MATLAB/GNU Octave for Python/NumPy users

This document is a reverse and updated version of "NumPy for MATLAB users" thesaurus written by Vidar Bronken Gundersen / Mathesaurus in 2006, and also inspired from another MATLAB/NumPy cross-reference by Numpy developers. Here the GNU Octave commands have been completed, fixed, and sometimes replaced by correct or more appropriate functions, as used by a real MATLAB/Octave programmer.

In the tables below, for Python commands it is assumed that you have imported some libraries as follows:

Also, we present here only the functional form of expressions, but most of Python commands have their strict equivalent using an object-oriented form, i.e., the method. Example: a.size is similar to np.size(a). Note that the method name may be different than the function name.

Python	Octave	Description
`help()`	`doc`	Browse help interactively
	`help help` `doc doc`	Help on using help
`help(plt.plot)`	`help plot` `doc plot`	Help for a function
`help(np)`	`doc splines`	Help for a toolbox/library package
	`demo`	Demonstration examples

Python	Octave	Description
	`lookfor plot`	Search keyword in help files
`help(); modules [Numeric]`	`help`	List available packages
`help(plt.plot)`	`which plot`	Locate functions

Python	Octave	Description
`ipython -pylab`	`octave -q`	Start session
`TAB`	`TAB`	Auto completion
`execfile('foo.py')` `run foo.py`	`foo` `foo.m`	Run code from file
`hist -n`	`history`	Command history
	`diary on [..] diary off`	Save command history
`CTRL-D` `CTRL-Z # windows` `sys.exit()`	`exit` `quit`	End session

Operators

Python	Octave	Description
	`help -`	Help on operator syntax

Arithmetic operators

Python	Octave	Description
`a=1; b=2`	`a=1; b=2;`	Assignment; defining a number
`a + b` `add(a,b)`	`a + b` `plus(a,b)`	Addition
`a - b` `subtract(a,b)`	`a - b` `minus(a,b)`	Subtraction
`a * b` `multiply(a,b)`	`a .* b` `times(a,b)`	Multiplication
`a / b` `divide(a,b)`	`a ./ b` `rdivide(a,b)`	Right division
`b / a`	`a .\ b` `ldivide(a,b)`	Left division
`a ** b` `np.power(a,b)` `math.pow(a,b)`	`a .^ b` `power(a,b)`	Power, a^b
`np.remainder(a,b)`	`rem(a,b)`	Remainder after division
`a % b` `np.fmod(a,b)` `math.fmod(a,b)`	`mod(a,b)`	Modulo
`a+=b` `add(a,b,a)`	`a+=b` `plus(a,b,a)`	In place operation to save array creation overhead
`math.factorial(a)`	`factorial(a)`	Factorial, n!

Relational operators

Python	Octave	Description
`a == b` `equal(a,b)`	`a == b` `eq(a,b)`	Equal
`a < b` `less(a,b)`	`a < b` `lt(a,b)`	Less than
`a > b` `greater(a,b)`	`a > b` `gt(a,b)`	Greater than
`a <= b` `less_equal(a,b)`	`a <= b` `le(a,b)`	Less than or equal
`a >= b` `greater_equal(a,b)`	`a >= b` `ge(a,b)`	Greater than or equal
`a != b` `not_equal(a,b)`	`a ~= b` `a != b` `ne(a,b)`	Not Equal

Logical operators

Python	Octave	Description
`a and b`	`a && b`	Short-circuit logical AND
`a or b`	`a \|\| b`	Short-circuit logical OR
`logical_and(a,b)` `a and b`	`a & b` `and(a,b)`	Element-wise logical AND
`logical_or(a,b)` `a or b`	`a \| b` `or(a,b)`	Element-wise logical OR
`logical_xor(a,b)`	`xor(a, b)`	Logical EXCLUSIVE OR
`logical_not(a)` `not a`	`~a` `not(a)` `!a`	Logical NOT
	`any(a)`	True if any element is nonzero
	`all(a)`	True if all elements are nonzero

root and logarithm

Python	Octave	Description
`math.sqrt(a)`	`sqrt(a)`	Square root
`math.log(a)`	`log(a)`	Logarithm, base e (natural)
`math.log10(a)`	`log10(a)`	Logarithm, base 10
`math.log(a, 2)`	`log2(a)`	Logarithm, base 2 (binary)
`math.exp(a)`	`exp(a)`	Exponential function

