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beamtime/README.md
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# beamtime
A package for processing and analysis of data from beamtime at SNBL
# 1.0 Installation
### 1.1 Virtual environment
It is recommended to use a new dedicated virtual environment to use this package to ensure that all depedency versions are the same. This can be done by first creating a new environtment with the Python version 3.9.7 as follows:
```
conda create --name beamtime python=3.9.7
```
Here you can replace `beamtime` with any name you prefer. If you do, make sure you replace it in the subsequent commands as well.
In order to use the virtual environment, you need to activate it. This is done by typing
```
conda activate beamtime
```
Note that you might have to initialise your shell first to allow for this. If so, you'll get a message saying so and you need to follow the instructions you get.
Once you are able to activate the virtual environment, you need to install all the packages required. These are listed in the requirements.txt file in the beamtime package folder, and can be installed by running the command (inside that folder):
```
conda install --file requirements.txt
```
Lastly, you might want to install this virtual environment as its own Jupyter kernel if you are planning to use Jupyter Notebook / Labs with this package. This way you won't have to activate the environment everytime you use it, you just create a Jupyter Notebook with this kernel.
To do so, run the command:
```
python -m ipykernel install --user --name beamtime --display-name "Python 3.9.7 (Beamtime)"
```
Here you need to change `beamtime` if you named it something else, and the display name can be whatever you want it to be. Note that you need to have the package `ipykernel` installed for this, but it should be installed from running the install command above.
### 1.2 Installation of the package
In order to also use `beamtime` package itself, you need to install it. It is not uploaded to any package manager, but it can be installed from the main folder containing the `setup.py` file. Run the following command in this folder:
```
pip install .
```
# 2.0 The `electrochemistry` module
The `electrochemistry` module allows to plot galvanostatic cycling data from BioLogic, Neware and Batsmall.
General use:
```py
import beamtime.electrochemistry as ec
path = 'path/to/data/file'
options = {
'x_vals': 'specific_capacity',
'y_vals': 'voltage',
'active_material_weight': 4.3
}
cycles, fig, ax = ec.plot.plot_gc(path=path, kind='neware', options=options)
```
Note that no options needs to be specified, all options will have default values that should make somewhat sense. A comprehensive list of options will be updated later.
The return values from the `plot_gc` function are:
- `cycles`, a list of lists containing the charge and discharge cycles of each cycle in the form of a `pandas` DataFrame
- `fig`, the `matplotlib.pyplot' Figure object to allow for any modifications after initial plotting.
- `ax`, the 'matplotlib'pyplot' Axes object to allow for any modification after initial plotting.
If these are not required, you can simply assign the return values to an underscore instead. However, omitting assignment will print all the DataFrames.

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beamtime/feature_list.txt
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- Must allow for automatic normalisation between different diffractograms, must only happen upon reading data
-

