%global _empty_manifest_terminate_build 0
Name:		python-MagnetiCalc
Version:	1.15.2
Release:	1
Summary:	MagnetiCalc calculates the magnetic flux density, vector potential, energy, self-inductance and magnetic dipole moment of arbitrary coils. Inside an OpenGL-accelerated GUI, the static magnetic flux density (B-field) or the magnetic vector potential (A-field) is displayed in interactive 3D, using multiple metrics for highlighting the field properties.
License:	ISC License
URL:		https://github.com/shredEngineer/MagnetiCalc
Source0:	https://mirrors.aliyun.com/pypi/web/packages/b9/97/e621696b60b1356a465f97b3507fc2e1997767835d15da653d00da695eb6/MagnetiCalc-1.15.2.tar.gz
BuildArch:	noarch

Requires:	python3-numpy
Requires:	python3-numba
Requires:	python3-scipy
Requires:	python3-PyQt5
Requires:	python3-vispy
Requires:	python3-qtawesome
Requires:	python3-sty
Requires:	python3-si-prefix
Requires:	python3-h5py

%description
[![PyPI version](https://img.shields.io/pypi/v/MagnetiCalc?label=PyPI)](https://pypi.org/project/MagnetiCalc/)
[![License: ISC](https://img.shields.io/badge/License-ISC-blue.svg)](https://opensource.org/licenses/ISC)
[![Donate](https://img.shields.io/badge/Donate-PayPal-green.svg)](https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=TN6YTPVX36YHA&source=url)
[![Documentation](https://img.shields.io/badge/Documentation-API-orange)](https://shredengineer.github.io/MagnetiCalc/)
🍀 [Always looking for beta testers!](#contribute)
**What does MagnetiCalc do?**
MagnetiCalc calculates the static magnetic flux density, vector potential, energy, self-inductance
and magnetic dipole moment of arbitrary coils. Inside an OpenGL-accelerated GUI, the magnetic flux density
(<img src="https://render.githubusercontent.com/render/math?math=\mathbf{B}" alt="B">-field,
in units of <i>Tesla</i>)
or the magnetic vector potential
(<img src="https://render.githubusercontent.com/render/math?math=\mathbf{A}" alt="A">-field,
in units of <i>Tesla-meter</i>)
is displayed in interactive 3D, using multiple metrics for highlighting the field properties.
<i>Experimental feature:</i> To calculate the energy and self-inductance of permeable (i.e. ferrous) materials,
different core media can be modeled as regions of variable relative permeability;
however, core saturation is currently not modeled, resulting in excessive flux density values.
**Who needs MagnetiCalc?**
MagnetiCalc does its job for hobbyists, students, engineers and researchers of magnetic phenomena.
I designed MagnetiCalc from scratch, because I didn't want to mess around
with expensive and/or overly complex simulation software
whenever I needed to solve a magnetostatic problem.
**How does it work?**
The <img src="https://render.githubusercontent.com/render/math?math=\mathbf{B}" alt="B">-field calculation
is implemented using the Biot-Savart law [**1**], employing multiprocessing techniques;
MagnetiCalc uses just-in-time compilation ([JIT](https://numba.pydata.org/))
and, if available, GPU-acceleration ([CUDA](https://numba.pydata.org/numba-doc/dev/cuda/overview.html))
to achieve high-performance calculations.
Additionally, the use of easily constrainable "sampling volumes" allows for selective calculation over
grids of arbitrary shape and arbitrary relative permeabilities
<img src="https://render.githubusercontent.com/render/math?math=\mu_r(\mathbf{x})" alt="µ_r(x)">
(<i>experimental</i>).
The shape of any wire is modeled as a 3D piecewise linear curve.