Round off

Python	Octave	Description
`np.around(a)`	`round(a)`	Round
`np.ceil(a)`	`ceil(a)`	Round up
`np.floor(a)`	`floor(a)`	Round down
`np.fix(a)`	`fix(a)`	Round towards zero

Mathematical constants

Python	Octave	Description
`math.pi`	`pi`	π=3.141592
`math.e` `math.exp(1)`	`exp(1)`	e=2.718281

Missing values; IEEE-754 floating point status flags

Python	Octave	Description
`nan`	`NaN`	Not a Number
`inf`	`Inf`	Infinity, ∞
`plus_inf`	`+Inf`	Infinity, +∞
`minus_inf`	`-Inf`	Infinity, -∞
`plus_zero`		Plus zero, +0
`minus_zero`		Minus zero, -0

Complex numbers

Python	Octave	Description
`1j`	`i,j,1i,1j`	Imaginary unit
`3 + 4j` `complex(3,4)`	`3 + 4i` `complex(3,4)`	A complex number, 3+4i
`abs(z)`	`abs(z)`	Absolute value (modulus)
`no.real(z)`	`real(z)`	Real part
`np.imag(z)`	`imag(z)`	Imaginary part
`np.angle(z)`	`arg(z)`	Argument
`np.conj(z)`	`conj(z)`	Complex conjugate

Trigonometry

Python	Octave	Description
`math.atan2(b,a)`	`atan2(b,a)`	Arctangent, arctan(b/a)
	`hypot(x,y)`	Hypotenus; Euclidean distance

Generate random numbers

Python	Octave	Description
`np.random.random((10,))` `np.random.uniform((10,))`	`rand(1,10)`	Uniform distribution
`np.random.uniform(2,7,(10,))`	`2+5*rand(1,10)`	Uniform: Numbers between 2 and 7
`np.random.uniform(0,1,(6,6))`	`rand(6)`	Uniform: 6,6 array
`np.random.standard_normal((10,))`	`randn(1,10)`	Normal distribution

Vectors

Python	Octave	Description
`a=np.array([2,3,4,5])`	`a=[2 3 4 5];`	Row vector, 1×n-matrix
`np.array([2,3,4,5])[:,NewAxis]` `np.array([2,3,4,5]).reshape(-1,1)` `r_[1:10,'c']`	`adash=[2 3 4 5]';`	Column vector, m×1-matrix

Sequences

Python	Octave	Description
`np.arange(1,11, dtype=Float)` `range(1,11)`	`1:10`	1,2,3, ... ,10
`np.arange(10.)`	`0:9`	0.0,1.0,2.0, ... ,9.0
`np.arange(1,11,3)`	`1:3:10`	1,4,7,10
`np.arange(10,0,-1)`	`10:-1:1`	10,9,8, ... ,1
`arange(10,0,-3)`	`10:-3:1`	10,7,4,1
`np.linspace(1,10,7)`	`linspace(1,10,7)`	Linearly spaced vector of n=7 points
`a[::-1]`	`flip(a)`	Reverse
`a[:] = 3`	`a(:) = 3`	Set all values to same scalar value

Concatenation (vectors)

Python	Octave	Description
`np.concatenate((a,a))`	`[a a] cat(2,a,a)`	Concatenate two vectors
`np.concatenate((range(1,5),a), axis=1)`	`[1:4 a]`

Repeating

Python	Octave	Description
`np.concatenate((a,a))`	`repmat(a,1,2)`	1 2 3 1 2 3
`np.repeat(a,3)`	`repelem(a,3)` `repmat(a,1,3)(:)'`	1 1 1 2 2 2 3 3 3
`np.repeat(a,a)`	`repelem(a,a)`	1 2 2 3 3 3

Miss those elements out

Python	Octave	Description
`a[1:]`	`a(2:end)`	miss the first element
	`a([1:9])`	miss the tenth element
`a[-1]`	`a(end)`	last element
`a[-2:]`	`a(end-1:end)`	last two elements

