Refresher and Functions
Python operators
The following operators can be used to perform basic mathematical calculations in Python
| Name | Operator |
|---|---|
| Addition | + |
| Subtraction | - |
| Multiplication | * |
| Division | / |
| Modulus | & |
| Exponentiation | ** |
Essential mathematical functions
Here is a list of the most useful functions available in Python for maths.
To use these make sure you imported the Numpy module:
import numpy as np
Trigonometric functions
np.sin(x)calculates the sin of x (in radians)np.cos(x)calculates the cosine of x (in radians)np.tan(x)calculates the tangent of x (in radians)np.arcsin(x)calculates the inverse sin of x (in radians)np.arccos(x)calculates the inverse cosine of x (in radians)np.arctan(x)calculates the inverse tangent of x (in radians)np.degrees(x)angles from radians to degreesnp.radians(x)angles from degrees to radians
Hyperbolic functions
np.sinh(x)calculates the hyperbolic sin of x (in radians)np.cosh(x)calculates the hyperbolic cosine of x (in radians)np.tanh(x)calculates the hyperbolic tangent of x (in radians)np.arcsinh(x)calculates the inverse hyperbolic sin of x (in radians)np.arccosh(x)calculates the inverse hyperbolic cosine of x (in radians)np.arctanh(x)calculates the inverse hyperbolic tangent of x (in radians)
Exponents and logarithms
np.exp(x)calculate the exponential of all elements in the input xnp.sqrt(x)calculate square root of xnp.log(x)calculate the natural logarithm of xnp.log10(x)calculate the base 10 logarithm of x
Drawing functions
You can easily draw functions using the matplotlib module.
So make sure you import the module:
import matplotlib.pyplot as plt
Here are some essential functions needed to plot a graph:
plt.title(x)input string to be graph titleplt.plot(x, y)plot x and y coordinates, inputs must be arraysplt.show()show the graph
For example, to plot the function sin(x)^2 with x between -4 and 4, you could write the following code:
import numpy as np
import matplotlib.pyplot as plt
# Compute the x and y coordinates for points on curve
x = np.arange(-4, 4, 0.1) # Generate array of numbers between -4 and 4 with step size of 0.1 for x coordinates
y = np.sin(x)**2
plt.title("sine wave form")
# Plot the points using matplotlib
plt.plot(x, y)
plt.show()