Implementing Rational Functions in Python
Unlike previous functions, rational functions need special care when plotted in Python. Because they have undefined points and infinite values, you must split the domain to prevent errors.
1. Defining the Function
We define our rational function as:
def rational_function(x):
return 1 / (x - 1)
Key Considerations:
- x=1 must be excluded from calculations to avoid division by zero;
- The function will be split into two domains (left and right of x=1).
2. Splitting the Domain
To avoid division by zero, we generate two separate sets of x-values:
x_left = np.linspace(-4, 0.99, 250) # Left of x = 1
x_right = np.linspace(1.01, 4, 250) # Right of x = 1
The values 0.99
and 1.01
ensure we never include x=1, preventing errors.
3. Plotting the Function
plt.plot(x_left, y_left, color='blue', linewidth=2, label=r"$f(x) = \frac{1}{x - 1}$")
plt.plot(x_right, y_right, color='blue', linewidth=2)
The function jumps at x=1, so we need to plot it in two pieces.
4. Marking Asymptotes and Intercepts
- Vertical Asymptote (x=1):
plt.axvline(1, color='red', linestyle='--',
linewidth=1, label="Vertical Asymptote (x=1)")
- Horizontal Asymptote (y=0):
plt.axhline(0, color='green', linestyle='--',
linewidth=1, label="Horizontal Asymptote (y=0)")
- Y-Intercept at x=0:
y_intercept = rational_function(0)
plt.scatter(0, y_intercept, color='purple', label="Y-Intercept")
5. Adding Directional Arrows
To indicate the function extends infinitely:
plt.annotate('', xy=(x_right[-1], y_right[-1]), xytext=(x_right[-2], y_right[-2]), arrowprops=dict(arrowstyle='->', color='blue', linewidth=1.5))
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Implementing Rational Functions in Python
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Unlike previous functions, rational functions need special care when plotted in Python. Because they have undefined points and infinite values, you must split the domain to prevent errors.
1. Defining the Function
We define our rational function as:
def rational_function(x):
return 1 / (x - 1)
Key Considerations:
- x=1 must be excluded from calculations to avoid division by zero;
- The function will be split into two domains (left and right of x=1).
2. Splitting the Domain
To avoid division by zero, we generate two separate sets of x-values:
x_left = np.linspace(-4, 0.99, 250) # Left of x = 1
x_right = np.linspace(1.01, 4, 250) # Right of x = 1
The values 0.99
and 1.01
ensure we never include x=1, preventing errors.
3. Plotting the Function
plt.plot(x_left, y_left, color='blue', linewidth=2, label=r"$f(x) = \frac{1}{x - 1}$")
plt.plot(x_right, y_right, color='blue', linewidth=2)
The function jumps at x=1, so we need to plot it in two pieces.
4. Marking Asymptotes and Intercepts
- Vertical Asymptote (x=1):
plt.axvline(1, color='red', linestyle='--',
linewidth=1, label="Vertical Asymptote (x=1)")
- Horizontal Asymptote (y=0):
plt.axhline(0, color='green', linestyle='--',
linewidth=1, label="Horizontal Asymptote (y=0)")
- Y-Intercept at x=0:
y_intercept = rational_function(0)
plt.scatter(0, y_intercept, color='purple', label="Y-Intercept")
5. Adding Directional Arrows
To indicate the function extends infinitely:
plt.annotate('', xy=(x_right[-1], y_right[-1]), xytext=(x_right[-2], y_right[-2]), arrowprops=dict(arrowstyle='->', color='blue', linewidth=1.5))
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