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6-InteractiveVanKrevelens.py
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# -*- coding: utf-8 -*-
"""
Created on Sun Feb 18 15:17:58 2018
@author: Will Kew
"""
from __future__ import print_function # Python 2 compatibility
from __future__ import absolute_import # Python 2 compatibility
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib import ticker
import os, sys
import numpy as np
import math
#import pandas as pd
#import matplotlib
#from matplotlib import cm
#import re
#import numpy as np
#import pyupset as pyu
from bokeh.embed import file_html
from bokeh.util.browser import view
from bokeh.plotting import figure
from bokeh.models import HoverTool, ColumnDataSource, OpenURL, TapTool, layouts, CustomJS, PrintfTickFormatter, ColorBar, LinearColorMapper, FixedTicker
from bokeh.models.widgets import Panel, Tabs, Button, DataTable, TableColumn, NumberFormatter#, Dropdown
#from bokeh.palettes import Viridis10, Inferno8
import bokeh.palettes as bp
from bokeh.resources import CDN #,JSResources,INLINE
from bokeh.io import reset_output
from jinja2 import Template
from collections import OrderedDict
path = "F:/Will/Dropbox/Documents/University/Edinburgh/FTICRMS/MixedIonisation3-formularity/"
path = "C:/Users/Will/Dropbox/Documents/University/Edinburgh/FTICRMS/MixedIonisation3-formularity/"
inputdata = path +"ReformAssignments/"
outputdata = path+"Images/"
#define the colourmap of choice
glocmap = list(bp.Viridis10)
glocmap2 = list(bp.Inferno8)
glocmap.reverse()
glocmap2.reverse()
#path = "G:/DATA/FTICRMS/KEW-20160319/data/PORg CSV/"
#inputpath = path +"OutputCSV/"
outputpath = path+"OutputHTML/"
def myround(x, base=5):
return int(base * round(float(x)/base))
def intfileplot():
filesA = os.listdir(inputdata)
for y in filesA:
if y[-4:]=="xlsx":
df = pd.read_excel(inputdata+y)
df = df.rename(columns={y[:-5]:'RA',
'Error_ppm':'Error',
'Mass':'mz'})
df['VKsize'] = np.sqrt((df["RA"]*1E-5)/np.pi)
nodata = df[df['Class']== "None"]
data = df[(df['C13']== 0) & (df['Class']!= "None")]
isodata = df[(df['C13']== 1) & (df['Class']!= "None")]
intplotter(data,isodata,nodata,y)#,hetclassintdf)
reset_output() #cleans up the cache which reduces file size
"""
filesB = []
for y in filesA:
if y[-8:] =="hits.csv" and y[-10:] != "nohits.csv" and y[-11:] !="isohits.csv":
filesB.append(y)
for y in filesB:
data,hetclassintdf = FTPM.mycsvreader(inputpath+y)
isodata = FTPM.isocsvreader(inputpath+y[:-8]+"isohits.csv")
nodata = FTPM.nohitsreader(inputpath+y[:-8]+"nohits.csv")
intplotter(data,isodata,nodata,y,hetclassintdf)
reset_output() #cleans up the cache which reduces file size
"""
def intplotter(data,isodata,nodata,y):#,hetclassintdf):
linewidth = 1.5
source = ColumnDataSource(data)
s2 = ColumnDataSource(data=dict(mz=data["mz"],Error=data["Error"],RA=data["RA"],Formula=data["Formula"],HeteroClass=data["HeteroClass"]))
isosource = ColumnDataSource(isodata)
nosource = ColumnDataSource(nodata)
url = "http://www.chemspider.com/Search.aspx?q=@Formula"
TOOLS="crosshair,pan,wheel_zoom,box_zoom,reset,tap,previewsave,box_select,poly_select,lasso_select,hover"
figdims = (900,500) #pixel dimensions for the normal figures
#msxlim = [200,700] #x limits in m/z for the mass spectra
msxlim = [myround(min(data["mz"]),100),myround(max(data["mz"]),100)]
vkxlim = [-0.02,round(max(data["OC"]),1)]
#vkxlim = [0,1]
#vkylim = [0,2]
vkylim = [round(min(data["HC"]),1)-0.1,round(max(data["HC"]),1)+0.1]
p1 = figure(tools=TOOLS, title=y[:-5]+" - Van Krevelen",width=figdims[0], height=figdims[1], x_axis_label='O/C',y_axis_label='H/C',x_range=vkxlim,y_range=vkylim)
color_mapper = LinearColorMapper(palette=glocmap, low=msxlim[0], high=msxlim[1])
p1.scatter(x='OC', y='HC',source=source,size='VKsize', fill_color={'field': 'mz', 'transform': color_mapper}, fill_alpha=0.75,line_color=None) #use size not radius.