Arbitrary loops of wire are sliced into differential current elements
(<img src="https://render.githubusercontent.com/render/math?math=\mathbf{\ell}" alt="l">),
each of which contributes to the total resulting field
(<img src="https://render.githubusercontent.com/render/math?math=\mathbf{A}" alt="A">,
<img src="https://render.githubusercontent.com/render/math?math=\mathbf{B}" alt="B">)
at some fixed 3D grid point (<img src="https://render.githubusercontent.com/render/math?math=\mathbf{x}" alt="x">),
summing over the positions of all current elements
(<img src="https://render.githubusercontent.com/render/math?math=\mathbf{x^'}" alt="x'">):
<img src="https://render.githubusercontent.com/render/math?math=\mathbf{A}(\mathbf{x})=I \cdot \frac{\mu_0}{4 \pi} \cdot \displaystyle \sum_\mathbf{x^'} \mu_r(\mathbf{x}) \cdot \frac{\mathbf{\ell}(\mathbf{x^')}}{\mid \mathbf{x} - \mathbf{x^'} \mid}"><br>
<img src="https://render.githubusercontent.com/render/math?math=\mathbf{B}(\mathbf{x})=I \cdot \frac{\mu_0}{4 \pi} \cdot \displaystyle \sum_\mathbf{x^'} \mu_r(\mathbf{x}) \cdot \frac{\mathbf{\ell}(\mathbf{x^'}) \times (\mathbf{x} - \mathbf{x^'})}{\mid \mathbf{x} - \mathbf{x^'} \mid}"><br>
At each grid point, the field magnitude (or field angle in some plane) is displayed
using colored arrows and/or dots;
field color and alpha transparency are individually mapped using one of the various
[available metrics](#appendix-metrics).
The coil's energy <img src="https://render.githubusercontent.com/render/math?math=E" alt="E"> [**2**]
and self-inductance <img src="https://render.githubusercontent.com/render/math?math=L" alt="L"> [**3**]
are calculated by summing the squared
<img src="https://render.githubusercontent.com/render/math?math=\mathbf{B}" alt="B">-field
over the entire sampling volume;
ensure that the sampling volume encloses a large, non-singular portion of the field:
<img src="https://render.githubusercontent.com/render/math?math=E=\frac{1}{\mu_0} \cdot \displaystyle \sum_\mathbf{x} \frac{\mathbf{B}(\mathbf{x}) \cdot \mathbf{B}(\mathbf{x})}{\mu_r(\mathbf{x})}"><br>
<img src="https://render.githubusercontent.com/render/math?math=L=\frac{1}{\I^2} \cdot E"><br>
Additionally, the scalar magnetic dipole moment
<img src="https://render.githubusercontent.com/render/math?math=m" alt="m"> [**4**]
is calculated by summing over all current elements:
<img src="https://render.githubusercontent.com/render/math?math=m=\Bigl| I \cdot \frac{1}{2} \cdot \displaystyle \sum_\mathbf{x^'} \mathbf{x^'} \times \mathbf{\ell}(\mathbf{x^'}) \Bigr|"><br>
***References***
[**1**]: Jackson, Klassische Elektrodynamik, 5. Auflage, S. 204, (5.4).<br>
[**2**]: Kraus, Electromagnetics, 4th Edition, p. 269, 6-9-1.<br>
[**3**]: Jackson, Klassische Elektrodynamik, 5. Auflage, S. 252, (5.157).<br>
[**4**]: Jackson, Klassische Elektrodynamik, 5. Auflage, S. 216, (5.54).

%package -n python3-MagnetiCalc
Summary:	MagnetiCalc calculates the magnetic flux density, vector potential, energy, self-inductance and magnetic dipole moment of arbitrary coils. Inside an OpenGL-accelerated GUI, the static magnetic flux density (B-field) or the magnetic vector potential (A-field) is displayed in interactive 3D, using multiple metrics for highlighting the field properties.