Maximum and minimum

Python	Octave	Description
`np.maximum(a,b)`	`max(a,b)`	pairwise max
`np.concatenate((a,b)).max()`	`max([a b])`	max of all values in two vectors
`v,i = a.max(0),a.argmax(0)`	`[v,i] = max(a)`

Vector multiplication

Python	Octave	Description
`a*a`	`a.*a`	Multiply two vectors
`dot(u,v)`	`dot(u,v)`	Vector dot product, u · v

Matrices

Python	Octave	Description
`a = array([[2,3],[4,5]])`	`a = [2 3;4 5]`	Define a matrix

Concatenation (matrices); rbind and cbind

Python	Octave	Description
`np.concatenate((a,b), axis=0)` `np.vstack((a,b))`	`[a;b]` `cat(1,a,b)`	Bind rows
`np.concatenate((a,b), axis=1)` `np.hstack((a,b))`	`[a,b]` `cat(2,a,b)`	Bind columns
`np.concatenate((a,b), axis=2)` `np.dstack((a,b))`	`cat(3,a,b)`	Bind slices (three-way arrays)
`np.concatenate((a,b), axis=None)`	`[a(:), b(:)]`	Concatenate matrices into one vector
`np.concatenate((r_[1:5],r_[1:5])).reshape(2,-1)` `np.vstack((r_[1:5],r_[1:5]))`	`[1:4 ; 1:4]`	Bind rows (from vectors)
	`[1:4 ; 1:4]'`	Bind columns (from vectors)

Array creation

Python	Octave	Description
`np.zeros((3,5))`	`zeros(3,5)`	0 filled array
`np.zeros((3,5),np.int8)`	`zeros(3,5,'int8') int8(zeros(3,5))`	0 filled array of 8-bit integers
`np.ones((3,5))`	`ones(3,5)`	1 filled array
	`ones(3,5)*9`	Any number filled array
`np.identity(3)`	`eye(3)`	Identity matrix
`np.diag((4,5,6))`	`diag([4 5 6])`	Diagonal
	`magic(3)`	Magic squares; Lo Shu
`a = np.empty((3,3))`		Empty array

Reshape and flatten matrices

Python	Octave	Description
`np.arange(1,7).reshape(2,-1)` `a.setshape(2,3)`	`reshape(1:6,3,2)'`	Reshaping (rows first)
`np.arange(1,7).reshape(-1,2).transpose()`	`reshape(1:6,2,3)`	Reshaping (columns first)
`np.ravel(a)`	`a'(:)` `a = a'; a(:)`	Flatten to vector (by rows, like comics)
`np.ravel(a, order='F')`	`a(:)`	Flatten to vector (by columns)
	`vech(a)`	Flatten upper triangle (by columns)

Shared data (slicing)

Python	Octave	Description
`b = a`		Reference to a (alias)
`b = a.copy()`	`b = a;`	Copy of a

Indexing and accessing elements (Python: slicing)

Python	Octave	Description
`a = array([[ 11, 12, 13, 14 ],` `[ 21, 22, 23, 24 ],` `[ 31, 32, 33, 34 ]])`	`a = [11 12 13 14;` `21 22 23 24;` `31 32 33 34];`	Input is a 3x4 array
`a[1,2]`	`a(2,3)`	Element 2,3 (row,col)
`a[0,]`	`a(1,:)`	First row
`a[:,0]`	`a(:,1)`	First column
`a.take([0,2]).take([0,3], axis=1)`	`a([1 3],[1 4]);`	Array as indices
`a[1:,]`	`a(2:end,:)`	All, except first row
`a[-2:,]`	`a(end-1:end,:)`	Last two rows
`a[::2,:]`	`a(1:2:end,:)`	Strides: Every other row
	`a[...,2]`	Third in last dimension (axis)
`a.take([0,2,3],axis=1)`	`a(:,[1 3 4])`	Remove one column
`a.diagonal(offset=0)`		Diagonal

