NumPy
The following are useful NumPy functions:
numpy.arange([start,] stop[, step,], dtype=None): This function creates a NumPy array with evenly spaced values within a specified range.
numpy.argsort(a, axis=-1, kind='quicksort', order=None): This function returns the indices that will sort the input array.
numpy.array(object, dtype=None, copy=True, order=None, subok=False, ndmin=0): This function creates a NumPy array from an array-like sequence such as a Python list.
numpy.dot(a, b, out=None): This function calculates the dot product of two arrays.
numpy.eye(N, M=None, k=0, dtype=<type 'float'>): This function returns the identity matrix.
numpy.load(file, mmap_mode=None): This function loads NumPy arrays or pickled objects from .npy, .npz, or pickles. A memory-mapped array is stored in the filesystem and doesn't have to be completely loaded in the memory. This is especially useful for large arrays.
numpy.loadtxt(fname, dtype=<type 'float'>...
