Introduction to Plotting (Matplotlib Basics)¶

Import¶

In [2]:

import numpy as np
import matplotlib.pyplot as plt

import numpy as np import matplotlib.pyplot as plt

Basic Line Plot¶

In [3]:

x = np.linspace(0, 2*np.pi, 200)
y = np.sin(x)

plt.plot(x, y)
plt.show()

x = np.linspace(0, 2*np.pi, 200) y = np.sin(x) plt.plot(x, y) plt.show()

With Labels and Title¶

In [4]:

plt.plot(x, y)
plt.xlabel("x")
plt.ylabel("sin(x)")
plt.title("Plot of sin(x)")
plt.show()

plt.plot(x, y) plt.xlabel("x") plt.ylabel("sin(x)") plt.title("Plot of sin(x)") plt.show()

Add Grid and Legend¶

In [5]:

plt.plot(x, y, label="sin(x)")
plt.xlabel("x")
plt.ylabel("y")
plt.grid(True)
plt.legend()
plt.show()

plt.plot(x, y, label="sin(x)") plt.xlabel("x") plt.ylabel("y") plt.grid(True) plt.legend() plt.show()

Customize Line and markers:¶

In [6]:

plt.plot(x, y, color="red", linestyle="--", linewidth=2)
plt.show()

plt.plot(x, y, color="red", linestyle="--", linewidth=2) plt.show()

In [7]:

plt.plot(x, y, marker="o", markersize=4)
plt.show()

plt.plot(x, y, marker="o", markersize=4) plt.show()

Multiple Curves¶

In [8]:

y1 = np.sin(x)
y2 = np.cos(x)

plt.plot(x, y1, label="sin(x)")
plt.plot(x, y2, label="cos(x)")

plt.legend()
plt.grid(True)
plt.show()

y1 = np.sin(x) y2 = np.cos(x) plt.plot(x, y1, label="sin(x)") plt.plot(x, y2, label="cos(x)") plt.legend() plt.grid(True) plt.show()

Change Figure Size¶

In [9]:

plt.figure(figsize=(4,2))
plt.plot(x, np.sin(x))
plt.show()

plt.figure(figsize=(4,2)) plt.plot(x, np.sin(x)) plt.show()

Save Figure¶

In [10]:

plt.plot(x, np.sin(x))
plt.savefig("sine_plot.png")

plt.plot(x, np.sin(x)) plt.savefig("sine_plot.png")

Scatter Plot¶

In [11]:

x = np.linspace(0, 10, 30)
y = x + np.random.randn(30)

plt.scatter(x, y)
plt.show()

x = np.linspace(0, 10, 30) y = x + np.random.randn(30) plt.scatter(x, y) plt.show()

Shade Between Two Functions¶

In [12]:

x = np.linspace(0, 2*np.pi, 400)
y1 = np.sin(x)
y2 = np.cos(x)

plt.plot(x, y1, label="sin(x)")
plt.plot(x, y2, label="cos(x)")

plt.fill_between(x, y1, y2, alpha=0.3)

plt.legend()
plt.grid(True)
plt.show()

x = np.linspace(0, 2*np.pi, 400) y1 = np.sin(x) y2 = np.cos(x) plt.plot(x, y1, label="sin(x)") plt.plot(x, y2, label="cos(x)") plt.fill_between(x, y1, y2, alpha=0.3) plt.legend() plt.grid(True) plt.show()

In [13]:

exact = np.sin(x)
numerical = np.sin(x) + 0.1*np.sin(5*x)

plt.plot(x, exact, label="Exact")
plt.plot(x, numerical, label="Numerical")

plt.fill_between(x, exact, numerical, alpha=0.3)

plt.legend()
plt.grid(True)
plt.show()

exact = np.sin(x) numerical = np.sin(x) + 0.1*np.sin(5*x) plt.plot(x, exact, label="Exact") plt.plot(x, numerical, label="Numerical") plt.fill_between(x, exact, numerical, alpha=0.3) plt.legend() plt.grid(True) plt.show()

Bar Plot¶

In [14]:

categories = ["A", "B", "C", "D"]
values = [10, 15, 7, 12]

plt.bar(categories, values)
plt.show()

categories = ["A", "B", "C", "D"] values = [10, 15, 7, 12] plt.bar(categories, values) plt.show()

Histogram¶

In [15]:

data = np.random.randn(1000)

plt.hist(data, bins=20)
plt.show()

data = np.random.randn(1000) plt.hist(data, bins=20) plt.show()

Subplots¶

In [16]:

x = np.linspace(0, 2*np.pi, 200)

plt.subplot(1, 2, 1)
plt.plot(x, np.sin(x))
plt.title("sin(x)")

plt.subplot(1, 2, 2)
plt.plot(x, np.cos(x))
plt.title("cos(x)")

plt.tight_layout()
plt.show()

x = np.linspace(0, 2*np.pi, 200) plt.subplot(1, 2, 1) plt.plot(x, np.sin(x)) plt.title("sin(x)") plt.subplot(1, 2, 2) plt.plot(x, np.cos(x)) plt.title("cos(x)") plt.tight_layout() plt.show()

