Merge halvor_xanes to master

.github/workflows/automated-testing.yml

@@ -0,0 +1,35 @@
+name: Automated testing
+
+on: [push]
+
+jobs:
+  build-linux:
+    runs-on: ubuntu-latest
+    strategy:
+      max-parallel: 5
+
+    steps:
+    - uses: actions/checkout@v3
+    - name: Set up Python 3.10
+      uses: actions/setup-python@v3
+      with:
+        python-version: 3.10.4
+    - name: Add conda to system path
+      run: |
+        # $CONDA is an environment variable pointing to the root of the miniconda directory
+        echo $CONDA/bin >> $GITHUB_PATH
+    - name: Install dependencies
+      run: |
+        conda env update --file environment.yml --name base
+        pip install .
+    - name: Lint with flake8
+      run: |
+        conda install flake8
+        # stop the build if there are Python syntax errors or undefined names
+        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
+        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
+        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+    - name: Test with pytest
+      run: |
+        conda install pytest
+        pytest

beamtime/reqirements2.txt

@@ -1,141 +0,0 @@
-# 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
-jsonschema=3.2.0=pyhd3eb1b0_2
-jupyter_client=7.0.1=pyhd3eb1b0_0
-jupyter_core=4.8.1=py39haa95532_0
-jupyterlab_pygments=0.1.2=py_0
-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
-libdeflate=1.8=h2bbff1b_5
-libiconv=1.16=he774522_0
-libpng=1.6.37=h1d00b33_2
-libssh2=1.10.0=h680486a_2
-libtiff=4.3.0=hd413186_2
-libwebp=1.2.0=h2bbff1b_0
-libxml2=2.9.12=h0ad7f3c_0
-libxslt=1.1.34=he774522_0
-libzlib=1.2.11=h8ffe710_1013
-lxml=4.6.3=py39h4fd7cdf_0
-lz4-c=1.9.3=h8ffe710_1
-mako=1.1.5=pyhd8ed1ab_0
-markupsafe=2.0.1=py39h2bbff1b_0
-matplotlib=3.4.3=py39hcbf5309_1
-matplotlib-base=3.4.3=py39h581301d_1
-matplotlib-inline=0.1.2=pyhd3eb1b0_2
-mistune=0.8.4=py39h2bbff1b_1000
-mkl=2021.3.0=haa95532_524
-mkl-service=2.4.0=py39h2bbff1b_0
-mkl_fft=1.3.1=py39h277e83a_0
-mkl_random=1.2.2=py39hf11a4ad_0
-nbclient=0.5.11=pyhd3eb1b0_0
-nbconvert=6.1.0=py39haa95532_0
-nbformat=5.1.3=pyhd3eb1b0_0
-nest-asyncio=1.5.1=pyhd3eb1b0_0
-notebook=6.4.8=py39haa95532_0
-numexpr=2.7.3=py39hb80d3ca_1
-numpy=1.21.2=py39hfca59bb_0
-numpy-base=1.21.2=py39h0829f74_0
-olefile=0.46=pyh9f0ad1d_1
-openjpeg=2.4.0=hb211442_1
-openssl=1.1.1m=h2bbff1b_0
-packaging=21.3=pyhd3eb1b0_0
-pandas=1.3.3=py39h6214cd6_0
-pandocfilters=1.5.0=pyhd3eb1b0_0
-parso=0.8.2=pyhd3eb1b0_0
-pickleshare=0.7.5=pyhd3eb1b0_1003
-pillow=8.4.0=py39hd45dc43_0
-pip=21.2.4=py39haa95532_0
-prometheus_client=0.13.1=pyhd3eb1b0_0
-prompt-toolkit=3.0.20=pyhd3eb1b0_0
-pycparser=2.21=pyhd3eb1b0_0
-pyfai=0.20.0=hd8ed1ab_0
-pyfai-base=0.20.0=py39h2e25243_0
-pygments=2.10.0=pyhd3eb1b0_0
-pyparsing=2.4.7=pyhd3eb1b0_0
-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

beamtime/requirements.txt

@@ -1,108 +0,0 @@
-# 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
-https://repo.anaconda.com/pkgs/main/win-64/icu-68.1-h6c2663c_0.conda
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-https://repo.anaconda.com/pkgs/main/win-64/jpeg-9d-h2bbff1b_0.conda
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beamtime/xrd/plot.py

