fxy 0.6.0

Convenience imports and scientific functions.

Imports and command fx with parameters to import libraries often used in research to emulate CAS software, or LAB software.

Installation

• pip install fxy to get the import shortcuts.

Simple Usage

$ fx --calc starts Python with CALC imports (to emulate scientific calculator) (or from fxy.calc import *)

$ fx --cas starts Python with CAS (Computer Algebra System) imports (to emulate Maple, Matematica,..) (or from fxy.cas import *)

$ fx --lab starts Python with LAB (Linear AlgeBra system) imports (to emulate MATLAB, R,…) (or from fxy.lab import *)

Introduction

The people coming from use of CAS tools like Maple, Mathematica or computing LAB languages Matlab and R may find that Python requires quite a few imports just to do equivalent computing.

This package fxy is a shorthand to do the imports packages to approximate these two domains (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.

Usage

The package defines the fx command, if you just want Python with something, run:

• fx (e.g., fx -ip) for quick CALC - Basic calculator

• fx -x (e.g., fx -ipx) for basic CAS software (“Numeric”) emulation

• fx -y (e.g., fx -ipy) for LAB software (“Symbolic”) emulation

In command line

• $ fx -i – to use IPython + explicit imports.

• $ fx -p – to import plotting.

CALC

>>> from fxy.calc import *
>>> pi
<pi: 3.14159~>

>>> from fxy.plot import *
>>> plt.plot([1, 2, 3, 4])
>>> plt.ylabel('some numbers')
>>> plt.show()

CAS

>>> 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)

LAB

>>> 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]]

Suggestions

If you use some initialization commonly, we suggest adding ~/.zshrc, something like, for example:

alias f=". ~/.venv/bin/activate && fx -if"

Or, pass params, and alias:

function f() {
    . ~/.venv/bin/activate
    fx "$@"
}

alias fx="f -ipx"  # for CAS with plotting
alias fy="f -ipy"  # for LAB with plotting

This way, running something like f makes a project folder and starts Python environment with import sets often used.