsize = (8, 8), facecolor = "white")
plt.title("Velocity field $\mathbf{u}(x,y)$ after 0.0 days", fontname = "serif", fontsize = 19)
plt.xlabel("x [km]", fontname = "serif", fontsize = 16)
plt.ylabel("y [km]", fontname = "serif", fontsize = 16)
q_int = 3
Q = ax.quiver(X[::q_int, ::q_int]/1000.0, Y[::q_int, ::q_int]/1000.0, u_list[0][::q_int,::q_int], v_list[0][::q_int,::q_int],
scale=0.2, scale_units='inches')
#qk = plt.quiverkey(Q, 0.9, 0.9, 0.001, "0.1 m/s", labelpos = "E", coordinates = "figure")
# Update function for quiver animation.
def update_quiver(num):
u = u_list[num]
v = v_list[num]
ax.set_title("Velocity field $\mathbf{{u}}(x,y,t)$ after t = {:.2f} hours".format(
num*frame_interval/3600), fontname = "serif", fontsize = 19)
Q.set_UVC(u[::q_int, ::q_int], v[::q_int, ::q_int])
return Q,
anim = animation.FuncAnimation(fig, update_quiver,
frames = len(u_list), interval = 10, blit = False)
mpeg_writer = animation.FFMpegWriter(fps = 24, bitrate = 10000,
codec = "libx264", extra_args = ["-pix_fmt", "yuv420p"])
fig.tight_layout()
anim.save("{}.mp4".format(filename), writer = mpeg_writer)
return anim # Need to return anim object to see the animation
def eta_animation3D(X, Y, eta_list, frame_interval, filename):
fig = plt.figure(figsize = (8, 8), facecolor = "white")
ax = fig.add_subplot(111, projection='3d')
surf = ax.plot_surface(X, Y, eta_list[0], cmap = plt.cm.RdBu_r)
def update_surf(num):
ax.clear()
surf = ax.plot_surface(X/1000, Y/1000, eta_list[num], cmap = plt.cm.RdBu_r)
ax.set_title("Surface elevation $\eta(x,y,t)$ after $t={:.2f}$ hours".format(
num*frame_interval/3600), fontname = "serif", fontsize = 19, y=1.04)
ax.set_xlabel("x [km]", fontname = "serif", fontsize = 14)
ax.set_ylabel("y [km]", fontname = "serif", fontsize = 14)
ax.set_zlabel("$\eta$ [m]", fontname = "serif", fontsize = 16)
ax.set_xlim(X.min()/1000, X.max()/1000)
ax.set_ylim(Y.min()/1000, Y.max()/1000)
ax.set_zlim(-0.3, 0.7)
plt.tight_layout()
return surf,
anim = animation.FuncAnimation(fig, update_surf,
frames = len(eta_list), interval = 10, blit = False)
mpeg_writer = animation.FFMpegWriter(fps = 24, bitrate = 10000,
codec = "libx264", extra_args = ["-pix_fmt", "yuv420p"])
anim.save("{}.mp4".format(filename), writer = mpeg_writer)
return anim # Need to return anim object to see the animation
def surface_plot3D(X, Y, eta, x_lim, y_lim, z_lim):
"""Function that takes input 1D coordinate arrays x, y and 2D array
array psi. Then plots psi as a surface in 3D space on a meshgrid."""
fig = plt.figure(figsize = (11, 7))
ax = Axes3D(fig)
surf = ax.plot_surface(X, Y, eta, rstride = 1, cstride = 1,
cmap = plt.cm.jet, linewidth = 0, antialiased = True)
ax.set_xlim(*x_lim)
ax.set_ylim(*y_lim)
ax.set_zlim(*z_lim)
ax.set_title("Surface elevation $\eta$", fontname = "serif", fontsize = 17)
ax.set_xlabel("x [m]", fontname = "serif", fontsize = 16)
ax.set_ylabel("y [m]", fontname = "serif", fontsize = 16)
ax.set_zlabel("Surface elevation [m]", fontname = "serif", fontsize = 16)
plt.show()
def pmesh_plot(X, Y, eta, plot_title):
"""Function that generates a colored contour plot of eta in the domain X, Y"""
plt.figure(figsize = (9, 8))
plt.pcolormesh(X, Y, eta, cmap = plt.cm.RdBu_r)
plt.colorbar(orientation = "vertical")
plt.title(plot_title, fontname = "serif", fontsize = 17)
plt.xlabel("x [m]", fontname = "serif", fontsize = 12)
plt.ylabel("y [s]", fontname = "serif", fontsize = 12)
def quiver_plot(X, Y, U, V, plot_title):
"""Function that makes a quiver plot of (U, V) at points (X, Y)."""
plt.figure()
plt.title(plot_title, fontname = "serif", fontsize = 17)
plt.xlabel("x [m]", fontname = "serif", fontsize = 12)
plt.ylabel("y [m]", fontname = "serif", fontsize = 12)
Q = plt.quiver(X[::4, ::4], Y[::4, ::4], U[::4, ::4], V[::4, ::4],
units = "xy", scale = 0.002, scale_units = "inches")
qk = plt.quiverkey(Q, 0.9, 0.9, 0.001, "0.1 m/s",
labelpos = "E", coordinates = "figure")
def hovmuller_plot(x, t, eta):
"""Function that generates a Hovmuller diagram of
eta as a function of x and t at a choosen y-coordinate"""
X, T = np.meshgrid(x, np.array(t))
X = np.transpose(X) # Transpose for plotting
T = np.transpose(T) # Transpose for plotting
eta_hm = np.transpose(np.array(eta)) # Transpose for plotting
plt.figure(figsize = (5, 8))
plt.pcolormesh(X, T, eta_hm, vmin = eta_hm.min(), vmax = eta_hm.max(), cmap = plt.cm.PiYG)
plt.colorbar(orientation = "vertical")
plt.title("x-t plot for middle of domain", fontname = "serif", fontsize = 17)
plt.xlabel("x [m]", fontname = "serif", fontsize = 12)
plt.ylabel("t [s]", fontname = "serif", fontsize = 12)
def plot_time_series_and_ft(t, signal):
"""Function that takes a signal and its corresponding time array.
Then plots the time signal as well as its Fourier transform."""
t = np.array(t)
signal = np.array(signal)
# Plotting the time series.
plt.figure(figsize = (8, 7))
plt.subplot(2, 1, 1)
plt.plot(t, signal, linewidth = 2)
plt.title("Time series of $\eta$ at center of domain", fontname = "serif", fontsize = 17)
plt.xlabel("t [s]", fontname = "serif", fontsize = 12)
plt.ylabel("$\eta$ [m]", fontname = "serif", fontsize = 12)
# Plotting the Fourier transform of the time series (calling homemade ft).
freq, spectrum = fourier_transform(signal, len(signal), len(signal)*np.diff(t)[1])
plt.subplot(2, 1, 2)
plt.plot(freq, spectrum, linewidth = 2)
plt.title("Fourier transformed signal", fontname = "serif", fontsize = 17)
plt.xlabel("Frequency [Hz]", fontname = "serif", fontsize = 12)
plt.ylabel("Amplitude", fontname = "serif", fontsize = 12)
plt.tight_layout()