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Montecarlo Packet Visualization¶
This visualization tool plots the RPackets that are generated by the Montecarlo method and creates an animated plot that contains the packet trajectories as they move away from the photosphere. The properties of individual RPackets are taken from the rpacket_tracker.
[1]:
from tardis import run_tardis
from tardis.io.configuration.config_reader import Configuration
from tardis.io.atom_data.util import download_atom_data
import plotly.express as px
import plotly.graph_objects as go
import math
import pandas as pd
import numpy as np
import random
/home/runner/micromamba/envs/tardis/lib/python3.11/site-packages/setuptools_scm/git.py:162: UserWarning: "/home/runner/work/tardis/tardis" is shallow and may cause errors
warnings.warn(f'"{wd.path}" is shallow and may cause errors')
[2]:
# Download atom data
download_atom_data('kurucz_cd23_chianti_H_He')
Atomic Data kurucz_cd23_chianti_H_He already exists in /home/runner/Downloads/tardis-data/kurucz_cd23_chianti_H_He.h5. Will not download - override with force_download=True.
[3]:
# Reading the Configuration stored in `tardis_example.yml` into config
config = Configuration.from_yaml("tardis_example.yml")
[4]:
# changing config file for plotting 15 packets
config["montecarlo"]["tracking"]["track_rpacket"]=True
config["montecarlo"]["seed"]= 457
config["montecarlo"]["no_of_packets"]=10
config["montecarlo"]["iterations"]=1
config["montecarlo"]["last_no_of_packets"]=15
config["montecarlo"]["no_of_virtual_packets"]=3
[5]:
sim = run_tardis(config, show_progress_bars=False)
[tardis.simulation.base][INFO ]
Reading Atomic Data from kurucz_cd23_chianti_H_He.h5 (base.py:679)
[tardis.io.atom_data.util][INFO ]
Atom Data kurucz_cd23_chianti_H_He.h5 not found in local path.
Exists in TARDIS Data repo /home/runner/Downloads/tardis-data/kurucz_cd23_chianti_H_He.h5 (util.py:36)
[tardis.io.atom_data.base][INFO ]
Reading Atom Data with: UUID = 6f7b09e887a311e7a06b246e96350010 MD5 = 864f1753714343c41f99cb065710cace (base.py:258)
[tardis.io.atom_data.base][INFO ]
Non provided Atomic Data: synpp_refs, photoionization_data, yg_data, two_photon_data, linelist (base.py:262)
[tardis.model.parse_input][WARNING]
Number of density points larger than number of shells. Assuming inner point irrelevant (parse_input.py:143)
[tardis.model.matter.decay][INFO ]
Decaying abundances for 1123200.0 seconds (decay.py:101)
[py.warnings ][WARNING]
/home/runner/work/tardis/tardis/tardis/plasma/properties/radiative_properties.py:93: RuntimeWarning: invalid value encountered in divide
(g_lower * n_upper) / (g_upper * n_lower)
(warnings.py:109)
[py.warnings ][WARNING]
/home/runner/work/tardis/tardis/tardis/plasma/properties/radiative_properties.py:93: RuntimeWarning: invalid value encountered in divide
(g_lower * n_upper) / (g_upper * n_lower)
(warnings.py:109)
[tardis.simulation.base][INFO ]
Simulation finished in 0 iterations
Simulation took 0.00 s
(base.py:473)
[tardis.simulation.base][INFO ]
Starting iteration 1 of 1 (base.py:395)
[tardis.simulation.base][INFO ]
Luminosity emitted = 7.917e+42 erg / s
Luminosity absorbed = 2.754e+42 erg / s
Luminosity requested = 1.059e+43 erg / s
(base.py:577)
[6]:
# accessing the rpacket_tracker dataframe
sim.transport.transport_state.rpacket_tracker_df
[6]:
| status | seed | r | nu | mu | energy | shell_id | interaction_type | ||
|---|---|---|---|---|---|---|---|---|---|
| index | step | ||||||||
| 0 | 0 | 0 | 1198907283 | 1.235520e+15 | 1.550353e+14 | 0.494472 | 0.067899 | 0 | -1 |
| 1 | 0 | 1198907283 | 1.286064e+15 | 1.550353e+14 | 0.550200 | 0.067899 | 1 | -1 | |
| 2 | 0 | 1198907283 | 1.336608e+15 | 1.550353e+14 | 0.595364 | 0.067899 | 2 | -1 | |
| 3 | 0 | 1198907283 | 1.387152e+15 | 1.550353e+14 | 0.632965 | 0.067899 | 3 | -1 | |
| 4 | 0 | 1198907283 | 1.437696e+15 | 1.550353e+14 | 0.664865 | 0.067899 | 4 | -1 | |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 14 | 16 | 0 | 1951128961 | 2.044224e+15 | 6.232667e+14 | 0.921115 | 0.068592 | 16 | -1 |
| 17 | 0 | 1951128961 | 2.094768e+15 | 6.232667e+14 | 0.925028 | 0.068592 | 17 | -1 | |
| 18 | 0 | 1951128961 | 2.145312e+15 | 6.232667e+14 | 0.928654 | 0.068592 | 18 | -1 | |
| 19 | 0 | 1951128961 | 2.195856e+15 | 6.232667e+14 | 0.932019 | 0.068592 | 19 | -1 | |
| 20 | 1 | 1951128961 | 2.246400e+15 | 6.232667e+14 | 0.935149 | 0.068592 | 19 | -1 |
259 rows × 8 columns
Finding packet coordinates¶
The diagram above shows the packet trajectory as it starts from photosphere P0 and continues to move along the subsequent points P1, P2, and so on.
