def GridPlots(curr_id, res):
rad = MakeRad(res)
fname_band = './dat/' + curr_id + '/Del/Plots/Bands/' + curr_id + '_del_subbands'
max_x = 0
max_y = 0
dpi_in = 400
for i in rad:
curr_fband = fname_band + '_r{:0.4f}'.format(i)
curr_fband = curr_fband + '_dpi' + str(dpi_in) + '.png'
cur_x = Image.open(curr_fband).size[0]
cur_y = Image.open(curr_fband).size[1]
if cur_x > max_x: max_x = cur_x
if cur_y > max_y: max_y = cur_y
print 'max (x,y) = ({:d},{:d})'.format(max_x,max_y)
blank_img = Image.new("RGB", (len(rad) * max_x, max_y), "white")
for i in range(len(rad)):
cur_x = i * max_x
curr_fband = fname_band + '_r{:0.4f}'.format(rad[i])
curr_fband = curr_fband + '_dpi' + str(dpi_in) + '.png'
print 'pasting ' + curr_fband
blank_img.paste(Image.open(curr_fband), (cur_x, 0))
out_img = './dat/' + curr_id + '/Del/Plots/' + curr_id + '_del_grid_dpi' + str(dpi_in) + '.png'
ensure_dir(out_img)
blank_img.save(out_img)
def GetNNStatsMany(main_id, min, max):
folder = './dat/' + main_id + '/'
fname = main_id + 'stats_NN.csv'
fout = folder + fname
ensure_dir(fout)
with open(fout,'w') as f:
for i in range(min, max):
curr_id = main_id + str(i)
[n_s, n_c, r_c, coords] = read(curr_id)
stats = GetNNStatsIndiv(curr_id, n_s, n_c, r_c, coords)
for s in stats:
print s
f.write(str(s))
f.write(',')
f.write('\n')
f.close()
def PlotSk(curr_id):
[n_s, n_c, r_c, coords] = readcenters.read(curr_id)
print 'plotting Sk...'
plt.figure(figsize=(12.0,4.0))
for i in range(0,n_s):
fname = './dat/' + curr_id + '/Sk/' + curr_id + '_Sk_' + str(i) + '.txt'
[k, Sk] = ReadSk(fname)
axes_indiv = plt.subplot(1, n_s + 2, i+1)
FormatPlotSk(axes_indiv, 'species {:d}'.format(i))
[popt, pcov, fit_k, fit_Sk] = FitSk(k,Sk)
PlotSkFit(popt, pcov, fit_k, fit_Sk, axes_indiv)
plt.loglog(k,Sk)
# run for all
fname = './dat/' + curr_id + '/Sk/' + curr_id + '_Sk_T.txt'
[k, Sk] = ReadSk(fname)
axes_combined = plt.subplot(1, n_s + 2, n_s+1)
FormatPlotSk(axes_combined, 'all species')
[popt, pcov, fit_k, fit_Sk] = FitSk(k,Sk)
PlotSkFit(popt, pcov, fit_k, fit_Sk, axes_combined)
plt.loglog(k,Sk)
# run for delaunay
fname = './dat/' + curr_id + '/Sk/' + curr_id + '_Sk_del.txt'
[k, Sk] = ReadSk(fname)
axes_delaunay = plt.subplot(1, n_s + 2, n_s+2)
FormatPlotSk(axes_delaunay, 'delaunay')
[popt, pcov, fit_k, fit_Sk] = FitSk(k,Sk)
PlotSkFit(popt, pcov, fit_k, fit_Sk, axes_delaunay)
plt.loglog(k,Sk)
fname = curr_id + '_Sk.eps'
fout = './dat/' + curr_id + '/Plots/' + fname
ensure_dir(fout)
plt.suptitle('structure factor, S(k)', fontsize=12)
plt.savefig(fout, bbox_inches=0, dpi = 300)
def PlotCenters(curr_id, n_s, n_c, r_c, coords):
print 'plotting centers...'