Assignment

Python	Octave	Description
`a[:,0] = 99`	`a(:,1) = 99;`
`a[:,0] = array([99,98,97])`	`a(:,1) = [99;98;97];`
`(a>90).choose(a,90)` `a.clip(min=None, max=90)`	`a(a>90) = 90;`	Clipping: Replace all elements over 90
`a.clip(min=2, max=5)`	`a(a<2) = 2; a(a>5) = 5;`	Clip upper and lower values

Transpose and inverse

Python	Octave	Description
`a.conj().transpose()`	`a'`	Transpose
`np.transpose(a)`	`a.'` `transpose(a)`	Non-conjugate transpose
`np.linalg.det(a)`	`det(a)`	Determinant
`np.linalg.inv(a)`	`inv(a)`	Inverse
`np.linalg.pinv(a)`	`pinv(a)`	Pseudo-inverse
`norm(a)`	`norm(a)`	Norms
`np.linalg.eig(a)[0]`	`eig(a)`	Eigenvalues
`np.linalg.svd(a)`	`svd(a)`	Singular values
`np.linalg.cholesky(a)`	`chol(a)`	Cholesky factorization
`np.linalg.eig(a)[1]`	`[v,l] = eig(a)`	Eigenvectors
`np.rank(a)`	`rank(a)`	Rank

Sum

Python	Octave	Description
`sum(a)`	`sum(a)`	Sum of each column
`np.sum(a,axis=1)`	`sum(a,2)`	Sum of each row
`np.sum(a)`	`sum(a(:))`	Sum of all elements
`np.trace(a)`	`trace(a)`	Sum along diagonal
`np.cumsum(a)`	`cumsum(a'(:))`	Cumulative sum of all values (by rows)
`np.cumsum(a,axis=0)`	`cumsum(a)`	Cumulative sum (each columns)

Sorting

Python	Octave	Description
`a = array([[4,3,2],[2,8,6],[1,4,7]])`	`a = [4,3,2;2,8,6;1,4,7];`	Example data
`a.ravel().sort()`	`sort(a(:))`	Flat and sorted
`a.sort(axis=0)` `msort(a)`	`sort(a)`	Sort each column
`a.sort(axis=1)`	`sort(a,2)`	Sort each row
`a[a[:,0].argsort(),]`	`sortrows(a,1)`	Sort rows (by first row)
`a.ravel().argsort()`	`[~,k]=sort(a)`	Sort, return indices
`a.argsort(axis=0)`	`[~,k]=sort(a,1)`	Sort each column, return indices
`a.argsort(axis=1)`	`[~,k]=sort(a,2)`	Sort each row, return indices

Maximum and minimum

Python	Octave	Description
`a.max(0)` `np.amax(a [,axis=0])`	`max(a)`	max in each column
`a.max(1)` `np.amax(a, axis=1)`	`max(a')` `max(a,[],2)`	max in each row
`a.max()`	`max(a(:))`	max in array
	`[v,i] = max(a)`	return indices, i
`np.maximum(b,c)`	`max(b,c)`	pairwise max
`a.ptp()`	`max(a(:)) - min(a(:))`	max-to-min range

Matrix manipulation

Python	Octave	Description
`np.fliplr(a)` `a[:,::-1]`	`fliplr(a)`	Flip left-right
`np.flipud(a)` `a[::-1,]`	`flipud(a)`	Flip up-down
`np.rot90(a)`	`rot90(a)`	Rotate 90 degrees
`kron(ones((2,3)),a)`	`repmat(a,2,3)` `kron(ones(2,3),a)`	Repeat matrix: [ a a a ; a a a ]
`np.triu(a)`	`triu(a)`	Triangular, upper
`np.tril(a)`	`tril(a)`	Triangular, lower

Matrix shape and size

Python	Octave	Description
`a.shape` `a.getshape()`	`size(a)`	Matrix dimensions
`a.shape[1]` `size(a, axis=1)`	`size(a,2)`	Number of columns
`a.size` `size(a[, axis=None])`	`numel(a)` `length(a(:))`	Total number of elements
`max(a.shape)`	`length(a)`	Number of elements along the largest dimension
`a.ndim`	`ndims(a)`	Number of dimensions
`a.nbytes`	`x = whos('a'); x.bytes`	Number of bytes used in memory

