Hello! Today I would like to tell you about scientific computing using the language Python and SciPy modules… In many scientific calculations in the field of mathematics or physics, it becomes necessary to find certain dependencies. For example: coordinates of the ball in time t for a given function, acceleration of a body, statistical values from a sample, and so on… Of course, the calculation of such values is provided in many languages, but still Python due to the clarity of the syntax, it allows you to find them without thinking about the complexity of the implementation. In addition, the language community is developing similar libraries that allow us to use ready-made constants and formulas. This feature is implemented in the library SciPy.
SciPy Is a scientific computing library that uses NumPy .
Abbreviation SciPy means Scientific Python.
Like NumPy, SciPy is open source so we can use it freely. Note that it is based on the library NumPy.
Why use SciPy?
If SciPy использует NumPy под капотом, почему мы не можем просто использовать NumPy?.
The fact is that SciPy содержит функции, которые часто используются в NumPy and Data Science.
На каком языке написан SciPy?
SciPy mostly written in Python, но некоторые сегменты написаны на C.
Where is the SciPy codebase located?
Source SciPy is in this scipy repository
Установка SciPy.
SciPy comes with the package Anaconda. Если же его нет, но установлены Python 3.8 и PIP в системе, то установка SciPy very simple. First, let’s create a virtual environment with venv for Python 3.6 и выше. И в терминале
we introduce:
# для Windows
>>> python3 -m venv My_Venv
>>> cd My_Venv/Scripts
>>> activate
# Мы должны увидеть следующее
(My_Venv)>>>
# Что обозначает активированную среду/папку
# перейдем к установке библиотеки
(My_Venv)>>>pip install scipy
Импорт констант SciPy.
from scipy import constants
'''
выведем список содержащихся в нем констант:
Avogadro
Boltzmann
Btu
Btu_IT
Btu_th
ConstantWarning
G
Julian_year
N_A
Planck
R
Rydberg
Stefan_Boltzmann
'''
# используя одну из констант, теперь вычислим сколько кубометров в одном литре
print(constants.liter)
# вывод
0.001
Thus using SciPy в научных вычислениях можно существенно сократить объем кода и сфокусироваться на решении самой задачи.
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