def contactm(distancem,threshold=None): if threshold == None: # Colormap pylab.matshow(np.transpose(distancem)) pylab.colorbar() pylab.savefig(protein_name + '.png') else: # Thresholded map contact_map = distancem > 15 pylab.autumn() pylab.imshow(np.transpose(contact_map)) pylab.savefig(protein_name + '_thr.png')
def contactm(distancem, threshold=None):
if threshold == None:
# Colormap
pylab.matshow(np.transpose(distancem))
pylab.colorbar()
pylab.savefig(protein_name + '.png')
else:
# Thresholded map
contact_map = distancem > 15
pylab.autumn()
pylab.imshow(np.transpose(contact_map))
pylab.savefig(protein_name + '_thr.png')
fh = pdbl.retrieve_pdb_file(
'1CON') #downloads the pdb file of 2CD0 protein
structure = parser.get_structure(
'1CON', fh
) #extrae la inform estruct de la proteina descargada. 2cd0 es trivial.
residues = structure.get_residues() #mirar si separa chains.
counter = 0
mylist2 = list()
i = 0
#for model in structure:
for chain in structure[0]:
for residue in chain:
j = 0
mylist = list()
for residue2 in chain:
try:
mylist.append(residue['CA'] - residue2['CA'])
except:
mylist.append(10000)
j += 1
#print j
mylist2.append(mylist)
i += 1
#print i
distancem = np.asarray(mylist2)
contact_map = distancem > 15
pylab.autumn()
pylab.imshow(np.transpose(contact_map))
pylab.show()
def _lss_corr(obs,
interactive=True,
maxcr=False,
figno=20,
rawxy=None,
target='target',
chatter=0):
'''determine the LSS correction for the readout streak source '''
import os
import numpy as np
try:
from astropy.io import fits
except:
import pyfits as fits
from pylab import figure,imshow,ginput,axvspan,\
axhspan,plot,autumn,title,clf
file = obs['infile']
ext = obs['extension']
cols = obs['streak_col_SN_CR_ERR']
kol = []
countrates = []
circle = [
np.sin(np.arange(0, 2 * np.pi, 0.05)),
np.cos(np.arange(0, 2 * np.pi, 0.05))
]
for k in cols:
kol.append(k[1]) # S/N
countrates.append(k[2])
kol = np.array(kol)
if len(kol) == 0:
print "zero array kol in _lss_corr ???!!!!"
print "LSS correction cannot be determined."
return 1.0, (0, 0), (1100.5, 1100.5)
k_sn_max = np.where(np.max(kol) == kol) # maximum s/n column
print "k S/N max=", k_sn_max[0][0]
kol = []
for k in cols:
kol.append(k[0]) # column number relative to bottom rh corner subimage
if len(kol) == 0:
print "LSS correction cannot be determined."
return 1.0, (0, 0), (1100.5, 1100.5)
im = fits.getdata(file, ext=ext)
hdr = fits.getheader(file, ext=ext)
#binx = hdr['binx']
mn = im.mean()
sig = im.std()
# plot
figure(figno)
clf()
autumn()
imshow(im, vmin=mn - 0.2 * sig, vmax=mn + 2 * sig)
if rawxy != None:
rawx, rawy = rawxy
R = hdr['windowdx'] / 15.
plot(R * circle[0] + rawx - hdr['windowy0'],
R * circle[1] + rawy - hdr['windowx0'],
'-',
color='m',
alpha=0.7,
lw=2)
title(u"PUT CURSOR on your OBJECT", fontsize=16)
if not maxcr:
count = 0
for k in kol:
axvspan(k - 6,
k + 6,
0.01,
0.99,
facecolor='k',
alpha=0.3 - 0.02 * count)
count += 1
else:
k = k_sn_max[0][0]
axvspan(k - 10, k + 10, 0.01, 0.99, facecolor='k', alpha=0.2)
happy = False
skip = False
count = 0
while not happy:
print "put the cursor on the location of your source"
count += 1
coord = ginput(timeout=0)
print "selected:", coord
if len(coord[0]) == 2:
print "window corner:", hdr['windowx0'], hdr['windowy0']
xloc = coord[0][0] + hdr['windowx0']
yloc = coord[0][1] + hdr['windowy0']
print "on detector (full raw image) should be :", xloc, yloc
#plot(coord[0][0],coord[0][1],'+',markersize=14,color='k',lw=2) #can't see it
axhspan(coord[0][1] - 6,
coord[0][1] + 6,
0,
1,
facecolor='k',
alpha=0.3)
if rawxy != None:
rawx, rawy = rawxy
R = hdr['windowdx'] / 15.
plot(R * circle[0] + rawx - hdr['windowx0'],
R * circle[1] + rawy - hdr['windowy0'],
'-',
color='k',
alpha=0.7,
lw=1)
#plot(rawx-hdr['windowx0'],rawy-hdr['windowy0'],'o',markersize=25,color='w',alpha=0.3)
ans = raw_input("happy (yes,skip,no): ")
if len(ans) > 0:
if ans.upper()[0] == 'Y':
happy = True
if ans.upper()[0] == 'S':
return 0.0, coord[0], (yloc + 104, xloc + 78)
else:
print "no position found"
if count > 10:
print "Too many tries: aborting"
happy = True
im = ''
try:
lss = 1.0
band = obs['band']
caldb = os.getenv('CALDB')
command = "quzcif swift uvota - "+band.upper()+\
" SKYFLAT "+\
obs['dateobs'].split('T')[0]+" "+\
obs['dateobs'].split('T')[1]+" - > lssfile.1234.tmp"
print command
os.system(command)
f = open('lssfile.1234.tmp')
lssfile = f.readline()
f.close()
f = fits.getdata(lssfile.split()[0], ext=int(lssfile.split()[1]))
lss = f[yloc, xloc]
print "lss correction = ", lss, " coords=", coord[0], (yloc + 104,
xloc + 78)
return lss, coord[0], (yloc + 104, xloc + 78)
except:
print "LSS correction cannot be determined."
