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Lære Implementing Identity-Quadratic Functions in Python | Functions and Their Properties
Mathematics for Data Science

bookImplementing Identity-Quadratic Functions in Python

Now that you've covered algebraic functions, let's work with them in Python. In this section, you'll learn not only function manipulation, but also visualization.

Identity Function

The identity function returns the input value unchanged, following the form f(x)=xf(x) = x. In Python, we implement it as:

# Identity Function
def identity_function(x):
    return x

To visualize it, we generate x-values from -10 to 10, plot the function, and mark the origin. The function extends infinitely in both directions, indicated by arrows.

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import numpy as np import matplotlib.pyplot as plt # Identity Function def identity_function(x): return x x = np.linspace(-10, 10, 100) # Generate values y = identity_function(x) plt.plot(x, y, label="f(x) = x", color='blue', linewidth=2) plt.scatter(0, 0, color='red') # Mark the origin plt.show()
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Constant Function

A constant function always returns the same output, regardless of the input. It follows f(x)=cf(x) = c.

# Constant Function
def constant_function(x, c):
    return np.full_like(x, c)

This implementation ensures all x-values yield the same output. The resulting plot is a horizontal line at y=cy = c, with arrows indicating infinite extension.

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import numpy as np import matplotlib.pyplot as plt # Constant Function def constant_function(x, c): return np.full_like(x, c) x = np.linspace(-10, 10, 100) y = constant_function(x, c=5) plt.plot(x, y, label="f(x) = 5", color='blue', linewidth=2) plt.show()
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Linear Function

A linear function follows the form f(x)=mx+bf(x) = mx + b, where mm represents the slope and bb the y-intercept.

# Linear Function
def linear_function(x, m, b):
    return m * x + b

The graph of a linear function is a straight line. We plot it with arrows indicating infinite extension, and mark key points such as the x-intercept and y-intercept.

123456789101112
import numpy as np import matplotlib.pyplot as plt # Linear Function def linear_function(x, m, b): return m * x + b x = np.linspace(-20, 20, 400) y = linear_function(x, m=2, b=-5) plt.plot(x, y, color='blue', linewidth=2) plt.scatter(0, -5, color='red', label="Y-Intercept") plt.show()
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Quadratic Function

A quadratic function follows f(x)=ax2+bx+cf(x) = ax^2 + bx + c, creating a parabolic curve. Key features include the vertex and x-intercepts.

# Quadratic Function
def quadratic_function(x):
    return x**2 - 4*x - 2

To analyze the function, we find its vertex and intercepts. The graph marks these points while arrows indicate that the parabola extends infinitely.

123456789101112
import numpy as np import matplotlib.pyplot as plt # Quadratic Function def quadratic_function(x): return x**2 - 4*x - 2 x = np.linspace(-2, 6, 200) y = quadratic_function(x) plt.plot(x, y, color='blue', linewidth=2) plt.scatter(2, quadratic_function(2), color='red', label="Vertex") plt.show()
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1. What is the output of the identity function for any input xx?

2. What does the constant function return for all values of xx?

3. In a linear function f(x)=mx+bf(x) = mx + b, what does mm represent?

question mark

What is the output of the identity function for any input xx?

Select the correct answer

question mark

What does the constant function return for all values of xx?

Select the correct answer

question mark

In a linear function f(x)=mx+bf(x) = mx + b, what does mm represent?

Select the correct answer

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Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 1. Kapittel 5

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bookImplementing Identity-Quadratic Functions in Python

Sveip for å vise menyen

Now that you've covered algebraic functions, let's work with them in Python. In this section, you'll learn not only function manipulation, but also visualization.

Identity Function

The identity function returns the input value unchanged, following the form f(x)=xf(x) = x. In Python, we implement it as:

# Identity Function
def identity_function(x):
    return x

To visualize it, we generate x-values from -10 to 10, plot the function, and mark the origin. The function extends infinitely in both directions, indicated by arrows.

12345678910111213
import numpy as np import matplotlib.pyplot as plt # Identity Function def identity_function(x): return x x = np.linspace(-10, 10, 100) # Generate values y = identity_function(x) plt.plot(x, y, label="f(x) = x", color='blue', linewidth=2) plt.scatter(0, 0, color='red') # Mark the origin plt.show()
copy

Constant Function

A constant function always returns the same output, regardless of the input. It follows f(x)=cf(x) = c.

# Constant Function
def constant_function(x, c):
    return np.full_like(x, c)

This implementation ensures all x-values yield the same output. The resulting plot is a horizontal line at y=cy = c, with arrows indicating infinite extension.

1234567891011
import numpy as np import matplotlib.pyplot as plt # Constant Function def constant_function(x, c): return np.full_like(x, c) x = np.linspace(-10, 10, 100) y = constant_function(x, c=5) plt.plot(x, y, label="f(x) = 5", color='blue', linewidth=2) plt.show()
copy

Linear Function

A linear function follows the form f(x)=mx+bf(x) = mx + b, where mm represents the slope and bb the y-intercept.

# Linear Function
def linear_function(x, m, b):
    return m * x + b

The graph of a linear function is a straight line. We plot it with arrows indicating infinite extension, and mark key points such as the x-intercept and y-intercept.

123456789101112
import numpy as np import matplotlib.pyplot as plt # Linear Function def linear_function(x, m, b): return m * x + b x = np.linspace(-20, 20, 400) y = linear_function(x, m=2, b=-5) plt.plot(x, y, color='blue', linewidth=2) plt.scatter(0, -5, color='red', label="Y-Intercept") plt.show()
copy

Quadratic Function

A quadratic function follows f(x)=ax2+bx+cf(x) = ax^2 + bx + c, creating a parabolic curve. Key features include the vertex and x-intercepts.

# Quadratic Function
def quadratic_function(x):
    return x**2 - 4*x - 2

To analyze the function, we find its vertex and intercepts. The graph marks these points while arrows indicate that the parabola extends infinitely.

123456789101112
import numpy as np import matplotlib.pyplot as plt # Quadratic Function def quadratic_function(x): return x**2 - 4*x - 2 x = np.linspace(-2, 6, 200) y = quadratic_function(x) plt.plot(x, y, color='blue', linewidth=2) plt.scatter(2, quadratic_function(2), color='red', label="Vertex") plt.show()
copy

1. What is the output of the identity function for any input xx?

2. What does the constant function return for all values of xx?

3. In a linear function f(x)=mx+bf(x) = mx + b, what does mm represent?

question mark

What is the output of the identity function for any input xx?

Select the correct answer

question mark

What does the constant function return for all values of xx?

Select the correct answer

question mark

In a linear function f(x)=mx+bf(x) = mx + b, what does mm represent?

Select the correct answer

Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 1. Kapittel 5
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