numpy.logical_and(x1, x2[, out]) = Compute the truth value of x1 AND x2 element-wise. Parameters: x1, x2 : array_like Input arrays. x1 and x2 must be of the same shape. Returns: y : ndarray or bool Boolean result with the same shape as x1 and x2 of the logical AND operation on corresponding elements of x1 and x2. See also logical_or, logical_not, logical_xor, bitwise_and Examples >>> np.logical_and(True, False) False >>> np.logical_and([True, False], [False, Fal

numpy.logaddexp2(x1, x2[, out]) = Logarithm of the sum of exponentiations of the inputs in base-2. Calculates log2(2**x1 + 2**x2). This function is useful in machine learning when the calculated probabilities of events may be so small as to exceed the range of normal floating point numbers. In such cases the base-2 logarithm of the calculated probability can be used instead. This function allows adding probabilities stored in such a fashion. Parameters: x1, x2 : array_like Input values.

numpy.logaddexp(x1, x2[, out]) = Logarithm of the sum of exponentiations of the inputs. Calculates log(exp(x1) + exp(x2)). This function is useful in statistics where the calculated probabilities of events may be so small as to exceed the range of normal floating point numbers. In such cases the logarithm of the calculated probability is stored. This function allows adding probabilities stored in such a fashion. Parameters: x1, x2 : array_like Input values. Returns: result : ndarray

numpy.log2(x[, out]) = Base-2 logarithm of x. Parameters: x : array_like Input values. Returns: y : ndarray Base-2 logarithm of x. See also log, log10, log1p, emath.log2 Notes New in version 1.3.0. Logarithm is a multivalued function: for each x there is an infinite number of z such that 2**z = x. The convention is to return the z whose imaginary part lies in [-pi, pi]. For real-valued input data types, log2 always returns real output. For each value that cannot be expressed as

numpy.log1p(x[, out]) = Return the natural logarithm of one plus the input array, element-wise. Calculates log(1 + x). Parameters: x : array_like Input values. Returns: y : ndarray Natural logarithm of 1 + x, element-wise. See also expm1 exp(x) - 1, the inverse of log1p. Notes For real-valued input, log1p is accurate also for x so small that 1 + x == 1 in floating-point accuracy. Logarithm is a multivalued function: for each x there is an infinite number of z such that exp(z)

numpy.log10(x[, out]) = Return the base 10 logarithm of the input array, element-wise. Parameters: x : array_like Input values. Returns: y : ndarray The logarithm to the base 10 of x, element-wise. NaNs are returned where x is negative. See also emath.log10 Notes Logarithm is a multivalued function: for each x there is an infinite number of z such that 10**z = x. The convention is to return the z whose imaginary part lies in [-pi, pi]. For real-valued input data types, log10 alwa

numpy.log(x[, out]) = Natural logarithm, element-wise. The natural logarithm log is the inverse of the exponential function, so that log(exp(x)) = x. The natural logarithm is logarithm in base e. Parameters: x : array_like Input value. Returns: y : ndarray The natural logarithm of x, element-wise. See also log10, log2, log1p, emath.log Notes Logarithm is a multivalued function: for each x there is an infinite number of z such that exp(z) = x. The convention is to return the z who

numpy.loadtxt(fname, dtype=, comments='#', delimiter=None, converters=None, skiprows=0, usecols=None, unpack=False, ndmin=0) [source] Load data from a text file. Each row in the text file must have the same number of values. Parameters: fname : file or str File, filename, or generator to read. If the filename extension is .gz or .bz2, the file is first decompressed. Note that generators should return byte strings for Python 3k. dtype : data-type, optional Data-type of the resulting arra

numpy.load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII') [source] Load arrays or pickled objects from .npy, .npz or pickled files. Parameters: file : file-like object or string The file to read. File-like objects must support the seek() and read() methods. Pickled files require that the file-like object support the readline() method as well. mmap_mode : {None, ?r+?, ?r?, ?w+?, ?c?}, optional If not None, then memory-map the file, using the given mode (see

numpy.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None) [source] Return evenly spaced numbers over a specified interval. Returns num evenly spaced samples, calculated over the interval [start, stop]. The endpoint of the interval can optionally be excluded. Parameters: start : scalar The starting value of the sequence. stop : scalar The end value of the sequence, unless endpoint is set to False. In that case, the sequence consists of all but the last of num + 1 even