Matrix - and elementwise - multiplication

Python	Octave	Description
`a * b` `np.multiply(a,b)`	`a .* b` `times(a,b)`	Elementwise operations
`np.matrixmultiply(a,b)`	`a * b` `mtimes(a,b)`	Matrix product (dot product)
	`np.inner(a,b)`	Inner matrix vector multiplication a · b'
	`np.outer(a,b)`	Outer product
`kron(a,b)`	`kron(a,b)`	Kronecker product
	`a / b`	Matrix division, b · a^-1
`np.linalg.solve(a,b)`	`a \ b`	Left matrix division, b^-1 · a (solve linear equations)
	`np.vdot(a,b)`	Vector dot product
	`np.cross(a,b)`	Cross product

Find; conditional indexing

Python	Octave	Description
`a.ravel().nonzero()`	`find(a)`	Non-zero elements, indices
`(i,j) = a.nonzero()` `(i,j) = where(a!=0)`	`[i j] = find(a)`	Non-zero elements, array indices
`v = a.compress((a!=0).flat)` `v = extract(a!=0,a)`	`[i j v] = find(a)`	Vector of non-zero values
`(a>5.5).nonzero()`	`find(a>5.5)`	Condition, indices
	`a.compress((a>5.5).flat)`	Return values
`np.where(a>5.5,0,a)` `a * (a>5.5)`	`a .* (a>5.5)`	Zero out elements above 5.5
`a.put(2,indices)`		Replace values

Python	Octave	Description
`a = array([[[1,2],[1,2]], [[3,4],[3,4]]])`	`a = cat(3, [1 2; 1 2],[3 4; 3 4]);`	Define a 3-way array
`a[0,...]`	`a(1,:,:)`

Python	Octave	Description
`f = np.fromfile("data.txt")` `f = load("data.txt");`	`f = load('data.txt')`	Reading from a file (2d)
`f = load('data.csv', delimiter=';')`	`x = dlmread('data.csv', ';');`	Reading fram a CSV file (2d)
`save('data.csv', f, fmt='%.6f', delimiter=';')`	`save -ascii data.txt f`	Writing to a file (2d)
`f.tofile(file='data.csv', format='%.6f', sep=';')`		Writing to a file (1d)
`f = np.fromfile(file='data.csv', sep=';')`		Reading from a file (1d)

Plotting

Basic x-y plots

Python	Octave	Description
`plot(a)`	`plot(a)`	1d line plot
`plot(x[:,0],x[:,1],'o')`	`plot(x(:,1),x(:,2),'o')`	2d scatter plot
`plot(x1,y1,'bo', x2,y2,'go')`	`plot(x1,y1, x2,y2)`	Two graphs in one plot
`plot(x1,y1,'o')` `plot(x2,y2,'o')` `show() # as normal`	`plot(x1,y1)` `hold on` `plot(x2,y2)`	Overplotting: Add new plots to current
`subplot(211)`	`subplot(211)`	subplots
`plot(x,y,'ro-')`	`plot(x,y,'ro-')`	Plotting symbols and color

Axes and titles

Python	Octave	Description
`grid()`	`grid on`	Turn on grid lines
`figure(figsize=(6,6))`	`axis equal`	1:1 aspect ratio
`axis([ 0, 10, 0, 5 ])`	`axis([ 0 10 0 5 ])`	Set axes manually
	`title('title')` `xlabel('x-axis')` `ylabel('y-axis')`	Axis labels and titles
	`text(2,25,'hello')`	Insert text

Log plots

Python	Octave	Description
`semilogy(a)`	`semilogy(a)`	logarithmic y-axis
`semilogx(a)`	`semilogx(a)`	logarithmic x-axis
`loglog(a)`	`loglog(a)`	logarithmic x and y axes

Filled plots and bar plots

Python	Octave	Description
`fill(t,s,'b', t,c,'g', alpha=0.2)`	`fill(t,s,'b', t,c,'g')`	Filled plot

