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Orbital Element Trajectories

Orbital element trajectory plots track how position, velocity, and orbital parameters evolve over time. Brahe provides two complementary views: Cartesian plots showing state vectors (x, y, z, vx, vy, vz) and Keplerian plots showing classical elements (a, e, i, Ω, ω, ν). These visualizations are essential for analyzing perturbations, verifying propagators, and understanding orbital dynamics.

Cartesian State Vector Plots

Cartesian plots display position and velocity components in ECI coordinates, useful for debugging propagators and analyzing state evolution.

Interactive Cartesian Plot (Plotly)

Plot Source
cartesian_trajectory_plotly.py
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"""
Cartesian Trajectory Plot Example - Plotly Backend

This script demonstrates how to plot Cartesian state elements (x, y, z, vx, vy, vz) vs time
using the plotly backend for interactive visualization.
"""

import os
import pathlib
import sys
import brahe as bh

# Add plots directory to path for importing brahe_theme
sys.path.insert(0, str(pathlib.Path(__file__).parent.parent.parent))
from brahe_theme import save_themed_html

# Configuration
SCRIPT_NAME = pathlib.Path(__file__).stem
OUTDIR = pathlib.Path(os.getenv("BRAHE_FIGURE_OUTPUT_DIR", "./docs/figures/"))
os.makedirs(OUTDIR, exist_ok=True)

# Initialize EOP data
bh.initialize_eop()

# ISS TLE for November 3, 2025
tle_line0 = "ISS (ZARYA)"
tle_line1 = "1 25544U 98067A   25306.42331346  .00010070  00000-0  18610-3 0  9999"
tle_line2 = "2 25544  51.6344 342.0717 0004969   8.9436 351.1640 15.49700017536601"

# Create SGP4 propagator
prop = bh.SGPPropagator.from_3le(tle_line0, tle_line1, tle_line2, 60.0)

# Define time range for one orbital period
epoch = prop.epoch
duration = bh.orbital_period(prop.semi_major_axis)
print(f"Propagating from {epoch} for {duration} seconds.")

# Generate trajectory by propagating
prop.propagate_to(epoch + duration)
traj = prop.trajectory

# Create Cartesian trajectory plot
fig = bh.plot_cartesian_trajectory(
    [{"trajectory": traj, "color": "blue", "label": "ISS"}],
    position_units="km",
    velocity_units="km/s",
    backend="plotly",
)

# Save themed HTML files
light_path, dark_path = save_themed_html(fig, OUTDIR / SCRIPT_NAME)
print(f"✓ Generated {light_path}")
print(f"✓ Generated {dark_path}")

Static Cartesian Plot (Matplotlib)

Cartesian Trajectory Plot Cartesian Trajectory Plot
Plot Source
cartesian_trajectory_matplotlib.py
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"""
Cartesian Trajectory Plot Example - Matplotlib Backend

This script demonstrates how to plot Cartesian state elements (x, y, z, vx, vy, vz) vs time
using the matplotlib backend.
"""

import brahe as bh

# Initialize EOP data
bh.initialize_eop()

# ISS TLE for November 3, 2025
tle_line0 = "ISS (ZARYA)"
tle_line1 = "1 25544U 98067A   25306.42331346  .00010070  00000-0  18610-3 0  9999"
tle_line2 = "2 25544  51.6344 342.0717 0004969   8.9436 351.1640 15.49700017536601"

# Create SGP4 propagator
prop = bh.SGPPropagator.from_3le(tle_line0, tle_line1, tle_line2, 60.0)

# Define time range for one orbital period (~92 minutes for ISS)
epoch = prop.epoch
duration = bh.orbital_period(prop.semi_major_axis)
print(f"Propagating from {epoch} for {duration} seconds.")