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beamtime/reqirements2.txt
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# This file may be used to create an environment using:
# $ conda create --name <env> --file <this file>
# platform: win-64
argon2-cffi=21.3.0=pyhd3eb1b0_0
argon2-cffi-bindings=21.2.0=py39h2bbff1b_0
attrs=21.4.0=pyhd3eb1b0_0
backcall=0.2.0=pyhd3eb1b0_0
beamtime=0.1=pypi_0
blas=1.0=mkl
bleach=4.1.0=pyhd3eb1b0_0
bottleneck=1.3.2=py39h7cc1a96_1
ca-certificates=2022.2.1=haa95532_0
cached-property=1.5.2=hd8ed1ab_1
cached_property=1.5.2=pyha770c72_1
certifi=2021.10.8=py39haa95532_2
cffi=1.15.0=py39h2bbff1b_1
colorama=0.4.4=pyhd3eb1b0_0
cycler=0.10.0=py_2
debugpy=1.4.1=py39hd77b12b_0
decorator=5.1.0=pyhd3eb1b0_0
defusedxml=0.7.1=pyhd3eb1b0_0
entrypoints=0.3=py39haa95532_0
fabio=0.12.0=py39h5d4886f_0
freetype=2.10.4=h546665d_1
glymur=0.9.4=pyhd8ed1ab_0
h5py=3.2.1=nompi_py39hf27771d_100
hdf5=1.10.6=nompi_h5268f04_1114
hdf5plugin=3.1.1=py39h71586dd_0
icc_rt=2019.0.0=h0cc432a_1
icu=68.1=h6c2663c_0
importlib-metadata=4.8.2=py39haa95532_0
importlib_metadata=4.8.2=hd3eb1b0_0
intel-openmp=2021.3.0=haa95532_3372
ipykernel=6.4.1=py39haa95532_1
ipython=7.27.0=py39hd4e2768_0
ipython_genutils=0.2.0=pyhd3eb1b0_1
ipywidgets=7.6.5=pyhd3eb1b0_1
jbig=2.1=h8d14728_2003
jedi=0.18.0=py39haa95532_1
jinja2=3.0.2=pyhd3eb1b0_0
jpeg=9d=h2bbff1b_0
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jupyterlab_widgets=1.0.0=pyhd3eb1b0_1
kiwisolver=1.3.2=py39h2e07f2f_0
krb5=1.19.2=hbae68bd_2
lerc=3.0=h0e60522_0
libclang=11.1.0=default_h5c34c98_1
libcurl=7.79.1=h789b8ee_1
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libwebp=1.2.0=h2bbff1b_0
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nest-asyncio=1.5.1=pyhd3eb1b0_0
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numpy=1.21.2=py39hfca59bb_0
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parso=0.8.2=pyhd3eb1b0_0
pickleshare=0.7.5=pyhd3eb1b0_1003
pillow=8.4.0=py39hd45dc43_0
pip=21.2.4=py39haa95532_0
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prompt-toolkit=3.0.20=pyhd3eb1b0_0
pycparser=2.21=pyhd3eb1b0_0
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pyqt=5.12.3=py39hcbf5309_7
pyqt-impl=5.12.3=py39h415ef7b_7
pyqt5-sip=4.19.18=py39h415ef7b_7
pyqtchart=5.12=py39h415ef7b_7
pyqtwebengine=5.12.1=py39h415ef7b_7
pyreadline=2.1=py39hcbf5309_1004
pyrsistent=0.18.0=py39h196d8e1_0
python=3.9.7=h6244533_1
python-dateutil=2.8.2=pyhd3eb1b0_0
python_abi=3.9=2_cp39
pytz=2021.3=pyhd3eb1b0_0
pywin32=228=py39hbaba5e8_1
pywinpty=2.0.2=py39h5da7b33_0
pyzmq=22.2.1=py39hd77b12b_1
qt=5.12.9=h5909a2a_4
qtconsole=5.1.1=pyhd3eb1b0_0
qtpy=1.11.2=pyhd8ed1ab_0
scipy=1.7.1=py39hbe87c03_2
send2trash=1.8.0=pyhd3eb1b0_1
setuptools=58.0.4=py39haa95532_0
silx=0.15.2=hd8ed1ab_0
silx-base=0.15.2=py39h2e25243_0
six=1.16.0=pyhd3eb1b0_0
sqlite=3.36.0=h2bbff1b_0
terminado=0.13.1=py39haa95532_0
testpath=0.5.0=pyhd3eb1b0_0
tk=8.6.11=h8ffe710_1
tornado=6.1=py39h2bbff1b_0
traitlets=5.1.0=pyhd3eb1b0_0
typing-extensions=3.10.0.2=hd3eb1b0_0
typing_extensions=3.10.0.2=pyh06a4308_0
tzdata=2021a=h5d7bf9c_0
vc=14.2=h21ff451_1
vs2015_runtime=14.27.29016=h5e58377_2
wcwidth=0.2.5=pyhd3eb1b0_0
webencodings=0.5.1=py39haa95532_1
wheel=0.37.0=pyhd3eb1b0_1
widgetsnbextension=3.5.2=py39haa95532_0
wincertstore=0.2=py39haa95532_2
winpty=0.4.3=4
xz=5.2.5=h62dcd97_1
zipp=3.7.0=pyhd3eb1b0_0
zlib=1.2.11=h8ffe710_1013
zstd=1.5.0=h6255e5f_0

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beamtime/requirements.txt
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# This file may be used to create an environment using:
# $ conda create --name <env> --file <this file>
# platform: win-64
@EXPLICIT
https://repo.anaconda.com/pkgs/main/win-64/blas-1.0-mkl.conda
https://conda.anaconda.org/conda-forge/win-64/ca-certificates-2021.10.8-h5b45459_0.tar.bz2
https://repo.anaconda.com/pkgs/main/win-64/icc_rt-2019.0.0-h0cc432a_1.conda
https://repo.anaconda.com/pkgs/main/win-64/intel-openmp-2021.3.0-haa95532_3372.conda
https://repo.anaconda.com/pkgs/main/noarch/tzdata-2021a-h5d7bf9c_0.conda
https://repo.anaconda.com/pkgs/main/win-64/vs2015_runtime-14.27.29016-h5e58377_2.conda
https://repo.anaconda.com/pkgs/main/win-64/mkl-2021.3.0-haa95532_524.conda
https://repo.anaconda.com/pkgs/main/win-64/vc-14.2-h21ff451_1.conda
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https://repo.anaconda.com/pkgs/main/win-64/jpeg-9d-h2bbff1b_0.conda
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https://repo.anaconda.com/pkgs/main/win-64/mkl_fft-1.3.1-py39h277e83a_0.conda
https://repo.anaconda.com/pkgs/main/win-64/mkl_random-1.2.2-py39hf11a4ad_0.conda
https://repo.anaconda.com/pkgs/main/win-64/numpy-1.21.2-py39hfca59bb_0.conda
https://repo.anaconda.com/pkgs/main/win-64/numexpr-2.7.3-py39hb80d3ca_1.conda
https://repo.anaconda.com/pkgs/main/win-64/scipy-1.7.1-py39hbe87c03_2.conda
https://repo.anaconda.com/pkgs/main/win-64/pandas-1.3.3-py39h6214cd6_0.conda
https://conda.anaconda.org/conda-forge/win-64/pyfai-base-0.20.0-py39h2e25243_0.tar.bz2