Functions

Python	Octave	Description
	`f = @(x) sin(x/3) - cos(x/5)`	Defining functions
`x = arrayrange(0,40,.5)` `y = sin(x/3) - cos(x/5)` `plot(x,y, 'o')`	`fplot(f,[0,40])` `ezplot('sin(x/3) - cos(x/5)',[0,40])`	Plot a function for given range

Polar plots

Python	Octave	Description
`theta = arange(0,2pi,0.001)` `rho = sin(2theta)`	`theta = 0:.001:2pi;` `rho = sin(2theta);`
`polar(theta, rho)`	`polar(theta, rho)`

Histogram plots

Python	Octave	Description
	`hist(randn(1000,1))`
	`hist(randn(1000,1), -4:4)`
	`plot(sort(a))`

3d data

Contour and image plots

Python	Octave	Description
`levels, colls = contour(Z, V,` `origin='lower', extent=(-3,3,-3,3))` `clabel(colls, levels, inline=1,` `fmt='%1.1f', fontsize=10)`	`contour(z)`	Contour plot
`contourf(Z, V,` `cmap=cm.gray,` `origin='lower',` `extent=(-3,3,-3,3))`	`contourf(z); colormap(gray)`	Filled contour plot
`im = imshow(Z,` `interpolation='bilinear',` `origin='lower',` `extent=(-3,3,-3,3))`	`image(z)` `colormap(gray)`	Plot image data
	`# imshow() and contour() as above`	Image with contours
`quiver()`	`quiver()`	Direction field vectors

Perspective plots of surfaces over the x-y plane

Python	Octave	Description
`n=arrayrange(-2,2,.1)` `[x,y] = meshgrid(n,n)` `z = xpower(math.e,-x2-y*2)`	`n=-2:.1:2;` `[x,y] = meshgrid(n,n);` `z=x.*exp(-x.^2-y.^2);`
	`mesh(z)`	Mesh plot
	`surf(x,y,z)` `surfl(x,y,z)`	Surface plot

Scatter (cloud) plots

Python	Octave	Description
	`plot3(x,y,z,'k+')`	3d scatter plot

Save plot to a graphics file

Python	Octave	Description
`savefig('foo.eps')`	`print('-depsc','foo.eps')`	PostScript
`savefig('foo.pdf')`	`print('-dpdf','foo.pdf')`	PDF
`savefig('foo.svg')`	`print('-dsvg','foo.svg')`	SVG (vector graphics for www)
`savefig('foo.png')`	`print('-dpng','foo.png')`	PNG (raster graphics)
	`savefig('foo.fig')`	Reloadable graphics object

Data analysis

Set membership operators

Python	Octave	Description
`a = array([1,2,2,5,2])` `b = array([2,3,4])` `a = set([1,2,2,5,2])` `b = set([2,3,4])`	`a = [1,2,2,5,2];` `b = [2,3,4];`	Create sets
`np.unique1d(a)` `np.unique(a)` `set(a)`	`unique(a)`	Set unique
`np.union1d(a,b)`	`union(a,b)`	Set union
`np.intersect1d(a)`	`intersect(a,b)`	Set intersection
`np.setdiff1d(a,b)`	`setdiff(a,b)`	Set difference
`np.setxor1d(a,b)`	`setxor(a,b)`	Set exclusion
`2 in a` `np.setmember1d(2,a)` `contains(a,2)`	`ismember(2,a)`	True for set member

Statistics

Python	Octave	Description
`a.mean(axis=0)` `mean(a [,axis=0])`	`mean(a)`	Average
`median(a)` `median(a [,axis=0])`	`median(a)`	Median
`np.std(a)`	`std(a(:))`	Standard deviation
`np.var(a)` `var(a)`	`var(a(:))`	Variance
`np.correlate(x,y)` `corrcoef(x,y)`	`corr(x,y)`	Correlation coefficient
`np.cov(x,y)`	`cov(x,y)`	Covariance

Interpolation and regression

Python	Octave	Description
`(a,b) = polyfit(x,y,1)` `plot(x,y,'o', x,a*x+b,'-')`	`p = polyfit(x,y,1);` `plot(x,y,'o',x,polyval(p,x),'-')`	Straight line fit
`np.linalg.lstsq(x,y)`	`a = x\y`	Linear least squares y = ax + b
`np.polyfit(x,y,3)`	`polyfit(x,y,3)`	Polynomial fit