hover = p1.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([('Formula', "@Formula"),('Mass',"@mz{1.11111}"),('Error (ppm)',"@Error{1.11}")])
taptool = p1.select(type=TapTool)
taptool.callback = OpenURL(url=url)
color_bar = ColorBar(color_mapper=color_mapper, title="m/z", border_line_color=None, location=(0,0), scale_alpha=0.7)
#orientation='horizontal',location='top_left', scale_alpha=0.7)#,ticker=FixedTicker(ticks=[2,6,10,14,18]))
p1.add_layout(color_bar,"right")
#dbexlim = [0,45]
#dbeylim = [0,40]
dbexlim = [0,max(data["C"])]
dbeylim = [0,myround(max(data["DBE"]),5)]
cmax = myround(max(data["O"]),5)
#cmax = int(5 * round(float(cmax)/5))
p2 = figure(tools=TOOLS, title=y[:-5]+" - DBE vs C# Plot",width=figdims[0], height=figdims[1], x_axis_label='C#',y_axis_label='DBE',x_range=dbexlim,y_range=dbeylim)
color_mapper2 = LinearColorMapper(palette=glocmap2, low=0, high=cmax)
p2.scatter(x='C', y='DBE',source=source,size='VKsize', fill_color={'field': 'O', 'transform': color_mapper2}, fill_alpha=0.75,line_color=None)
hover = p2.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([('Formula', "@Formula"),('Mass',"@mz{1.11111}"),('Error (ppm)',"@Error{1.11}")])
taptool = p2.select(type=TapTool)
taptool.callback = OpenURL(url=url)
color_bar2 = ColorBar(color_mapper=color_mapper2, title="O#", border_line_color=None, location=(0,0), scale_alpha=0.7,ticker=FixedTicker(ticks=[0,int(cmax/4),int(cmax/2),int(3*cmax/4),cmax]))
p2.add_layout(color_bar2,"right")
#aixlim=[0,45]
aiylim= [0,1]
aixlim = [0,max(data["C"])]
#aiylim = [0,myround(max(data["AImod"]),5)]
p3 = figure(tools=TOOLS, title=y[:-5]+" - AI(mod) vs C# Plot",width=figdims[0], height=figdims[1], x_axis_label='C#',y_axis_label='AI(mod)',x_range=aixlim,y_range=aiylim)
color_mapper3 = LinearColorMapper(palette=glocmap2, low=0, high=cmax)
p3.scatter(x='C', y='AImod',source=source,size='VKsize', fill_color={'field': 'O', 'transform': color_mapper3}, fill_alpha=0.75,line_color=None)
hover = p3.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([('Formula', "@Formula"),('Mass',"@mz{1.11111}"),('Error (ppm)',"@Error{1.11}")])
taptool = p3.select(type=TapTool)
taptool.callback = OpenURL(url=url)
color_bar3 = ColorBar(color_mapper=color_mapper3,title="O#", border_line_color=None, location=(0,0), scale_alpha=0.7,ticker=FixedTicker(ticks=[0,int(cmax/4),int(cmax/2),int(3*cmax/4),cmax]))
#orientation='horizontal',location='top_left', scale_alpha=0.7)#,ticker=FixedTicker(ticks=[2,6,10,14,18]))
p3.add_layout(color_bar3,"right")
p4 = figure(tools=TOOLS, title=y[:-5]+" - Assigned Centroid MS",width=figdims[0], height=figdims[1], x_axis_label='m/z',y_axis_label='Abundance',y_range=[min(data["RA"]),max(data["RA"])],x_range=msxlim)
p4.segment(x0=0,x1=800,y0=0,y1=0,line_width=1, line_color="black")
p4.segment(x0='mz',y0=0,x1='mz',y1='RA',source=source,line_width=linewidth, line_color="black")
p4.scatter(x='mz', y='RA',source=source,fill_color='black',line_color=None)
hover = p4.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([('Formula', "@Formula"),('Mass',"@mz{1.11111}"),('Error (ppm)',"@Error{1.11}")])
taptool = p4.select(type=TapTool)
taptool.callback = OpenURL(url=url)
p4.yaxis[0].formatter = PrintfTickFormatter(format="%4.1e")
"""
#this is me trying to plot a barplot of heteroatomic class distributions...
