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parallel-from-db.py
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parallel-from-db.py
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import glob
import numpy as np
from db import mldb
import matplotlib.pyplot as plt
#Functions from pyOPALTools
#https://gitlab.psi.ch/OPAL/pyOPALTools
from opal.analysis.pareto_fronts import *
from opal import load_dataset
from opal.datasets.filetype import FileType
from opal.visualization.plots import *
from opal.datasets.OptimizerDataset import *
plt.rc('text', usetex=True)
plt.rc('font', family='serif')
root = '/home/nicole/Documents/awa-tba/'
#baseFN = ['ex-1', 'ex-2', 'ex-4']
#baseFN = ['ex-1', 'ex-2-bounded', 'ex-4-bounded'] #'ex-3-bounded',
#ex = ['ex-1', 'ex-2', 'ex-4']
baseFN = ['paper-run-ex4']
#dbpath = root+baseFN[0]+'.pk'
#Read db and save data to file
#data = get_all_data_db(dbpath)
#np.save('data.npy', data)
# Load db dict from file
#data = np.load('dict_paper-run-ex4.npy').item()
#(pfdata1, ind1) = pareto_pts(data['RMSS1'], data['EMITX1'])
#(pfdata2, ind2) = pareto_pts(data['RMSS2'], data['EMITX2'])
for fn in baseFN:
#dbpath = root+fn+'.pk'
#data = get_all_data_db(dbpath)
#np.save(fn+'.npy', data)
##data = np.load(fn+'.npy').item()
#print(ind1, ind2)
#print(np.shape(data['KQ1']))
#print(data['KQ1'][ind1])
#print(data['KQ1'][ind2])
#ex = fn.split('-b')[0]
#Trying parallel plot
#print(ex)
#dset = load_dataset(root, fname=fn+'.pk')
#print(dir(dset[0][0].keys()))
#print(dset.getXNames())
allemx2 = []
allrmss2 = []
allrmsx2 = []
allq1 = []
allq2 = []
allq3 = []
allq4 = []
ngen = len(glob.glob(fn+'/results/*.json'))
dsets = load_dataset(fn+'/results/', ftype=FileType.OPTIMIZER)
ds = dsets[0]
for i in range(1,ngen+1):
de = ds.getData('DE1', gen=i)
emx1 = ds.getData('EMITX1', gen=i)
emx2 = ds.getData('EMITX2', gen=i)
rmss1 = ds.getData('RMSS1', gen=i)
rmss2 = ds.getData('RMSS2', gen=i)
rmsx1 = ds.getData('RMSX1', gen=i)
rmsx2 = ds.getData('RMSX2', gen=i)
gphs = ds.getData('GPHASE', gen=i)
fwhm = ds.getData('FWHM', gen=i)
im = ds.getData('IM', gen=i)
ib = ds.getData('IBF', gen=i)
q1 = ds.getData('KQ1', gen=i)
q2 = ds.getData('KQ2', gen=i)
q3 = ds.getData('KQ3', gen=i)
q4 = ds.getData('KQ4', gen=i)
allemx1 = np.append(emx1, allemx1)
allrmss1 = np.append(rmss1, allrmss1)
allrmsx1 = np.append(rmsx1, allrmsx1)
allemx2 = np.append(emx2, allemx2)
allrmss2 = np.append(rmss2, allrmss2)
allrmsx2 = np.append(rmsx2, allrmsx2)
allq1 = np.append(q1, allq1)
allq2 = np.append(q2, allq2)
allq3 = np.append(q3, allq3)
allq4 = np.append(q4, allq4)
(pfdata1, ind1) = pareto_pts(allrmss1, allemx2)
(pfdata2, ind2) = pareto_pts(allrmsx2, allemx2)
(pfdata3, ind1) = pareto_pts(allrmss2, allemx2)
(pfdata4, ind2) = pareto_pts(allrmsx2, allemx2)
#plt.plot(pfdata2['x'], pfdata2['y'], '-.')
#plt.show()
#print(len(data))
#gens = ds.getLabel(data)
#print(gens)
#print(data)
#ds.design_variables()
#num = getattr(ds, "num_generations")
#print(num)
#ds.getData('objective or design variable', gen=gen)
#allxy = dsets.get_all_data()
#print(allxy)
#ds = dsets[0]
#plot_parallel_coordinates(dsets[0], 1)
#print(dsets)
#df = pand.read_csv("https://raw.githubusercontent.com/bcdunbar/datasets/master/parcoords_data.csv")
#layout = go.Layout(font = dict(family='Droid Serif', size=20),
# plot_bgcolor = '#E5E5E5',
# paper_bgcolor = '#E5E5E5') #, color='#7f7f7f')
#
#
#l1 = np.arange(1.5, 10.5, 0.5)
#l2 = np.arange(-30, 5, 5)
#l3 = np.arange(200, 550, 50)
#l4 = np.arange(170, 270, 15)
#l5 = np.arange(-8, 9, 2)
#l6 = np.arange(1.0, 1.8, 0.25)
#l7 = np.arange(50, 1450, 50)
#
#alldata = {}
#for i, fn in enumerate(baseFN):