@@ -1,378 +0,0 @@
-import matplotlib.pyplot as plt
-from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,AutoMinorLocator)
-
-import pandas as pd
-import numpy as np
-import math
-
-import ipywidgets as widgets
-
-import beamtime.xrd as xrd
-import beamtime.auxillary as aux
-import beamtime.plotting as btp
-
-
-def plot_diffractogram(data, options={}):
-    ''' Plots a diffractogram.
-    
-    Input:
-    data (dict): Must include path = string to diffractogram data, and plot_kind = (recx, beamline, image)'''
-
-    # Update options
-    required_options = ['x_vals', 'y_vals', 'ylabel', 'xlabel', 'xunit', 'yunit', 'line', 'scatter', 'xlim', 'ylim',
-    'reflections_plot', 'reflections_indices', 'reflections_data', 'plot_kind', 'palettes', 'interactive', 'rc_params', 'format_params']
-
-    default_options = {
-        'x_vals': '2th', 
-        'y_vals': 'I',
-        'ylabel': 'Intensity', 'xlabel': '2theta', 
-        'xunit': 'deg', 'yunit': 'a.u.',
-        'xlim': None, 'ylim': None, 
-        'line': True, # whether or not to plot diffractogram as a line plot
-        'scatter': False, # whether or not to plot individual data points
-        'reflections_plot': False, # whether to plot reflections as a plot
-        'reflections_indices': False, # whether to plot the reflection indices
-        'reflections_data': None, # Should be passed as a list of dictionaries on the form {path: rel_path, reflection_indices: number of indices, colour: [r,g,b], min_alpha: 0-1]
-        'plot_kind': None,
-        'palettes': [('qualitative', 'Dark2_8')],
-        'interactive': False,
-        'interactive_session_active': False,
-        'rc_params': {},
-        'format_params': {},
-        }
-
-    options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
-
-    if not 'diffractogram' in data.keys():
-        diffractogram = xrd.io.read_data(data=data, options=options)
-        data['diffractogram'] = diffractogram
-
-    else:
-        diffractogram = data['diffractogram']
-
-    # Sets the xlim if this has not bee specified
-    if not options['xlim']:
-        options['xlim'] = [diffractogram[options['x_vals']].min(), diffractogram[options['x_vals']].max()]
-
-
-    # Start inteactive session with ipywidgets
-    if options['interactive']:
-        options['interactive'] = False
-        options['interactive_session_active'] = True
-        plot_diffractogram_interactive(data=data, options=options)
-        return
-    
-    
-    # Makes a list out of reflections_data if it only passed as a dict, as it will be looped through later
-    if options['reflections_data']:
-        if not isinstance(options['reflections_data'], list):
-            options['reflections_data'] = [options['reflections_data']]
-
-    # Determine number of subplots and height ratios between them
-    if len(options['reflections_data']) >= 1:
-        options = determine_grid_layout(options=options)
-
-
-    # Prepare plot, and read and process data
-
-    fig, ax = btp.prepare_plot(options=options)
-
-
-    # Assign the correct axes
-    if options['reflections_plot'] or options['reflections_indices']:
-        
-        if options['reflections_indices']:
-            indices_ax = ax[0]
-
-            if options['reflections_plot']:
-                ref_axes = [axx for axx in ax[range(1,len(options['reflections_data'])+1)]]
-
-        else:
-            ref_axes = [axx for axx in ax[range(0,len(options['reflections_data']))]]
-
-        ax = ax[-1]
-
-    colours = btp.generate_colours(options['palettes'])
-
-
-    if options['line']:
-        diffractogram.plot(x=options['x_vals'], y=options['y_vals'], ax=ax, c=next(colours), zorder=1)
-    
-    if options['scatter']:
-        ax.scatter(x=diffractogram[options['x_vals']], y = diffractogram[options['y_vals']], c=[(1,1,1,0)], edgecolors=[next(colours)], linewidths=plt.rcParams['lines.markeredgewidth'], zorder=2) #, edgecolors=np.array([next(colours)]))
-
-
-
-    fig, ax = btp.adjust_plot(fig=fig, ax=ax, options=options)
-
-    
-
-    # Make the reflection plots
-    if options['reflections_plot'] and options['reflections_data']:
-        options['xlim'] = ax.get_xlim()
-        options['to_wavelength'] = data['wavelength']
-        
-        for reference, axis in zip(options['reflections_data'], ref_axes):
-            plot_reflection_table(data=reference, ax=axis, options=options)
-
-    # Print the reflection indices
-    if options['reflections_indices'] and options['reflections_data']:
-        options['xlim'] = ax.get_xlim()
-        options['to_wavelength'] = data['wavelength']
-
-        for reference in options['reflections_data']:
-            plot_reflection_indices(data=reference, ax=indices_ax, options=options)
-
-
-    if options['interactive_session_active']:
-        btp.update_widgets(options=options)
-
-
-    return diffractogram, fig, ax
-
-
-def determine_grid_layout(options):
-
-
-    nrows = 1 if not options['reflections_indices'] else 2
-
-    if options['reflections_plot']:
-        for reference in options['reflections_data']:
-            nrows += 1
-
-    options['format_params']['nrows'] = nrows
-    options['format_params']['grid_ratio_height'] = [1 for i in range(nrows-1)]+[10]
-
-    return options
-
-
-
-def plot_diffractogram_interactive(data, options):
-
-    options['widgets'] = {
-        'xlim': {
-            'w': widgets.FloatRangeSlider(value=[data['diffractogram']['2th'].min(), data['diffractogram']['2th'].max()], min=data['diffractogram']['2th'].min(), max=data['diffractogram']['2th'].max(), step=0.5, layout=widgets.Layout(width='95%')),
-            '2th_default': {'min': data['diffractogram']['2th'].min(), 'max': data['diffractogram']['2th'].max(), 'value': [data['diffractogram']['2th'].min(), data['diffractogram']['2th'].max()], 'step': 0.5},
-            '2th_cuka_default': {'min': data['diffractogram']['2th_cuka'].min(), 'max': data['diffractogram']['2th_cuka'].max(), 'value': [data['diffractogram']['2th_cuka'].min(), data['diffractogram']['2th_cuka'].max()], 'step': 0.5},
-            '2th_moka_default': {'min': data['diffractogram']['2th_moka'].min(), 'max': data['diffractogram']['2th_moka'].max(), 'value': [data['diffractogram']['2th_moka'].min(), data['diffractogram']['2th_moka'].max()], 'step': 0.5},
-            'd_default': {'min': data['diffractogram']['d'].min(), 'max': data['diffractogram']['d'].max(), 'value': [data['diffractogram']['d'].min(), data['diffractogram']['d'].max()], 'step': 0.5},
-            '1/d_default': {'min': data['diffractogram']['1/d'].min(), 'max': data['diffractogram']['1/d'].max(), 'value': [data['diffractogram']['1/d'].min(), data['diffractogram']['1/d'].max()], 'step': 0.5},
-            'q_default': {'min': data['diffractogram']['q'].min(), 'max': data['diffractogram']['q'].max(), 'value': [data['diffractogram']['q'].min(), data['diffractogram']['q'].max()], 'step': 0.5},
-            'q2_default': {'min': data['diffractogram']['q2'].min(), 'max': data['diffractogram']['q2'].max(), 'value': [data['diffractogram']['q2'].min(), data['diffractogram']['q2'].max()], 'step': 0.5},
-            'q4_default': {'min': data['diffractogram']['q4'].min(), 'max': data['diffractogram']['q4'].max(), 'value': [data['diffractogram']['q4'].min(), data['diffractogram']['q4'].max()], 'step': 0.5},
-            'state': '2th'
-        }
-    }
-
-
-    if options['reflections_data']:
-        w = widgets.interactive(btp.ipywidgets_update, func=widgets.fixed(plot_diffractogram), data=widgets.fixed(data), options=widgets.fixed(options), 
-        scatter=widgets.ToggleButton(value=False), 
-        line=widgets.ToggleButton(value=True), 
-        reflections_plot=widgets.ToggleButton(value=True),
-        reflections_indices=widgets.ToggleButton(value=False),
-        x_vals=widgets.Dropdown(options=['2th', 'd', '1/d', 'q', 'q2', 'q4', '2th_cuka', '2th_moka'], value='2th', description='X-values'),
-        xlim=options['widgets']['xlim']['w'])
-    
-    else:
-        w = widgets.interactive(btp.ipywidgets_update, func=widgets.fixed(plot_diffractogram), data=widgets.fixed(data), options=widgets.fixed(options), 
-        scatter=widgets.ToggleButton(value=False), 
-        line=widgets.ToggleButton(value=True),
-        xlim=options['widgets']['xlim']['w'])
-    
-    
-    display(w)
-
-
-def update_widgets(options):
-
-    for widget in options['widgets'].values():
-
-        if widget['state'] != options['x_vals']:
-            for arg in widget[f'{options["x_vals"]}_default']:
-                setattr(widget['w'], arg, widget[f'{options["x_vals"]}_default'][arg])
-            
-            widget['state'] = options['x_vals']
-
-
-
-def plot_reflection_indices(data, ax, options={}):
-    ''' Print reflection indices from output generated by VESTA.
-    
-    Required contents of data:
-    path (str): relative path to reflection table file'''
-
-    required_options = ['reflection_indices', 'text_colour', 'hide_indices']
-
-    default_options = {
-        'reflection_indices': 3, # Number of reflection indices to plot, from highest intensity and working its way down
-        'text_colour': 'black',
-        'hide_indices': False
-    }
-
-    data = aux.update_options(options=data, required_options=required_options, default_options=default_options)
-
-    if not data['hide_indices']:
-        reflection_table = xrd.io.load_reflection_table(data=data, options=options)
-        
-        if data['reflection_indices'] > 0:
-
-            # Get the data['reflection_indices'] number of highest reflections within the subrange options['xlim']
-            reflection_indices = reflection_table.loc[(reflection_table[options['x_vals']] > options['xlim'][0]) & (reflection_table[options['x_vals']] < options['xlim'][1])].nlargest(options['reflection_indices'], 'I')
-
-            # Plot the indices
-            for i in range(data['reflection_indices']):
-                if reflection_indices.shape[0] > i:
-                    ax.text(s=f'({reflection_indices["h"].iloc[i]} {reflection_indices["k"].iloc[i]} {reflection_indices["l"].iloc[i]})', x=reflection_indices[options['x_vals']].iloc[i], y=0, fontsize=2.5, rotation=90, va='bottom', ha='center', c=data['text_colour'])    
-
-        
-        if options['xlim']:
-            ax.set_xlim(options['xlim'])
-        
-        ax.axis('off')
-
-
-    return
-    
-def plot_reflection_table(data, ax=None, options={}):
-    ''' Plots a reflection table from output generated by VESTA.
-    
-    Required contents of data:
-    path (str): relative path to reflection table file'''
-
-    required_options = ['reflection_indices', 'reflections_colour', 'min_alpha', 'wavelength', 'format_params', 'rc_params', 'label']
-
-    default_options = {
-        'reflection_indices': 0, # Number of indices to print
-        'reflections_colour': [0,0,0],
-        'min_alpha': 0,
-        'wavelength': 1.54059, # CuKalpha, [Å] 
-        'format_params': {},
-        'rc_params': {},
-        'label': None
-    }
-
-    if 'colour' in data.keys():
-        options['reflections_colour'] = data['colour']
-    if 'min_alpha' in data.keys():
-        options['min_alpha'] = data['min_alpha']
-    if 'reflection_indices' in data.keys():
-        options['reflection_indices'] = data['reflection_indices']
-    if 'label' in data.keys():
-        options['label'] = data['label']
-    if 'wavelength' in data.keys():
-        options['wavelength'] = data['wavelength']
-
-    options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
-
-    
-    if not ax:
-        _, ax = btp.prepare_plot(options)
-
-    reflection_table = xrd.io.load_reflection_table(data=data, options=options)
-
-    reflections, intensities  = reflection_table[options['x_vals']], reflection_table['I']
-
-
-    
-    colours = []
-
-    for ref, intensity in zip(reflections, intensities):
-
-        colour = list(options['reflections_colour'])
-        rel_intensity = (intensity / intensities.max())*(1-options['min_alpha']) + options['min_alpha']
-        colour.append(rel_intensity)
-        colours.append(colour)
-
-    
-
-    
-    ax.vlines(x=reflections, ymin=-1, ymax=1, colors=colours, lw=0.5)
-    ax.set_ylim([-0.5,0.5])
-
-
-    ax.tick_params(which='both', bottom=False, labelbottom=False, right=False, labelright=False, left=False, labelleft=False, top=False, labeltop=False)
-    
-    if options['xlim']:
-        ax.set_xlim(options['xlim'])
-
-
-    if options['label']:
-        xlim_range = ax.get_xlim()[1] - ax.get_xlim()[0]
-        ylim_avg = (ax.get_ylim()[0]+ax.get_ylim()[1])/2
-
-        ax.text(s=data['label'], x=(ax.get_xlim()[0]-0.01*xlim_range), y=ylim_avg, ha = 'right', va = 'center')
-
-
-
-
-
-def prettify_labels(label):
-	
-	labels_dict = {
-		'2th': '2$\\theta$',
-        'I': 'Intensity'	
-        }
-
-	return labels_dict[label]
-
-def plot_diffractograms(paths, kind, options=None):
-
-
-    fig, ax = prepare_diffractogram_plot(options=options)
-
-    diffractograms = []
-
-    for path in paths:
-        diffractogram = xrd.io.read_data(path=path, kind=kind, options=options)
-        diffractograms.append(diffractogram)
-
-
-    required_options = ['type', 'xvals', 'yvals', 'x_offset', 'y_offset', 'normalise', 'normalise_around', 'reverse_order']
-    default_options = {
-        'type': 'stacked',
-        'xvals': '2th',
-        'yvals': 'I',
-        'x_offset': 0,
-        'y_offset': 0.2,
-        'normalise': True,
-        'normalise_around': None,
-        'reverse_order': False
-    }
-
-
-    # If reverse_order is enabled, reverse the order
-    if options['reverse_order']:
-        diffractograms = reverse_diffractograms(diffractograms)
-
-
-    # If normalise is enbaled, normalise all the diffractograms
-    if options['normalise']:
-        if not options['normalise_around']:
-            for diffractogram in diffractograms:
-                diffractogram["I"] = diffractogram["I"]/diffractogram["I"].max()
-            else:
-                diffractogram["I"] = diffractogram["I"]/diffractogram["I"].loc[(diffractogram['2th'] > options['normalise_around'][0]) & (diffractogram['2th'] < options['normalise_around'][1])].max()
-
-    
-    if options['type'] == 'stacked':
-        for diffractogram in diffractograms:
-            diffractogram.plot(x=options['xvals'], y=options['yvals'], ax=ax)
-
-
-    fig, ax = prettify_diffractogram_plot(fig=fig, ax=ax, options=options)
-
-
-    return diffractogram, fig, ax
-
-
-def reverse_diffractograms(diffractograms):
-
-    rev_diffractograms = []
-
-    for i in len(diffractograms):
-        rev_diffractograms.append(diffractograms.pop())
-
-    return rev_diffractograms
-
-#def plot_heatmap():

environment.yml

@@ -0,0 +1,16 @@
+name: nafuma
+channels:
+  - diffpy
+  - defaults
+  - conda-forge
+dependencies:
+  - ipywidgets
+  - seaborn
+  - sympy
+  - matplotlib
+  - pytest
+  - numpy
+  - pandas
+  - palettable
+  - pyfai
+prefix: C:\Users\rasmusvt\Anaconda3\envs\nafuma

nafuma/auxillary.py

@@ -1,4 +1,5 @@
 import json
+import numpy as np
 
 def update_options(options, required_options, default_options):
     ''' Takes a dictionary of options along with a list of required options and dictionary of default options, and sets all keyval-pairs of options that is not already defined to the default values'''
@@ -37,6 +38,18 @@ def swap_values(dict, key1, key2):
 
 
 
-def hello_world2(a=1, b=2):
+def ceil(a, roundto=1):
 
-    print(f'Halla, MAFAKKAS! a = {a} og b = {b}')
+    fac = 1/roundto
+
+    a = np.ceil(a*fac) / fac
+
+    return a
+
+def floor(a, roundto=1):
+
+    fac = 1/roundto
+
+    a = np.floor(a*fac) / fac
+
+    return a

nafuma/electrochemistry/plot.py

@@ -5,7 +5,7 @@ import pandas as pd
 import numpy as np
 import math
 
-import beamtime.electrochemistry as ec
+import nafuma.electrochemistry as ec
 
 
 def plot_gc(path, kind, options=None):

nafuma/plotting.py

@@ -1,13 +1,11 @@
-import beamtime.auxillary as aux
+import nafuma.auxillary as aux
 
 import matplotlib.pyplot as plt
-from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,AutoMinorLocator)
+from matplotlib.ticker import (MultipleLocator)
-from mpl_toolkits.axes_grid.inset_locator import (inset_axes, InsetPosition, mark_inset)
 import importlib
 import matplotlib.patches as mpatches
 from matplotlib.lines import Line2D
 import matplotlib.lines as mlines
-from cycler import cycler
 import itertools
 
 
@@ -22,8 +20,15 @@ def prepare_plot(options={}):
     
     format_params will determine the size, aspect ratio, resolution etc. of the figure. Should be modified to conform with any requirements from a journal.'''
 