plt.figure(figsize=(12.0,4.0))
axes_combined = plt.subplot(1, n_s + 1, n_s+1)
axes_combined.grid()
plt.axis('scaled')
plt.axis([0,1,0,1])
plt.xlabel('x')
plt.ylabel('y')
plt.title('all species')
jet = cm = plt.get_cmap('jet')
cNorm = colors.Normalize(vmin=0, vmax=n_s)
scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet)
for i in range(0,n_s):
rad = r_c[i]
axes_indiv = plt.subplot(1, n_s + 1, i+1)
axes_indiv.grid()
colorVal = scalarMap.to_rgba(i)
for j in range(n_c[i]):
x = coords[i][j][0]
y = coords[i][j][1]
my_circle_scatter(axes_indiv, [x], [y], radius=rad, alpha=0.5, color=colorVal)
my_circle_scatter(axes_combined, [x], [y], radius=rad, alpha=0.5, color=colorVal)
plt.axis('scaled')
plt.axis([0,1,0,1])
plt.xlabel('x')
plt.ylabel('y')
plt.title('species {:d}, rad {:0.4f}'.format(i,rad))
fname = curr_id + '_centers.eps'
fout = './dat/' + curr_id + '/Plots/' + fname
ensure_dir(fout)
plt.suptitle('centers', fontsize=12)
plt.savefig(fout, bbox_inches=0, dpi = 300)
def GridPlots2(curr_id, res):
min = 0
max = 0.5
inc = 0.05
dpi = 400
rad = [i * inc for i in range(0, int(max/inc)+1)]
fname_out = './dat/' + curr_id + '/Download/' + curr_id + '_out'
fname_band = './dat/' + curr_id + '/Plots/Bands/' + curr_id + '_subbands'
max_x = 0
max_y = 0
dpi_in = 400
for r in rad:
if r == 0: continue
curr_fband = fname_band + '_r{:0.4f}'.format(r)
curr_fband = curr_fband + '_dpi' + str(dpi_in) + '.png'
cur_x = Image.open(curr_fband).size[0]
cur_y = Image.open(curr_fband).size[1]
if cur_x > max_x: max_x = cur_x
if cur_y > max_y: max_y = cur_y
print 'max (x,y) = ({:d},{:d})'.format(max_x,max_y)
blank_img = Image.new("RGB", (len(rad) * max_x, max_y), "white")
for i in range(len(rad)):
if rad[i]==0: continue
cur_x = i * max_x
curr_fband = fname_band + '_r{:0.4f}'.format(rad[i])
curr_fband = curr_fband + '_dpi' + str(dpi_in) + '.png'
print 'pasting ' + curr_fband
blank_img.paste(Image.open(curr_fband), (cur_x, 0))
out_img = './dat/' + curr_id + '/Plots/' + curr_id + 'grid_dpi' + str(dpi_in) + '.png'
ensure_dir(out_img)
blank_img.save(out_img)
def CalcSk(curr_id):
fout_Sk = './dat/' + curr_id + '/Sk/' + curr_id + '_Sk_'
ensure_dir(fout_Sk)
[n_s, n_c, r_c, coords] = readcenters.read(curr_id)
N = 0
for i in range(0,n_s):
N += n_c[i]
total_in = [maxx, maxy, N]
for i in range(0,n_s):
inputs = [maxx, maxy, n_c[i]]
for j in range(0,n_c[i]):
tmpx = coords[i][j][0]
tmpy = coords[i][j][1]
inputs.extend( [ tmpx, tmpy ] )
total_in.extend( [ tmpx, tmpy ] )
outname = fout_Sk + str(i) + '.txt'
RunSk(inputs, outname)
outname = fout_Sk + 'T.txt'
RunSk(total_in, outname)