# Generate trajectory by propagating
prop.propagate_to(epoch + duration)
traj = prop.trajectory

# Create Cartesian trajectory plot in light mode
fig = bh.plot_cartesian_trajectory(
    [{"trajectory": traj, "color": "blue", "label": "ISS"}],
    position_units="km",
    velocity_units="km/s",
    backend="matplotlib",
    matplotlib_config={"dark_mode": False},
)

# Save light mode figure
fig.savefig(
    "docs/figures/plot_cartesian_trajectory_matplotlib_light.svg",
    dpi=300,
    bbox_inches="tight",
)
print(
    "Cartesian trajectory plot (matplotlib, light mode) saved to: docs/figures/plot_cartesian_trajectory_matplotlib_light.svg"
)

# Create Cartesian trajectory plot in dark mode
fig = bh.plot_cartesian_trajectory(
    [{"trajectory": traj, "color": "blue", "label": "ISS"}],
    position_units="km",
    velocity_units="km/s",
    backend="matplotlib",
    matplotlib_config={"dark_mode": True},
)

# Set background color to match Plotly dark theme
fig.patch.set_facecolor("#1c1e24")
for ax in fig.get_axes():
    ax.set_facecolor("#1c1e24")

# Save dark mode figure
fig.savefig(
    "docs/figures/plot_cartesian_trajectory_matplotlib_dark.svg",
    dpi=300,
    bbox_inches="tight",
)
print(
    "Cartesian trajectory plot (matplotlib, dark mode) saved to: docs/figures/plot_cartesian_trajectory_matplotlib_dark.svg"
)

The 2×3 subplot layout shows:

  • Top row: x, y, z position components (km)
  • Bottom row: vx, vy, vz velocity components (km/s)

For circular orbits, you'll see sinusoidal patterns. Elliptical orbits show variations in velocity magnitude.

Keplerian Orbital Element Plots

Keplerian plots display classical orbital elements, ideal for understanding long-term evolution and perturbation effects.

Interactive Keplerian Plot (Plotly)

Plot Source
keplerian_trajectory_plotly.py
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"""
Keplerian Trajectory Plot Example - Plotly Backend

This script demonstrates how to plot Keplerian orbital elements (a, e, i, Ω, ω, ν) vs time
using the plotly backend for interactive visualization.
"""

import os
import pathlib
import sys
import brahe as bh

# Add plots directory to path for importing brahe_theme
sys.path.insert(0, str(pathlib.Path(__file__).parent.parent.parent))
from brahe_theme import save_themed_html

# Configuration
SCRIPT_NAME = pathlib.Path(__file__).stem
OUTDIR = pathlib.Path(os.getenv("BRAHE_FIGURE_OUTPUT_DIR", "./docs/figures/"))
os.makedirs(OUTDIR, exist_ok=True)

# Initialize EOP data
bh.initialize_eop()

# ISS TLE for November 3, 2025
tle_line0 = "ISS (ZARYA)"
tle_line1 = "1 25544U 98067A   25306.42331346  .00010070  00000-0  18610-3 0  9999"
tle_line2 = "2 25544  51.6344 342.0717 0004969   8.9436 351.1640 15.49700017536601"

# Create SGP4 propagator
prop = bh.SGPPropagator.from_3le(tle_line0, tle_line1, tle_line2, 60.0)

# Define time range for one orbital period (~92 minutes for ISS)
epoch = prop.epoch
duration = 92.0 * 60.0  # seconds

# Generate trajectory by propagating
prop.propagate_to(epoch + duration)
traj = prop.trajectory

# Create Keplerian trajectory plot
fig = bh.plot_keplerian_trajectory(
    [{"trajectory": traj, "color": "green", "label": "ISS"}],
    sma_units="km",
    angle_units="deg",
    backend="plotly",
    plotly_config={"set_angle_ylim": True},
)

# Save themed HTML files
light_path, dark_path = save_themed_html(fig, OUTDIR / SCRIPT_NAME)
print(f"✓ Generated {light_path}")
print(f"✓ Generated {dark_path}")

Static Keplerian Plot (Matplotlib)

Keplerian Trajectory Plot Keplerian Trajectory Plot
Plot Source
keplerian_trajectory_matplotlib.py
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"""
Keplerian Trajectory Plot Example - Matplotlib Backend

This script demonstrates how to plot Keplerian orbital elements (a, e, i, Ω, ω, ν) vs time
using the matplotlib backend.
"""

import brahe as bh

# Initialize EOP data
bh.initialize_eop()

# ISS TLE for November 3, 2025
tle_line0 = "ISS (ZARYA)"
tle_line1 = "1 25544U 98067A   25306.42331346  .00010070  00000-0  18610-3 0  9999"
tle_line2 = "2 25544  51.6344 342.0717 0004969   8.9436 351.1640 15.49700017536601"