-    rc_params = options['rc_params']
+    if 'rc_params' in options.keys():
-    format_params = options['format_params']
+        rc_params = options['rc_params']
+    else:
+        rc_params = {}
+
+    if 'format_params' in options.keys():
+        format_params = options['format_params']
+    else:
+        format_params = {}
     
     required_format_params = ['single_column_width', 'double_column_width', 'column_type', 'width_ratio', 'aspect_ratio', 
     'width', 'height', 'compress_width', 'compress_height', 'upscaling_factor', 'dpi',
@@ -82,53 +87,14 @@ def prepare_plot(options={}):
 
         return fig, axes
 
-def prepare_plots(options={}):
-
-    rc_params = options['rc_params']
-    format_params = options['format_params']
-    
-    required_options = ['single_column_width', 'double_column_width', 'column_type', 'width_ratio', 'aspect_ratio', 'compress_width', 'compress_height', 'upscaling_factor', 'dpi']
-
-    default_options = {
-    'single_column_width': 8.3,
-    'double_column_width': 17.1,
-    'column_type': 'single',
-    'width_ratio': '1:1',
-    'aspect_ratio': '1:1',
-    'compress_width': 1,
-    'compress_height': 1,
-    'upscaling_factor': 1.0,
-    'dpi': 600, 
-    }
-    
-    format_params = aux.update_options(format_params, required_options, default_options)
-
-
-    # Reset run commands
-    plt.rcdefaults()
-    
-    # Update run commands if any is passed (will pass an empty dictionary if not passed)
-    update_rc_params(rc_params)
-    
-    width = determine_width(format_params)
-    height = determine_height(format_params, width)
-    width, height = scale_figure(options=format_params, width=width, height=height)
-
-
-    if options['plot_kind'] == 'relative':
-        fig, axes = plt.subplots(nrows=1, ncols=options['number_of_frames'], figsize=(width,height), facecolor='w', dpi=format_params['dpi'])
-
-    elif options['plot_kind'] == 'absolute':
-        fig, axes = plt.subplots(nrows=2, ncols=options['number_of_frames'], figsize=(width,height), gridspec_kw={'height_ratios': [1,5]}, facecolor='w', dpi=format_params['dpi'])
-    
-    return fig, axes
-
 
 def adjust_plot(fig, ax, options):
     ''' A general function to adjust plot according to contents of the options-dictionary '''
     
     required_options = [
     'plot_kind', 
+    'xlabel', 'ylabel',
+    'xunit', 'yunit',
     'hide_x_labels', 'hide_y_labels',
     'hide_x_ticklabels', 'hide_y_ticklabels',
     'hide_x_ticks', 'hide_y_ticks',
@@ -143,6 +109,8 @@ def adjust_plot(fig, ax, options):
 
     default_options = {
         'plot_kind': None, # defaults to None, but should be utilised when requiring special formatting for a particular plot 
+        'xlabel': None, 'ylabel': None,
+        'xunit': None, 'yunit': None,
         'hide_x_labels': False, 'hide_y_labels': False, # Whether the main labels on the x- and/or y-axes should be hidden
         'hide_x_ticklabels': False, 'hide_y_ticklabels': False, # Whether ticklabels on the x- and/or y-axes should be hidden
         'hide_x_ticks': False, 'hide_y_ticks': False, # Whether the ticks on the x- and/or y-axes should be hidden
@@ -182,10 +150,10 @@ def adjust_plot(fig, ax, options):
         ax.xaxis.set_minor_locator(MultipleLocator(options['x_tick_locators'][1]))
 
     
-    # THIS NEEDS REWORK FOR IT TO FUNCTION PROPERLY!
+    # FIXME THIS NEEDS REWORK FOR IT TO FUNCTION PROPERLY!
-    if options['xticks']:
+    #if options['xticks']:
-        ax.set_xticks(np.arange(plot_data['start'], plot_data['end']+1))
+    #    ax.set_xticks(np.arange(plot_data['start'], plot_data['end']+1))
-        ax.set_xticklabels(options['xticks'])
+    #    ax.set_xticklabels(options['xticks'])
     # else:
     #     ax.set_xticks(np.arange(plot_data['start'], plot_data['end']+1))
     #     ax.set_xticklabels([x/2 for x in np.arange(plot_data['start'], plot_data['end']+1)])
@@ -307,17 +275,6 @@ def ipywidgets_update(func, data, options={}, **kwargs):
     func(data=data, options=options)
 
 
-def update_widgets(options):
-
-    for widget in options['widgets'].values():
-
-        if widget['state'] != options['x_vals']:
-            for arg in widget[f'{options["x_vals"]}_default']:
-                setattr(widget['w'], arg, widget[f'{options["x_vals"]}_default'][arg])
-            
-            widget['state'] = options['x_vals']
-
-
 
 def determine_width(format_params):
     ''' '''
@@ -366,16 +323,20 @@ def update_rc_params(rc_params):
             plt.rcParams.update({key: rc_params[key]})
 
 
-def generate_colours(palettes):
+def generate_colours(palettes, kind=None):
 
-    # Creates a list of all the colours that is passed in the colour_cycles argument. Then makes cyclic iterables of these. 
+    if kind == 'single':
-    colour_collection = []
+        colour_cycle = itertools.cycle(palettes)
-    for palette in palettes:
-        mod = importlib.import_module("palettable.colorbrewer.%s" % palette[0])
-        colour = getattr(mod, palette[1]).mpl_colors
-        colour_collection = colour_collection + colour
 
-    colour_cycle = itertools.cycle(colour_collection)
+    else:
+        # Creates a list of all the colours that is passed in the colour_cycles argument. Then makes cyclic iterables of these. 
+        colour_collection = []
+        for palette in palettes:
+            mod = importlib.import_module("palettable.colorbrewer.%s" % palette[0])
+            colour = getattr(mod, palette[1]).mpl_colors
+            colour_collection = colour_collection + colour
+
+        colour_cycle = itertools.cycle(colour_collection)
 
 
     return colour_cycle

nafuma/test/pytest.ini

@@ -0,0 +1,9 @@
+# pytest.ini
+
+[pytest]
+minversion = 6.0
+testpaths = 
+	.
+
+filterwarnings =
+	ignore::DeprecationWarning

nafuma/test/test_auxillary.py

@@ -0,0 +1,78 @@
+import nafuma.auxillary as aux
+import os
+
+def test_swap_values():
+
+
+    dict = {'test1': 1, 'test2': 2}
+    key1 = 'test1'
+    key2 = 'test2'
+
+    oldval1 = dict[key1]
+    oldval2 = dict[key2]
+
+    new_dict = aux.swap_values(dict=dict, key1=key1, key2=key2) 
+
+    assert (dict[key1] == oldval2) and (dict[key2] == oldval1)
+
+
+def test_ceil() -> None:
+
+    assert aux.ceil(1.05, 0.5) == 1.5
+    assert aux.ceil(1.05, 1) == 2.0
+    assert aux.ceil(1.1, 0.2) == 1.2
+
+
+def test_floor() -> None:
+
+    assert aux.floor(2.02, 1) == 2.0
+    assert aux.floor(2.02, 0.01) == 2.02
+    assert aux.floor(2.013, 0.01) == 2.01
+
+
+
+def test_options() -> None:
+
+
+    options = {}
+    required_options = ['test1', 'test2', 'test3', 'test4']
+    default_options = {
+        'test1': 1,
+        'test2': 2, 
+        'test3': 3,
+        'test4': 4,
+        'test5': 5,
+    }
+
+
+    options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
+
+    assert options['test1'] == default_options['test1']
+    assert len(options.items()) == len(required_options)
+    assert 'test5' not in options.keys()
+
+
+def test_save_options() -> None:
+    
+    options = {'test1': 1, 'test2': 2}
+    path = 'tmp.dat'
+
+    aux.save_options(options, path)
+
+    assert os.path.isfile(path)
+
+    os.remove(path)
+
+
+def test_load_options() -> None:
+    
+    options = {'test1': 1, 'test2': 2}
+    path = 'tmp.dat'
+
+    aux.save_options(options, path)
+
+    loaded_options = aux.load_options(path)
+
+    assert (loaded_options['test1'] == 1) and (loaded_options['test2'] == 2)
+
+    os.remove(path)