Provides:	python-MagnetiCalc
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-MagnetiCalc
[![PyPI version](https://img.shields.io/pypi/v/MagnetiCalc?label=PyPI)](https://pypi.org/project/MagnetiCalc/)
[![License: ISC](https://img.shields.io/badge/License-ISC-blue.svg)](https://opensource.org/licenses/ISC)
[![Donate](https://img.shields.io/badge/Donate-PayPal-green.svg)](https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=TN6YTPVX36YHA&source=url)
[![Documentation](https://img.shields.io/badge/Documentation-API-orange)](https://shredengineer.github.io/MagnetiCalc/)
🍀 [Always looking for beta testers!](#contribute)
**What does MagnetiCalc do?**
MagnetiCalc calculates the static magnetic flux density, vector potential, energy, self-inductance
and magnetic dipole moment of arbitrary coils. Inside an OpenGL-accelerated GUI, the magnetic flux density
(<img src="https://render.githubusercontent.com/render/math?math=\mathbf{B}" alt="B">-field,
in units of <i>Tesla</i>)
or the magnetic vector potential
(<img src="https://render.githubusercontent.com/render/math?math=\mathbf{A}" alt="A">-field,
in units of <i>Tesla-meter</i>)
is displayed in interactive 3D, using multiple metrics for highlighting the field properties.
<i>Experimental feature:</i> To calculate the energy and self-inductance of permeable (i.e. ferrous) materials,
different core media can be modeled as regions of variable relative permeability;
however, core saturation is currently not modeled, resulting in excessive flux density values.
**Who needs MagnetiCalc?**
MagnetiCalc does its job for hobbyists, students, engineers and researchers of magnetic phenomena.
I designed MagnetiCalc from scratch, because I didn't want to mess around
with expensive and/or overly complex simulation software
whenever I needed to solve a magnetostatic problem.
**How does it work?**
The <img src="https://render.githubusercontent.com/render/math?math=\mathbf{B}" alt="B">-field calculation
is implemented using the Biot-Savart law [**1**], employing multiprocessing techniques;
MagnetiCalc uses just-in-time compilation ([JIT](https://numba.pydata.org/))
and, if available, GPU-acceleration ([CUDA](https://numba.pydata.org/numba-doc/dev/cuda/overview.html))
to achieve high-performance calculations.
Additionally, the use of easily constrainable "sampling volumes" allows for selective calculation over
grids of arbitrary shape and arbitrary relative permeabilities
<img src="https://render.githubusercontent.com/render/math?math=\mu_r(\mathbf{x})" alt="µ_r(x)">
(<i>experimental</i>).
The shape of any wire is modeled as a 3D piecewise linear curve.
Arbitrary loops of wire are sliced into differential current elements
(<img src="https://render.githubusercontent.com/render/math?math=\mathbf{\ell}" alt="l">),
each of which contributes to the total resulting field
(<img src="https://render.githubusercontent.com/render/math?math=\mathbf{A}" alt="A">,
<img src="https://render.githubusercontent.com/render/math?math=\mathbf{B}" alt="B">)
at some fixed 3D grid point (<img src="https://render.githubusercontent.com/render/math?math=\mathbf{x}" alt="x">),
summing over the positions of all current elements
(<img src="https://render.githubusercontent.com/render/math?math=\mathbf{x^'}" alt="x'">):
<img src="https://render.githubusercontent.com/render/math?math=\mathbf{A}(\mathbf{x})=I \cdot \frac{\mu_0}{4 \pi} \cdot \displaystyle \sum_\mathbf{x^'} \mu_r(\mathbf{x}) \cdot \frac{\mathbf{\ell}(\mathbf{x^')}}{\mid \mathbf{x} - \mathbf{x^'} \mid}"><br>
<img src="https://render.githubusercontent.com/render/math?math=\mathbf{B}(\mathbf{x})=I \cdot \frac{\mu_0}{4 \pi} \cdot \displaystyle \sum_\mathbf{x^'} \mu_r(\mathbf{x}) \cdot \frac{\mathbf{\ell}(\mathbf{x^'}) \times (\mathbf{x} - \mathbf{x^'})}{\mid \mathbf{x} - \mathbf{x^'} \mid}"><br>
At each grid point, the field magnitude (or field angle in some plane) is displayed
using colored arrows and/or dots;
field color and alpha transparency are individually mapped using one of the various
[available metrics](#appendix-metrics).
