interp1d for 1D interpolation in SciPy - Mini Project: Build & Apply

Using interp1d for 1D Interpolation

📖 Scenario: Imagine you have temperature readings taken at certain hours of the day, but you want to estimate the temperature at times between those hours.

🎯 Goal: You will create a simple program that uses interp1d from scipy to estimate temperatures at new times based on existing data.

📋 What You'll Learn

Create arrays for known time points and their corresponding temperatures

Set up an interpolation function using interp1d

Use the interpolation function to find temperatures at new time points

Print the interpolated temperature values

💡 Why This Matters

🌍 Real World

Interpolation helps estimate unknown values between measured data points, useful in weather forecasting, finance, and engineering.

💼 Career

Data scientists often use interpolation to fill missing data or create smooth curves from discrete data points.

1

Create arrays for time and temperature data

Create a NumPy array called time_hours with values [0, 3, 6, 9, 12] representing hours of the day. Create another NumPy array called temperatures with values [15, 18, 21, 24, 27] representing temperatures at those hours.

SciPy

import numpy as np
# Create the time_hours array with values [0, 3, 6, 9, 12]
# Create the temperatures array with values [15, 18, 21, 24, 27]

Need a hint?

Use np.array to create arrays with the exact values given.

2

Set up the interpolation function

Import interp1d from scipy.interpolate. Create a variable called interp_func by calling interp1d with time_hours and temperatures as arguments.

SciPy

import numpy as np
from scipy.interpolate import interp1d

time_hours = np.array([0, 3, 6, 9, 12])
temperatures = np.array([15, 18, 21, 24, 27])
# Create interp_func using interp1d with time_hours and temperatures

Need a hint?

Use from scipy.interpolate import interp1d and then call interp1d(time_hours, temperatures).

3

Interpolate temperatures at new times

Create a NumPy array called new_times with values [1, 4, 7, 10]. Use interp_func to find interpolated temperatures at new_times and store the result in a variable called new_temperatures.

SciPy

import numpy as np
from scipy.interpolate import interp1d

time_hours = np.array([0, 3, 6, 9, 12])
temperatures = np.array([15, 18, 21, 24, 27])

interp_func = interp1d(time_hours, temperatures)
# Create new_times array with [1, 4, 7, 10]
# Use interp_func to get new_temperatures at new_times

Need a hint?

Create new_times with the given values and call interp_func(new_times).

4

Print the interpolated temperatures

Write a print statement to display the new_temperatures array.

SciPy

import numpy as np
from scipy.interpolate import interp1d

time_hours = np.array([0, 3, 6, 9, 12])
temperatures = np.array([15, 18, 21, 24, 27])

interp_func = interp1d(time_hours, temperatures)

new_times = np.array([1, 4, 7, 10])
new_temperatures = interp_func(new_times)
# Print the new_temperatures array

Need a hint?

Use print(new_temperatures) to show the interpolated values.