How to specify upper and lower limits when using numpy.random.normal

by

It sounds like you want a truncated normal distribution.
Using scipy, you could use scipy.stats.truncnorm to generate random variates from such a distribution:

import matplotlib.pyplot as plt
import scipy.stats as stats

lower, upper = 3.5, 6
mu, sigma = 5, 0.7
X = stats.truncnorm(
    (lower - mu) / sigma, (upper - mu) / sigma, loc=mu, scale=sigma)
N = stats.norm(loc=mu, scale=sigma)

fig, ax = plt.subplots(2, sharex=True)
ax[0].hist(X.rvs(10000), normed=True)
ax[1].hist(N.rvs(10000), normed=True)
plt.show()

enter image description here

The top figure shows the truncated normal distribution, the lower figure shows the normal distribution with the same mean mu and standard deviation sigma.

More Related Contents:

  1. Generating Discrete random variables with specified weights using SciPy or NumPy
  2. How do I read CSV data into a record array in NumPy?
  3. A tool to convert MATLAB code to Python [closed]
  4. Compute a confidence interval from sample data
  5. Import Error: No module named numpy
  6. calling dot products and linear algebra operations in Cython?
  7. matplotlib – extracting data from contour lines
  8. ImportError: cannot import name NUMPY_MKL
  9. Installing NumPy and SciPy on 64-bit Windows (with Pip)
  10. How to add a new row to an empty numpy array
  11. Interpolation over an irregular grid
  12. How to get a normal distribution within a range in numpy? [duplicate]
  13. Overflow Error in Python’s numpy.exp function
  14. Creating same random number sequence in Python, NumPy and R
  15. How can I efficiently process a numpy array in blocks similar to Matlab’s blkproc (blockproc) function
  16. How do I plot list of tuples in Python?
  17. generalized cumulative functions in NumPy/SciPy?
  18. Principal component analysis in Python
  19. How to generate a random normal distribution of integers
  20. How to convert a column or row matrix to a diagonal matrix in Python?
  21. How to do a polynomial fit with fixed points
  22. Working with floating point NumPy arrays for comparison and related operations
  23. Generate random locations within a triangular domain
  24. How to smooth a curve for a dataset
  25. How to transform numpy.matrix or array to scipy sparse matrix
  26. Matplotlib – Finance volume overlay
  27. sparse 3d matrix/array in Python?
  28. Convert Pandas dataframe to Sparse Numpy Matrix directly
  29. Structure of inputs to scipy minimize function
  30. ValueError: Dimension mismatch

Leave a Comment