small doku fix

Author: OrtnerMichael

docs/_pages/0_documentation.rst

@@ -1,7 +1,7 @@
 .. _docu:
 
 ******************************
-Documentation v2.0.1b
+Documentation v2.3.0b
 ******************************
 
 The idea behind magpylib is to provide a simple and easy-to-use interface for computing the magnetic field of magnets, currents and moments. The computations are based on (semi-)analytical solutions found in the literature, discussed in the :ref:`physComp` section.

docs/_pages/4_contguide.rst

@@ -1,6 +1,6 @@
-**********************
-Credits & Contribution
-**********************
+*********************************
+Credits, Contribution & Citation
+*********************************
 
 
 
@@ -18,9 +18,21 @@ Maintainers & Contact
 
 
 
+Credits
+########
+
+We want to thank a lot of ppl who have helped to realize and advance this project over the years. The project was supported by CTR-AG and is now supported by the `Silicon Austria Labs <https://silicon-austria-labs.com/>`_ public research center.
+
+
+
 Contributions
 #############
 
-We want to thank a lot of ppl who have helped to realize and advance this project.
+We welcome any feedback (Bug reports, feature requests, comments, really anything 😃) via email `[email protected] <mailto:[email protected]>`_ or through `gitHub <https://github.com/magpylib/magpylib/issues>`_ channels.
+
+
+
+Citation
+########
 
-We welcome any feedback (Bug reports, feature requests, comments, really anything 😃) via email `[email protected] <mailto:[email protected]>`_ or through `gitHub <https://github.com/magpylib/magpylib/issues>`_ channels.
+A fundamental paper on Magpylib is being published in SoftwareX the moment. Details coming soon.

docs/index.rst

@@ -3,17 +3,23 @@
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
-What is magpylib ?
+What is Magpylib ?
 ##################
 
 - Free Python package for calculating magnetic fields of magnets, currents and moments (sources).
 - Provides convenient methods to create, geometrically manipulate, group and visualize assemblies of sources.
-- The magnetic fields are determined from underlying analytical solutions which results in fast computation times and requires little computation power.
+- The magnetic fields are determined from underlying analytical solutions which results in fast computation times and requires little computation power, memory and background knowledge.
 - For high performance computation (e.g. for multivariate parameter space analysis) all functions are also available in vectorized form.
 
 .. image:: _static/images/index/sourceFundamentals.png
    :align: center
 
+When can you use Magpylib ?
+###########################
+
+The analytical solutions are only valid if there is little or no material response. This means that whenever there is a lot of demagnetization in permanent magnets or soft magnetic materials like magnetic shields or transformer cores, these computations cannot be used. Magpylib is at its best dealing with air-coils and permanent magnet assemblies (Ferrite, NdFeB, SmCo or similar materials).
+
+
 Quickstart
 ##########
 

docs/pyplots/examples/01_SimpleCollection.py

@@ -1,35 +1,39 @@
-# imports
 import numpy as np
 import matplotlib.pyplot as plt
-import magpylib as magpy
-
-# create figure
-fig = plt.figure(figsize=(8,4))
-ax1 = fig.add_subplot(121, projection='3d')  # this is a 3D-plotting-axis
-ax2 = fig.add_subplot(122)                   # this is a 2D-plotting-axis
+from magpylib.source.magnet import Box,Cylinder
+from magpylib import Collection, displaySystem
 
 # create magnets
-s1 = magpy.source.magnet.Box(mag=[0,0,600],dim=[3,3,3],pos=[-4,0,3])
-s2 = magpy.source.magnet.Cylinder(mag=[0,0,500], dim=[3,5])
-
-# manipulate magnets
-s1.rotate(45,[0,1,0],anchor=[0,0,0])
-s2.move([5,0,-4])
+s1 = Box(mag=(0,0,600), dim=(3,3,3), pos=(-4,0,3))
+s2 = Cylinder(mag=(0,0,500), dim=(3,5))
 
 # create collection
-c = magpy.Collection(s1,s2)
+c = Collection(s1,s2)
 
-# display system geometry on ax1
-magpy.displaySystem(c,subplotAx=ax1,suppress=True)
+# manipulate magnets individually
+s1.rotate(45,(0,1,0), anchor=(0,0,0))
+s2.move((5,0,-4))
+
+# manipulate collection
+c.move((-2,0,0))
 
 # calculate B-field on a grid
-xs = np.linspace(-10,10,29)
-zs = np.linspace(-10,10,29)
-Bs = np.array([[c.getB([x,0,z]) for x in xs] for z in zs])
+xs = np.linspace(-10,10,33)
+zs = np.linspace(-10,10,44)
+POS = np.array([(x,0,z) for z in zs for x in xs])
+Bs = c.getB(POS).reshape(44,33,3)     #<--VECTORIZED
+
+# create figure
+fig = plt.figure(figsize=(9,5))
+ax1 = fig.add_subplot(121, projection='3d')  # 3D-axis
+ax2 = fig.add_subplot(122)                   # 2D-axis
+
+# display system geometry on ax1
+displaySystem(c, subplotAx=ax1, suppress=True)
 
 # display field in xz-plane using matplotlib
 X,Z = np.meshgrid(xs,zs)
 U,V = Bs[:,:,0], Bs[:,:,2]
-ax2.streamplot(X, Z, U, V, color=np.log(U**2+V**2),density=2)
+ax2.streamplot(X, Z, U, V, color=np.log(U**2+V**2))
 
 plt.show()