Convenience imports and scientific functions.
Project description
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.
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