April 4, 2022
At the end of this article, my goal is to convince you that: if you need to use random numbers, you should consider using scipy.stats.qmc instead of np.random.
In the following, we assume that SciPy, NumPy and Matplotlib are installed and imported:
import numpy as np from scipy.stats import qmc import matplotlib.pyplot as plt Note that no seeding is used in these examples. This will be the topic of another article: seeding should only be used for testing purposes.
At the end of this article, my goal is to convince you that: if you need to use random numbers, you should consider using scipy.stats.qmc instead of np.random.
In the following, we assume that SciPy, NumPy and Matplotlib are installed and imported:
import numpy as np from scipy.stats import qmc import matplotlib.pyplot as plt Note that no seeding is used in these examples. This will be the topic of another article: seeding should only be used for testing purposes.At the end of this article, my goal is to convince you that: if you need to use random numbers, you should consider using scipy.stats.qmc instead of np.random.
In the following, we assume that SciPy, NumPy and Matplotlib are installed and imported:
import numpy as np from scipy.stats import qmc import matplotlib.pyplot as plt Note that no seeding is used in these examples. This will be the topic of another article: seeding should only be used for testing purposes.