This is MatPy mode. Type help to get started nan: exp(x) : elementwise exponential of x solve(a,b) : return LMS solution of a*x==b map1(f, *args): a costly reimplementation of map acosm(x) : matrix arc cosine of x cumprod(x) : return columnwise cumulative prod map2(f, *args): elementwise f on matrices args trapz(x) : return columnwise integration using trapzoidal rule svd(x) : return Matrix u, array s, Matrix v as svd decomposition max2(x) : return max of all elements std(x) : return covariance matrix for columns of x Stats.distribs : Defines statistical distributions atan(x) : elementwise arc tangent of x mmap2(f, *args): return Matrix as elementwise f on matrices args wait(wtime, str, prompt) : wait wtime or Int: sinc(x) : elementwise sin(x)/x Interp: min2(x) : return min of all elements __name__: Matrix_cr(x) : return a matrix from a double list as a column of rows sinh(x) : elementwise hyperbolic sine of x acos(x) : elementwise arc cosine of x ibeta(x,a,b) : elementwise incomplete beta integral of x, sinm(x) : matrix sine of x beta(a,b) : elementwise beta function = gamma(a) * gamma(b) / gamma(a+b) This module provides access to some objects used or maintained by the Diag(x) : return diag matrix if x is row or col vector efunc(f, *args) : elementwise function f of args max(x) : return columnwise maximum if one argument, flipud(x) : return up-down flipped Matlab(tm) compatibility functions. class MatrixType : base class for Matrix - only defines repr and str names to see list of current objects (functions, classes,...) cephes: sin(x) : elementwise sine of x prod(x) : return columnwise product to_arrayC(data) : convert to complex array RandomArray: exit([status]) mreduce2(f, *args): return Matrix as elementwise f on matrices args lgam(x) : elementwise log gam |x| mfuncC(f, x) : matrix function with possibly complex eigenvalues. sqrt(x) : elementwise square root of x to_number(data) : conbert to number if possible sum(x) : return columnwise sum diag(x) : return diagonal of x as row vector class Gplot(Gnuplot) : gnuplot window as an object with methods for min(x) : return columnwise minimum if one argument, diff(x) : return columnwise diff, keeping first row. Inverse of cumsum asin(x) : elementwise arc sine of x class Tensor : rudimentary wrapper around NumPy arrays sinhm(x) : matrix hyperbolic sine of x any(x) : return row 0-1 vector, indicates each column being partly true exit([status]) logm(x) : matrix logarithm of x base e inf: to_array(data) : convert to array triu(x, k=0) : upper triangular part (on >=k)-th diagonal) of x. class ScalarType : base class for Scalar - only defines repr tanm(x) : matrix tangent of x NaN: LinearAlgebra: cosh(x) : elementwise hyperbolic cosine of x interp: cosem(x) : matrix cosine of x demo : Run demos one by one DynSys.kalman : Defines LinearSystem with kalman filtering MatPy.Stats : statistics oriented stuff atanm(x) : matrix arc tangent of x tril(x, k=0) : lower triangular part (on <=k-th diagonal) of x. mfuncs.py : Matrix-wise functions mean(x) : return columnwise mean Inf: efuncRC(*args) : elementwise function of matrices args, r_range(*i) : row vector of range(i) eig(x) : return eigenvalues as an array, eigenvectors as a Matrix cols(x) : split x into a list of columns class Scalar : class of numbers with customizable formats flipud(x) : return left-right flipped igamc(x>0,a>0) : elementwise complemented incomplete gamma integral rgam(x) : elementwise 1 / gam(x) Numeric module defining a multi-dimensional array and useful procedures for to_list(data) : convert to double list median(x) : return columnwise median efuncC(f, *args) : elementwise function f of args with possible complex elements tanh(x) : elementwise hyperbolic tangent of x igami(y, a>=0) : elementwise inverse incomplete gamma integral cose(x) : elementwise cosine of x mfunc(f, x) : matrix function f of matrix x. std(x) : return columnwise standard deviation MatPy.DynSys : Modules for dynamical systems efuncs.py - element-wise functions floor(x) : elementwise largest integer not greater than x ones(size) : matrix of ones of given size gam(x) : elementwise gamma function of x ceil(x) : elementwise smallest integer not less than x sign(x) : elementwise sign of x in (-1, 0, +1) to_Matrix(data) : covert to Matrix if possible tan(x) : elementwise tangent of x __file__: asinm(x) : matrix arc sine of x expm(x) : matrix exponential of x A collection of string operations (most are no longer used in Python 1.6). psi(x) : elementwise derivative of log gam(x) asinh(x) : elementwise inverse hyperbolic sine of x sort(x) : return columnwise sorted norm(x) : return Frobenius norm of x __doc__: log10(x) : elementwise logarithm of x base 10 names: Matrix_r(x) : return a matrix from a list as a row __builtins__: igam(x>0, a>0) : elementwise incomplete gamma integral zeros(a, typecode) : return a zero tensor c_range(*i) : col vector of range(i) tanhm(x) : matrix hyperbolic tangent of x reduce2(f, *args): elementwise f on matrices args Matrix_c(x) : return a matrix from a list as a column reduce1(f, list): a costly reimplementation of reduce lookfor(name) : Search docs for keyword <name> log(x) : elementwise logarithm of x base e eye(size) : identity matrix of given size rows(x) : split x into a list of rows solve(a,b) : return LMS solution of a*x==b approx_real(x) : return x.real if |x.imag| < |x.real| * _eps_approx size(data) : return data.shape unit(n, m) : unit vector of dimension n, pointing at mth direction find(x) : return list of indices (i,j) for which x[i,j] is true cumsum(x) : return columnwise cumulative sum norm1(x) : return columnwise norms diff(x) : return columnwise diff sqrtm(x) : matrix square root of x coshm(x) : matrix hyperbolic cosine of x Statistics utilities lbeta(a,b) : elementwise log |beta(x)| Mrange(*i) : row vector of range(i) - deprecated MatPy : Matrix package for python, with visualization. solve(a,b) : return solution of a*x==b abs(x) : elementwise absolute value of x sum2(x) : return sum of all elements ibetai(y, a>=0, b>=0) : elementwise inverse incomplete beta integral mfunc_p(f, x) : matrix function with positive eigenvalues class Matrix : main matrix class ptp(x) : return columnwise ptp? norm(x) : return Hilbert-Schmidt (?) norm of x rand(size) : standard uniformly distributed random matrix of given size all(x) : return row 0-1 vector, indicates each column being all true