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LICENSE

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+MIT License
+
+Copyright (c) 2021 Umberto Zanovello
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+# CoSimPy
+
+CoSimPy is an open source Pyhton library aiming to combine results from electromagnetic (EM) simulation with circuits analysis through a co-simulation environment.
+
+## Summary
+
+  - [Getting Started](#getting-started)
+  - [Deployment](#deployment)
+  - [License](#license)
+  - [Acknowledgments](#acknowledgments)
+
+## Getting Started
+
+The library has been developed with Python 3.7. and tested on previous versions down to Python 3.5.
+
+### Prerequisites
+
+The library uses the follwong additional packages:
+
+- [numpy](https://numpy.org/) (>=1.15.2)
+- [matplotlib](https://matplotlib.org/) (>=3.0.0)
+- [h5py](https://www.h5py.org/) (>=2.8.0)
+- [scipy](https://www.scipy.org/) (>=1.1.0)
+
+The package versions reported in brackets represent the oldest releases with which the library has been succesfully tested.
+
+### Installing
+
+With [pip](https://pypi.org/project/pip/)  (coming soon...):
+```
+pip install cosimpy
+```
+
+With [anaconda](https://www.anaconda.com/products/individual):
+```
+conda install --channel umbertopy cosimpy
+```
+
+## Deployment
+
+After installation, the library can be imported as:
+
+```python
+import cosimpy
+```
+
+### An Example
+
+In the following example, a 1-port RF coil is modeled as a 5 ohm resistance in series with a 300 nH inductance. The RF coil is supposed to generate a 0.1 μT magnetic flux density oriented along the y-direction when it is supplied with 1 W incident power at 128 MHz. The coil is connected to a tuning/matching network through a 5 cm long lossless transmission line. The network is designed to transform the impedance at its output to 50 ohm at 128 MHz. 
+
+```python
+import numpy as np
+import cosimpy
+
+L_coil = 300e-9 #Coil inductance
+R_coil = 5 #Coil resistance
+
+#Frequency values at which the S parameters are evaluated
+frequencies = np.linspace(50e6,250e6,1001)
+
+#Number of points along x-, y-, z-direction where the magnetic flux density is evaluated
+nPoints = [20,20,20] 
+
+#b_field is evaluated at one frequency (128 MHz) at one port
+b_field = np.zeros((1,1,3,np.prod(nPoints)))
+#Only the y-component is different from zero 
+b_field[:,:,1,:] = 0.1e-6 
+
+#S_Matrix instance to be associated with the RF coil instance
+s_coil = cosimpy.S_Matrix.sMatrixRLseries(R_coil,L_coil,frequencies) 
+#EM_Field instance defined at 128 MHz to be associated with the RF coil instance
+em_coil = cosimpy.EM_Field([128e6], nPoints, b_field)
+
+#RF_Coil instance
+rf_coil = cosimpy.RF_Coil(s_coil,em_coil) 
+
+#The average value of the y-component of the magnetic flux density
+np.average(np.abs(rf_coil.em_field.b_field[0,0,1,:])).round(10)
+
+'''
+Out:
+    1e-07
+'''
+
+#5 cm lossless transmission line
+tr_line = cosimpy.S_Matrix.sMatrixTrLine(5e-2,frequencies) 
+
+#Connection between the RF coil and the transmission line
+rf_coil_line = rf_coil.singlePortConnRFcoil([tr_line],True) 
+
+#To design the tuning/matching network, I need to know the impedance value at 128 MHz
+rf_coil_line.s_matrix[128e6].getZMatrix()
+
+'''
+Out:
+    array([[[41.66705459+708.46385311j]]])
+'''
+
+#The impedance can be transormed to 50 ohm at 128 MHz deploying a T-network made of two capacitors and one inductor with the following values:
+
+Ca = 1.87e-12 #farad
+Cb = 27.24e-12 #farad
+L = 56.75e-9 #henry
+
+#I create the S_Matrix instances associated with Ca, Cb and L
+S_Ca = cosimpy.S_Matrix.sMatrixRCseries(0,Ca,frequencies)
+S_Cb = cosimpy.S_Matrix.sMatrixRCseries(0,Cb,frequencies)
+S_L = cosimpy.S_Matrix.sMatrixRLseries(0,L,frequencies)
+
+#I create the S_Matrix instance of the tuning/matching network. 
+tun_match_network = cosimpy.S_Matrix.sMatrixTnetwork(S_Ca,S_L,S_Cb)
+
+#The RF coil is connected to the matching network. The capacitor Ca will be in series with the transmission line
+rf_coil_line_matched = rf_coil_line.singlePortConnRFcoil([tun_match_network], True) 
+
+#The average value of the y-component of the magnetic flux density
+np.average(np.abs(rf_coil_line_matched.em_field.b_field[0,0,1,:])).round(10)
+
+'''
+Out:
+    7.825e-07
+'''
+
+rf_coil_line_matched.s_matrix.plotS(["S1-1"])
+```
+![](./docs/images/example_S.png)
+
+## License
+
+This project is licensed under the MIT
+License - see the [LICENSE](LICENSE) file for
+details.
+
+## Acknowledgments
+
+The library has been developed in the framework of the Researcher Mobility Grant (RMG) associated with the european project 17IND01 MIMAS. This RMG: 17IND01-RMG1 MIMAS has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme.
+
+[![](./docs/images/EMPIR_logo.jpg)](https://www.euramet.org/research-innovation/research-empir/)
+[![](./docs/images/MIMAS_logo.png)](https://www.ptb.de/mimas/home/)
+