update utility

lingress/__init__.py

@@ -3,6 +3,4 @@
 
 from .lingress import lin_regression, unipair, group_plot
 
-__all__ = ['lin_regression', 'unipair']
-
-__version__ = '1.1.0'
+from .utility import plot_spectra

lingress/utility.py

@@ -9,38 +9,53 @@
 import plotly.express as px
 import dash
 
-class plot_spectra:
 
+class plot_NMR_spec:
+    def __init__(self, spectra, ppm, label):
+
+        self.spectra = spectra
+        self.ppm = ppm
+        self.label = label
+
+
+    def median_spectra_group(self, color_map=None, 
+                    title='<b>Medien Spectra of <sup>1</sup>H NMR data</b>', title_font_size=28, 
+                    legend_name='<b>Group</b>', legend_font_size=20, 
+                    axis_font_size=20, 
+                    fig_height = 800, fig_width = 2000,
+                    line_width = 1.5, legend_order=None
+                    ):
+
+        from plotly import graph_objs as go
+        from plotly import express as px
 
-    def __init__(self, data, x, y, title, xlabel, ylabel, color, width, height):
+        spectra = self.spectra
+        ppm = self.ppm
+        label = self.label
 
-        import plotly.graph_objects as go
-        import numpy as np
-        import pandas as pd
-        import plotly.express as px
-        import dash
 
+        df_mean = spectra.groupby(label).median()
 
-        self.data = data
-        self.x = x
-        self.y = y
-        self.title = title
-        self.xlabel = xlabel
-        self.ylabel = ylabel
-        self.color = color
-        self.width = width
-        self.height = height
+        #check if color_map is provided
+        if color_map is None:
+            color_map = dict(zip(df_mean.index, px.colors.qualitative.Plotly))
+        else:
+            if len(color_map) != len(df_mean.index):
+                raise ValueError('Color map must have the same length as group labels')
+            else:
+                color_map = color_map
 
+
 
         #plot spectra
         fig = go.Figure()
-        for i in df3.index:
-            fig.add_trace(go.Scatter(x=ppm, y=df3.loc[i,:], mode='lines', name=i, line=dict(color=line_color[i], width=1.5)))
+        for i in df_mean.index:
+            fig.add_trace(go.Scatter(x=ppm, y=df_mean.loc[i,:], mode='lines', name=i, line=dict(color=color_map[i], width=line_width)))
 
         fig.update_layout(
             autosize=False,
-            width=3000,
-            height=1000,
+            width=fig_width,
+            height=fig_height,
             margin=dict(
                 l=50,
                 r=50,
@@ -50,32 +65,30 @@ def __init__(self, data, x, y, title, xlabel, ylabel, color, width, height):
             )
         )
 
-        #add line tick of Y and X axis
-
         fig.update_xaxes(showline=True, showgrid=False, linewidth=1, linecolor='rgb(82, 82, 82)', mirror=True)
         fig.update_yaxes(showline=True, showgrid=False, linewidth=1, linecolor='rgb(82, 82, 82)', mirror=True)
 
         #Set font size of label
-        fig.update_layout(font=go.layout.Font(size=20))
+        fig.update_layout(font=go.layout.Font(size=axis_font_size))
         #Add title
-        fig.update_layout(title={'text': 'Medien Spectra'}, 
+        fig.update_layout(title={'text': title, 'xanchor': 'center', 'yanchor': 'top'}, 
                         title_x=0.5, 
-                        xaxis_title="δ <sup>1</sup>H", yaxis_title="Intensity",
-                        title_font_size=28,
+                        xaxis_title="<b>δ<sup>1</sup>H</b>", yaxis_title="<b>Intensity</b>",
+                        title_font_size=title_font_size,
                         title_yanchor="top",
                         title_xanchor="center")
 
+        #Add legend
 
-
-
+        fig.update_layout(legend=dict( title=legend_name, font=dict(size=legend_font_size)))
         #Invert x-axis
         fig.update_xaxes(autorange="reversed")
         #Alpha background
         fig.update_layout(paper_bgcolor='rgba(0,0,0,0)',plot_bgcolor='rgba(0,0,0,0)')
         #fig.update_layout(title='Medien Spectra', xaxis_title='δ <sup>1</sup>H', yaxis_title='Intensity')
-        #Y axis scale unite as scientific style decimal 4 digit
 
-        fig.update_yaxes(tickformat='e')
+        #set y-axis tick format to scientific notation with 4 decimal places
+        fig.update_layout(yaxis=dict(tickformat=".2e"))
+
+        return fig
 
-        fig.show()
-        fig.write_html(f'{project}.html')

setup.py

@@ -12,14 +12,14 @@
 setup(
   name = 'lingress',      
   packages = ['lingress'], 
-  version = '2.0.2',  
+  version = '2.1.0',  
   license='MIT', 
   description = 'Metabolomics data analysis with univariate (linear regression) and visualization tools.',
   long_description=DESCRIPTION,
   author = 'aeiwz',                 
   author_email = '[email protected]',     
   url = 'https://github.com/aeiwz/lingress.git',  
-  download_url = 'https://github.com/aeiwz/lingress/archive/refs/tags/v2.0.2.tar.gz',  
+  download_url = 'https://github.com/aeiwz/lingress/archive/refs/tags/v2.1.0.tar.gz',  
   keywords = ['Omics', 'Chemometrics', 'Visualization', 'Data Analysis', 'Univariate', 'Linear Regression'],
   install_requires=[            
           'scikit-learn',