# Create SGP4 propagator
prop = bh.SGPPropagator.from_3le(tle_line0, tle_line1, tle_line2, 60.0)

# Define time range for one orbital period (~92 minutes for ISS)
epoch = prop.epoch
duration = 92.0 * 60.0  # seconds

# Generate trajectory by propagating
prop.propagate_to(epoch + duration)
traj = prop.trajectory

# Create Keplerian trajectory plot in light mode
fig = bh.plot_keplerian_trajectory(
    [{"trajectory": traj, "color": "green", "label": "ISS"}],
    sma_units="km",
    angle_units="deg",
    backend="matplotlib",
    matplotlib_config={"dark_mode": False, "set_angle_ylim": True},
)

# Save light mode figure
fig.savefig(
    "docs/figures/plot_keplerian_trajectory_matplotlib_light.svg",
    dpi=300,
    bbox_inches="tight",
)
print(
    "Keplerian trajectory plot (matplotlib, light mode) saved to: docs/figures/plot_keplerian_trajectory_matplotlib_light.svg"
)

# Create Keplerian trajectory plot in dark mode
fig = bh.plot_keplerian_trajectory(
    [{"trajectory": traj, "color": "green", "label": "ISS"}],
    sma_units="km",
    angle_units="deg",
    backend="matplotlib",
    matplotlib_config={"dark_mode": True, "set_angle_ylim": True},
)

# Set background color to match Plotly dark theme
fig.patch.set_facecolor("#1c1e24")
for ax in fig.get_axes():
    ax.set_facecolor("#1c1e24")

# Save dark mode figure
fig.savefig(
    "docs/figures/plot_keplerian_trajectory_matplotlib_dark.svg",
    dpi=300,
    bbox_inches="tight",
)
print(
    "Keplerian trajectory plot (matplotlib, dark mode) saved to: docs/figures/plot_keplerian_trajectory_matplotlib_dark.svg"
)

The 2×3 subplot layout shows:

  • Semi-major axis (a): Average orbital radius
  • Eccentricity (e): Orbit shape (0 = circular, >0 = elliptical)
  • Inclination (i): Orbital plane tilt
  • RAAN (Ω): Right ascension of ascending node
  • Argument of periapsis (ω): Orbit orientation in plane
  • Mean anomaly (M): Position along orbit

Comparing Different Propagators

Compare different propagators to verify agreement or identify perturbation effects. These examples show how Keplerian (two-body) and SGP4 propagators diverge over time due to atmospheric drag and other perturbations.

The plots show how the two propagation methods diverge:

  • Keplerian (blue): Assumes pure two-body dynamics with no perturbations
  • SGP4 (red): Includes atmospheric drag and other perturbations

For near-circular LEO orbits, we notice there is significant variation in the argument of perigee (ω) and mean anomaly (M) over time due to numerical instability and ill-conditioning of these elements for near-circular orbits.

Cartesian State Comparison

Comparing propagators in Cartesian space shows position and velocity component differences:

Interactive Cartesian Comparison (Plotly)

Plot Source
comparing_propagators_cartesian_plotly.py
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"""
Comparing Propagators (Cartesian) Example - Plotly Backend

This script demonstrates how to compare different propagators (Keplerian vs SGP4)
by plotting their Cartesian state trajectories side-by-side using the plotly backend for interactive visualization.
"""

import os
import pathlib
import sys
import brahe as bh

# Add plots directory to path for importing brahe_theme
sys.path.insert(0, str(pathlib.Path(__file__).parent.parent.parent))
from brahe_theme import save_themed_html

# Configuration
SCRIPT_NAME = pathlib.Path(__file__).stem
OUTDIR = pathlib.Path(os.getenv("BRAHE_FIGURE_OUTPUT_DIR", "./docs/figures/"))
os.makedirs(OUTDIR, exist_ok=True)

# Initialize EOP data
bh.initialize_eop()

# ISS TLE for November 3, 2025
tle_line0 = "ISS (ZARYA)"
tle_line1 = "1 25544U 98067A   25306.42331346  .00010070  00000-0  18610-3 0  9999"
tle_line2 = "2 25544  51.6344 342.0717 0004969   8.9436 351.1640 15.49700017536601"

