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src/p/e/PEATDB-2.3/PEATDB/plugins/KineticsAnalysis.py   PEATDB(Download)
import os, sys, math, random, glob, numpy, string
import ConfigParser, csv, xlrd
from PEATDB.Ekin.Base import EkinProject, EkinDataset
from PEATDB.Ekin.Web import EkinWeb
#from PEATDB.Ekin.Convert import EkinConvert
                                r = r + rowoffset
                            row+=1
                            rawdata[name][dupname][temp][ph] = EkinDataset(xy=[mins, yvals],
                                                errorlists=(xerrs, yerrs), labels=('t','A'))
                        i+=1
                    #print name, ph, active
                    dsetname = dup+'_'+ph
                    ek = EkinDataset(xy=[temps, activities], yerrs=yerrors, active=active,
                                                xlabel='temp',ylabel='res act.')
                    E.insertDataset(ek, dsetname)
 
                #finally add temp vs ph plot and fit
                ek = EkinDataset(xy=[phvals, tms], xerr=None, yerr=tmerrs,
                                                xlabel='ph',ylabel='tm')
                E.insertDataset(ek, dup+'_'+'pHvsTm')
                    row+=1
                    S=subconcs[s]
                    rawdata[name][ph][S] = EkinDataset(xy=[mins, yvals],
                                               yerrs=yerrs, xlabel='t',ylabel='A')
                i+=1

src/d/a/DataPipeline-1.2/DataPipeline/Utilities.py   DataPipeline(Download)
from math import *
import numpy as np
from PEATDB.Ekin.Base import EkinProject, EkinDataset
 
def setAttributesfromConfigParser(obj, cp):
                name = str(d)+sep+str(lbl)
                xy = data[d][lbl]
                ek=EkinDataset(xy=xy)
                E.insertDataset(ek, name)
        else:
                if yerror!=None:
                    yerrs=[yerror for i in y]
            ek = EkinDataset(xy=[x,y], xerrs=xerrs, yerrs=yerrs)
            E.insertDataset(ek, d)
            #print ek.errors

src/p/e/PEATDB-2.3/PEATDB/Ekin/Titration.py   PEATDB(Download)
from NMR import NMR_data
import Utils
from PEATDB.Ekin.Base import EkinProject, EkinDataset
import Fitting
from PEATDB.Ekin.Plotting import Options
                for ed in E.datasets:
                    try:
		                ek = EkinDataset(E.data[ed])
		                totalphpoints.append(ek.length())
		                maxphpoints.append(ek.maxX())
                comb.append(sqrt(pow(ch1[v]-ref1,2)+pow((ch2[v2]-ref2)/factor,2)))
 
        dc = EkinDataset(xy=[ph1, comb])
        return dc
 

src/p/e/PEATDB-2.3/PEATDB/plugins/VantHoffAnalysis.py   PEATDB(Download)
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties
from PEATDB.Ekin.Base import EkinProject,EkinDataset
import PEATDB.Ekin.Fitting
 

src/p/e/PEATDB-2.3/PEATDB/scripts/titDB_Stats.py   PEATDB(Download)
from PEATDB.Base import PDatabase 
from PEATDB.Ekin.Titration import TitrationAnalyser
from PEATDB.Ekin.Base import EkinProject, EkinDataset
 
path=os.environ['HOME']

src/p/e/PEATDB-2.3/PEATDB/Ekin/ModelDesign.py   PEATDB(Download)
import Pmw
from PEATDB.Ekin.Plotting import PlotPanel
from PEATDB.Ekin.Base import EkinProject, EkinDataset
import PEATDB.Ekin.Fitting as Fitting
import Ekin_images

src/d/a/DataPipeline-1.2/DataPipeline/Base.py   DataPipeline(Download)
from Processing import Processor
import Utilities
from PEATDB.Ekin.Base import EkinProject, EkinDataset
import PEATDB.Ekin.Fitting as Fitting
 

src/p/e/PEATDB-2.3/PEATDB/plugins/Correlation.py   PEATDB(Download)
    pass
from PEATDB.TableModels import TableModel
from PEATDB.Ekin.Base import EkinDataset
import PEATDB.Ekin.Fitting as Fitting