Updated documentation including github.io documentation

README.md

@@ -6,13 +6,13 @@
   <br>
 </div>
 
-# MagTense version 2024
+# MagTense
 
 MagTense consists of both a magnetostatic and a micromagnetism calculation framework.
 
 The magnetostatic framework can calculate the magnetic field from objects shaped as cylinders, pieces of cylinders, prisms, circular pieces and tetrahedrons. This is done using a fully analytical calculation of the demagnetization tensor. The framework is fully implemented in Fortran and has both a Matlab MEX interface and a Python interface.
 
-The micromagnetism framework solves the Landau-Lifshitz equation. The framework is fully implemented in Fortran and has a Matlab MEX interface and a Python interface, as well as an older Matlab implementation. The micromagnetism framework utilizes the magnetostatic framework for calculating the demagnetization field.
+The micromagnetism framework solves the Landau-Lifshitz equation. The framework is fully implemented in Fortran and has a Matlab MEX interface and a Python interface. The micromagnetism framework utilizes the magnetostatic framework for calculating the demagnetization field.
 
 The webpage of the code is available at https://www.magtense.org.
 
@@ -45,7 +45,3 @@ Instructions on how to build and use the Python interface are listed in [python]
   conda install magtense -c cmt-dtu-energy/label/cpu -c https://software.repos.intel.com/python/conda/ -c conda-forge
   ```
 
-## Current code development
-The main features being worked on at the moment are:
-- Proper code documentation
-- Non-uniform grids

docs/_sources/Micromagnetism.rst.txt

@@ -4,9 +4,9 @@ Micromagnetism
 ========================================
 Basic input
 ========================================
-The matlab file *DefaultMicroMagProblem.m* contains an updated list of all parameters that can be specified in a micromagnetic problem.
+The matlab file `DefaultMicroMagProblem.m <https://github.com/cmt-dtu-energy/MagTense/blob/master/matlab/util/DefaultMicroMagProblem.m>`_ and similarly the python file `micromag.py <https://github.com/cmt-dtu-energy/MagTense/blob/master/python/src/magtense/micromag.py>`_ contains an updated list of all parameters that can be specified in a micromagnetic problem.
 
-For now, the micromagnetic model automatically generates a rectangular grid.
+The micromagnetic model automatically generates a rectangular grid, if not provided with a grid. See the example files for how to do this.
 
 The common parameters are:
 
@@ -17,15 +17,14 @@ The common parameters are:
 * Anisotropy constant
 * Damping constant, :math:`\alpha`
 * Precession constant, :math:`\gamma`
-
+
+
 ========================================
 Dynamic simulations
 ========================================
-An example of how to run a dynamic simulation is given in matlab/examples/NIST_micromag_Std_problem_2
+An example of how to run a dynamic simulation in Matlab is given `here <https://github.com/cmt-dtu-energy/MagTense/blob/master/matlab/examples/Micromagnetism/mumag_micromag_Std_problem_2/Standard_problem_2.m>`_.
 
 ========================================
 Hysteresis loop simulation
 ========================================
-An example of how to run a hysteresis loop simulation is given in matlab/examples/NIST_micromag_Std_problem_4
-
-
+An example of how to run a hysteresis loop simulation in Matlab is given `here <https://github.com/cmt-dtu-energy/MagTense/blob/master/matlab/examples/Micromagnetism/mumag_micromag_Std_problem_4/Standard_problem_4.m>`_ and in python `here <https://github.com/cmt-dtu-energy/MagTense/blob/master/python/examples/micromagnetism/std_problem_4.py>`_.

docs/_sources/about.rst.txt

@@ -1,30 +1,8 @@
 About
 ==============================================
 
-MagTense is actively developed at the Technical University of Denmark 
-by the Department of Energy Conversion and Storage.
+MagTense is actively developed at the Technical University of Denmark by the Department of Energy Conversion and Storage. The code is developed by Rasmus Bjørk, Stefan Pollok and Kaspar Kirstein Nielsen. Major current and past code developers are Andrea Roberto Insinga and Emil Blaabjerg Poulsen.
 
-Major code developers are 