del_fin = './dat/' + curr_id + '/Del/' + curr_id + '_del_T.txt'
del_data = list(csv.reader( open(del_fin, 'rb') , delimiter = '\t' ))
del_in = [maxx, maxy, len(del_data)]
for i in range( len(del_data) ):
tmpx = float(del_data[i][0])
tmpy = float(del_data[i][1])
del_in.extend( [tmpx, tmpy] )
outname = fout_Sk + 'del.txt'
RunSk(del_in,outname)
def GridPlots(curr_id, res, n_s):
min = 0
max = 0.5
inc = 0.05
dpi = 400
rad = [i * inc for i in range(0, int(max/inc)+1)]
fname_band = './dat/' + curr_id + '/Plots/Bands/' + curr_id + '_subbands'
max_x = 0
max_y = 0
for i in rad:
for j in rad:
curr_fband = fname_band + '_r{:0.4f}_r{:0.4f}'.format(i,j)
curr_fband = curr_fband + '_dpi' + str(dpi) + '.png'
cur_x = Image.open(curr_fband).size[0]
cur_y = Image.open(curr_fband).size[1]
if cur_x > max_x: max_x = cur_x
if cur_y > max_y: max_y = cur_y
print 'max (x,y) = ({:d},{:d})'.format(max_x,max_y)
blank_img = Image.new("RGB", (len(rad) * max_x, len(rad) * max_y), "white")
for i in range(len(rad)):
for j in range(len(rad)):
cur_x = i * max_x
cur_y = j * max_y
curr_fband = fname_band + '_r{:0.4f}_r{:0.4f}'.format(rad[i],rad[j])
curr_fband = curr_fband + '_dpi' + str(dpi) + '.png'
print 'pasting ' + curr_fband
blank_img.paste(Image.open(curr_fband), (cur_x, cur_y))
out_img = './dat/' + curr_id + '/Plots/' + curr_id + 'grid_dpi' + str(dpi) + '.png'
ensure_dir(out_img)
blank_img.save(out_img)
def GetNNStatsDelMany(main_id, min, max):
folder = './dat/' + main_id + '/'
fname = main_id + 'stats_NN_del.csv'
fout = folder + fname
ensure_dir(fout)
with open(fout,'w') as f:
for i in range(min, max):
curr_id = main_id + str(i)
stats = GetNNStatsDelIndiv(curr_id)
for s in stats:
print s
f.write(str(s))
f.write(',')
f.write('\n')
f.close()
def CalcBands(curr_id, res):
print 'calculating bands...'
rad = MakeRad(1)
fname_out = './dat/' + curr_id + '/Del/Download/' + curr_id + '_out'
fname_band = './dat/' + curr_id + '/Del/' + curr_id + '_del_bands.csv'
ensure_dir(fname_band)
initiate = 0
if not os.path.exists(fname_band):
lines = [[]]
lines[0].append('rad')
numrows = 0
numcols = 0
numbands_i = 0
initiate = 1
for r in rad:
cur_fout = fname_out + '_r{:0.4f}'.format(float(r)) + '.OUT'
print 'opening file ' + cur_fout
print 'adding bands for',
print r
if not initiate:
lines = list(csv.reader( open(fname_band, 'rb') , delimiter = '\t' ))
lines = [line[0].split(',') for line in lines]
numrows = len(lines)
numcols = len(lines[0])
numbands_i = ((numcols-2)+1)/3
cur_row = numrows
print('(rows,cols,bands) = {:d}, {:d}, {:d}'.format(numrows,numcols,numbands_i))
print 'checking if already in file...'
