Metadata-Version: 2.1
Name: bokeh-plot
Version: 0.1.14
Summary: Matlab-inspired call syntax for bokeh plots
Home-page: https://github.com/axil/bokeh-plot
Author: Lev Maximov
Author-email: lev.maximov@gmail.com
License: MIT License
Description: # bokeh-plot
        
        ## Installation: 
        
            pip install bokeh-plot
        
        ## Usage:
        
        To load this extension in jupyter notebook:
        
            %load_ext bokeh_plot
        
        The following syntax is supported:
        
            plot([1,4,9])             # x is automatic 
            plot([1,4,9], '.-')       # line and dots 
            plot([1,2,3], [1,4,9])    # x and y 
            plot([1,2,3], [1,4,9], '.-')    # x, y and line style
        
        Several plots in one figure: 
        
        <img src="https://raw.githubusercontent.com/axil/bokeh-plot/master/img/simple.png" width="800">
        
        Interactive controls:
        
            click and drag = pan
            mouse wheel = zoom, 
            wheel on x axis = scroll horizontally
            wheel on y axis = scroll vertically
        
        Multiple plot syntax:
        
            x = [1,5,10]
            y1 = [1,4,9]
            y2 = [1,8,27]
        
            - plot(x, y1, '.-')        # solid line with dots
              plot(x, y2, '.-g')       # the second plot is green
        
            - plot([y1, y2])           # auto x, auto colors       
        
            - plot(x, [y1, y2])
        
            - plot([y1, y2], '.-bg')   # blue and green
        
            - plot([y1, y2], style=['.', '.-'], color=['b', 'g'])
        
            - plot(x, y1, '.-', x, y2, '.-g')
        
        
        The following markers are supported so far:
        
            '.' dots
            '-' line
            '.-' dots+line
        
        The following colors are supported so far:
        
            'b' blue
            'g' green
            'r' red
            'o' orange
            
        NB The color specifier must go after the marker if both are present.
        
        Legend:
        
            - plot([1,2,3], [1,4,9], legend='plot1')
              plot([1,2,3], [2,5,10], legend='plot2')
        
            - plot([y1, y2], legend=['y1', 'y2'])
        
        Legend location:
        
            - plot([1,2,3], [1,4,9], legend='plot1', legend_loc='top_left')
              plot([1,2,3], [2,5,10], legend='plot2')
        
        <img src="https://raw.githubusercontent.com/axil/bokeh-plot/master/img/legend.png" width="800">
        
        Other legend locations:
        https://docs.bokeh.org/en/latest/docs/user_guide/styling.html#location
        
        Other uses:
        
        `semilogx()`, `semilogy()` and `loglog()` show (semi)logarithmic plots with the same syntax as `plot()`.
        
        `plot(x, y, hover=True)` displays point coordinates on mouse hover.
        
        `imshow(a)` displays an array as an image:
        
        <img src="https://raw.githubusercontent.com/axil/bokeh-plot/master/img/imshow.png" width="800">
        
        Complete list of palettes: https://docs.bokeh.org/en/latest/docs/reference/palettes.html
        
        See also a contour plot example in the bokeh gallery [page](https://docs.bokeh.org/en/latest/docs/gallery/image.html)
        
        ## Comparison to bokeh
        
        bokeh-plot is a thin wrapper over the excellent bokeh library that cuts down the amount of boilerplate code.
        
        The following two cells are equivalent:
        
        <img src="https://raw.githubusercontent.com/axil/bokeh-plot/master/img/wrapper.png" width="800">
        
Keywords: bokeh,jupyter,notebook,plot
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