nafuma/test/test_plotting.py

@@ -0,0 +1,181 @@
+import nafuma.plotting as btp
+from cycler import cycler
+import itertools
+import numpy as np
+
+import matplotlib.pyplot as plt
+import matplotlib as mpl
+
+
+def test_generate_colours() -> None:
+
+    assert type(btp.generate_colours('black', kind='single')) == itertools.cycle
+
+    palettes = [('qualitative', 'Dark2_8')]
+    colour_cycle = btp.generate_colours(palettes)
+
+    assert type(colour_cycle) == itertools.cycle
+
+
+    # Test that it actually loaded 8 colours when given a set of 8 colours to 
+
+    same_colour = None
+    for i in range(10):
+        colour = next(colour_cycle)
+        if i == 0:
+            first_colour = colour
+        
+        if colour == first_colour:
+            repeat_colour_index = i
+
+        
+    assert repeat_colour_index == 8
+
+
+
+
+def test_update_rc_params() -> None:
+
+    rc_params = {
+        'lines.linewidth': 100
+    }
+
+    prev_params = plt.rcParams['lines.linewidth']
+    
+    # Update run commands if any is passed (will pass an empty dictionary if not passed)
+    btp.update_rc_params(rc_params)
+
+    new_params = plt.rcParams['lines.linewidth']
+    
+    assert new_params == 100
+    assert prev_params != new_params
+
+
+    # Reset run commands
+    plt.rcdefaults()
+
+
+
+def test_scale_figure() -> None:
+
+    width, height = 1, 1
+
+    format_params = {
+        'upscaling_factor': 2,
+        'compress_width': 1,
+        'compress_height': 1
+    }
+
+    width1, height1 = btp.scale_figure(format_params=format_params, width=width, height=height)
+
+    assert width1 == 2 and height1 == 2
+
+    format_params = {
+        'upscaling_factor': 1,
+        'compress_width': 0.5,
+        'compress_height': 1
+    }
+
+    width2, height2 = btp.scale_figure(format_params=format_params, width=width, height=height)
+
+    assert width2 == 0.5 and height2 == 1
+
+    format_params = {
+        'upscaling_factor': 2,
+        'compress_width': 0.5,
+        'compress_height': 0.2
+    }
+
+    width2, height2 = btp.scale_figure(format_params=format_params, width=width, height=height)
+
+    assert width2 == 1 and height2 == 0.4
+
+    
+def test_determine_width() -> None:
+
+    conversion_cm_inch = 0.3937008 # cm to inch
+
+    format_params = {
+        'column_type': 'single',
+        'single_column_width': 5,
+        'double_column_width': 10,
+        'width_ratio': '1:1'
+    }
+
+    assert np.round(btp.determine_width(format_params),6) == np.round(5*conversion_cm_inch,6)
+    
+    format_params['column_type'] = 'double'
+
+    assert np.round(btp.determine_width(format_params), 6) == np.round(10*conversion_cm_inch, 6)
+    
+
+    format_params['column_type'] = 'single'
+    format_params['width_ratio'] = '1:2'
+
+    assert np.round(btp.determine_width(format_params), 6) == np.round(2.5*conversion_cm_inch, 6)
+
+def test_determine_height() -> None:
+
+
+    width = 1
+
+    format_params = {
+        'aspect_ratio': '1:1'
+    }
+
+    assert btp.determine_height(format_params=format_params, width=width) == 1
+
+    format_params['aspect_ratio'] = '3:1'
+
+    assert (btp.determine_height(format_params=format_params, width=width) - 0.333333333333333) < 10e-7
+
+    assert True
+
+
+
+def test_prepare_plot() -> None:
+
+    fig, ax = btp.prepare_plot()
+
+    assert type(fig) == plt.Figure
+    assert fig.get_dpi() == 600
+    assert ax.get_xlim() == (0.0, 1.0)
+
+
+
+def test_adjust_plot() -> None:
+
+    fig, ax = btp.prepare_plot()
+
+    options = {
+        'xlim': (0.0, 2.0),
+        'title': 'Test'
+    }
+
+    fig, ax = btp.adjust_plot(fig, ax, options)
+
+
+    assert ax.get_xlim() == (0.0, 2.0)
+    assert ax.get_title() == 'Test'
+
+
+    
+def test_ipywidgets_update() -> None:
+
+
+
+    def test_func(data, options):
+        test1 = options['test1']
+        test2 = options['test2']
+
+        assert type(data) == dict
+        assert test1 == 1
+        assert test2 == 2
+
+
+
+    data = {}
+    options = {}
+
+    btp.ipywidgets_update(func=test_func, data=data, options=options, test1=1, test2=2)
+

nafuma/xanes/calib.py

@@ -24,6 +24,7 @@ def finding_edge(df):
         edge='Ni'
         return(edge)
 
+<<<<<<< HEAD:beamtime/xanes/calib.py
 #def pre_edge_subtraction(df,filenames, options={}):
 def test(innmat):
     df_test= xas.io.put_in_dataframe(innmat)
@@ -40,6 +41,11 @@ def pre_edge_subtraction(path, options={}):
     filenames = xas.io.get_filenames(path)
     df= xas.io.put_in_dataframe(path)
     edge=finding_edge(df)
+=======
+def split_xanes_scan(filename, destination=None, replace=False):
+    #root is the path to the beamtime-folder
+    #destination should be the path to the processed data
+>>>>>>> master:nafuma/xanes/calib.py
     
     #Defining the end of the region used to define the background, thus start of the edge
     #implement widget

nafuma/xrd/io.py

@@ -9,7 +9,7 @@ import zipfile
 import xml.etree.ElementTree as ET
 
 
-import beamtime.auxillary as aux
+import nafuma.auxillary as aux
 
 
 def get_image_array(path):
@@ -27,7 +27,7 @@ def get_image_headers(path):
     return image.header
 
 
-def integrate_1d(data, options={}):
+def integrate_1d(data, options={}, index=0):
     ''' Integrates an image file to a 1D diffractogram. 
 
     Required content of data:
@@ -40,10 +40,12 @@ def integrate_1d(data, options={}):
     df: DataFrame contianing 1D diffractogram if option 'return' is True
     ''' 
 
-    required_options = ['unit', 'save', 'save_filename', 'save_extension', 'save_folder', 'overwrite']
+    required_options = ['unit', 'nbins', 'save', 'save_filename', 'save_extension', 'save_folder', 'overwrite', 'extract_folder']
 
     default_options = {
         'unit': '2th_deg', 
+        'nbins': 3000,
+        'extract_folder': 'tmp',
         'save': False,
         'save_filename': None,
         'save_extension': '_integrated.xy',
@@ -51,51 +53,57 @@ def integrate_1d(data, options={}):
         'overwrite': False}
 
     options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
+
+    if not isinstance(data['path'], list):
+        data['path'] = [data['path']]
     
 
     # Get image array from filename if not passed
     if 'image' not in data.keys():
-        data['image'] = get_image_array(data['path'])
+        data['image'] = get_image_array(data['path'][index])
     
     # Instanciate the azimuthal integrator from pyFAI from the calibrant (.poni-file)
     ai = pyFAI.load(data['calibrant'])
 
     # Determine filename
-    filename = make_filename(data=data, options=options)
+    filename = make_filename(options=options, path=data['path'][index])
     
     # Make save_folder if this does not exist already
-    if not os.path.isdir(options['save_folder']):
+    if not os.path.isdir(options['extract_folder']):
-        os.makedirs(options['save_folder'])
+        os.makedirs(options['extract_folder'])
 
 
-    res = ai.integrate1d(data['image'], data['nbins'], unit=options['unit'], filename=filename)
+    res = ai.integrate1d(data['image'], options['nbins'], unit=options['unit'], filename=filename)
 
-    data['path'] = filename
+    data['path'][index] = filename
-    diffractogram = read_xy(data=data, options=options)
+    diffractogram, wavelength = read_xy(data=data, options=options, index=index)
 
     if not options['save']:
         os.remove(filename)
-        shutil.rmtree('tmp')
+        shutil.rmtree(f'tmp')
+
+
+    # Reset this option
+    options['save_folder'] = None
     
-    return diffractogram
+    return diffractogram, wavelength
     
 
 
-def make_filename(data, options):
+def make_filename(options, path=None):
 
     # Define save location for integrated diffractogram data
     if not options['save']:
-            options['save_folder'] = 'tmp'
+            filename = os.path.join(options['extract_folder'], 'tmp_diff.dat')
-            filename = os.path.join(options['save_folder'], 'tmp_diff.dat')
 
     elif options['save']:
 
         # Case 1: No filename is given. 
         if not options['save_filename']:
             # If a path is given instead of an image array, the path is taken as the trunk of the savename
-            if data['path']:
+            if path:
                 # Make filename by joining the save_folder, the filename (with extension deleted) and adding the save_extension
-                filename = os.path.join(options['save_folder'], os.path.split(data['path'])[-1].split('.')[0] + options['save_extension'])
+                filename = os.path.join(options['save_folder'], os.path.split(path)[-1].split('.')[0] + options['save_extension'])
             else:
                 # Make filename just "integrated.dat" in the save_folder
                 filename = os.path.join(options['save_folder'], 'integrated.xy')
@@ -141,7 +149,7 @@ def average_images(images):
     image_arrays = []
 
     for image in images:
-        image_array = xrd.io.get_image_array(image)
+        image_array = get_image_array(image)
         image_arrays.append(image_array)
     
     
@@ -176,7 +184,10 @@ def view_integrator(calibrant):
 
 
 
-def read_brml(data, options={}):
+def read_brml(data, options={}, index=0):
+
+
+    # FIXME: Can't read RECX1-data, apparently must be formatted differently from RECX2. Check the RawData-files and compare between the two files.
 
 
     required_options = ['extract_folder', 'save_folder']
@@ -194,7 +205,7 @@ def read_brml(data, options={}):
 
 
     # Extract the RawData0.xml file from the brml-file
-    with zipfile.ZipFile(data['path'], 'r') as brml:
+    with zipfile.ZipFile(data['path'][index], 'r') as brml:
         for info in brml.infolist():
             if "RawData" in info.filename:
                 brml.extract(info.filename, options['extract_folder'])
@@ -213,31 +224,66 @@ def read_brml(data, options={}):
 
     for chain in root.findall('./DataRoutes/DataRoute'):
 
-        for scantype in chain.findall('ScanInformation/ScanMode'):
-            if scantype.text == 'StillScan':
 
-                if chain.get('Description') == 'Originally measured data.':
+        # Get the scan type to be able to handle different data formats
-                    for scandata in chain.findall('Datum'):
+        scantype = chain.findall('ScanInformation')[0].get('VisibleName')
+
+        # Check if the chain is the right one to extract the data from
+        if chain.get('Description') == 'Originally measured data.':
+            
+            
+            if scantype == 'TwoTheta':
+                for scandata in chain.findall('Datum'):
+                    scandata = scandata.text.split(',')
+                    twotheta, intensity = float(scandata[2]), float(scandata[3])
+                    
+                    if twotheta > 0:
+                        diffractogram.append({'2th': twotheta, 'I': intensity})
+
+            elif scantype == 'Coupled TwoTheta/Theta':
+                for scandata in chain.findall('Datum'):
+                    scandata = scandata.text.split(',')
+                    twotheta, intensity = float(scandata[2]), float(scandata[4])
+                    
+                    if twotheta > 0:
+                        diffractogram.append({'2th': twotheta, 'I': intensity})
+
+            elif scantype == 'Still (Eiger2R_500K (1D mode))':
+
+                start = float(chain.findall('ScanInformation/ScaleAxes/ScaleAxisInfo/Start')[0].text)
+                stop = float(chain.findall('ScanInformation/ScaleAxes/ScaleAxisInfo/Stop')[0].text)
+                
+
+
+
+                for scandata in chain.findall('Datum'):
                         scandata = scandata.text.split(',')
-                        scandata = [float(i) for i in scandata]
+                        raw = [float(i) for i in scandata]
-                        twotheta, intensity = float(scandata[2]), float(scandata[3])
 