# Create SGP4 propagator
prop_sgp = bh.SGPPropagator.from_3le(tle_line0, tle_line1, tle_line2, 60.0)
epoch = prop_sgp.epoch

# Get initial Cartesian state from SGP4 propagator for Keplerian propagator
initial_state = prop_sgp.state_eci(epoch)

# Create Keplerian propagator with same initial state
prop_kep = bh.KeplerianPropagator.from_eci(epoch, initial_state, 60.0)

# Propagate both for 4 orbital periods to see differences
duration = 4 * bh.orbital_period(prop_sgp.semi_major_axis)
print(
    f"Propagating from {epoch} for {duration:.0f} seconds ({duration / 3600:.1f} hours)."
)

# Propagate both propagators
prop_kep.propagate_to(epoch + duration)
prop_sgp.propagate_to(epoch + duration)

# Get trajectories
traj_kep = prop_kep.trajectory
traj_sgp = prop_sgp.trajectory

# Create comparison plot
fig = bh.plot_cartesian_trajectory(
    [
        {"trajectory": traj_kep, "color": "blue", "label": "Keplerian"},
        {"trajectory": traj_sgp, "color": "red", "label": "SGP4"},
    ],
    position_units="km",
    velocity_units="km/s",
    backend="plotly",
)

# Save themed HTML files
light_path, dark_path = save_themed_html(fig, OUTDIR / SCRIPT_NAME)
print(f"✓ Generated {light_path}")
print(f"✓ Generated {dark_path}")

Static Cartesian Comparison (Matplotlib)

Comparing Propagators Cartesian Plot Comparing Propagators Cartesian Plot
Plot Source
comparing_propagators_cartesian_matplotlib.py
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"""
Comparing Propagators (Cartesian) Example - Matplotlib Backend

This script demonstrates how to compare different propagators (Keplerian vs SGP4)
by plotting their Cartesian state trajectories side-by-side using the matplotlib backend.
"""

import brahe as bh

# Initialize EOP data
bh.initialize_eop()

# ISS TLE for November 3, 2025
tle_line0 = "ISS (ZARYA)"
tle_line1 = "1 25544U 98067A   25306.42331346  .00010070  00000-0  18610-3 0  9999"
tle_line2 = "2 25544  51.6344 342.0717 0004969   8.9436 351.1640 15.49700017536601"

# Create SGP4 propagator
prop_sgp = bh.SGPPropagator.from_3le(tle_line0, tle_line1, tle_line2, 60.0)
epoch = prop_sgp.epoch

# Get initial Cartesian state from SGP4 propagator for Keplerian propagator
initial_state = prop_sgp.state_eci(epoch)

# Create Keplerian propagator with same initial state
prop_kep = bh.KeplerianPropagator.from_eci(epoch, initial_state, 60.0)

# Propagate both for 4 orbital periods to see differences
duration = 4 * bh.orbital_period(prop_sgp.semi_major_axis)
print(
    f"Propagating from {epoch} for {duration:.0f} seconds ({duration / 3600:.1f} hours)."
)

# Propagate both propagators
prop_kep.propagate_to(epoch + duration)
prop_sgp.propagate_to(epoch + duration)

# Get trajectories
traj_kep = prop_kep.trajectory
traj_sgp = prop_sgp.trajectory

print(f"Keplerian trajectory: {len(traj_kep)} states")
print(f"SGP4 trajectory: {len(traj_sgp)} states")

# Create comparison plot in light mode
fig = bh.plot_cartesian_trajectory(
    [
        {"trajectory": traj_kep, "color": "blue", "label": "Keplerian"},
        {"trajectory": traj_sgp, "color": "red", "label": "SGP4"},
    ],
    position_units="km",
    velocity_units="km/s",
    backend="matplotlib",
    matplotlib_config={"dark_mode": False},
)

# Save light mode figure
fig.savefig(
    "docs/figures/comparing_propagators_cartesian_matplotlib_light.svg",
    dpi=300,
    bbox_inches="tight",
)
print(
    "Comparing propagators (Cartesian) plot (matplotlib, light mode) saved to: docs/figures/comparing_propagators_cartesian_matplotlib_light.svg"
)

