Metadata-Version: 2.1
Name: PulseShape
Version: 0.1.4
Summary: A pulse shaping program for EPR!
Home-page: https://gitlab.com/mtessmer/PulseShape
Author: Maxx Tessmer
Author-email: mhtessmer@gmail.com
License: GNU GPLv3
Project-URL: Source, https://gitlab.com/mtessmer/PulseShape
Keywords: pulse shape,EPR,DEER,PELDOR,AWG
Platform: UNKNOWN
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.6
Description-Content-Type: text/markdown

# PusleShape

PulseShape is an EasySpin `pulse` function clone written in python. The major purpose for 
rewriting pulse in Python is to free the function from the proprietary MATLAB universe and 
make it easier to use on Linux systems that often ship with e580 spectrometers. 

PulseShape is built around the `Pulse` object which accepts arguments similar to those 
used by the easyspin `pulse` function. 

## Installation
PulseShape can be installed and updated using `pip`, the python package manager. 

```bash
pip install PulseShape
```
PulseShape is tested to work on python 3.6-3.9. While one of the major purposes of PulseShape is to work on Linux systems, PulseShape works well on all systems (Windows, Mac and Linux) and only depends on numpy and scipy.

Alternatively, PulseShape can be installed by downloading or cloning the git repository.

```bash
git clone https://gitlab.com/mtessmer/PulseShape.git
cd PulseShape
python setup.py install
```

## e580 Setup
Instructions for setting up python and PulseShape on the Linux system that usually ships with e580 spectrometers coming soon.

## Example: sech\tanh pulse with resonator compensation
<table>
<tr>
<th>PulseShape</th>
<th>EasySpin</th>
</tr>
<tr>
<td>

```python
import numpy as np
import matplotlib.pyplot as plt
from PulseShape import Pulse

profile = np.loadtxt('data/Transferfunction.dat')
pulse = Pulse(pulse_time=0.150, 
              time_step=0.000625, 
              flip=np.pi, 
              shape='sech/tanh', 
              freq=[40, 120], 
              beta=10, 
              profile=profile)

plt.figure(figsize=(5, 5))
plt.plot(pulse.time * 1000, pulse.IQ.real, label='real')
plt.plot(pulse.time * 1000, pulse.IQ.imag, label='imaginary')
plt.xlabel('time (ns)')
plt.ylabel('Amplitude')
plt.legend()
plt.show()
```
<img src="https://gitlab.com/mtessmer/PulseShape/-/raw/master/img/sechtanh.png" width="400"  class="center"/>


</td>
<td>

```matlab
Par = struct
Par.Type = 'sech/tanh';
Par.beta = 10;
Par.tp = 0.150;
Par.Phase = 0;
Par.Flip = pi;
Par.Frequency = [40 120]
Par.TimeStep=0.000625

filename = 'Transferfunction.dat';
delimiter = ' ';
formatSpec = '%f%f%[^\n\r]';
fileID = fopen(filename,'r');
dataArray = textscan(fileID, formatSpec, 'Delimiter', ... 
                    delimiter, 'MultipleDelimsAsOne', ...
                    true, 'TextType', 'string');
fclose(fileID);

Par.FrequencyResponse = [dataArray{:, 1}, dataArray{:, 2}];

[t, IQ] = pulse(Par)
[t, IQ, modulation] = pulse(Par) 

figure(1)
hold on
plot(t, real(IQ))
plot(t, imag(IQ))
xlabel('time ns')
ylabel('Amplitude')
x0=10;
y0=10;
width=465;
height=448;
set(gcf,'position',[x0,y0,width,height])

```
<img src="https://gitlab.com/mtessmer/PulseShape/-/raw/master/img/sechtanhes.png" width="400" class="center"/>
</td>
</tr>
</table>

## Example: Working with multiple pulses

All `time`, `IQ`, other paramters and data are stored withing the `Pulse` object itself so it's easy to work with multiple pulses

```python
import numpy as np
import matplotlib.pyplot as plt
from PulseShape import Pulse

profile = np.loadtxt('data/Transferfunction.dat')
st_pulse = Pulse(pulse_time=0.150,
                 time_step=0.000625,
                 flip=np.pi,
                 shape='sech/tanh',
                 freq=[40, 120],

                 beta=10,
                 profile=profile)

g_pulse = Pulse(pulse_time=0.06,
                time_step=0.000625,
                flip=np.pi,
                shape='gaussian',
                trunc=0.1)

offsets = np.linspace(-20, 140, 256)
st_pulse.exciteprofile(offsets)
g_pulse.exciteprofile(offsets)

fig, (ax1, ax2) = plt.subplots(2, figsize=(8, 10))
ax1.set_title('Pulse IQ')
ax1.plot(st_pulse.time * 1e3, st_pulse.IQ.real, label=r'sech/tanh $\Re$', color='C0')
ax1.plot(st_pulse.time * 1e3, st_pulse.IQ.imag, label=r'sech/tanh $\Im$', alpha=0.5, color='C0')
ax1.plot(g_pulse.time * 1e3, g_pulse.IQ.real, label='gaussian', color='C1')
ax1.set_ylabel('Amplitude')
ax1.set_ylabel("Time (ns)")
ax1.legend()

ax2.set_title('Excitation Profile')
ax2.plot(offsets, st_pulse.Mz)
ax2.plot(offsets, g_pulse.Mz)
ax2.set_xlabel('Frequency Offset (MHz)')
ax2.set_ylabel('Mz')
plt.show()
```
<img src="https://gitlab.com/mtessmer/PulseShape/-/raw/master/img/g_st.png" width="800" class="center"/>