LaTeX in Labels¶

In [17]:

x = np.linspace(-5, 5, 400)
y = np.exp(-x**2)

plt.plot(x, y)
plt.xlabel("$x$")
plt.ylabel("$e^{-x^2}$")
plt.title("Gaussian Curve")
plt.show()

x = np.linspace(-5, 5, 400) y = np.exp(-x**2) plt.plot(x, y) plt.xlabel("$x$") plt.ylabel("$e^{-x^2}$") plt.title("Gaussian Curve") plt.show()

Logarithmic Plots¶

Used for:

• Convergence studies

• Error decay

• Stability analysis

Semilog-y¶

In [18]:

n = np.array([10, 20, 40, 80, 160])
error = np.exp(-0.3*n)

plt.semilogy(n, error, marker="o")
plt.xlabel("n")
plt.ylabel("Error")
plt.grid(True)
plt.show()

n = np.array([10, 20, 40, 80, 160]) error = np.exp(-0.3*n) plt.semilogy(n, error, marker="o") plt.xlabel("n") plt.ylabel("Error") plt.grid(True) plt.show()

Log-Log Plot¶

In [19]:

h = np.array([0.1, 0.05, 0.025, 0.0125])
error = h**2

plt.loglog(h, error, marker="o")
plt.xlabel("h")
plt.ylabel("Error")
plt.grid(True, which="both")
plt.show()

h = np.array([0.1, 0.05, 0.025, 0.0125]) error = h**2 plt.loglog(h, error, marker="o") plt.xlabel("h") plt.ylabel("Error") plt.grid(True, which="both") plt.show()

In [20]:

order = np.log(error[:-1]/error[1:]) / np.log(h[:-1]/h[1:])
print(order)

order = np.log(error[:-1]/error[1:]) / np.log(h[:-1]/h[1:]) print(order)

[2. 2. 2.]

Contour Plot¶

In [21]:

x = np.linspace(-2, 2, 100)
y = np.linspace(-2, 2, 100)
X, Y = np.meshgrid(x, y)

Z = np.exp(-(X**2 + Y**2))

plt.contour(X, Y, Z, levels=20)
plt.colorbar()
plt.show()

x = np.linspace(-2, 2, 100) y = np.linspace(-2, 2, 100) X, Y = np.meshgrid(x, y) Z = np.exp(-(X**2 + Y**2)) plt.contour(X, Y, Z, levels=20) plt.colorbar() plt.show()

Filled contour:¶

In [22]:

plt.contourf(X, Y, Z, levels=20)
plt.colorbar()
plt.show()

plt.contourf(X, Y, Z, levels=20) plt.colorbar() plt.show()

Heatmap¶

In [23]:

A = np.random.rand(20, 20)

plt.imshow(A, origin="lower")
plt.colorbar()
plt.show()

A = np.random.rand(20, 20) plt.imshow(A, origin="lower") plt.colorbar() plt.show()

Read and display image¶

{python}
import matplotlib.pyplot as plt
img = plt.imread("image.jpg")
plt.imshow(img)
plt.axis("off")
plt.show()

3D Surface Plot¶

In [24]:

fig = plt.figure()
ax = fig.add_subplot(projection="3d")
ax.plot_surface(X, Y, Z)
plt.show()

fig = plt.figure() ax = fig.add_subplot(projection="3d") ax.plot_surface(X, Y, Z) plt.show()

In [25]:

fig = plt.figure()
ax = fig.add_subplot(projection="3d")

surf = ax.plot_surface(X, Y, Z, cmap="viridis")

fig.colorbar(surf)
plt.show()

fig = plt.figure() ax = fig.add_subplot(projection="3d") surf = ax.plot_surface(X, Y, Z, cmap="viridis") fig.colorbar(surf) plt.show()

In [26]:

x = np.linspace(0, 1, 100)
y = np.linspace(0, 1, 100)

X, Y = np.meshgrid(x, y)
Z = np.sin(np.pi*X)*np.sin(np.pi*Y)

fig = plt.figure()
ax = fig.add_subplot(projection="3d")

surf = ax.plot_surface(X, Y, Z, cmap="plasma")
fig.colorbar(surf)

plt.show()

x = np.linspace(0, 1, 100) y = np.linspace(0, 1, 100) X, Y = np.meshgrid(x, y) Z = np.sin(np.pi*X)*np.sin(np.pi*Y) fig = plt.figure() ax = fig.add_subplot(projection="3d") surf = ax.plot_surface(X, Y, Z, cmap="plasma") fig.colorbar(surf) plt.show()