The coil's energy <img src="https://render.githubusercontent.com/render/math?math=E" alt="E"> [**2**]
and self-inductance <img src="https://render.githubusercontent.com/render/math?math=L" alt="L"> [**3**]
are calculated by summing the squared
<img src="https://render.githubusercontent.com/render/math?math=\mathbf{B}" alt="B">-field
over the entire sampling volume;
ensure that the sampling volume encloses a large, non-singular portion of the field:
<img src="https://render.githubusercontent.com/render/math?math=E=\frac{1}{\mu_0} \cdot \displaystyle \sum_\mathbf{x} \frac{\mathbf{B}(\mathbf{x}) \cdot \mathbf{B}(\mathbf{x})}{\mu_r(\mathbf{x})}"><br>
<img src="https://render.githubusercontent.com/render/math?math=L=\frac{1}{\I^2} \cdot E"><br>
Additionally, the scalar magnetic dipole moment
<img src="https://render.githubusercontent.com/render/math?math=m" alt="m"> [**4**]
is calculated by summing over all current elements:
<img src="https://render.githubusercontent.com/render/math?math=m=\Bigl| I \cdot \frac{1}{2} \cdot \displaystyle \sum_\mathbf{x^'} \mathbf{x^'} \times \mathbf{\ell}(\mathbf{x^'}) \Bigr|"><br>
***References***
[**1**]: Jackson, Klassische Elektrodynamik, 5. Auflage, S. 204, (5.4).<br>
[**2**]: Kraus, Electromagnetics, 4th Edition, p. 269, 6-9-1.<br>
[**3**]: Jackson, Klassische Elektrodynamik, 5. Auflage, S. 252, (5.157).<br>
[**4**]: Jackson, Klassische Elektrodynamik, 5. Auflage, S. 216, (5.54).

%package help
Summary:	Development documents and examples for MagnetiCalc
Provides:	python3-MagnetiCalc-doc
%description help
[![PyPI version](https://img.shields.io/pypi/v/MagnetiCalc?label=PyPI)](https://pypi.org/project/MagnetiCalc/)
[![License: ISC](https://img.shields.io/badge/License-ISC-blue.svg)](https://opensource.org/licenses/ISC)
[![Donate](https://img.shields.io/badge/Donate-PayPal-green.svg)](https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=TN6YTPVX36YHA&source=url)
[![Documentation](https://img.shields.io/badge/Documentation-API-orange)](https://shredengineer.github.io/MagnetiCalc/)
🍀 [Always looking for beta testers!](#contribute)
**What does MagnetiCalc do?**
MagnetiCalc calculates the static magnetic flux density, vector potential, energy, self-inductance
and magnetic dipole moment of arbitrary coils. Inside an OpenGL-accelerated GUI, the magnetic flux density
(<img src="https://render.githubusercontent.com/render/math?math=\mathbf{B}" alt="B">-field,
in units of <i>Tesla</i>)
or the magnetic vector potential
(<img src="https://render.githubusercontent.com/render/math?math=\mathbf{A}" alt="A">-field,
in units of <i>Tesla-meter</i>)
is displayed in interactive 3D, using multiple metrics for highlighting the field properties.
<i>Experimental feature:</i> To calculate the energy and self-inductance of permeable (i.e. ferrous) materials,
different core media can be modeled as regions of variable relative permeability;
however, core saturation is currently not modeled, resulting in excessive flux density values.
**Who needs MagnetiCalc?**
MagnetiCalc does its job for hobbyists, students, engineers and researchers of magnetic phenomena.
I designed MagnetiCalc from scratch, because I didn't want to mess around
with expensive and/or overly complex simulation software
whenever I needed to solve a magnetostatic problem.
**How does it work?**
The <img src="https://render.githubusercontent.com/render/math?math=\mathbf{B}" alt="B">-field calculation
is implemented using the Biot-Savart law [**1**], employing multiprocessing techniques;
MagnetiCalc uses just-in-time compilation ([JIT](https://numba.pydata.org/))
and, if available, GPU-acceleration ([CUDA](https://numba.pydata.org/numba-doc/dev/cuda/overview.html))
to achieve high-performance calculations.