p7 = figure(tools=TOOLS, title=y[:-9]+"",width=800, height=600, x_axis_label='HeteroClass',y_axis_label='Count',webgl=True)
p7.quad(left="HetClassInts",y=hetclassdf[0],source=source,width=5,height=)
t7 = layouts.Column(hist)
tab7 = Panel(child=t7,title="test")
"""
stretch = msxlim[0]*0.1
p5 = figure(tools=TOOLS, title=y[:-5]+" - Assigned Centroid MS",width=1400, height=600, x_axis_label='m/z',y_axis_label='Abundance', y_range=[min(data["RA"]),max(data["RA"])],x_range=(msxlim[0]-stretch,msxlim[1]+stretch))
p5.segment(x0=0,x1=800,y0=0,y1=0,line_width=1, line_color="black")
no1 =p5.segment(x0='mz',y0=0,x1='mz',y1='RA',source=nosource,line_width=linewidth, line_color="red")
no2 =p5.scatter(x='mz', y='RA',source=nosource,fill_color='red',line_color=None,legend="Unassigned Peaks")
p5.scatter(x='mz', y='RA',source=source,fill_color='black',line_color=None,legend="Assigned Peaks")
p5.segment(x0='mz',y0=0,x1='mz',y1='RA',source=source,line_width=linewidth, line_color="black")
iso1 =p5.segment(x0='mz',y0=0,x1='mz',y1='RA',source=isosource,line_width=linewidth, line_color="green")
iso2 =p5.scatter(x='mz', y='RA',source=isosource,fill_color='green',line_color=None, legend="Isotologue Peaks")
hover = p5.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([('Formula', "@Formula"),('Mass',"@mz{1.11111}"),('Error (ppm)',"@Error{1.11}")])
taptool = p5.select(type=TapTool)
taptool.callback = OpenURL(url=url)
p5.yaxis[0].formatter = PrintfTickFormatter(format="%4.1e")
js_code1 = "iso1.glyph.visible = false; iso2.glyph.visible = false; no1.glyph.visible = false; no2.glyph.visible = false;"
cb1 = CustomJS(code=js_code1, args=dict(iso1=iso1,iso2=iso2,no1=no1,no2=no2))
js_code2 = "iso1.glyph.visible = true; iso2.glyph.visible = true; no1.glyph.visible = true; no2.glyph.visible = true;"
cb2 = CustomJS(code=js_code2, args=dict(iso1=iso1,iso2=iso2,no1=no1,no2=no2))
toggleOn = Button(label="Hide", button_type="success",callback=cb1)
toggleOff = Button(label="Show", button_type="success",callback=cb2)
top = layouts.Row(toggleOn,toggleOff)
t3 = layouts.Column(top,p5)
tab3 = Panel(child=t3,title="Centroid MS with Isotopomers and No Hits")
downloadbutton = Button(label="Download", button_type="success")
downloadbutton.callback = CustomJS(args=dict(s2=s2), code="""
var data = s2.get('data');
var filetext = 'mz,Error,RA,Formula,HeteroClass\\n';
for (i=0; i < data['mz'].length; i++) {
var currRow = [data['mz'][i].toString(),
data['Error'][i].toString(),
data['RA'][i].toString(),
data['Formula'][i].toString(),
data['HeteroClass'][i].toString().concat('\\n')];
var joined = currRow.join();
filetext = filetext.concat(joined);
}
var filename = 'data_result.csv';