Note
Here μ represents the direction of packet propagation with respect to the radial line.
To determine the polar coordinates of any arbitrary point, say P2, we need r2 and θ2. r2 is already present in the array obtained from the simulation. To determine θ2, we use sine rule and apply it to the triangle OP1P2, where O is the center.
\[\frac{r_{2}}{\sin(\pi - \mu_{1})} = \frac{r_{1}}{\sin(\alpha)}\]
Now, writing α in terms of μ1 and θ2
\[α = μ_{1} - θ_{2}\]
\[\frac{r_{2}}{\sin(\pi - \mu_{1})} = \frac{r_{1}}{\sin(μ_{1} - θ_{2})}\]
Thus,
\[θ_{2} = -\sin^{-1}(\frac{r1}{r2}\sin(\mu_{1})) + \mu_{1}\]
Hence, for ith point, θ will be:
\[θ_{i} = -\sin^{-1}(\frac{r_{i-1}}{r_{i}}\sin(\mu_{i-1})) + \mu_{i-1}\]
[7]:
# function for getting x y coordinates and interactions for a packet
def get_x_y_ints_with_theta_init(r_track,mu_track,time,last_interaction_type,direction="normal",theta_initial=0):
xs,ys,theta,ints = [],[],[],[]
for i in range(len(r_track)):
if(i==0):
theta.append(theta_initial)
else:
if(direction == 'random' or direction == 'r'):
multiplier = random.choice([-1,1])
elif(direction == 'opposite' or direction == 'o'):
multiplier = -1
else:
multiplier = 1
if (r_track[i]<r_track[i-1]):
theta.append(theta[-1] - math.pi + math.asin(r_track[i-1]*math.sin(multiplier * math.acos(mu_track[i-1]))/r_track[i]) + multiplier * math.acos(mu_track[i-1]))
else:
theta.append(theta[-1]+math.asin(-1*r_track[i-1]*math.sin(multiplier * math.acos(mu_track[i-1]))/r_track[i]) + multiplier * math.acos(mu_track[i-1]))
xs = (np.array(r_track))*np.cos(np.array(theta))*1e-5/time
ys = (np.array(r_track))*np.sin(np.array(theta))*1e-5/time
for i in range(len(r_track)):
if(i==0 or i == len(r_track)-1):
ints.append(0)
else:
s0 = (ys[i]-ys[i-1])/(xs[i]-xs[i-1])
s1 = (ys[i+1]-ys[i])/(xs[i+1]-xs[i])
if(math.isclose(s0,s1,rel_tol=1e-11)):
ints.append(0)
else:
ints.append(last_interaction_type[i])
return xs,ys,ints
[8]:
# function for getting coordinates of all packets
def get_coordinates_multiple_packets_ints(r_packet_tracker,time):
thetas = np.linspace(0, 2*math.pi,sim.transport.transport_state.rpacket_tracker_df.index[-1][0]+2)
x = []
y = []
inters = []
for i in range(sim.transport.transport_state.rpacket_tracker_df.index[-1][0]+1):
xs,ys,ints = get_x_y_ints_with_theta_init(r_packet_tracker.loc[i]["r"],r_packet_tracker.loc[i]["mu"],time,r_packet_tracker.loc[i]["interaction_type"],'n',thetas[i])
x.append(xs)
y.append(ys)
inters.append(ints)
return np.array(x,dtype="object"),np.array(y,dtype="object"),np.array(inters,dtype="object")
[9]:
# function for normalizing array size for animation
def get_equal_array_size(xs,ys,ints):
max_size = max(list(map(len,xs)))
for i in range(len(xs)):
xs[i] = np.append(xs[i],xs[i][-1]*np.ones([max_size-len(xs[i])]))
ys[i] = np.append(ys[i],ys[i][-1]*np.ones([max_size-len(ys[i])]))
ints[i] = np.append(ints[i],ints[i][-1]*np.ones([max_size-len(ints[i])]))
return xs,ys,ints,max_size
Plotting Packet Trajectories¶
[10]:
# animated plot
v_shells = sim.simulation_state.radius.value * 1e-5 / sim.simulation_state.time_explosion.value
xs,ys,ints = get_coordinates_multiple_packets_ints(sim.transport.transport_state.rpacket_tracker_df,sim.simulation_state.time_explosion.value)
xs,ys,ints,max_size = get_equal_array_size(xs,ys,ints)
fig = go.Figure()
