datprep.store_compounds(results, res_file)
print("results were successfully stored to ", res_file)
if do_plot_derivatives:
yvals = []
norms_nuc = []
for i in range(5):
resfile = database + namelist[i] + "der_results.pickle"
res_list = datprep.read_compounds(resfile)
xlist, ylist, results = \
pltder.prepresults(results = res_list,\
rep = namelist[i],\
repno = i,\
yval = "perc",\
with_whichd = True)
yvals.extend(ylist)
for i in ylist:
norms_nuc.append(xlist)
print(yvals)
pltder.plot_percentage_zeroEV([1,2], yvals, title = "4 C Atoms",\
savetofile = "./Images/Final/BOB_conformations.png", oneplot = False,\
representations = [0,1,2,3,4],\
xaxis_title = "Compound",\
Include_Title = False,\
BOB = True)
plt.xlabel(xtitle)
plt.ylabel(ytitle)
fig.subplots_adjust(top=0.92, bottom = 0.1, left = 0.12, right = 0.97)
for i in representations:
repro = reprolist[i]
filename = results_file[i]
if i == 0:
results = datprep2.read_compounds(filename)
#get xdata and ydata with labels (ydatalist[i][1] stores labels)
xdata, ydata, newresults = prepresults(results, rep = repro,\
dwhich = which_d, repno = i,\
norm = xnorm, yval = yvalues,\
with_whichd = False)
#datprep.store_compounds(newresults, partialfilename)
for yd in ydata:
ax.scatter(xdata, yd[0], c = colorlist[i], label = repro)
del(xdata)
del(ydata)
del(newresults)
del(results)
else:
j = 0 #important so only one label is displayed
unsrt_numbers = ["100-120", "120-140", "140-160", "160-180", "180-200",\
"220-240", "240-260", "260-280", "280-300",\
xdatalist = []
for i in representations:
repro = reprolist[i]
#print("representation:", repro)
#print("len ydatalist:", len(ydatalist))
filename = results_file[i]
if i < 2:
#repro is pickled in one file
results = datprep.read_compounds(filename)
#get xdata and ydata with labels (ydatalist[i][1] stores labels)
xdata, ydata, newresults = prepresults(results, rep = repro,\
dwhich = which_d, repno = i,\
norm = xnorm, yval = yvalues)
xdatalist.append(xdata)
ydatalist.extend(ydata)
else:
#for BOB, EVOM and OM results were stored in files containing 100 compounds each
j = 0
#collect and append numbers to one array, to later merge to one dataset in yaxis
fullydata = []
fullxdata = []
ydatalabel = ""
for k in [100, 200, 300, 400, 500, 600, 800, 900, 1000, 1100, 1200, 1300, 1400, 1500, 1600, 1700, 1800, 1900,\