-        
+                        intensity = []
-            else:
+                        for r in raw:
-                if chain.get('Description') == 'Originally measured data.':
+                            if r > 601:
-                    for scandata in chain.findall('Datum'):
+                                intensity.append(r)
-                        scandata = scandata.text.split(',')
+
-                        twotheta, intensity = float(scandata[2]), float(scandata[3])
+                        intensity = np.array(intensity)
-                        
+
-                        if twotheta > 0:
+            
-                            diffractogram.append({'2th': twotheta, 'I': intensity})
+             
+
+                twotheta = np.linspace(start, stop, len(intensity))
+
+                diffractogram = {'2th': twotheta, 'I': intensity}
 
 
-    if 'wavelength' not in data.keys():
+
-        for chain in root.findall('./FixedInformation/Instrument/PrimaryTracks/TrackInfoData/MountedOptics/InfoData/Tube/WaveLengthAlpha1'):
+    #if 'wavelength' not in data.keys():
-            data['wavelength'] = float(chain.attrib['Value'])
+    # Find wavelength
+    for chain in root.findall('./FixedInformation/Instrument/PrimaryTracks/TrackInfoData/MountedOptics/InfoData/Tube/WaveLengthAlpha1'):
+        wavelength = float(chain.attrib['Value'])
+
 
     diffractogram = pd.DataFrame(diffractogram)
+    
 
 
 
@@ -249,15 +295,16 @@ def read_brml(data, options={}):
 
 
 
-    return diffractogram
+    return diffractogram, wavelength
     
 
-def read_xy(data, options={}):
+def read_xy(data, options={}, index=0):
     
-    if 'wavelength' not in data.keys():
+    #if 'wavelength' not in data.keys():
-            find_wavelength_from_xy(data=data)
+    # Get wavelength from scan
+    wavelength = find_wavelength_from_xy(path=data['path'][index])
 
-    with open(data['path'], 'r') as f:
+    with open(data['path'][index], 'r') as f:
         position = 0
 
         current_line = f.readline()
@@ -276,37 +323,89 @@ def read_xy(data, options={}):
         diffractogram.columns = ['2th', 'I', 'sigma']
 
 
-    return diffractogram
+    return diffractogram, wavelength
 
 
-def read_data(data, options={}):
+def read_data(data, options={}, index=0):
 
     beamline_extensions = ['mar3450', 'edf', 'cbf']
-    file_extension = data['path'].split('.')[-1]
+    file_extension = data['path'][index].split('.')[-1]
 
     if file_extension in beamline_extensions:
-        diffractogram = integrate_1d(data=data, options=options)
+        diffractogram, wavelength = integrate_1d(data=data, options=options, index=index)
         
     elif file_extension == 'brml':
-        diffractogram = read_brml(data=data, options=options)
+        diffractogram, wavelength = read_brml(data=data, options=options, index=index)
 
     elif file_extension in['xy', 'xye']:
-        diffractogram = read_xy(data=data, options=options)
+        diffractogram, wavelength = read_xy(data=data, options=options, index=index)
 
 
-    diffractogram = translate_wavelengths(data=diffractogram, wavelength=data['wavelength'])
+
+
+    if options['offset'] or options['normalise']:
+        # Make copy of the original intensities before any changes are made through normalisation or offset, to easily revert back if need to update.
+        diffractogram['I_org'] = diffractogram['I']
+        diffractogram['2th_org'] = diffractogram['2th']
+        
+        diffractogram = apply_offset(diffractogram, wavelength, index, options)
+
+
+    diffractogram = translate_wavelengths(data=diffractogram, wavelength=wavelength)
+
+    return diffractogram, wavelength
+
+
+def apply_offset(diffractogram, wavelength, index, options):
+
+    if 'current_offset_y' not in options.keys():
+        options['current_offset_y'] = options['offset_y']
+    else:
+        if options['current_offset_y'] != options['offset_y']:
+            options['offset_change'] = True
+        
+        options['current_offset_y'] = options['offset_y']
+
+    options['current_offset_x'] = options['offset_x']
+
+    
+
+    #Apply offset along y-axis
+    diffractogram['I'] = diffractogram['I_org'] # Reset intensities
+
+    if options['normalise']:
+        diffractogram['I'] = diffractogram['I'] / diffractogram['I'].max()
+
+    diffractogram['I'] = diffractogram['I'] + index*options['offset_y']
+
+    # Apply offset along x-axis
+    relative_shift = (wavelength / 1.54059)*options['offset_x'] # Adjusts the offset-factor to account for wavelength, so that offset_x given is given in 2th_cuka-units
+    diffractogram['2th'] = diffractogram['2th_org']
+    diffractogram['2th'] = diffractogram['2th'] + index*relative_shift
+
 
     return diffractogram
-                
 
+def revert_offset(diffractogram,which=None):
 
+    if which == 'both':
+        diffractogram['2th'] = diffractogram['2th_org']
+        diffractogram['I'] = diffractogram['I_org']
+        
+    if which == 'y':
+        diffractogram['I'] = diffractogram['I_org']
+    
+    if which == 'x':
+        diffractogram['2th'] = diffractogram['2th_org']
 
-def load_reflection_table(data, options={}):
+    return diffractogram
 
-    required_options = ['wavelength', 'to_wavelength']
+def load_reflection_table(data: dict, reflections_params: dict, options={}):
+
+    required_options = ['ref_wavelength', 'to_wavelength']
 
     default_options = {
-        'wavelength': 1.54059,
+        'ref_wavelength': 1.54059,
         'to_wavelength': None
     }
 
@@ -314,12 +413,12 @@ def load_reflection_table(data, options={}):
 
     # VESTA outputs the file with a header that has a space between the parameter and units - so there is some extra code to rectify the issue
     # that ensues from this formatting
-    reflections = pd.read_csv(data['path'], delim_whitespace=True)
+    reflections = pd.read_csv(reflections_params['path'], delim_whitespace=True)
 
     # Remove the extra column that appears from the headers issue
     reflections.drop(reflections.columns[-1], axis=1, inplace=True)
 
-    with open(data['path'], 'r') as f:
+    with open(reflections_params['path'], 'r') as f:
         line = f.readline()
 
         headers = line.split()
@@ -333,15 +432,32 @@ def load_reflection_table(data, options={}):
     # Set the new modified headers as the headers of 
     reflections.columns = headers
 
-    reflections = translate_wavelengths(data=reflections, wavelength=options['wavelength'], to_wavelength=options['to_wavelength'])
+    reflections = translate_wavelengths(data=reflections, wavelength=options['ref_wavelength'], to_wavelength=options['to_wavelength'])
 
-    #print(reflections)
+    if 'heatmap' in data.keys():
+        
+        start_2th, stop_2th = data['diffractogram'][0]['2th'].min(), data['diffractogram'][0]['2th'].max()
+        len_2th = stop_2th - start_2th 
+        #print(start_2th, stop_2th, len_2th)
+        
+        start_heatmap, stop_heatmap = 0, data['heatmap'].shape[1]
+        len_heatmap = stop_heatmap - start_heatmap
+        #print(start_heatmap, stop_heatmap, len_heatmap)
+
+        scale = len_heatmap/len_2th
+
+        #print(scale)
+        #print(stop_2th * scale)
+
+        reflections['heatmap'] = (reflections['2th']-start_2th) * scale
 
     return reflections
 
 
 
-def translate_wavelengths(data, wavelength, to_wavelength=None):
+def translate_wavelengths(data: pd.DataFrame, wavelength: float, to_wavelength=None) -> pd.DataFrame:
+    # FIXME Somewhere here there is an invalid arcsin-argument. Not sure where.
+
     pd.options.mode.chained_assignment = None
 
     # Translate to CuKalpha
@@ -378,8 +494,7 @@ def translate_wavelengths(data, wavelength, to_wavelength=None):
 
 
     if to_wavelength:
-        
+        if to_wavelength >= cuka:
-        if to_wavelength > cuka:
             max_2th = 2*np.arcsin(cuka/to_wavelength) * 180/np.pi
         else:
             max_2th = data['2th_cuka'].max()
@@ -395,19 +510,24 @@ def translate_wavelengths(data, wavelength, to_wavelength=None):
 
 
 
-def find_wavelength_from_xy(data):
+def find_wavelength_from_xy(path):
+
 
- 
     wavelength_dict = {'Cu': 1.54059, 'Mo': 0.71073}
 
-    with open(data['path'], 'r') as f:
+    with open(path, 'r') as f:
         lines = f.readlines()
 
         for line in lines:
+            # For .xy-files output from EVA
             if 'Anode' in line:
                 anode = line.split()[8].strip('"')
-                data['wavelength'] = wavelength_dict[anode]
+                wavelength = wavelength_dict[anode]
 
+            # For .xy-files output from pyFAI integration
             elif 'Wavelength' in line:
-                data['wavelength'] = float(line.split()[2])*10**10
+                wavelength = float(line.split()[2])*10**10
 
