print(f"{zr[k]:12.6f}", end=' ')
print(f"{vzr[k] / (zr[k] * zr[k]):14.6f}", end=' ')
print()
vmlnl = sum(vzr / (zr * zr))
lnml = sum(numpy.log(zr) + maxima)
if args.gram:
from gram import Plot
gp = Plot()
xx = list(bb[:-1])
yy = list(meanLogLikes)
#gp.svgPxForCm = 100
gp.baseName = 'meanLogLikes'
#gp.scatter(xx, yy)
gp.line(xx, yy)
gp.xAxis.title = r'$\beta_k$'
gp.yAxis.title = 'mean log likelihood'
gp.minXToShow = 0
gp.maxXToShow = 1
gp.pdf()
#print(meanLogLikes)
#print(maxima)
#print(zr)
#print(ess)
#print(vzr)
# print(vmlnl)
print("log marginal likelihood:", lnml)
from gram import Plot
read("data1.py")
gp = Plot()
gp.svgPxForCm = 100
gp.baseName = 'scatter'
gp.scatter(xx1, yy1)
gp.yAxis.title = 'scratches'
gp.xAxis.title = 'itches'
gp.minXToShow = 0
gp.maxXToShow = 12
gp.minYToShow = 0.
gp.maxYToShow = 34
gp.png()
gp.svg()
from gram import Plot from data5 import xx1, yy1, binNames, binVals gp = Plot() gp.baseName = 'lineAndBar_good' c = gp.bars(binNames,binVals) gp.minBarValToShow = 0.0 gp.barNameAxis.title = None gp.barValAxis.title = 'frequency' c.barSets[0].fillColor = 'black!10' gp.barNameAxis.barLabelsEvery = 2 #gp.barNameAxis.textRotate = 90 gp.line(xx1, yy1, smooth=True) gp.xAxis.position = 't' gp.yAxis.position = 'r' gp.xAxis.title = None gp.yAxis.title = 'density' gp.maxXToShow = 4.0 gp.xAxis.tickLabelsEvery = 1 gp.maxBarValToShow = 5000 gp.maxYToShow = 1.0 gp.font = 'helvetica' gp.png() gp.svg()
from gram import Plot
read('data5.py')
gp = Plot()
gp.baseName = 'lineAndBar_good'
c = gp.bars(binNames, binVals)
gp.minBarValToShow = 0.0
gp.barNameAxis.title = None
gp.barValAxis.title = 'frequency'
c.barSets[0].fillColor = 'black!10'
gp.barNameAxis.barLabelsEvery = 2
#gp.barNameAxis.textRotate = 90
gp.line(xx1, yy1, smooth=True)
gp.xAxis.position = 't'
gp.yAxis.position = 'r'
gp.xAxis.title = None
gp.yAxis.title = 'density'
gp.maxXToShow = 4.0
gp.xAxis.tickLabelsEvery = 1
gp.maxBarValToShow = 5000
gp.maxYToShow = 1.0
gp.png()
gp.svg()