changerad = 0
for row in range(1,numrows):
print '(cur, new) = ',
cur_rad = float('{:0.4f}'.format(float(lines[row][0])))
my_rad = float('{:0.4f}'.format(float(r)))
print cur_rad,
print ',',
print my_rad
if(cur_rad == my_rad):
print('ALREADY IN FILE')
changerad = 1
break
if(changerad): continue
tmp_bands = 'tmp_bands.del'
tmp_bands2 = 'tmp.del'
cmd0 = 'cat ' + cur_fout + ' | grep -i \"Range\" > ' + tmp_bands2
cmd1 = 'awk \'{print $4, $10}\' tmp.del > ' + tmp_bands
os.system(cmd0)
os.system(cmd1)
# write all band lines to cur_line
cur_line = []
with open(tmp_bands,'r') as fin_bands:
bands = [band.split() for band in fin_bands]
numbands_f = len(bands)
print 'num bands...' + str(numbands_f)
# first write all radii
cur_line.append(r)
prv_lo = 0.0
prv_hi = 0.0
for band in bands:
cur_lo = float(band[0])
cur_hi = float(band[1])
if(cur_lo > prv_hi):
gap = cur_lo - prv_hi
midfreq = (cur_lo + prv_hi)/2
normgap = gap/midfreq
else:
normgap = 0
if(cur_lo>0):
cur_line.append(normgap)
cur_line.append(cur_lo)
cur_line.append(cur_hi)
prv_lo = cur_lo
prv_hi = cur_hi
cmd0 = 'rm ' + tmp_bands2
cmd1 = 'rm ' + tmp_bands
os.system(cmd0)
os.system(cmd1)
lines.append(cur_line)
# add band numbers to topline if exceed existing
if(initiate):
print 'initating bands'
lines[0].append('1L')
lines[0].append('1H')
for i in range(2,numbands_f+1):
col1 = '{:d}to{:d}'.format(i-1,i)
col2 = '{:d}L'.format(i)
col3 = '{:d}H'.format(i)
lines[0].extend([col1,col2,col3])
initiate = 0
elif(numbands_f > numbands_i):
print 'adding new bands'
for i in range(numbands_i+1,numbands_f+1):
col1 = '{:d}to{:d}'.format(i-1,i)
col2 = '{:d}L'.format(i)
col3 = '{:d}H'.format(i)
lines[0].extend([col1,col2,col3])
with open(fname_band, 'w') as f:
for line in lines:
for el in line:
f.write('%s,' % el)
f.write('\n')
f.close()
cur_row = numrows + 1
def PlotSomeBands(curr_id, res, subbands):
print 'plotting bands...'
rad = MakeRad(res)
fname_out = './dat/' + curr_id + '/Del/Download/' + curr_id + '_out'
fname_band = './dat/' + curr_id + '/Del/Plots/Bands/' + curr_id + '_del_subbands'
ensure_dir(fname_band)
min = 0.15
max = 0.60
dpi_in = 400
jet = cm = plt.get_cmap('jet')
cNorm = colors.Normalize(vmin=0, vmax=len(subbands))
scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet)
for r in rad:
curr_fout = fname_out + '_r{:0.4f}.OUT'.format(float(r))
curr_fband = fname_band + '_r{:0.4f}'.format(float(r)) + '_dpi' + str(dpi_in) + '.png'
print 'plotting bands for ' + curr_fout
tmp_bands = 'tmp_bands.del'
tmp_bands2 = 'tmp.del'
cmd0 = 'cat ' + curr_fout + ' | grep -i \"Range\" > ' + tmp_bands2
cmd1 = 'awk \'{print $4, $10}\' tmp.del > ' + tmp_bands
os.system(cmd0)
os.system(cmd1)
fig = plt.figure(figsize=(10,10))
ax = fig.gca()
ax.set_aspect(5)
ax.xaxis.set_ticks_position('none')
ax.yaxis.set_ticks_position('none')
plt.xticks([])
plt.yticks([0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5, 0.55, 0.6])
plt.tick_params(axis='y', which='major', labelsize=2)
plt.tick_params(axis='x', which='major', labelsize=0)
plt.tick_params(axis='both', which='minor', labelsize=0)
plt.setp(ax.get_xticklabels(), visible=False)
with open(tmp_bands,'r') as fin_bands:
bands = [b.split() for b in fin_bands]
for i in range(len(subbands)):
colorVal = scalarMap.to_rgba(i)
print int(subbands[i-1])+1,
cur_hi = float(bands[int(subbands[i-1])][1])
nxt_lo = float(bands[int(subbands[i-1])+1][0])
print cur_hi,
print ',',
print nxt_lo,
if(nxt_lo > cur_hi):
print 'gap!'
