Symbolic mathematics language
nbviewer.jupyter.org
. These are the same notebooks found in the TutorialNotebooks directory
in this repositoy. But the rendering at nbviewer
is better.symata_test
, not test
)TAB
completion? Topic
(with completion)h"word"
regular expression searchHelp()
and Help(topic)
a language for symbolic computations and mathematics, where, for the most part, "mathematics" means what it typically does for a scientist or engineer.
a language based mostly on expressions, on "evaluating" and rewriting them, like Wolfram, Maple, or Maxima. It is neither a language, nor an extension of a language, that is mostly procedural, or designed around data types and functions, or a hierarchy of classes, etc., like C or Python or Java. Nor is it language like Sage; that is, one meant to provide a unifying interface to a number of mathematics languages with various programming models.
meant to be useful to people who do not like to program computers, as well as those who do. The former includes people who prefer not to think about classes, methods, objects, dispatch, stack traces, etc.
Symata is largely modeled on the pattern matching and evaluation sequence of Mathematica. Evaluation, pattern matching, flow control, etc. are written in Julia. Much of the mathematics and symbolic manipulation is achieved by wrapping SymPy. There are more than 600 functions implemented, including integration, transformation of special functions, expression manipulation, writing and reading expressions to and from a file etc.
Symata is a registered module. It can be installed like this
(v0.7) pkg> add Symata
julia> using Symata
symata> Help() # type '=' alone on a line to enter symata mode
Symata
can be installed on Linux, OSX, and Windows.
Symata
depends on the PyCall
package and
the python SymPy module. You can install SymPy
via pip install sympy
. Symata is compatible with SymPy v1.0 and v1.2 (and probably v1.1).
Alternatively, you may install SymPy via Conda.jl
.
When you load Symata
with using Symata
, sympy
is installed automatically via PyCall
, which uses Conda
. However, to do this, PyCall
must be configured to not use you system version of python
.
If you do not have PyCall
installed, do this
julia> ENV["PYTHON"]=""
julia> Pkg.add("PyCall")
If you do have PyCall
installed, but it is configured to use your system python
, reconfigure
it like this.
julia> ENV["PYTHON"]=""
julia> Pkg.build("PyCall")
If you use linux, you may have your distribution's sympy
package installed and it may be
out of date. In this case, try the procedure above, and/or try removing your distribution's sympy
package.
SymPy
, or sympy
, here refers to the python SymPy distribution
(sometimes called sympy), not the Julia package SymPy
. Symata
does not require the Julia package
SymPy.jl, which has a different goal.
Symata requires mpmath
package for python. This
should be automatically installed when installing sympy
via
PyCall
as described above. This also works on OSX.
However, if you use pip
, you should just be able to run pip install mpmath
.
See below for instructions on precompiling Symata to get more-or-less instant start up and many precompiled function calls.
Three environments for running Symata
are supported: the Julia
REPL, Jupyter
, and a dumb terminal.
A Symata
mode is added to the Julia
REPL. Enter the mode by typing =
as the first character. Exit
the mode by typing backspace
as the first character.
julia> using Symata
symata 1> # after entering `=`
Under some circumstances, e.g. when using PackageCompiler
, the Symata
repl is not initialized after the module is loaded.
You can initialize it with the exported Julia command run_repl
. After this, the repl is entered with the =
key.
An executable ./scripts/symata
is included. It is a (UNIX
sh) shell script that just starts julia, loads the module, and enters Symata
mode.
There is also a script ./scripts/symatap
for starting from an image
with Symata precompiled. (See below.)
Switch between Julia
and Symata
modes by typing =
, or backspace, as the first character on a line.
You can do tab completion to see a list of functions and symbols.
In [1]: using Symata
In [2]: Expand((a+b)^2)
Out[2]: a^2 + 2a*b + b^2
In [3]: Julia() # return to Julia mode
In Jupyter
, the Symata
expressions In(n)
and Out(n)
reevaluate the input and output cells. TAB completion
works in Jupyter
. To see a list of all possible completions, type *[TAB]
.
If you do using Symata
in a dumb terminal, the Symata
prompt should appear automatically.
From the julia prompt, type isympy()
to enter the sympy shell.
You can precompile Symata. It will load very quickly and be generally much more responsive.
The script ./scripts/gen_compile_symata.sh
writes a Julia image.
The shell script ./scripts/symatap
runs Julia with this image and immediately
enters the Symata repl. See the contents of these files if you can't run shell scripts on
your platform.
You can install a Jupyter kernel using the precompiled image.
You must not insert any whitespace between -J
and the path to the image.
julia> using IJulia
julia> installkernel("Symata", "-J/home/username/path/to/symataimage.so")
Run the test suite from the symata
prompt with Tests()
.
This runs tests in the symata_test directory
Pkg.test("Symata")
runs the same test suite from Julia
and
some Julia-level unit tests, as well.