`np.linspace` is a function in the NumPy library, which is a popular library in Python for scientific computing and working with arrays. The `linspace` function is used to create a linearly spaced array of numbers over a specified range.
The function has the following signature:
numpy.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0)
Parameters:
1. `start`: The starting value of the sequence.
2. `stop`: The end value of the sequence.
3. `num` (optional, default=50): The number of equally spaced samples to generate in the range. The default value is 50.
4. `endpoint` (optional, default=True): If True, the `stop` value is included in the output array. If False, the `stop` value is excluded from the output array.
5. `retstep` (optional, default=False): If True, the function will return the step size between the samples along with the array.
6. `dtype` (optional): The desired data type of the output array. If not provided, the function will try to infer the data type based on the input values.
7. `axis` (optional, default=0): The axis in the result to store the samples.
The function returns an ndarray containing `num` equally spaced samples in the closed interval `[start, stop]` or the half-open interval `[start, stop)` (depending on whether `endpoint` is True or False).
Here’s an example of using `np.linspace`:
import numpy as np
# Create an array of 10 equally spaced values between 1 and 5
arr = np.linspace(1, 5, num=10)
print(arr)
Output:
[1. 1.44444444 1.88888889 2.33333333 2.77777778 3.22222222 3.66666667 4.11111111 4.55555556 5. ]