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.. |isympy| replace:: isympy
Imports and command fxy
with parameters to import libraries often used in research to emulate CAS software, or LAB software.
R
, love that you can start quickly using it as a CALCulator,Maple
, Mathematica
have isympy
, that is narrowly focused,Matlab
and R
may find that Python
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 fxy
, 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.$ fxy
(pass, -i
for IPython)
from fxy.calc import *
for quick CALC - basic mpmath
calculator, and eday
for timefrom 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 fxy
command, if you just want Python with something, run:
$ fxy --calc
starts Python with CALC imports (basic mpmath
calculator)$ fxy --cas
(or -x
) starts Python with CAS (Computer Algebra System) imports (to emulate Maple, Matematica,..)$ fxy --lab
(or -y
) starts Python with LAB (Linear AlgeBra system) imports (to emulate MATLAB, R,...)$ fxy --plot
(or -p
) for plotting importsSo, for example, if you want LAB imports with plotting and in IPython, then you'd:
$ fxy -ip --lab
You can also run the equivalent of --calc
environment, that imports mpmath
and eday
, like this:
python -m fxy "pi**2"
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
:
::
# Basic Calculaor
function f() {
. ~/.venv/bin/activate
fxy "$@"
}
# Computer Algebra System
function F() {
. ~/.venv/bin/activate
fxy --qt --cas
}
Aliasing fxy
as f
command as simplest generic, and commonly used specific as F
command makes it possible to:
f
to start Python with just mpmath
for fastest scientific calculations without IPython
.F
to start Python with some specific other pre-configuration that you often use (e.g., f -ix
emulates isympy
)... _isympy: https://linux.die.net/man/1/isympy
FAQs
Convenience imports and scientific functions.
We found that fxy demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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