-`Andrea Roberto Insinga <https://www.dtu.dk/english/service/phonebook/person?id=86373&tab=2&qt=dtupublicationquery>`_, 
-`Emil Blaabjerg Poulsen <https://www.dtu.dk/english/service/phonebook/person?id=142409&cpid=262058&tab=3&qt=dtuprojectquery>`_
-and `Stefan Pollok <https://www.dtu.dk/service/telefonbog/person?id=144368&cpid=265240&tab=3&qt=dtuprojectquery>`_.
+MagTense development has been sponsored by the Carlsberg Foundation Semper Ardens Advance project CF24-0920 entitled "Novel magnets through interdisiplinarity and nanocomposites", by the Villum Foundation Synergy project number 50091 entitled "Physics-aware machine learning", by the Independent Research Fund Denmark, grant “Magnetic Enhancements through Nanoscale Orientation (METEOR)”, 1032-00251B, by the Poul Due Jensen Foundation, in the project "Browns paradox in permanent magnets", project nr. 2018-016, by the Independent Research Fund Denmark project, contract. no. 7017-00034. 
 
-.. sidebar:: Funded by
-
-   |pic|
-
-.. |pic| image:: ./static/poul_due_jensen_foundation.png
-    :width: 100%
-    :alt: Poul Due Jensen Foundation
-
-Development of the code and the associated research on permanent magnets 
-is sponsored by the Poul Due Jensen Foundation, in a project aimed to 
-understand the coercivity of permanent magnets. Furthermore, development 
-is also sponsored by the Independent Research Fund Denmark project, 
-contract. no. 7017-00034.
-
-Previously the development of the demagnetization part of the framework 
-has been partly financed by the ENOVHEAT project, which is funded by 
-Innovation Fund Denmark (contract no. 12-132673), and also the Programme 
-Commission on Energy and Environment (EnM) (contract no. 2104-06-0032) 
-which was part of the Danish Council for Strategic Research.
+Previously the development of the demagnetization part of the framework has been partly financed by the ENOVHEAT project, which is funded by Innovation Fund Denmark (contract no. 12-132673), and also the Programme Commission on Energy and Environment (EnM) (contract no. 2104-06-0032) which was part of the Danish Council for Strategic Research.

docs/_sources/documentation.rst.txt

@@ -5,125 +5,131 @@ Documentation
 Python
 ========================================
 
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Tiles [`source <https://github.com/cmt-dtu-energy/MagTense/blob/00179ccaa29a5c452de1aa1f6991df2bdc9ed9e1/python/src/magtense/magstatics.py#L9>`_]
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+::
+
+    self.init(
+        n: int,
+        center_pos: Optional[List] = None,
+        dev_center: Optional[List] = None,
+        size: Optional[List] = None,
+        vertices: Optional[List] = None,
+        tile_type: Union[int, List, None] = None,
+        offset: Optional[List] = None,
+        rot: Optional[List] = None,
+        M_rem: Union[int, List, None] = None,
+        easy_axis: Optional[List] = None,
+        color: Optional[List] = None,
+        magnet_type: Optional[List] = None,
+        mag_angle: Optional[List] = None,
+    ) -> None
+
+    self.set_easy_axis(
+        val: Optional[List] = None,
+        idx: Optional[int] = None,
+        seed: int = 42
+    ) -> None
+
+    self.refine_prism(
+        idx: Union[int, List],
+        mat: List
+    ) -> None
+
+
 ----------------------------------------
-Objects
+Functions
 ----------------------------------------
 
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-`MagTiles <https://github.com/cmt-dtu-energy/MagTense/blob/master/python/source/MagTense.py#L9>`_
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+grid_config [`source <https://github.com/cmt-dtu-energy/MagTense/blob/00179ccaa29a5c452de1aa1f6991df2bdc9ed9e1/python/src/magtense/magstatics.py#L528>`_]
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 ::
 
-    def __init__(self, n):
-        # Initialization of arrays for specific tile parameters
-        # Input to Fortran derived type MagTile     
-        self.center_pos = np.zeros(shape=(n,3), dtype=np.float64, order='F') # r0, theta0, z0
-        self.dev_center = np.zeros(shape=(n,3), dtype=np.float64, order='F') # dr, dtheta, dz
-        self.size = np.zeros(shape=(n,3), dtype=np.float64, order='F') # a, b, c
