regression_hist.py

#        bokeh serve --show regression_hist.py
import numpy as np

from numpy.random import random

from bokeh.io import curdoc
from bokeh.layouts import column, row
from bokeh.plotting import ColumnDataSource, Figure
from bokeh.models.widgets import Select, TextInput
from bokeh.models import HoverTool

from bokeh.io import curdoc
from bokeh.layouts import row, column, widgetbox
from bokeh.models import ColumnDataSource, Spacer
from bokeh.models.widgets import PreText, Select
from bokeh.plotting import Figure
from bokeh.io import output_notebook, show
from scipy.stats import pearsonr

import json

try:
    data_json = json.load(open('QLFmock_trend_data-b0.json'))
except Exception as err:
    print(err)
noise = data_json['noise']
bias =  data_json['bias']
fidsnr = data_json['fidsnr']
peakcount = data_json['peakcount']


data_model=dict(
        noise1 = noise[0], noise2=noise[1], noise3=noise[2], noise4=noise[3],
        bias1 = bias[0], bias2=bias[1], bias3=bias[2], bias4=bias[3], 
        peak = peakcount)

for i in list(range(len(fidsnr))):
    data_model['snr%s'%(i+1)] = fidsnr[i]

source = ColumnDataSource(data=dict(
        x=data_model['noise1'],
        y=data_model['noise2']
        ))

def style(p):
    # Title 
    p.title.align = 'center'
    p.title.text_font_size = '20pt'
    p.title.text_font = 'serif'

    # Axis titles
    p.xaxis.axis_label_text_font_size = '14pt'
    p.xaxis.axis_label_text_font_style = 'bold'
    p.yaxis.axis_label_text_font_size = '14pt'
    p.yaxis.axis_label_text_font_style = 'bold'

    # Tick labels
    p.xaxis.major_label_text_font_size = '12pt'
    p.yaxis.major_label_text_font_size = '12pt'

    return p



fiber_tooltip = """
            <div>
                <div>
                    <span style="font-size: 12px; font-weight: bold; color: #303030;">x: </span>
                    <span style="font-size: 13px; color: #515151">@x</span>
                </div>
                <div>
                    <span style="font-size: 12px; font-weight: bold; color: #303030;">y: </span>
                    <span style="font-size: 13px; color: #515151;">@y</span>
                </div>
            </div>
        """

hover = HoverTool(tooltips=fiber_tooltip)

corr = pearsonr(data_model['noise1'], data_model['noise2'])

plot = Figure(title='r: {:3.2f}'.format(corr[0]), plot_width=600, plot_height=600,
            toolbar_location='above',
            x_axis_label='Noise (AMP 1)', y_axis_label='Noise (AMP 2)',
            tools=[hover,'pan,wheel_zoom,box_select,reset'])

q = plot.circle('x', 'y', source=source, size= 8,
             fill_color='dodgerblue',
            hover_fill_color='blue', line_color='black')

qa_options =  ["noise%s"%i for i in list(range(1,5)) ]\
            + ["bias%s"%i for i in list(range(1,5)) ]\
            + ["snr%s"%(i+1) for i in list(range(len(fidsnr))) ]\
            + ['peak']

label_dict =  dict( zip( qa_options,
            ["Noise (AMP %s)"%i for i in list(range(1,5)) ]\
            + ["Bias (AMP %s)"%i for i in list(range(1,5)) ]\
            + ["SNR %s"%(i+1) for i in list(range(len(fidsnr))) ]\
            + ['Peak Count']            
            ))

select_x = Select(title="x", value="noise1", options= qa_options)
select_y = Select(title="y", value="noise2", options= qa_options) 

plot = style(plot)



hhist, hedges = np.histogram(source.data['x'], bins='sqrt')
hzeros = np.zeros(len(hedges)-1)
hmax = max(hhist)*1.1


ph = Figure(tools='pan,wheel_zoom, reset', toolbar_location='left', plot_width=plot.plot_width, plot_height=200, x_range=plot.x_range,
            y_range=(-0.1*hmax, hmax),
             min_border=10, min_border_left=50, y_axis_location="right")

ph.xgrid.grid_line_color = None
ph.yaxis.major_label_orientation = 0

qh = ph.quad(bottom=0, left=hedges[:-1], right=hedges[1:], top=hhist, color="#a7bae1", line_color="black")


# create the vertical histogram
vhist, vedges = np.histogram(source.data['y'], bins='sqrt')
vzeros = np.zeros(len(vedges)-1)
vmax = max(vhist)*1.1

pv = Figure(tools='pan,wheel_zoom, reset', toolbar_location='above', plot_width=200, plot_height=plot.plot_height, x_range=(-0.1*vmax, vmax),
            y_range=plot.y_range, min_border=10, y_axis_location="right")
pv.ygrid.grid_line_color = None
pv.xaxis.major_label_orientation = -np.pi/2
pv.background_fill_color = "#fafafa"

qv =pv.quad(left=0, bottom=vedges[:-1], top=vedges[1:], right=vhist, color="#a7bae1", line_color="black")





def update_x(attrname, old, new):
    source.data['x'] = data_model[select_x.value]
    plot.xaxis.axis_label = label_dict[select_x.value]

    corr = pearsonr(data_model[select_x.value], data_model[select_y.value])
    hhist1, hedges1= np.histogram( data_model[select_x.value], bins='sqrt')
    hmax = max(hhist1)*1.1
    ph.y_range.end= hmax
    plot.title.text = 'r: {:3.2f}'.format(corr[0])

    qh.data_source.data['left'] = hedges1[:-1]
    qh.data_source.data['right'] = hedges1[1:]
    qh.data_source.data["top"] = hhist1    



select_x.on_change('value', update_x)


def update_y(attrname, old, new):
    source.data['y'] = data_model[select_y.value]
    plot.yaxis.axis_label = label_dict[select_y.value]
    vhist1, vedges1 = np.histogram( data_model[select_y.value], bins='sqrt')
    vmax = max(vhist1)*1.1

    pv.x_range.end= vmax
    qv.data_source.data["right"] = vhist1
    qv.data_source.data["bottom"] = vedges1[:-1]
    qv.data_source.data["top"] = vedges1[1:]
    
    corr = pearsonr(data_model[select_x.value], data_model[select_y.value])
    plot.title.text =  'r: {:3.2f}'.format(corr[0])


    #pv.y_range = plot.y_range 


print(corr)

select_y.on_change('value', update_y)
        

# title = PreText("cam: b0")
layout = column(
     row( column(widgetbox(select_x),widgetbox(select_y)), column( row(plot, pv), 
    row(ph, Spacer(width= pv.width, height=ph.height))  )))

curdoc().add_root(layout)




# def get_data(N):
#     return dict(x=random(size=N), y=random(size=N), r=random(size=N) * 0.03)

# source = ColumnDataSource(data=get_data(200))

# p = Figure(tools="", toolbar_location=None)
# r = p.circle(x='x', y='y', radius='r', source=source,
#              color="navy", alpha=0.6, line_color="white")

# COLORS = ["black", "firebrick", "navy", "olive", "goldenrod"]
# select = Select(title="Color", value="navy", options=COLORS)
# input_txt = TextInput(title="Number of points", value="200")

# def update_color(attrname, old, new):
#     r.glyph.fill_color = select.value
# select.on_change('value', update_color)

# def update_points(attrname, old, new):
#     N = int(input.value)
#     source.data = get_data(N)
# input_txt.on_change('value', update_points)

# layout = column(row(select, input_txt, width=400), row(p))

# curdoc().add_root(layout)