+
+
+    return wavelength

nafuma/xrd/plot.py

@@ -0,0 +1,672 @@
+import seaborn as sns
+import matplotlib.pyplot as plt
+from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,AutoMinorLocator)
+
+import pandas as pd
+import numpy as np
+import math
+
+import ipywidgets as widgets
+from IPython.display import display
+
+import nafuma.xrd as xrd
+import nafuma.auxillary as aux
+import nafuma.plotting as btp
+
+
+def plot_diffractogram(data, options={}):
+    ''' Plots a diffractogram.
+    
+    Input:
+    data (dict): Must include path = string to diffractogram data, and plot_kind = (recx, beamline, image)'''
+
+    # Update options
+    required_options = ['x_vals', 'y_vals', 'ylabel', 'xlabel', 'xunit', 'yunit', 'line', 'scatter', 'xlim', 'ylim', 'normalise', 'offset', 'offset_x', 'offset_y', 'offset_change',
+    'reflections_plot', 'reflections_indices', 'reflections_data', 'heatmap', 'cmap', 'plot_kind', 'palettes', 'interactive', 'rc_params', 'format_params', 'interactive_session_active']
+
+    default_options = {
+        'x_vals': '2th', 
+        'y_vals': 'I',
+        'ylabel': 'Intensity', 'xlabel': '2theta', 
+        'xunit': 'deg', 'yunit': 'a.u.',
+        'xlim': None, 'ylim': None, 
+        'normalise': True,
+        'offset': True,
+        'offset_x': 0,
+        'offset_y': 1,
+        'offset_change': False,
+        'line': True, # whether or not to plot diffractogram as a line plot
+        'scatter': False, # whether or not to plot individual data points
+        'reflections_plot': False, # whether to plot reflections as a plot
+        'reflections_indices': False, # whether to plot the reflection indices
+        'reflections_data': None, # Should be passed as a list of dictionaries on the form {path: rel_path, reflection_indices: number of indices, colour: [r,g,b], min_alpha: 0-1]
+        'heatmap': False,
+        'cmap': 'viridis',
+        'plot_kind': None,
+        'palettes': [('qualitative', 'Dark2_8')],
+        'interactive': False,
+        'interactive_session_active': False,
+        'rc_params': {},
+        'format_params': {},
+        }
+
+    if 'offset_y' not in options.keys():
+        if len(data['path']) > 10:
+            default_options['offset_y'] = 0.05
+
+    options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
+    #options['current_offset_y'] = options['offset_y']
+
+    # Convert data['path'] to list to allow iteration over this to accommodate both single and multiple diffractograms
+    if not isinstance(data['path'], list):
+        data['path'] = [data['path']]
+
+   
+
+    # Check if there is some data stored already, load in data if not. This speeds up replotting in interactive mode.
+    if not 'diffractogram' in data.keys():
+        # Initialise empty list for diffractograms and wavelengths
+        data['diffractogram'] = [None for _ in range(len(data['path']))]
+        data['wavelength'] = [None for _ in range(len(data['path']))]
+
+        for index in range(len(data['path'])):
+            diffractogram, wavelength = xrd.io.read_data(data=data, options=options, index=index)
+            
+            data['diffractogram'][index] = diffractogram
+            data['wavelength'][index] = wavelength
+
+        # Sets the xlim if this has not bee specified
+        if not options['xlim']:
+            options['xlim'] = [data['diffractogram'][0][options['x_vals']].min(), data['diffractogram'][0][options['x_vals']].max()]
+
+        # Generate heatmap data
+        data['heatmap'], data['heatmap_xticks'], data['heatmap_xticklabels'] = generate_heatmap(data=data, options=options)
+        options['heatmap_loaded'] = True
+
+        if options['heatmap']:
+            options['xlim'] = options['heatmap_xlim']
+
+    else:
+        if not isinstance(data['diffractogram'], list):
+            data['diffractogram'] = [data['diffractogram']]
+            data['wavelength'] = [data['wavelength']]
+
+
+
+    if options['interactive_session_active']:
+        if options['offset']:
+            if (options['offset_x'] != options['current_offset_x']) or (options['offset_y'] != options['current_offset_y']):
+                for i, (diff, wl) in enumerate(zip(data['diffractogram'], data['wavelength'])):
+                    xrd.io.apply_offset(diff, wl, i, options)
+
+
+    # Start inteactive session with ipywidgets. Disables options['interactive'] in order for the interactive loop to not start another interactive session
+    if options['interactive']:
+        options['interactive'] = False
+        options['interactive_session_active'] = True
+        plot_diffractogram_interactive(data=data, options=options)
+        return
+    
+    
+    # Makes a list out of reflections_data if it only passed as a dict, as it will be looped through later
+    if options['reflections_data']:
+        if not isinstance(options['reflections_data'], list):
+            options['reflections_data'] = [options['reflections_data']]
+
+    # Determine number of subplots and height ratios between them
+    if len(options['reflections_data']) >= 1:
+        options = determine_grid_layout(options=options)
+
+
+    # Prepare plot, and read and process data
+    fig, ax = btp.prepare_plot(options=options)
+
+
+    # Assign the correct axes
+    if options['reflections_plot'] or options['reflections_indices']:
+        
+        if options['reflections_indices']:
+            indices_ax = ax[0]
+
+            if options['reflections_plot']:
+                ref_axes = [axx for axx in ax[range(1,len(options['reflections_data'])+1)]]
+
+        else:
+            ref_axes = [axx for axx in ax[range(0,len(options['reflections_data']))]]
+
+        ax = ax[-1]
+
+    if len(data['path']) < 10:
+        colours = btp.generate_colours(options['palettes'])
+    else:
+        colours = btp.generate_colours(['black'], kind='single')
+
+    if options['heatmap']:
+        sns.heatmap(data['heatmap'], cmap=options['cmap'], cbar=False, ax=ax)
+        ax.set_xticks(data['heatmap_xticks'][options['x_vals']])
+        ax.set_xticklabels(data['heatmap_xticklabels'][options['x_vals']])
+        ax.tick_params(axis='x', which='minor', bottom=False, top=False)
+
+    else:
+        for diffractogram in data['diffractogram']:
+            if options['line']:
+                diffractogram.plot(x=options['x_vals'], y=options['y_vals'], ax=ax, c=next(colours), zorder=1)
+        
+            if options['scatter']:
+                ax.scatter(x=diffractogram[options['x_vals']], y = diffractogram[options['y_vals']], c=[(1,1,1,0)], edgecolors=[next(colours)], linewidths=plt.rcParams['lines.markeredgewidth'], zorder=2) #, edgecolors=np.array([next(colours)]))
+
+
+
+    fig, ax = btp.adjust_plot(fig=fig, ax=ax, options=options)
+
+    
+
+    # Make the reflection plots. By default, the wavelength of the first diffractogram will be used for these.
+    if options['reflections_plot'] and options['reflections_data']:
+        options['xlim'] = ax.get_xlim()
+        options['to_wavelength'] = data['wavelength'][0]
+        
+        for reflections_params, axis in zip(options['reflections_data'], ref_axes):
+            plot_reflection_table(data=data, reflections_params=reflections_params, ax=axis, options=options)
+
+    # Print the reflection indices. By default, the wavelength of the first diffractogram will be used for this.
+    if options['reflections_indices'] and options['reflections_data']:
+        options['xlim'] = ax.get_xlim()
+        options['to_wavelength'] = data['wavelength'][0]
+
+        for reflections_params in options['reflections_data']:
+            plot_reflection_indices(data=data, reflections_params=reflections_params, ax=indices_ax, options=options)
+
+
+    if options['interactive_session_active']:
+        options['current_y_offset'] = options['widget'].kwargs['offset_y']
+        update_widgets(data=data, options=options)
+
+
+
+    return data['diffractogram'], fig, ax
+
+
+
+def generate_heatmap(data, options={}):
+
+    required_options = ['x_tick_locators']
+
+    default_options = {
+        'x_tick_locators': [0.5, 0.1]
+    }
+
+    options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
+
+    twotheta = []
+    intensities = []
+    scans = []
+
+    for i, d in enumerate(data['diffractogram']):
+        twotheta = np.append(twotheta, d['2th'].to_numpy())
+        intensities = np.append(intensities, d['I'].to_numpy())
+        scans = np.append(scans, np.full(len(d['2th'].to_numpy()), int(i)))
+
+
+    heatmap = pd.DataFrame({'2th': twotheta, 'scan': scans, 'I': intensities})
+    xrd.io.translate_wavelengths(data=heatmap, wavelength=data['wavelength'][0])
+    min_dict = {'2th': heatmap['2th'].min(), '2th_cuka': heatmap['2th_cuka'].min(), '2th_moka': heatmap['2th_moka'].min(),
+                        'q': heatmap['q'].min(), 'q2': heatmap['q2'].min(), 'q4': heatmap['q4'].min(), '1/d': heatmap['1/d'].min()}
+
+    max_dict = {'2th': heatmap['2th'].max(), '2th_cuka': heatmap['2th_cuka'].max(), '2th_moka': heatmap['2th_moka'].max(),
+                        'q': heatmap['q'].max(), 'q2': heatmap['q2'].max(), 'q4': heatmap['q4'].max(), '1/d': heatmap['1/d'].max()}
+
+
+    ndatapoints = len(data['diffractogram'][0]['2th'])
+
+    xlims = [0, ndatapoints, 0, ndatapoints] # 0: xmin, 1: xmax, 2: xmin_start, 3: xmax_start
+    xticks = {}
+    xticklabels = {}
+
+    for xval in min_dict.keys():
+       
+       # Add xticks labels
+        
+        label_max = aux.floor(max_dict[xval], roundto=options['x_tick_locators'][0])
+        label_min = aux.ceil(min_dict[xval], roundto=options['x_tick_locators'][0])
+        label_steps = (label_max - label_min)/options['x_tick_locators'][0]
+
+        xticklabels[xval] = np.linspace(label_min, label_max, num=int(label_steps)+1)
+
+        # Add xticks
+        xval_span = max_dict[xval] - min_dict[xval]
+        steps = xval_span / ndatapoints
+        
+        
+        xticks_xval = []
+
+        for tick in xticklabels[xval]:
+            xticks_xval.append((tick-min_dict[xval])/steps)
+
+        xticks[xval] = xticks_xval
+
+
+    options['x_tick_locators'] = None
+
+    heatmap = heatmap.reset_index().pivot_table(index='scan', columns='2th', values='I')
+
+    options['heatmap_xlim'] = xlims
+
+
+    return heatmap, xticks, xticklabels
+
+
+
+
+
+
+
+# #results = np.transpose(np.vstack([twotheta, scans, intensities]))