-        self.vertices = np.zeros(shape=(n,3,4), dtype=np.float64, order='F') # v1, v2, v3, v4 as column vectors
-        self.M = np.zeros(shape=(n,3), dtype=np.float64, order='F') # Mx, My, Mz
-        self.u_ea = np.zeros(shape=(n,3), dtype=np.float64, order='F') # Easy axis
-        self.u_oa1 = np.zeros(shape=(n,3), dtype=np.float64, order='F')
-        self.u_oa2 = np.zeros(shape=(n,3), dtype=np.float64, order='F')
-        self.mu_r_ea = np.ones(shape=(n), dtype=np.float64, order='F')
-        self.mu_r_oa = np.ones(shape=(n), dtype=np.float64, order='F')
-        self.M_rem = np.zeros(shape=(n), dtype=np.float64, order='F')
-        # Implemented tile types: 
-        # 1 = cylinder, 2 = prism, 3 = circ_piece, 4 = circ_piece_inv,
-        # 5 = tetrahedron, 6 = sphere, 7 = spheroid, 10 = ellipsoid
-        self.tile_type = np.ones(n, dtype=np.int32, order='F')
-        self.offset = np.zeros(shape=(n,3), dtype=np.float64, order='F') # offset of global coordinates
-        self.rot = np.zeros(shape=(n,3), dtype=np.float64, order='F')
-        self.color = np.zeros(shape=(n,3), dtype=np.float64, order='F')
-        self.magnetic_type = np.ones(n, dtype=np.int32, order='F') # 1 = hard magnet, 2 = soft magnet
-        self.stfcn_index = np.ones(shape=(n), dtype=np.int32, order='F') # default index into the state function
-        self.incl_it = np.ones(shape=(n), dtype=np.int32, order='F') # if equal to zero the tile is not included in the iteration
-        self.use_sym = np.zeros(shape=(n), dtype=np.int32, order='F') # whether to exploit symmetry
-        self.sym_op = np.ones(shape=(n,3), dtype=np.float64, order='F') # 1 for symmetry and -1 for anti-symmetry respectively to the planes
-        self.M_rel = np.zeros(shape=(n), dtype=np.float64, order='F')
- 
-        # Internal parameters for python to prepare configuration
-        self.grid_pos = np.zeros(shape=(n,3), dtype=np.float64, order='F') # positions in the grid
-        self.n = n
-
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-Evaluation points
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+    grid_config(
+        spots: Union[List, np.ndarray],
+        area: Union[List, np.ndarray],
+        filled_pos: Optional[List] = None,
+        n_pts: List = [20, 20, 1],
+        mode: str = "uniform",
+        n_tiles: Optional[int] = None,
+        mag_angles: Optional[List] = None,
+        B_rem: float = 1.2,
+        seed: int = 42
+    ) -> tuple[Tiles, np.ndarray]
 
-::
 
-    points = np.zeros(shape=(number_of_points,3), dtype=np.float64, order='F')
-
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-Demagnetization tensor
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+iterate_magnetization [`source <https://github.com/cmt-dtu-energy/MagTense/blob/00179ccaa29a5c452de1aa1f6991df2bdc9ed9e1/python/src/magtense/magstatics.py#L666>`_]
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Iterate through tiles to determine their influence on each other.
 
 ::
 
-    N = np.zeros(shape=(number_of_tiles,number_of_points,3,3), dtype=np.float64, order='F')
+    iterate_magnetization(
+        tiles: Tiles,
+        max_error: float = 1e-5,
+        max_it: int = 500,
+        T: float = 300.,
+        mu_r: float = 20
+    ) -> Tiles
 
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-H-field
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+get_demag_tensor [`source <https://github.com/cmt-dtu-energy/MagTense/blob/00179ccaa29a5c452de1aa1f6991df2bdc9ed9e1/python/src/magtense/magstatics.py#L724>`_]
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Get demagnetization tensor of tiles and the specified evaluation points.
 
 ::
 
-    H = np.zeros(shape=(number_of_points,3), dtype=np.float64, order='F')
-
+    get_demag_tensor(
+        tiles: Tiles,
+        pts: np.ndarray
+    ) -> np.ndarray
 
-----------------------------------------
-Functions
-----------------------------------------
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+get_H_field [`source <https://github.com/cmt-dtu-energy/MagTense/blob/00179ccaa29a5c452de1aa1f6991df2bdc9ed9e1/python/src/magtense/magstatics.py#L763>`_]
