#!/usr/bin/env python2 import os os.environ[ 'HOME' ] = '/tmp/' import cgi, cgitb cgitb.enable() import pandas as pd import numpy as np import cgi, cgitb, urllib, jinja2, json from bokeh.plotting import figure,show from bokeh.embed import components from bokeh.models import ColumnDataSource, HoverTool from bokeh.palettes import Spectral5, viridis httpfrom = cgi.FieldStorage() SID = httpfrom.getvalue('sID') if SID == None : SID='Stomata_density' #SID="heat%SS" #--- variation ------------------------------------------------------ phenohead={'phytate_ug/ml': 'Free phosphorus content(ug/ml)(Phytate)', 'Water_stress_T': 'Water stress', 'Stomata_density': 'Stomata density', 'heat%SS': '%seed set under heat stress at reproductive stage', 'Bph': 'Bph marker detection', 'salt(repro)%SS': '%seed set under salt stress at reproductive stage', 'Amylose': 'Amylose content', 'Stomata_Size': 'Stomata Size', 'Aroma': 'Aromatic rice', 'Irondensity_2000-1-2': 'Iron density (2000-1-2)', 'Submergence%PSS': '%plant survival under submergence at seedling stage', 'HighYield': 'High Yield', 'Iron_toxic_2000-1-2': 'Iron toxic (2000-1-2)', '%Recovery': '%Plant recovery after Water stress', 'Blast': 'Blast Resistant', 'male_sterile%SS': '%seed set under normal condition (male sterility)', 'cold%SS': '%seed set under clod stress at reproductive stage'} pheno=pd.read_csv('phenotype.txt', sep='\t', header=0) if len(pheno[pheno[SID] >= 0][SID].unique()) <=5 : pheno[SID]=pheno[SID].astype(str) ptd=pheno.groupby(SID)["Name"].nunique() x_la=ptd.index.tolist() x_la=map(str,x_la)[1:] topmem=ptd.tolist()[1:] variety=[pheno[pheno[SID] == x ]['Name'].tolist() for x in ptd.index.tolist() ][1:] fac_colo=viridis(len(x_la)) tza=zip(x_la, variety) variatyurl='http://sinin.kps.ku.ac.th/mutant/variety.py?sID=' tza=zip(x_la, variety) #-------------------------------------------------------------------- source = ColumnDataSource(data=dict( x=x_la, y=topmem, desc=variety, )) hover = HoverTool(tooltips=[("desc", "@desc")]) plot = figure(plot_width=800, plot_height=400, tools=[hover,'save'], title="Note: -9 means missing value.", x_range=x_la, responsive = True) plot.vbar(x='x', top='y', width=1, source=source, line_color="white", fill_color=fac_colo, hover_color="red", ) plot.xgrid.grid_line_color = None plot.y_range.start = 0 plot.xaxis.major_label_orientation = 0.8 #plot.y_range.end = 10 plot.legend.orientation = "horizontal" plot.legend.location = "top_center" else: hist, edges=np.histogram(pheno[pheno[SID] >= 0][SID], bins=20) fac_colo=viridis(len(edges[1:])) plot=figure(plot_width=800, plot_height=400) plot.quad(top=hist, bottom=0, left=edges[:-1], right=edges[1:], fill_color=fac_colo, line_color="white") plot.xgrid.grid_line_color = None plot.y_range.start = 0 plot.xaxis.major_label_orientation = 0.8 plot.legend.orientation = "horizontal" plot.legend.location = "top_center" script, divplot = components(plot) pheno=pd.read_csv('phenotype.txt', sep='\t', header=0) pheno[SID]=pheno[SID].astype(str) ptd=pheno.groupby(SID)["Name"].nunique() x_la=ptd.index.tolist() x_la=map(str,x_la) variety=[pheno[pheno[SID] == x ]['Name'].tolist() for x in ptd.index.tolist() ][1:] variatyurl='http://sinin.kps.ku.ac.th/mutant/variety.py?sID=' tza=zip(x_la, variety) set4="""

Search for individual phenotype data :

Please select Phenotype from the list box

""" set5="""
""" print """ individual phenotype data """ print(script) print " \n " print set4 print set5 print '
' print "

" +phenohead[SID]+ "

" print "
" print(divplot) print "
" print "

" #---------------------------- print "
" print """ """ print "

Table of "+phenohead[SID]+ " value.

" print """ """ for x in tza: if x[0] != '-9.0': for y in x[1]: print " " print """
Value Variaty
"+x[0]+''+y+"
Value Variaty
""" print "
" print "
" print " \n "