+
+
+def determine_grid_layout(options):
+
+
+    nrows = 1 if not options['reflections_indices'] else 2
+
+    if options['reflections_plot']:
+        for reference in options['reflections_data']:
+            nrows += 1
+
+    options['format_params']['nrows'] = nrows
+    options['format_params']['grid_ratio_height'] = [1 for i in range(nrows-1)]+[10]
+
+    return options
+
+
+
+
+
+def plot_diffractogram_interactive(data, options):
+
+
+    # Format here is xminmax[0]: xmin, xminmax[1]: xmax, xminmax[2]: xmin_start, xminmax[3]: xmax_start, where "_start" denotes starting value of the slider
+    xminmax = { '2th':      [None, None, None, None], '2th_cuka':   [None, None, None, None],   '2th_moka':     [None, None, None, None], 
+                'd':        [None, None, None, None], '1/d':        [None, None, None, None], 
+                'q':        [None, None, None, None], 'q2':         [None, None, None, None],   'q4':           [None, None, None, None], 
+                'heatmap':  [None, None, None, None], 'start':      [None, None, None, None]}
+
+    yminmax = { 'diff':     [None, None, None, None], 'heatmap':    [None, None, None, None],   'start':        [None, None, None, None]}
+    
+    update_xminmax(xminmax=xminmax, data=data, options=options)
+    update_yminmax(yminmax=yminmax, data=data, options=options)
+
+    options['xminmax'], options['yminmax'] = xminmax, yminmax
+
+    # Get start values for ylim slider based on choice (FIXME This can be impleneted into update_yminmax). Can also make a 'start' item that stores the start values, instead of having 4 items in 'diff' as it is now.
+    if options['heatmap']:
+        ymin = yminmax['heatmap'][0]
+        ymax = yminmax['heatmap'][1]
+        ymin_start = yminmax['heatmap'][0]
+        ymax_start = yminmax['heatmap'][1]
+
+    elif not options['heatmap']:
+        ymin = yminmax['diff'][0]
+        ymax = yminmax['diff'][1]
+        ymin_start = yminmax['diff'][2]
+        ymax_start = yminmax['diff'][3]
+
+    
+    # FIXME The start values for xlim should probably also be decided by initial value of x_vals, and can likewise be implemented in update_xminmax() 
+
+
+        
+    options['widgets'] = {
+        'xlim': {
+            'w': widgets.FloatRangeSlider(value=[xminmax['start'][2], xminmax['start'][3]], min=xminmax['start'][0], max=xminmax['start'][1], step=0.5, layout=widgets.Layout(width='95%')),
+            'state': options['x_vals'],
+            '2th_default':      {'min': xminmax['2th'][0],          'max': xminmax['2th'][1],           'value': [xminmax['2th'][0],            xminmax['2th'][1]],             'step': 0.5},
+            '2th_cuka_default': {'min': xminmax['2th_cuka'][0],     'max': xminmax['2th_cuka'][1],      'value': [xminmax['2th_cuka'][0],       xminmax['2th_cuka'][1]],        'step': 0.5},
+            '2th_moka_default': {'min': xminmax['2th_moka'][0],     'max': xminmax['2th_moka'][1],      'value': [xminmax['2th_moka'][0],       xminmax['2th_moka'][1]],        'step': 0.5},
+            'd_default':        {'min': xminmax['d'][0],            'max': xminmax['d'][1],             'value': [xminmax['d'][0],              xminmax['d'][1]],               'step': 0.5},
+            '1/d_default':      {'min': xminmax['1/d'][0],          'max': xminmax['1/d'][1],           'value': [xminmax['1/d'][0],            xminmax['1/d'][1]],             'step': 0.5},
+            'q_default':        {'min': xminmax['q'][0],            'max': xminmax['q'][1],             'value': [xminmax['q'][0],              xminmax['q'][1]],               'step': 0.5},
+            'q2_default':       {'min': xminmax['q2'][0],           'max': xminmax['q2'][1],            'value': [xminmax['q2'][0],             xminmax['q2'][1]],              'step': 0.5},
+            'q4_default':       {'min': xminmax['q4'][0],           'max': xminmax['q4'][1],            'value': [xminmax['q4'][0],             xminmax['q4'][1]],              'step': 0.5},
+            'heatmap_default':  {'min': xminmax['heatmap'][0],      'max': xminmax['heatmap'][1],       'value': [xminmax['heatmap'][0],        xminmax['heatmap'][1]],         'step': 10}
+        },
+        'ylim': { 
+            'w': widgets.FloatRangeSlider(value=[yminmax['start'][2], yminmax['start'][3]], min=yminmax['start'][0], max=yminmax['start'][1], step=0.5, layout=widgets.Layout(width='95%')),
+            'state': 'heatmap' if options['heatmap'] else 'diff',
+            'diff_default':     {'min': yminmax['diff'][0],         'max': yminmax['diff'][1],          'value': [yminmax['diff'][2],           yminmax['diff'][3]],            'step': 0.1},
+            'heatmap_default':  {'min': yminmax['heatmap'][0],      'max': yminmax['heatmap'][1],       'value': [yminmax['heatmap'][0],        yminmax['heatmap'][1]],         'step': 0.1}
+        }
+    }
+
+    if options['reflections_data']:
+        w = widgets.interactive(btp.ipywidgets_update, func=widgets.fixed(plot_diffractogram), data=widgets.fixed(data), options=widgets.fixed(options), 
+        scatter=widgets.ToggleButton(value=False), 
+        line=widgets.ToggleButton(value=True), 
+        reflections_plot=widgets.ToggleButton(value=True),
+        reflections_indices=widgets.ToggleButton(value=False),
+        heatmap=widgets.ToggleButton(value=options['heatmap']),
+        x_vals=widgets.Dropdown(options=['2th', 'd', '1/d', 'q', 'q2', 'q4', '2th_cuka', '2th_moka'], value='2th', description='X-values'),
+        xlim=options['widgets']['xlim']['w'],
+        ylim=options['widgets']['ylim']['w'],
+        offset_y=widgets.BoundedFloatText(value=options['offset_y'], min=-5, max=5, step=0.01, description='offset_y'),
+        offset_x=widgets.BoundedFloatText(value=options['offset_x'], min=-1, max=1, step=0.01, description='offset_x')
+        )
+    
+    else:
+        w = widgets.interactive(btp.ipywidgets_update, func=widgets.fixed(plot_diffractogram), data=widgets.fixed(data), options=widgets.fixed(options), 
+        scatter=widgets.ToggleButton(value=False), 
+        line=widgets.ToggleButton(value=True),
+        xlim=options['widgets']['xlim']['w'])
+    
+    
+    options['widget'] = w
+
+    display(w)
+
+
+def update_xminmax(xminmax, data, options={}):
+    ''' Finds minimum and maximum values of each column and updates the minmax dictionary to contain the correct values.
+    
+    Input:
+    minmax (dict): contains '''
+
+    xminmax['2th'] = [None, None, None, None]
+    for index, diffractogram in enumerate(data['diffractogram']):
+        
+        if not xminmax['2th'][0] or diffractogram['2th'].min() < xminmax['2th'][0]:
+            xminmax['2th'][0] = diffractogram['2th'].min()
+            min_index = index
+
+        if not xminmax['2th'][1] or diffractogram['2th'].max() > xminmax['2th'][1]:
+            xminmax['2th'][1] = diffractogram['2th'].max()
+            max_index = index
+
+
+    xminmax['2th'][2], xminmax['2th'][3] = xminmax['2th'][0], xminmax['2th'][1]
+
+    xminmax['2th_cuka'][0], xminmax['2th_cuka'][1]  = data['diffractogram'][min_index]['2th_cuka'].min(),  data['diffractogram'][max_index]['2th_cuka'].max()
+    xminmax['2th_cuka'][2], xminmax['2th_cuka'][3]  = xminmax['2th_cuka'][0], xminmax['2th_cuka'][1]
+
+    xminmax['2th_moka'][0], xminmax['2th_moka'][1]  = data['diffractogram'][min_index]['2th_moka'].min(),  data['diffractogram'][max_index]['2th_moka'].max()
+    xminmax['2th_moka'][2], xminmax['2th_moka'][3]  = xminmax['2th_moka'][0], xminmax['2th_moka'][1]
+
+    xminmax['d'][0], xminmax['d'][1]                = data['diffractogram'][max_index]['d'].min(),         data['diffractogram'][min_index]['d'].max() # swapped, intended
+    xminmax['d'][2], xminmax['d'][3]                = xminmax['d'][0], xminmax['d'][1]
+
+    xminmax['1/d'][0], xminmax['1/d'][1]            = data['diffractogram'][min_index]['1/d'].min(),       data['diffractogram'][max_index]['1/d'].max()
+    xminmax['1/d'][2], xminmax['1/d'][3]            = xminmax['1/d'][0], xminmax['1/d'][1]
+
+    xminmax['q'][0], xminmax['q'][1]                = data['diffractogram'][min_index]['q'].min(),         data['diffractogram'][max_index]['q'].max()
+    xminmax['q'][2], xminmax['q'][3]                = xminmax['q'][0], xminmax['q'][1]
+
+    xminmax['q2'][0], xminmax['q2'][1]              = data['diffractogram'][min_index]['q2'].min(),        data['diffractogram'][max_index]['q2'].max()
+    xminmax['q2'][2], xminmax['q2'][3]              = xminmax['q2'][0], xminmax['q2'][1]
+
+    xminmax['q4'][0], xminmax['q4'][1]              = data['diffractogram'][min_index]['q4'].min(),        data['diffractogram'][max_index]['q4'].max()
+    xminmax['q4'][2], xminmax['q4'][3]              = xminmax['q4'][0], xminmax['q4'][1]
+
+
+    xminmax['heatmap'] = options['heatmap_xlim'] # This value is set in the generate_heatmap()-function
+
+
+    xminmax['start'][0], xminmax['start'][1] = xminmax[options['x_vals']][0], xminmax[options['x_vals']][1]
+    xminmax['start'][2], xminmax['start'][3] = xminmax[options['x_vals']][2], xminmax[options['x_vals']][3]
+
+
+def update_yminmax(yminmax: dict, data: dict, options={}) -> None:
+    
+    yminmax['diff'] = [None, None, None, None]
+    # Go through diffractograms and find the minimum and maximum intensity values
+    for diffractogram in data['diffractogram']:
+        if not yminmax['diff'][0] or (yminmax['diff'][0] > (diffractogram['I'].min())): 
+            yminmax['diff'][0] = diffractogram['I'].min()
+
+        if not yminmax['diff'][1] or (yminmax['diff'][1] < (diffractogram['I'].max())):
+            yminmax['diff'][1] = diffractogram['I'].max()
+
+
+    # Set start values of ymin and ymax to be slightly below lowest data points and slightly above highest data points to give some whitespace around the plot
+    yminmax['diff'][2] = yminmax['diff'][0] - 0.1*yminmax['diff'][1]
+    yminmax['diff'][3] = yminmax['diff'][1] + 0.2*yminmax['diff'][1]
+    
+    # Allow for adjustment up to five times ymax above and below data
+    yminmax['diff'][0] = yminmax['diff'][0] - 5*yminmax['diff'][1]
+    yminmax['diff'][1] = yminmax['diff'][1]*5
+
+
+    # Set start values to the edges of the dataset
+    yminmax['heatmap'][0], yminmax['heatmap'][1] = 0, data['heatmap'].shape[0]
+    yminmax['heatmap'][2], yminmax['heatmap'][3] = yminmax['heatmap'][0], yminmax['heatmap'][1]
+