Additionally, the use of easily constrainable "sampling volumes" allows for selective calculation over
grids of arbitrary shape and arbitrary relative permeabilities
<img src="https://render.githubusercontent.com/render/math?math=\mu_r(\mathbf{x})" alt="µ_r(x)">
(<i>experimental</i>).
The shape of any wire is modeled as a 3D piecewise linear curve.
Arbitrary loops of wire are sliced into differential current elements
(<img src="https://render.githubusercontent.com/render/math?math=\mathbf{\ell}" alt="l">),
each of which contributes to the total resulting field
(<img src="https://render.githubusercontent.com/render/math?math=\mathbf{A}" alt="A">,
<img src="https://render.githubusercontent.com/render/math?math=\mathbf{B}" alt="B">)
at some fixed 3D grid point (<img src="https://render.githubusercontent.com/render/math?math=\mathbf{x}" alt="x">),
summing over the positions of all current elements
(<img src="https://render.githubusercontent.com/render/math?math=\mathbf{x^'}" alt="x'">):
<img src="https://render.githubusercontent.com/render/math?math=\mathbf{A}(\mathbf{x})=I \cdot \frac{\mu_0}{4 \pi} \cdot \displaystyle \sum_\mathbf{x^'} \mu_r(\mathbf{x}) \cdot \frac{\mathbf{\ell}(\mathbf{x^')}}{\mid \mathbf{x} - \mathbf{x^'} \mid}"><br>
<img src="https://render.githubusercontent.com/render/math?math=\mathbf{B}(\mathbf{x})=I \cdot \frac{\mu_0}{4 \pi} \cdot \displaystyle \sum_\mathbf{x^'} \mu_r(\mathbf{x}) \cdot \frac{\mathbf{\ell}(\mathbf{x^'}) \times (\mathbf{x} - \mathbf{x^'})}{\mid \mathbf{x} - \mathbf{x^'} \mid}"><br>
At each grid point, the field magnitude (or field angle in some plane) is displayed
using colored arrows and/or dots;
field color and alpha transparency are individually mapped using one of the various
[available metrics](#appendix-metrics).
The coil's energy <img src="https://render.githubusercontent.com/render/math?math=E" alt="E"> [**2**]
and self-inductance <img src="https://render.githubusercontent.com/render/math?math=L" alt="L"> [**3**]
are calculated by summing the squared
<img src="https://render.githubusercontent.com/render/math?math=\mathbf{B}" alt="B">-field
over the entire sampling volume;
ensure that the sampling volume encloses a large, non-singular portion of the field:
<img src="https://render.githubusercontent.com/render/math?math=E=\frac{1}{\mu_0} \cdot \displaystyle \sum_\mathbf{x} \frac{\mathbf{B}(\mathbf{x}) \cdot \mathbf{B}(\mathbf{x})}{\mu_r(\mathbf{x})}"><br>
<img src="https://render.githubusercontent.com/render/math?math=L=\frac{1}{\I^2} \cdot E"><br>
Additionally, the scalar magnetic dipole moment
<img src="https://render.githubusercontent.com/render/math?math=m" alt="m"> [**4**]
is calculated by summing over all current elements:
<img src="https://render.githubusercontent.com/render/math?math=m=\Bigl| I \cdot \frac{1}{2} \cdot \displaystyle \sum_\mathbf{x^'} \mathbf{x^'} \times \mathbf{\ell}(\mathbf{x^'}) \Bigr|"><br>
***References***
[**1**]: Jackson, Klassische Elektrodynamik, 5. Auflage, S. 204, (5.4).<br>
[**2**]: Kraus, Electromagnetics, 4th Edition, p. 269, 6-9-1.<br>
[**3**]: Jackson, Klassische Elektrodynamik, 5. Auflage, S. 252, (5.157).<br>
[**4**]: Jackson, Klassische Elektrodynamik, 5. Auflage, S. 216, (5.54).

%prep
%autosetup -n MagnetiCalc-1.15.2

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-MagnetiCalc -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Fri Jun 09 2023 Python_Bot <Python_Bot@openeuler.org> - 1.15.2-1
- Package Spec generated