plt.vlines(0, cur_hi, nxt_lo, color=colorVal, linewidths = 100)
print '\n'
cmd0 = 'rm ' + tmp_bands
cmd1 = 'rm ' + tmp_bands2
#os.system(cmd0)
#os.system(cmd1)
plt.axis([-0.1,0.1,min,max])
ax.yaxis.labelpad = -1
ax.text(0.5,0.97,r,
horizontalalignment='center',
transform=ax.transAxes)
# plt.text(0,5.05,fname_out,size='8',horizontalalignment='center')
plt.savefig(curr_fband, format='png', dpi=dpi_in, bbox_inches='tight')
def GetNN(curr_id, n_s, n_c, r_c, coords):
print 'getting nearest neighbor information...'
plt.figure(figsize=(12.0,4.0))
# do species first
for i in range(0,n_s):
NN_sp = []
for j in range(0, n_c[i]):
curr_nbr = []
pos1 = coords[i][j]
for l in range(0 , n_c[i]):
if (l == j): continue
pos2 = coords[i][l]
dist = GetDist(pos1,pos2)
curr_nbr.append(dist)
tmp_a = np.array(curr_nbr)
min = np.min(tmp_a)
NN_sp.append(min)
axes_indiv = plt.subplot(1, n_s + 1, i+1)
axes_indiv.grid()
plt.title('species {:d}'.format(i))
tmp_a = np.array(NN_sp)
N = len(NN_sp)
y,binEdges=np.histogram(NN_sp,bins=N**0.5)
bincenters = 0.5*(binEdges[1:]+binEdges[:-1])
pyl.plot(bincenters,y,'-', color='r')
plt.hist(NN_sp, bins=int(N**0.5))
mean = np.mean(tmp_a)
med = np.median(tmp_a)
std = np.std(tmp_a)
stats = 'N = {:d}\n\
mean = {:0.4f}\n\
med = {:0.4f}\n\
std = {:0.4f}'.format(N,mean,med,std)
plt.text(0.8, 0.8, stats, horizontalalignment='right',
verticalalignment='center',
transform=axes_indiv.transAxes)
NN_all = []
for i in range(0,n_s):
for k in range(0, n_c[i]):
curr_nbr = []
pos1 = coords[i][k]
for j in range(0,n_s):
for l in range(0, n_c[j]):
if (i==j and k==l): continue
pos2 = coords[j][l]
dist = GetDist(pos1,pos2)
curr_nbr.append(dist)
tmp_a = np.array(curr_nbr)
min = np.min(tmp_a)
NN_all.append(min)
axes_combined = plt.subplot(1, n_s + 1, n_s+1)
axes_combined.grid()
plt.title('all species')
tmp_a = np.array(NN_all)
N = len(NN_all)
y,binEdges=np.histogram(NN_all,bins=N**0.5)
bincenters = 0.5*(binEdges[1:]+binEdges[:-1])
pyl.plot(bincenters,y,'-',color='r')
plt.hist(NN_all, bins=N**0.5)
mean = np.mean(tmp_a)
med = np.median(tmp_a)
std = np.std(tmp_a)
stats = 'N = {:d}\n\
mean = {:0.4f}\n\
med = {:0.4f}\n\
std = {:0.4f}'.format(N,mean,med,std)
plt.text(0.8, 0.8, stats, horizontalalignment='right',
verticalalignment='center',
transform=axes_combined.transAxes)
fname = curr_id + '_NN.eps'
fout = './dat/' + curr_id + '/Plots/' + fname
ensure_dir(fout)
plt.suptitle('nearest neighbor distribution', fontsize=12)
plt.savefig(fout, bbox_inches=0, dpi = 300)
def CalcBands(curr_id, res, n_s):
print 'calculating bands...'