# Set axes properties
fig.update_xaxes(range=[-1.1*v_shells[-1],1.1*v_shells[-1]],title="VELOCITY (KM/S)",exponentformat="none",linecolor="#555",gridcolor="#fafafa",zerolinecolor="#fafafa")
fig.update_yaxes(range=[-1.1*v_shells[-1],1.1*v_shells[-1]],title="VELOCITY (KM/S)",exponentformat="none",linecolor="#555",gridcolor="#fafafa",zerolinecolor="#fafafa")
# adding the shells
shell_shapes={}
for i in range(len(sim.simulation_state.radius.value)-2,-2,-1):
if i==0:
fig.add_shape(type="circle",
xref="x", yref="y",
x0=-1*v_shells[i], y0=-1*v_shells[i], x1=v_shells[i], y1=v_shells[i],
line_color="black",
fillcolor="darkgrey",
opacity=1
)
elif i==(len(sim.simulation_state.radius.value)-1):
fig.add_shape(type="circle",
xref="x", yref="y",
x0=-1*v_shells[i], y0=-1*v_shells[i], x1=v_shells[i], y1=v_shells[i],
line_color="black",
opacity=1
)
else:
fig.add_shape(type="circle",
xref="x", yref="y",
x0=-1*v_shells[i], y0=-1*v_shells[i], x1=v_shells[i], y1=v_shells[i],
line_color="black",
opacity=0.1
)
#Add the packet trajectory
df = sim.transport.transport_state.rpacket_tracker_df
interaction_from_num = {0: "No Interaction", 1: "EScattering", 2: "Line"}
interaction_color_from_num = {0: "darkslategrey", 1: "#3366FF", 2: "#FF3300"}
interaction_opacity_from_num = {0: 0, 1: 1, 2: 1}
for i in range(len(xs)):
fig.add_trace(go.Scatter(
x=xs[i],
y=ys[i],
mode="markers+lines",
name="Packet "+str(i+1),
showlegend=False,
hovertemplate =
'<b>X</b>: %{x}'+
'<br><b>Y</b>: %{y}<br>'+
'<b>Last Interaction: %{text}</b>',
text = [interaction_from_num.get(ints[i][j]) for j in range(len(xs[i]))],
line = dict(color="darkslategrey"),
# line_shape = "spline",
marker = dict(opacity = [interaction_opacity_from_num.get(ints[i][j]) for j in range(len(xs[i]))],color=[interaction_color_from_num.get(ints[i][j]) for j in range(len(xs[i]))])
))
#adding legends
fig.add_trace(go.Scatter(
x=[9999999],
y=[0],
legendgroup="a",
opacity=1,
legendgrouptitle=dict(font=dict(color="#444"),text="Interaction Type:"),
mode="lines+markers",
name="Escattering",
hoverlabel=dict(font=dict(color="#222")),
marker = dict(color="#3366FF"),
))
fig.add_trace(go.Scatter(
x=[9999999],
y=[0],
legendgroup="a",
opacity=1,
mode="lines+markers",
name="Line",
marker = dict(color="#FF3300"),
))
# Set figure size
fig.layout.plot_bgcolor = '#fafafa'
fig.layout.paper_bgcolor = '#fafafa'
fig.update_layout(width=900, height=900,
title="Packet Trajectories",
title_font_color="#444",
updatemenus=[dict(type="buttons",
pad=dict(t=750),
buttons=[dict(label="Play",
method="animate",
args=[None])])])
# creating frames for animation
def get_frames(l):
frames=[]
for i in range(len(xs)):
frames.append(go.Scatter(
x=xs[i].tolist()[0:l],
y=ys[i].tolist()[0:l],
mode="markers+lines",
name="Packet "+str(i+1),
showlegend=False,
hovertemplate =
'<b>X</b>: %{x}'+
'<br><b>Y</b>: %{y}<br>'+
'<b>Last Interaction: %{text}</b>',
text = [interaction_from_num.get(ints[i][j]) for j in range(len(xs[i]))],
line = dict(color="darkslategrey"),
# line_shape = "spline",
marker = dict(opacity = [interaction_opacity_from_num.get(ints[i][j]) for j in range(len(xs[i]))],color=[interaction_color_from_num.get(ints[i][j]) for j in range(len(xs[i]))])
))
return frames
fig.frames=[go.Frame(data=get_frames(i)) for i in range(max_size+1)]
fig.show(renderer="notebook_connected")