trees['tpa'][-tn:] = fvs.arrays.prob[:tn]
#trees['spp'][-tn:] = spp_codes[fvs.arrays.isp[:tn]]
#print sum(trees[-tn:]['tpa']) - summary[run_id,cycle]['tpa']
print('{:>6s}{:>5s}{:>5s}{:>10s}'.format('year','stop','spp','tpa'))
print('{:>6d}{:>5d}{:>5s}{:>10.3f}'.format(trees[-tn:]['year'][0],trees[-tn:]['stop'][0],trees[-tn:]['spp'][0],sum(trees[-tn:]['tpa'])))
print('{:>6d}{:>5d}{:>5s}{:>10.3f}'.format(trees[-tn:]['year'][0],trees[-tn:]['stop'][0],trees[-tn:]['spp'][-1],trees[-tn:]['tpa'][-1]))
# ntrees,ncycles,nplots,maxtrees,maxspecies,maxplots,maxcycles = fvs.fvsdimsizes()
# attrs = numpy.zeros(ntrees)
# fvs.fvstreeattr('tpa',3,'get',attrs)
#
# print sum(trees[-tn:]['tpa']) - summary[run_id,cycle]['tpa'], sum(attrs) - summary[run_id,cycle]['tpa']
#close all IO files
fvs.filclose()
# print summary[:,:6]
# print summary[cnt,:]
print 'Rep: %-4d' % x, ','.join('%6d' % v for v in summary[run_id,:]['tcuft'])
# print 'BDFT',','.join('%6d' % v for v in summary[:,5])
# if plot:
# pylab.plot(summary[:, 3])
run_id += 1
et = time.clock()
#replace the overwritten tree data file
shutil.copy2('pnt01.tre.save','pnt01.tre')
cycle_year = year_zero
# Initialize the FVS run
fvs.fvs_step.fvs_init(kwd)
# loop through growth cycles, collecting summary and tree stats
for cycle in range(1, num_cycles + 1):
# call the FVS grower loop
fvs.fvs_step.fvs_grow()
cycle_year += cycle_len
# close all IO files
fvs.fvs_step.fvs_end()
fvs.filclose()
run_id += 1
# rep_trees.append(
# fvs_tables.trees_to_dataframe(
# fvs.tree_data, spp_codes, stand_id=0, run_id=x
# , year_zero=year_zero, cycle_len=cycle_len
# ))
#
# d = fvs.snag_data
# open('snags.csv', 'w').close()
# for cycle in range(num_cycles):
# snags = pandas.DataFrame({
# 'cycle':cycle