rad = tm.MakeRad(res, n_s)
fname_out = './dat/' + curr_id + '/Download/' + curr_id + '_out'
fname_band = './dat/' + curr_id + '/' + curr_id + '_bands.csv'
ensure_dir(fname_band)
initiate = 0
if not os.path.exists(fname_band):
lines = [[]]
for i in range(n_s):
lines[0].append('r' + str(i))
numrows = 0
numcols = 0
numbands_i = 0
initiate = 1
for r in rad:
cur_fout = fname_out
for i in range(0, n_s):
cur_fout += '_r{:0.4f}'.format(float(r[i]))
cur_fout += '.OUT'
print 'opening file ' + cur_fout
print 'adding bands for',
print r
if not initiate:
lines = list(csv.reader( open(fname_band, 'rb') , delimiter = '\t' ))
lines = [line[0].split(',') for line in lines]
numrows = len(lines)
numcols = len(lines[0])
numbands_i = ((numcols-2)+1)/3
cur_row = numrows
print('(rows,cols,bands) = {:d}, {:d}, {:d}'.format(numrows,numcols,numbands_i))
print 'checking if already in file...'
changerad = 0
for row in range(1,numrows):
checknum = 0
print '(cur, new) = ',
print [ float(i) for i in lines[row][0:n_s] ],
print r
for c in range(n_s):
cur_rad = float('{:0.4f}'.format(float(lines[row][c])))
my_rad = float('{:0.4f}'.format(float(r[c])))
if(cur_rad != my_rad):
break
checknum = checknum + 1
if(checknum == n_s):
print('ALREADY IN FILE')
changerad = 1
break
if(changerad): break
def PlotBands(curr_id, res, n_s):
print 'plotting bands...'
rad = tm.MakeRad(res, n_s)
fname_out = './dat/' + curr_id + '/Download/' + curr_id + '_out'
fname_band = './dat/' + curr_id + '/Plots/Bands/' + curr_id + '_bands'
ensure_dir(fname_band)
for r in rad:
curr_fout = fname_out
curr_fband = fname_band
for i in range(0, n_s):
curr_fout += '_r{:0.4f}'.format(float(r[i]))
curr_fband += '_r{:0.4f}'.format(float(r[i]))
curr_fout += '.OUT'
curr_fband += '.png'
print 'plotting bands for ' + curr_fout
tmp_bands = 'tmp_bands.del'
tmp_bands2 = 'tmp.del'
cmd0 = 'cat ' + curr_fout + ' | grep -i \"Range\" > ' + tmp_bands2
cmd1 = 'awk \'{print $4, $10}\' tmp.del > ' + tmp_bands
os.system(cmd0)
os.system(cmd1)
fig = plt.figure(figsize=(10,10))
ax = fig.gca()
ax.set_aspect(5)
ax.xaxis.set_ticks_position('none')
plt.tick_params(axis='y', which='major', labelsize=8)
plt.tick_params(axis='x', which='major', labelsize=0)
plt.tick_params(axis='both', which='minor', labelsize=0)
plt.setp(ax.get_xticklabels(), visible=False)
with open(tmp_bands,'r') as fin_bands:
bands = [band.split() for band in fin_bands]
numbands_f = len(bands)
print 'num bands...' + str(numbands_f)
prv_lo = 0.0
prv_hi = 0.0
for band in bands:
cur_lo = float(band[0])
cur_hi = float(band[1])
#print '(lo, hi) = ({:0.4f}, {:0.4f})'.format(cur_lo, cur_hi)
if(cur_lo > prv_hi):
plt.vlines(0, prv_hi, cur_lo, color='r', linewidths = 4)
prv_lo = cur_lo
prv_hi = cur_hi
cmd0 = 'rm ' + tmp_bands
cmd1 = 'rm ' + tmp_bands2
os.system(cmd0)
os.system(cmd1)
plt.axis([-0.25,0.25,0,1])
# plt.text(0,5.05,fname_out,size='8',horizontalalignment='center')
plt.title(r)
plt.savefig(curr_fband, format='png', dpi=300, bbox_inches='tight')