# Create comparison plot in dark mode
fig = bh.plot_cartesian_trajectory(
    [
        {"trajectory": traj_kep, "color": "blue", "label": "Keplerian"},
        {"trajectory": traj_sgp, "color": "red", "label": "SGP4"},
    ],
    position_units="km",
    velocity_units="km/s",
    backend="matplotlib",
    matplotlib_config={"dark_mode": True},
)

# Set background color to match Plotly dark theme
fig.patch.set_facecolor("#1c1e24")
for ax in fig.get_axes():
    ax.set_facecolor("#1c1e24")

# Save dark mode figure
fig.savefig(
    "docs/figures/comparing_propagators_cartesian_matplotlib_dark.svg",
    dpi=300,
    bbox_inches="tight",
)
print(
    "Comparing propagators (Cartesian) plot (matplotlib, dark mode) saved to: docs/figures/comparing_propagators_cartesian_matplotlib_dark.svg"
)

Keplerian Element Comparison

Comparing propagators using Keplerian elements reveals how orbital parameters evolve differently:

Interactive Keplerian Comparison (Plotly)

Plot Source
comparing_propagators_keplerian_plotly.py
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"""
Comparing Propagators (Keplerian) Example - Plotly Backend

This script demonstrates how to compare different propagators (Keplerian vs SGP4)
by plotting their Keplerian element trajectories side-by-side using the plotly backend for interactive visualization.
"""

import os
import pathlib
import sys
import brahe as bh

# Add plots directory to path for importing brahe_theme
sys.path.insert(0, str(pathlib.Path(__file__).parent.parent.parent))
from brahe_theme import save_themed_html

# Configuration
SCRIPT_NAME = pathlib.Path(__file__).stem
OUTDIR = pathlib.Path(os.getenv("BRAHE_FIGURE_OUTPUT_DIR", "./docs/figures/"))
os.makedirs(OUTDIR, exist_ok=True)

# Initialize EOP data
bh.initialize_eop()

# ISS TLE for November 3, 2025
tle_line0 = "ISS (ZARYA)"
tle_line1 = "1 25544U 98067A   25306.42331346  .00010070  00000-0  18610-3 0  9999"
tle_line2 = "2 25544  51.6344 342.0717 0004969   8.9436 351.1640 15.49700017536601"

# Create SGP4 propagator
prop_sgp = bh.SGPPropagator.from_3le(tle_line0, tle_line1, tle_line2, 60.0)
epoch = prop_sgp.epoch

# Create Keplerian propagator with same initial Cartesian state as SGP4
# This ensures both propagators store states in the same representation (Cartesian)
prop_kep = bh.KeplerianPropagator.from_eci(epoch, prop_sgp.state_eci(epoch), 60.0)

# Propagate both for 4 orbital periods to see differences
duration = 4 * bh.orbital_period(prop_sgp.semi_major_axis)

# Propagate both propagators
prop_kep.propagate_to(epoch + duration)
prop_sgp.propagate_to(epoch + duration)

# Get trajectories
traj_kep = prop_kep.trajectory
traj_sgp = prop_sgp.trajectory

# Create comparison plot using Keplerian elements with fixed angle and eccentricity limits
fig = bh.plot_keplerian_trajectory(
    [
        {"trajectory": prop_kep.trajectory, "color": "blue", "label": "Keplerian"},
        {"trajectory": prop_sgp.trajectory, "color": "red", "label": "SGP4"},
    ],
    sma_units="km",
    angle_units="deg",
    backend="plotly",
    plotly_config={"set_angle_ylim": True, "set_eccentricity_ylim": True},
)

# Save themed HTML files
light_path, dark_path = save_themed_html(fig, OUTDIR / SCRIPT_NAME)
print(f"✓ Generated {light_path}")
print(f"✓ Generated {dark_path}")

Static Keplerian Comparison (Matplotlib)

Comparing Propagators Keplerian Plot Comparing Propagators Keplerian Plot
Plot Source
comparing_propagators_keplerian_matplotlib.py
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"""
Comparing Propagators (Keplerian) Example - Matplotlib Backend