+
+    if options['heatmap']:
+        yminmax['start'][0], yminmax['start'][1] = yminmax['heatmap'][0], yminmax['heatmap'][1]
+        yminmax['start'][2], yminmax['start'][3] = yminmax['heatmap'][0], yminmax['heatmap'][1]
+
+    else:
+        # The third and fourth index are different here to not be zoomed completely out to begin with.
+        yminmax['start'][0], yminmax['start'][1] = yminmax['diff'][0], yminmax['diff'][1]
+        yminmax['start'][2], yminmax['start'][3] = yminmax['diff'][2], yminmax['diff'][3]
+    
+
+def update_defaults(widget: dict, minmax: dict) -> None:
+    ''' Updates the default x- or y-limits of a given widget. Refer to plot_diffractogram_interactive() to see the form of the widget that is passed in. An update of the min/max-values is done just prior to calling this function.
+    Changes dictionaries in place.
+    
+    Input:
+    widget (dict): A dictionary containing the widget itself (widget['w']) and all its default-values (e.g. widget['2th_default'])
+    minmax (dict): A dictionary containing min and max values, as well as min_start and max_start values. (e.g. minmax['2th'] is a list with four elements: [xmin, xmax, xmin_start, xmax_start])
+    
+    Output:
+    None.'''
+
+    for name, attr in widget.items():
+        if name.endswith('default'):
+            attr['min'] = minmax[name.replace('_default', '')][0]
+            attr['max'] = minmax[name.replace('_default', '')][1]           
+            attr['value'] = [minmax[name.replace('_default', '')][2], minmax[name.replace('_default', '')][3]]
+
+
+def update_widgets(data, options):
+
+
+    for widget_name, widget in options['widgets'].items():
+
+        # Make changes to xlim-widget
+        if widget_name == 'xlim':
+            # First update the min and max values
+            update_xminmax(xminmax=options['xminmax'], data=data, options=options)
+            update_defaults(widget=widget, minmax=options['xminmax'])
+           
+
+            if options['heatmap'] and (widget['state'] != 'heatmap'):
+
+
+                setattr(widget['w'], 'min', widget['heatmap_default']['min'])
+                setattr(widget['w'], 'max', widget['heatmap_default']['max'])
+                setattr(widget['w'], 'value', widget['heatmap_default']['value'])
+                setattr(widget['w'], 'step', widget['heatmap_default']['step'])
+
+                widget['state'] = 'heatmap'
+            
+            elif not options['heatmap'] and (widget['state'] != options['x_vals']):              
+                # Then loop through all attributes in the widget and change to current mode.
+                for arg in widget[f'{options["x_vals"]}_default']:
+                    
+                    # If new min value is larger than previous max, or new max value is smaller than previous min, set the opposite first
+                    if arg == 'min':
+                        if widget[f'{options["x_vals"]}_default']['min'] > getattr(widget['w'], 'max'):
+                            setattr(widget['w'], 'max', widget[f'{options["x_vals"]}_default']['max'])
+                    
+                    elif arg == 'max':
+                        if widget[f'{options["x_vals"]}_default']['max'] < getattr(widget['w'], 'min'):
+                            setattr(widget['w'], 'min', widget[f'{options["x_vals"]}_default']['min'])
+
+                
+                    setattr(widget['w'], arg, widget[f'{options["x_vals"]}_default'][arg])
+                
+                
+                widget['state'] = options['x_vals']
+
+        # Make changes to ylim-widget
+        elif widget_name == 'ylim':
+            update_yminmax(yminmax=options['yminmax'], data=data, options=options)
+            update_defaults(widget=widget, minmax=options['yminmax'])
+            
+            state = 'heatmap' if options['heatmap'] else 'diff' 
+    
+            if widget['state'] != state or options['offset_change']:
+
+                for arg in widget[f'{state}_default']:
+                    # If new min value is larger than previous max, or new max value is smaller than previous min, set the opposite first
+                    if arg == 'min':                     
+                        if widget[f'{state}_default']['min'] > getattr(widget['w'], 'max'):
+                            setattr(widget['w'], 'max', widget[f'{state}_default']['max'])
+                    
+                    elif arg == 'max':
+                        if widget[f'{state}_default']['max'] < getattr(widget['w'], 'min'):
+                            setattr(widget['w'], 'min', widget[f'{state}_default']['min'])
+
+                
+                    setattr(widget['w'], arg, widget[f'{state}_default'][arg])
+                
+                options['offset_change'] = False
+                widget['state'] = state
+
+
+
+
+def plot_reflection_indices(data, reflections_params, ax, options={}):
+    ''' Print reflection indices from output generated by VESTA.
+    
+    Required contents of data:
+    path (str): relative path to reflection table file'''
+
+    required_options = ['reflection_indices', 'text_colour', 'hide_indices']
+
+    default_options = {
+        'reflection_indices': 3, # Number of reflection indices to plot, from highest intensity and working its way down
+        'text_colour': 'black',
+        'hide_indices': False
+    }
+
+    reflections_params = aux.update_options(options=reflections_params, required_options=required_options, default_options=default_options)
+
+    if not reflections_params['hide_indices']:
+        reflection_table = xrd.io.load_reflection_table(data=data, reflections_params=reflections_params, options=options)
+        
+        if reflections_params['reflection_indices'] > 0:
+
+            # Get the data['reflection_indices'] number of highest reflections within the subrange options['xlim']
+            x_vals = 'heatmap' if options['heatmap'] else options['x_vals']
+            reflection_indices = reflection_table.loc[(reflection_table[x_vals] > options['xlim'][0]) & (reflection_table[x_vals] < options['xlim'][1])].nlargest(options['reflection_indices'], 'I')
+
+            # Plot the indices
+            for i in range(reflections_params['reflection_indices']):
+                if reflection_indices.shape[0] > i:
+                    ax.text(s=f'({reflection_indices["h"].iloc[i]} {reflection_indices["k"].iloc[i]} {reflection_indices["l"].iloc[i]})', x=reflection_indices[x_vals].iloc[i], y=0, fontsize=2.5, rotation=90, va='bottom', ha='center', c=reflections_params['text_colour'])    
+
+        
+        if options['xlim']:
+            ax.set_xlim(options['xlim'])
+        
+        ax.axis('off')
+
+
+    return
+    
+def plot_reflection_table(data, reflections_params, ax=None, options={}):
+    ''' Plots a reflection table from output generated by VESTA.
+    
+    Required contents of data:
+    path (str): relative path to reflection table file'''
+
+    required_options = ['reflection_indices', 'reflections_colour', 'min_alpha', 'wavelength', 'format_params', 'rc_params', 'label']
+
+    default_options = {
+        'reflection_indices': 0, # Number of indices to print
+        'reflections_colour': [0,0,0],
+        'min_alpha': 0,
+        'wavelength': 1.54059, # CuKalpha, [Å] 
+        'format_params': {},
+        'rc_params': {},
+        'label': None
+    }
+
+    if 'colour' in data.keys():
+        options['reflections_colour'] = reflections_params['colour']
+    if 'min_alpha' in reflections_params.keys():
+        options['min_alpha'] = reflections_params['min_alpha']
+    if 'reflection_indices' in reflections_params.keys():
+        options['reflection_indices'] = reflections_params['reflection_indices']
+    if 'label' in reflections_params.keys():
+        options['label'] = reflections_params['label']
+    if 'wavelength' in reflections_params.keys():
+        options['wavelength'] = reflections_params['wavelength']
+
+    options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
+
+    
+    if not ax:
+        _, ax = btp.prepare_plot(options)
+
+    x_vals = 'heatmap' if options['heatmap'] else options['x_vals']
+
+    reflection_table = xrd.io.load_reflection_table(data=data, reflections_params=reflections_params, options=options)
+    reflections, intensities  = reflection_table[x_vals], reflection_table['I']
+
+
+    
+    colours = []
+
+    for ref, intensity in zip(reflections, intensities):
+
+        colour = list(options['reflections_colour'])
+        rel_intensity = (intensity / intensities.max())*(1-options['min_alpha']) + options['min_alpha']
+        colour.append(rel_intensity)
+        colours.append(colour)
+
+    
+
+    
+    ax.vlines(x=reflections, ymin=-1, ymax=1, colors=colours, lw=0.5)
+    ax.set_ylim([-0.5,0.5])
+
+
+    ax.tick_params(which='both', bottom=False, labelbottom=False, right=False, labelright=False, left=False, labelleft=False, top=False, labeltop=False)
+    
+    if options['xlim']:
+        ax.set_xlim(options['xlim'])
+
+
+    if options['label']:
+        xlim_range = ax.get_xlim()[1] - ax.get_xlim()[0]
+        ylim_avg = (ax.get_ylim()[0]+ax.get_ylim()[1])/2
+
+        ax.text(s=reflections_params['label'], x=(ax.get_xlim()[0]-0.01*xlim_range), y=ylim_avg, ha = 'right', va = 'center')
+
+
+
+
+
+def prettify_labels(label):
+	
+	labels_dict = {
+		'2th': '2$\\theta$',
+        'I': 'Intensity'	
+        }
+
+	return labels_dict[label]
+
+
+
+def reverse_diffractograms(diffractograms):
+
+    rev_diffractograms = []
+
+    for i in len(diffractograms):
+        rev_diffractograms.append(diffractograms.pop())
+
+    return rev_diffractograms
+
+#def plot_heatmap():

setup.py

@@ -1,11 +1,11 @@
 from setuptools import setup, find_packages
 
-setup(name='beamtime',
+setup(name='nafuma',
-      version='0.1',
+      version='0.2',
-      description='Package for process and analysis of beamtime data from SNBL',
+      description='Analysis tools for inorganic materials chemistry at the NAFUMA-group at the University of Oslo',
-      url='http://github.uio.no/rasmusvt/beamtime',
+      url='https://github.com/rasmusthog/nafuma',
       author='Rasmus Vester Thøgersen, Halvor Høen Hval',
-      author_email='rasmusvt@smn.uio.no',
+      author_email='code@rasmusthog.me',
       license='MIT',
       packages=find_packages(),
       zip_safe=False)