var blob = new Blob([filetext], { type: 'text/csv;charset=utf-8;' });
//addresses IE
if (navigator.msSaveBlob) {
navigator.msSaveBlob(blob, filename);
}
else {
var link = document.createElement("a");
link = document.createElement('a');
link.href = URL.createObjectURL(blob);
link.download = filename;
link.target = "_blank";
link.style.visibility = 'hidden';
link.dispatchEvent(new MouseEvent('click'))
}
""")
columns = [TableColumn(field="mz",title="m/z",formatter=NumberFormatter(format="0.00000")),
TableColumn(field="Error", title="Error (ppm)",formatter=NumberFormatter(format="0.00")),
TableColumn(field="RA",title="Abundance"),
TableColumn(field="Formula",title="Formula"),
TableColumn(field="HeteroClass",title="Heteroatomic Class")]
data_table = DataTable(source=s2, columns=columns, width=1400,row_headers=False,fit_columns=True)
t4 = layouts.Column(data_table,downloadbutton)
tab4=Panel(child=t4,title="Selected Data Table")
source.callback = CustomJS(args=dict(s2=s2,dt=data_table), code="""
var inds = cb_obj.get('selected')['1d'].indices;
var d1 = cb_obj.get('data');
var d2 = s2.get('data');
if (inds.length == 0) {
d2['mz'] = d1['mz']
d2['Error'] = d1['Error']
d2['RA'] = d1['RA']
d2['Formula'] = d1['Formula']
d2['HeteroClass'] = d1['HeteroClass']
}
else if (inds.length != 0) {
d2['mz'] = []
d2['Error'] = []
d2['RA'] = []
d2['Formula'] = []
d2['HeteroClass'] = []
for (i = 0; i < inds.length; i++) {
d2['mz'].push(d1['mz'][inds[i]])
d2['Error'].push(d1['Error'][inds[i]])
d2['RA'].push(d1['RA'][inds[i]])
d2['Formula'].push(d1['Formula'][inds[i]])
d2['HeteroClass'].push(d1['HeteroClass'][inds[i]])
}
}
s2.trigger('change');
dt.trigger('change');
""")
"""
hetclasslist = hetclassintdf["HetClass"].tolist()
hetclasslistnew = []
for x in hetclasslist:
hetclasslistnew.append([x,x])
dropdown = Dropdown(label="Dropdown button", button_type="warning", menu=hetclasslistnew)
"""
t1 = layouts.Row(p1,p4)
t2 = layouts.Row(p2,p3)
t12 = layouts.Column(t1,t2)
tab1 = Panel(child=t12, title="Main")
tabs = Tabs(tabs=[ tab1, tab3, tab4])
for figs in [p1,p2,p3,p4,p5]:
figs.xaxis.axis_label_text_font_size = "14pt"
figs.xaxis.major_label_text_font_size = "14pt"
figs.yaxis.axis_label_text_font_size = "14pt"
figs.yaxis.major_label_text_font_size = "14pt"
figs.title.text_font_size = "14pt"
figs.toolbar_location = "above"
with open(outputpath+'templates/index.html', 'r') as f:
template = Template(f.read())
#js_resources = JSResources(mode='inline')
html = file_html(tabs,(CDN,CDN),"Interactive Van Krevelen Diagrams",template=template)
output_file2 = outputpath+y[:-5]+'-plot.html'
with open(output_file2, 'w') as f:
f.write(html)
view(output_file2)
#show(tabs) # open a browser
intfileplot()