Loading data from a .csv file

In this example, we will load the data from a .csv file to set up the environment.

As you might already know, an atmospheric model in RocketPy is defined by a pressure, temperature, height (or geopotential height) and wind profiles. What we will need to do is to create a .csv file with these profiles and load it into the environment using a Custom Atmosphere model.

Create a .csv file

This step is not mandatory, you can create the .csv file with any text editor or spreadsheet software. The file should have the following structure:

import numpy as np
import pandas as pd

from rocketpy import Environment, Function


# Create a .csv file with the profiles
data = {
    'height': [0, 1000, 2000, 3000, 4000], # m
    'pressure': [101325, 89876, 79508, 70122, 61653], # Pa
    'temperature': [288.15, 281.65, 275.15, 268.65, 262.15], # K
    'wind_u': [0, 1.0, 3, -0.5, -1], # m/s
    'wind_v': [0, 3.0, 2.2, 5.8, 10], # m/s
}

df = pd.DataFrame(data)
df.to_csv('atmosphere.csv', index=False)

df.head()

	height	pressure	temperature	wind_u	wind_v
0	0	101325	288.15	0.0	0.0
1	1000	89876	281.65	1.0	3.0
2	2000	79508	275.15	3.0	2.2
3	3000	70122	268.65	-0.5	5.8
4	4000	61653	262.15	-1.0	10.0

Important

To avoid errors and misinterpretations, RocketPy expects all the values to be in SI units. Of course you can import the data in different units and convert them to SI units before saving the .csv file.

Load the .csv file

Now we will load the .csv file into the environment.

# Load the .csv file into the environment
df = pd.read_csv('atmosphere.csv')

# Create Function objects to represent the profiles
pressure_func = Function(np.column_stack([df['height'], df['pressure']]))
temperature_func = Function(np.column_stack([df['height'], df['temperature']]))
wind_u_func = Function(np.column_stack([df['height'], df['wind_u']]))
wind_v_func = Function(np.column_stack([df['height'], df['wind_v']]))

# Set up the environment
env_csv = Environment()
env_csv.set_atmospheric_model(
    type="custom_atmosphere",
    pressure=pressure_func,
    temperature=temperature_func,
    wind_u=wind_u_func,
    wind_v=wind_v_func,
)

# Plot the atmospheric model
env_csv.plots.atmospheric_model()