Non-linear methods

Polynomials, root finding

Python	Octave	Description
`np.poly()`	`poly(x)`	Polynomial
`np.roots()`	`roots([1 -1 -1])`	Find zeros of polynomial
	`f = @(x) 1/x - (x-1);` `fzero(f,1)`	Find a zero near x = 1
	`solve('1/x = x-1')`	Solve symbolic equations
`polyval(array([1,2,1,2]),arange(1,11))`	`polyval([1 2 1 2],1:10)`	Evaluate polynomial

Differential equations

Python	Octave	Description
`np.diff(x, n=1, axis=0)`	`diff(x)`	Discrete difference function and approximate derivative
`integrate.solve_ivp(f)`	`ode45(f)`	Solve differential equations

Fourier analysis

Python	Octave	Description
`np.fft(a)`	`fft(a)`	Fast fourier transform
`np.ifft(a)`	`ifft(a)`	Inverse fourier transform
`np.convolve(x,y)`	`conv(x,y)`	Linear convolution

Programming

Python	Octave	Description
`.py`	`.m`	Script file extension
`#`	`%` `#`	Comment symbol (rest of line)
`from pylab import *`	`% must be in current directory or MATLABPATH` `% must be in current directory or LOADPATH`	Import library functions
`string="a=234"` `eval(string)`	`string='a=234';` `eval(string)`	Eval

Loops

Python	Octave	Description
`for i in range(1,6): print(i)`	`for i=1:5, disp(i), end`	for-statement
`for i in range(1,6):` `print(i)` `print(i*2)`	`for i=1:5` `disp(i)` `disp(i*2)` `end`	Multiline for statements

Conditionals

Python	Octave	Description
`if 1>0: a=100`	`if 1>0 a=100; end`	if-statement
	`if 1>0 a=100; else a=0; end`	if-else-statement

Debugging

Python	Octave	Description
	`ans`	Most recent evaluated expression
	`whos` `who`	List variables loaded into memory
	`clear x` `clear [all]`	Clear variable x from memory
`a print(a)`	`a disp(a)`	Display variable content
`pdb.set_trace()` `breakpoint()`	`keyboard`	Insert a break for manual debugging
`pdb.pm()`	`dbstop if error`	Will break for debugging at error

Working directory and OS

Python	Octave	Description
`os.listdir(".")`	`dir` `ls`	List files in directory
	`what`	List script or environment files in directory
`os.getcwd()`	`pwd`	Displays the current working directory
`os.chdir('foo')`	`cd foo`	Change working directory
`os.system('notepad')` `os.popen('notepad')`	`system('notepad')`	Invoke a System Command

GNU Octave for Python/NumPy users

Help

Searching available documentation

Using interactively

Operators

Arithmetic operators

Relational operators

Logical operators

root and logarithm

Round off

Mathematical constants

Missing values; IEEE-754 floating point status flags

Complex numbers

Trigonometry

Generate random numbers

Vectors

Sequences

Concatenation (vectors)

Repeating

Miss those elements out

Maximum and minimum

Vector multiplication

Matrices

Concatenation (matrices); rbind and cbind

Array creation

Reshape and flatten matrices

Shared data (slicing)

Indexing and accessing elements (Python: slicing)

Assignment

Transpose and inverse

Sum

Sorting

Maximum and minimum

Matrix manipulation

Matrix shape and size

Matrix - and elementwise - multiplication

Find; conditional indexing

Multi-way arrays

File input and output

Plotting

Basic x-y plots

Axes and titles

Log plots

Filled plots and bar plots

Functions

Polar plots

Histogram plots

3d data

Contour and image plots

Perspective plots of surfaces over the x-y plane

Scatter (cloud) plots

Save plot to a graphics file

Data analysis

Set membership operators

Statistics

Interpolation and regression

Non-linear methods

Polynomials, root finding

Differential equations

Fourier analysis

Symbolic algebra, calculus

Programming

Loops

Conditionals

Debugging

Working directory and OS