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Calculate the demagnetizing field strength of a magnetic setup.
 
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-`iterate_magnetization (tiles, **options) <https://github.com/cmt-dtu-energy/MagTense/blob/master/python/source/MagTense.py#L441>`_
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-Returns updated tiles. Iterates through the given tiles to determine their influence 
-on each other.
+::
+    
+    get_H_field(
+        tiles: Tiles,
+        pts: np.ndarray,
+        demag_tensor: Optional[np.ndarray] = None
+    ) -> np.ndarray
+
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+run_simulation [`source <https://github.com/cmt-dtu-energy/MagTense/blob/00179ccaa29a5c452de1aa1f6991df2bdc9ed9e1/python/src/magtense/magstatics.py#L601>`_]
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Run MagTense with the Fortran source code as Python module.
 
 ::
 
-    # Options:
-    max_error = 0.00001 # Iteration stops if magnetization change of tiles is below this value
-    max_it = 500 # Maximum number of performed iterations
-    T = 300. # Temperature for the state function if required
-
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-`get_N_tensor (tiles, points) <https://github.com/cmt-dtu-energy/MagTense/blob/master/python/source/MagTense.py#L459>`_
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-Returns the demagnetization tensor N of the given tiles and 
-the specified evaluation points.
-
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-`get_H_field (tiles, points, N=None) <https://github.com/cmt-dtu-energy/MagTense/blob/master/python/source/MagTense.py#L468>`_
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-Returns the magnetic field H at the specified evaluation 
-points of the given tiles.
-Optionally, a precalculated demagnetization tensor N can be 
-handed over in order to prevent unnecessary and expensive 
-recalculation of N if geometry of the setup does not change.
-
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-`run_simulation (tiles, points, **options) <https://github.com/cmt-dtu-energy/MagTense/blob/master/python/source/MagTense.py#L406>`_
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-Does the previous mentioned steps all together.
-Demagnetization tensor will not be reused.
+    run_simulation(
+        tiles: Tiles,
+        pts: np.ndarray,
+        max_error: float = 1e-5,
+        max_it: int = 500,
+        T: float = 300.,
+    ) -> tuple[Tiles, np.ndarray]:
+
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+create_plot [`source <https://github.com/cmt-dtu-energy/MagTense/blob/00179ccaa29a5c452de1aa1f6991df2bdc9ed9e1/python/src/magtense/utils.py#L452>`_]
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Creates a plot with the iterated tiles and the calculated magnetic field H at the
+evaluation points as quiver plot. Additionally, an optional grid can be displayed.
+**Tile types**: 1 = cylinder, 2 = prism, 3 = circ_piece, 4 = circ_piece_inv, 5 = tetrahedron, 6 = sphere, 7 = spheroid, 10 = ellipsoid
 
 ::
 
-    # Options:
-    plot = False # Boolean if results shall be plotted
-    grid = None # Optional grid can be displayed
-    max_error = 0.00001 # Iteration stops if magnetization change of tiles is below this value
-    max_it = 500 # Maximum number of performed iterations
-    T = 300. # Temperature for the state function if required
-    iterate_solution = True # Boolean if the magnetization of the tiles shall be iterated
-    return_field=True # Boolean if magnetic field shall be calculated
-
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-`create_plot (iterated_tiles, points, H, grid=None) <https://github.com/cmt-dtu-energy/MagTense/blob/master/python/source/util_plot.py#L422>`_
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-Creates a matplotlib with the iterated tiles and the calculated 
-H-field at the evaluation points as quiver plot.
-Additionally, an optional grid can be displayed.
+    create_plot(
+        tiles: Optional[Tiles] = None,
+        eval_pts: Optional[np.ndarray] = None,
+        field: Optional[np.ndarray] = None,
+        spots: Optional[List] = None,
+        area: Optional[List] = None,
+    ) -> None