This script demonstrates how to compare different propagators (Keplerian vs SGP4)
by plotting their Keplerian element trajectories side-by-side using the matplotlib backend.
"""

import brahe as bh

# Initialize EOP data
bh.initialize_eop()

# ISS TLE for November 3, 2025
tle_line0 = "ISS (ZARYA)"
tle_line1 = "1 25544U 98067A   25306.42331346  .00010070  00000-0  18610-3 0  9999"
tle_line2 = "2 25544  51.6344 342.0717 0004969   8.9436 351.1640 15.49700017536601"

# Create SGP4 propagator
prop_sgp = bh.SGPPropagator.from_3le(tle_line0, tle_line1, tle_line2, 60.0)
epoch = prop_sgp.epoch

# Get initial Cartesian state from SGP4 propagator for Keplerian propagator
# Using state_eci() to ensure we get Cartesian coordinates
initial_state = prop_sgp.state_eci(epoch)

# Create Keplerian propagator with same initial Cartesian state
# This ensures both propagators store states in the same representation (Cartesian)
prop_kep = bh.KeplerianPropagator.from_eci(epoch, initial_state, 60.0)

# Propagate both for 4 orbital periods to see differences
duration = 4 * bh.orbital_period(prop_sgp.semi_major_axis)

# Propagate both propagators
prop_kep.propagate_to(epoch + duration)
prop_sgp.propagate_to(epoch + duration)

# Get trajectories
traj_kep = prop_kep.trajectory
traj_sgp = prop_sgp.trajectory

# Create comparison plot using Keplerian elements in light mode with fixed angle and eccentricity limits
fig = bh.plot_keplerian_trajectory(
    [
        {"trajectory": traj_kep, "color": "blue", "label": "Keplerian"},
        {"trajectory": traj_sgp, "color": "red", "label": "SGP4"},
    ],
    sma_units="km",
    angle_units="deg",
    backend="matplotlib",
    matplotlib_config={
        "dark_mode": False,
        "set_angle_ylim": True,
        "set_eccentricity_ylim": True,
    },
)

# Save light mode figure
fig.savefig(
    "docs/figures/comparing_propagators_keplerian_matplotlib_light.svg",
    dpi=300,
    bbox_inches="tight",
)
print(
    "Comparing propagators (Keplerian) plot (matplotlib, light mode) saved to: docs/figures/comparing_propagators_keplerian_matplotlib_light.svg"
)

# Create comparison plot using Keplerian elements in dark mode with fixed angle and eccentricity limits
fig = bh.plot_keplerian_trajectory(
    [
        {"trajectory": traj_kep, "color": "blue", "label": "Keplerian"},
        {"trajectory": traj_sgp, "color": "red", "label": "SGP4"},
    ],
    sma_units="km",
    angle_units="deg",
    backend="matplotlib",
    matplotlib_config={
        "dark_mode": True,
        "set_angle_ylim": True,
        "set_eccentricity_ylim": True,
    },
)

# Set background color to match Plotly dark theme
fig.patch.set_facecolor("#1c1e24")
for ax in fig.get_axes():
    ax.set_facecolor("#1c1e24")

# Save dark mode figure
fig.savefig(
    "docs/figures/comparing_propagators_keplerian_matplotlib_dark.svg",
    dpi=300,
    bbox_inches="tight",
)
print(
    "Comparing propagators (Keplerian) plot (matplotlib, dark mode) saved to: docs/figures/comparing_propagators_keplerian_matplotlib_dark.svg"
)

Unit Customization

Cartesian Plots

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# Meters and m/s
fig = bh.plot_cartesian_trajectory(
    [{"trajectory": traj}],
    position_units="m",
    velocity_units="m/s"
)

# Kilometers and km/s (default)
fig = bh.plot_cartesian_trajectory(
    [{"trajectory": traj}],
    position_units="km",
    velocity_units="km/s"
)

Keplerian Plots

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# Degrees (default)
fig = bh.plot_keplerian_trajectory(
    [{"trajectory": traj}],
    sma_units="km",
    angle_units="deg"
)

# Radians
fig = bh.plot_keplerian_trajectory(
    [{"trajectory": traj}],
    sma_units="km",
    angle_units="rad"
)

See Also