Creating Figures¶

The Figure object is the top-level container for all plot elements in Matplotlib.

Using plt.figure¶

Create an empty figure:

```python import matplotlib.pyplot as plt

fig = plt.figure() plt.show() ```

With size specification:

python fig = plt.figure(figsize=(10, 4))

The figsize parameter takes (width, height) in inches.

Using plt.subplots¶

The most common way to create a figure with axes:

```python import matplotlib.pyplot as plt import numpy as np

x = np.linspace(-2np.pi, 2np.pi, 100) y = np.sin(x)

fig, ax = plt.subplots(figsize=(12, 3)) ax.plot(x, y) plt.show() ```

Adding Axes with fig.add_axes¶

For precise axes positioning, use fig.add_axes:

```python import matplotlib.pyplot as plt import numpy as np

x = np.linspace(-2, 2, 1000) y1 = np.cos(40 * x) y2 = np.exp(-x**2)

fig = plt.figure()

Axes coordinates: [left, bottom, width, height] (0 to 1)¶

left, bottom, width, height = 0.1, 0.1, 0.8, 0.8 ax = fig.add_axes((left, bottom, width, height))

ax.plot(x, y1 * y2) ax.plot(x, y2, 'g') ax.plot(x, -y2, 'g') ax.set_xlabel("x") ax.set_ylabel("y")

plt.show() ```

Adding Axes with fig.add_subplot¶

Add subplots one at a time:

```python import matplotlib.pyplot as plt import numpy as np

x = np.linspace(0, 1, 50) y1 = x ** 2 y2 = np.sqrt(x)

fig = plt.figure(figsize=(12, 6))

for s in range(11): ax = fig.add_subplot(3, 4, s + 1) if s % 2 == 0: ax.plot(y1, label=f"state {s}") else: ax.plot(y2, label=f"state {s}")

plt.show() ```

Creating Inset Axes¶

Use multiple add_axes calls for inset plots:

```python import matplotlib.pyplot as plt import numpy as np

x = np.linspace(0, 3, 50) y1 = x ** 2 y2 = np.sqrt(x)

fig = plt.figure()

ax0 = fig.add_axes([0.1, 0.1, 0.8, 0.8]) # Main axes ax1 = fig.add_axes([0.2, 0.5, 0.4, 0.3]) # Inset axes

ax0.plot(x, y1) # Main figure ax1.plot(y1, x) # Inset

plt.show() ```

Figure Keywords¶

Common plt.figure parameters:

python fig = plt.figure( figsize=(8, 6), # Size in inches dpi=100, # Dots per inch facecolor='#f1f1f1', # Background color edgecolor='black', # Border color linewidth=2 # Border width )

Figure Title¶

Add a title to the entire figure (spanning all subplots):

```python import matplotlib.pyplot as plt

fig, (ax0, ax1) = plt.subplots(1, 2, figsize=(12, 3)) fig.suptitle("My Figure Title", fontsize=20)

ax0.plot([1, 2, 3]) ax1.plot([3, 2, 1])

plt.show() ```

Key Takeaways¶

• plt.figure() creates an empty figure
• plt.subplots() creates figure and axes together
• fig.add_axes() gives precise position control
• fig.add_subplot() adds subplots one at a time
• figsize=(width, height) sets size in inches

Exercises¶

Exercise 1. Write code that creates a figure using plt.subplots() with figsize=(10, 4), plots \(y = \sin(x)\) on it, and adds a title and axis labels.

Exercise 2. Predict the difference between plt.figure() followed by fig.add_subplot(1, 1, 1) versus using plt.subplots(). Which approach is more concise for creating a single plot?

Exercise 3. Create a figure with an inset plot using fig.add_axes(). The main plot should show \(y = x^2\) for \(x \in [0, 5]\), and the inset (positioned in the upper-left corner) should show a zoomed-in view of the same function for \(x \in [0, 1]\).

Exercise 4. Write code that creates a 3x4 grid of subplots using fig.add_subplot() in a loop. In each subplot, plot either \(y = x^2\) or \(y = \sqrt{x}\) alternating, and set the title to the subplot index.

Exercise 5. Explain the difference between fig.add_axes([0.1, 0.1, 0.8, 0.4]) and fig.add_subplot(2, 1, 1). What coordinate system does add_axes use? Create a figure with one main axes and one small overlay axes using add_axes, positioning the overlay in the bottom-left corner at 20% width and 20% height.