# nn = root+fn+'.pk'
# dbr = mldb.mldb()
# dbr.load(nn)
# dvars = dbr.getXNames()
# onames = dbr.getYNames()
# gens = dbr.getNumberOfSamples()
# #dbr.printOverview()
#
# with open(nn, 'rb') as f:
# dbr = pick.load(f, encoding='latin1')
#
# allx = dbr[gens+1]['allDvarValues']
# ally = dbr[gens+1]['allObjValues']
# emitx1 = np.array(ally[:,0])
# emitx2 = np.array(ally[:,1])
# rmss1 = np.array(ally[:,2])
# rmss2 = np.array(ally[:,3])
#
# (px, py, pd) = pareto(rmss1, emitx1, allx)
# (px2, py2, pd2) = pareto(rmss2, emitx2, allx)
# tosave = {'px':px, 'py':py, 'pd':pd}
# alldata = np.append(alldata, tosave)
# print(len(px), len(px2))
# #print(pd)
# #plt.plot(px, py)
# #plt.show()
# print(np.shape(alldata))#np.shape(px), np.shape(py), np.shape(pd))
#
# #for i in range(0,7):
# # print('min ', np.max(pd[:,i]))
# # print('max ', np.min(pd[:,i]))
# #for i in range(0,8):
# # print('min ', np.min(px))
# # print('max ', np.max(px))
# # print('min ', np.min(py))
# # print('max ', np.max(py))
#
# pardata = [go.Parcoords(
# #line = dict(color = [-300, 0, 1, 100, 500]),
# #line = dict(color = ['blue', 'green']),
# line = dict(color = [-3000, -700, -1500, -1800, -2700, -3000, -4000],
# colorscale = 'Jet',
# #showscale = True,
# #reversescale = True,
# cmin = -4000,
# cmax = 0),
# #width = 1,
# dimensions = list([
#
# dict(range = [-30,0],
# tickvals = l2,
# label = dvars[1]+ ' [deg]', values = pd[:,1]),
#
# dict(range = [200,500],
# tickvals = l3, #[1.5,3,4.5],
# label = dvars[2]+ ' [A]', values = pd[:,2]),
#
# dict(range = [170,260],
# tickvals = l4, #[1,2,4,5],
# label = dvars[3]+ ' [A]', values = pd[:,3]),
# #ticktext = ['text 1', 'text 2', 'text 3', 'text 4']),
#
# dict(range = [-8,8],
# tickvals = l5,
# label = dvars[4]+' [A]', values = pd[:,4]),
#
# dict(range = [-8,8], tickvals = l5,
# label = dvars[5]+' [A]', values = pd[:,5]),
#
# dict(range = [-8,8],
# #tickvals = [1.5,3,4.5],
# tickvals = l5,label = dvars[6]+' [A]', values = pd[:,6]),
#
# dict(range = [-8,8],
# #tickvals = [1,2,4,5],
# tickvals = l5,label = dvars[7]+' [A]', values = pd[:,7]),
# #ticktext = ['text 1', 'text 2', 'text 3', 'text 4']),
#
# dict(range = [1.5,10],
# tickvals = l1, #[1.5,5.0,10.0],
# label = dvars[0]+' [ps]', values = pd[:,0]),
#
# dict(range = [1.0, 1.75],
# tickvals = l6,label = onames[2]+' [mm]', values = px*10**3),
#
# #dict(range = [1.0,1.75],
# # tickvals = l6, label = onames[2]+ '[mm]', values = px2*10**3),
#
# dict(range = [50.0,1350],
# tickvals = l7, label = onames[0]+' [mm-mr]', values = py*10**6),
#
# #dict(range = [50,1350],
# # tickvals = l7, label = onames[0]+ '[mm-mr]', values = py2*10**6),
#
# ]))]
# fig = go.Figure(data=pardata, layout=layout)
# offline.plot(fig, filename = fn+'.html')
#def with_jax(fig, filename):
#
# plot_div = offline.plot(fig, output_type = 'div')
#
# template = """
# <head>
# <script type="text/javascript" async
# src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-MML-AM_SVG">
# </script>
# </head>
# <body>
# {plot_div:s}
# </body>""".format(plot_div = plot_div)
# with open(filename, 'w') as fp:
# fp.write(template)
# #os.startfile(filename)
# subprocess.call(['xdg-open', filename])
#with_jax(fig, 'cube.html')
#for gen in range(0,gens):
# nsims = dbr.getSampleSize(i=gen)
# print(nsims) #len(dbr[gen]['dvarValues'])
# for x in range(0,nsims):
# #print(x)
# xsim = dbr.getDVarVec(gen,x)
# ysim = dbr.getObjVec(gen,x)
# xvals.append(xsim)
#print(np.shape(xvals))
#
# #print('Generation #: ', gen)
# #print('Num of individuals: ', np.size(ns))
# #print('first check:', np.size(ns), cols)
# data = np.zeros((np.size(ns), cols))
# #print("individual: ", np.size(indiv))
# ##print('Total num of gens: ', count)
# dvars = optjson.getDesignVariables()
# #print ( "Design variables: ", dvars)
# #print ( "number of design variables", np.size(dvars))
# objs = optjson.getObjectives()
# #print ( "Objectives: ", objs)
# #print ( "number of objectives", np.size(objs))
#
# for i, simid in enumerate(ns):
# #Load add data in 1 generation into data array
# # The data array is N rows X M columns
# # N = number of simulations in generation
# # M = number of davars + objs + 1 (for ID number)
# #print(i)
# indiv = optjson.getIndividualWithID(simid)
# if (-10.0 <= indiv[5] <= 0.0) & (-10.0 <= indiv[6] <= 0.0) & (60 <= indiv[0] <= 75) & (15 <= indiv[1] <= 25) & (400 <= indiv[2] <= 550) & (180 <= indiv[3] <= 280) & (0.001 <= indiv[4] <= 0.004):
# #print('ok')
# goodpoints = goodpoints +1
# else:
# #print('good')
# badpoints = badpoints +1
# #print(np.shape(data), np.shape(indiv))
# data[i,:] = indiv
# #print(indiv)
# else:
# print('Nope', gen)
# if np.size(ns)< 656:
# diff = diff+1
# count = count + np.size(ns)
# count2 = count2 + len(data[:,0])
#
#print('less than 656:', diff)
#print('goodpoints', goodpoints)
#print('badpoints', badpoints)