Imports and command fx
with parameters to import libraries often used in research to emulate CAS software, or LAB software.
- People coming from
R
, love that you can start quickly using it as a CALCulator, - People coming from use of CAS tools like
Maple
,Mathematica
haveisympy
, that is narrowly focused, - People coming from computing LAB languages
Matlab
andR
may find thatPython
requires quite a few imports just to do equivalent computing in Python.
This package fxy
is a shorthand to do the imports packages to approximate these domains (CALC, CAS, and LAB) you've got a command fx
, that starts Python with needed packages pre-imported: so, you can start using Python like a calculator right away.
pip install fxy
to get the import shortcuts.
`` $ fx ``
(pass, -i
for IPython)
from fxy.calc import *
for quick CALC - basicmpmath
calculatorfrom fxy.cas import *
for basic CAS software ("Symbolic") emulationfrom fxy.lab import *
for LAB software ("Numeric") emulationfrom fxy.plot import *
for plotting imports.
The package defines the fx command, if you just want Python with something, run:
$ fx --calc
starts Python with CALC imports (basicmpmath
calculator)$ fx --cas
(or-x
) starts Python with CAS (Computer Algebra System) imports (to emulate Maple, Matematica,..)$ fx --lab
(or-y
) starts Python with LAB (Linear AlgeBra system) imports (to emulate MATLAB, R,...)$ fx --plot
(or-p
) for plotting imports
So, for example, if you want LAB imports with plotting and in IPython, then you'd:
$ fx -ip --lab
The following are usage examples.
>>> from fxy.calc import * >>> pi <pi: 3.14159~> >>> mp.dps = 250 >>> print(pi) >>> from fxy.plot import * >>> plt.plot([1, 2, 3, 4]) >>> plt.ylabel('some numbers') >>> plt.show()
>>> from fxy.cas import * >>> f = x**4 - 4*x**3 + 4*x**2 - 2*x + 3 >>> f.subs([(x, 2), (y, 4), (z, 0)]) -1 >>> plot(f) >>> plot3d(x**2-y**2)
>>> from fxy.lab import * >>> df = pandas.DataFrame({'x': numpy.arange(10), 'y': np.random.random(10)}) >>> df.sum() x 45.000000 y 4.196558 dtype: float64 >>> X = [[0], [1], [2], [3]] >>> y = [0, 0, 1, 1] >>> neigh = sklearn.neighbors.KNeighborsClassifier(n_neighbors=3) >>> neigh.fit(X, y) >>> print(neigh.predict([[1.1]])) [0] >>> print(neigh.predict_proba([[0.9]])) [[0.66666667 0.33333333]]
If you envy R
users being able to start their 'calculator' with just one key, add something like the below to your ~/.zshrc
:
function f() { . ~/.venv/bin/activate fx "$@" } function F() { f -ix # (your custom pre-configuration you often use) }
Aliasing fx
as f
command as simplest generic, and commonly used specific as F
command makes it possible to:
- Use
f
to start Python with justmpmath
for fastest scientific calculations withoutIPython
. - Use
F
to start Python with some specific other pre-configuration that you often use (e.g.,f -ix
emulatesisympy
).