return 1.0, (0, 0), (1100.5, 1100.5)
pdb_filename = "1XI4.pdb"
def calc_residue_dist(residue_one, residue_two) :
"""Returns the C-alpha distance between two residues"""
diff_vector = residue_one["CA"].coord - residue_two["CA"].coord
return numpy.sqrt(numpy.sum(diff_vector * diff_vector))
def calc_dist_matrix(chain_one, chain_two) :
"""Returns a matrix of C-alpha distances between two chains"""
answer = numpy.zeros((len(chain_one), len(chain_two)), numpy.float)
for row, residue_one in enumerate(chain_one) :
for col, residue_two in enumerate(chain_two) :
answer[row, col] = calc_residue_dist(residue_one, residue_two)
return answer
structure = Bio.PDB.PDBParser().get_structure(pdb_code, pdb_filename)
model = structure[0]
dist_matrix = calc_dist_matrix(model["D"], model["D"])
contact_map = dist_matrix < 20.0
# print "Minimum distance", numpy.min(dist_matrix)
# print "Maximum distance", numpy.max(dist_matrix)
import pylab
pylab.autumn()
pylab.imshow(numpy.transpose(contact_map))
pylab.show()
def _lss_corr(obs,interactive=True,maxcr=False,figno=20,
rawxy=None,
target='target',
chatter=0):
'''determine the LSS correction for the readout streak source '''
import os
import numpy as np
try:
from astropy.io import fits
except:
import pyfits as fits
from pylab import figure,imshow,ginput,axvspan,\
axhspan,plot,autumn,title,clf
file = obs['infile']
ext = obs['extension']
cols = obs['streak_col_SN_CR_ERR']
kol = []
countrates=[]
circle=[np.sin(np.arange(0,2*np.pi,0.05)),np.cos(np.arange(0,2*np.pi,0.05))]
for k in cols:
kol.append(k[1]) # S/N
countrates.append(k[2])
kol = np.array(kol)
if len(kol) == 0:
print("zero array kol in _lss_corr ???!!!!")
print("LSS correction cannot be determined.")
return 1.0, (0,0), (1100.5,1100.5)
k_sn_max = np.where(np.max(kol) == kol) # maximum s/n column
print("k S/N max=",k_sn_max[0][0])
kol = []
for k in cols:
kol.append(k[0]) # column number relative to bottom rh corner subimage
if len(kol) == 0:
print("LSS correction cannot be determined.")
return 1.0, (0,0), (1100.5,1100.5)
im=fits.getdata(file, ext=ext)
hdr=fits.getheader(file, ext=ext)
#binx = hdr['binx']
mn = im.mean()
sig = im.std()
# plot
figure(figno)
clf()
autumn()
imshow(im,vmin=mn-0.2*sig,vmax=mn+2*sig)
if rawxy != None:
rawx,rawy = rawxy
R = hdr['windowdx']/15.
plot(R*circle[0]+rawx-hdr['windowy0'],R*circle[1]+rawy-hdr['windowx0'],
'-',color='m',alpha=0.7,lw=2)
title(u"PUT CURSOR on your OBJECT",fontsize=16)
if not maxcr:
count = 0
for k in kol:
axvspan(k-6,k+6,0.01,0.99, facecolor='k',alpha=0.3-0.02*count)
count += 1
else:
k = k_sn_max[0][0]
axvspan(k-10,k+10,0.01,0.99, facecolor='k',alpha=0.2)
happy = False
skip = False
count = 0
while not happy :
print("put the cursor on the location of your source")
count += 1
coord = ginput(timeout=0)
print("selected:",coord)
if len(coord[0]) == 2:
print("window corner:", hdr['windowx0'],hdr['windowy0'])
xloc = coord[0][0]+hdr['windowx0']
yloc = coord[0][1]+hdr['windowy0']
print("on detector (full raw image) should be :",xloc,yloc)
#plot(coord[0][0],coord[0][1],'+',markersize=14,color='k',lw=2) #can't see it
axhspan(coord[0][1]-6,coord[0][1]+6,0,1,facecolor='k',alpha=0.3)
if rawxy != None:
rawx,rawy = rawxy
R = hdr['windowdx']/15.
plot(R*circle[0]+rawx-hdr['windowx0'],R*circle[1]+rawy-hdr['windowy0'],
'-',color='k',alpha=0.7,lw=1)
#plot(rawx-hdr['windowx0'],rawy-hdr['windowy0'],'o',markersize=25,color='w',alpha=0.3)
ans = raw_input("happy (yes,skip,no): ")
if len(ans) > 0:
if ans.upper()[0] == 'Y':
happy = True
if ans.upper()[0] == 'S':
return 0.0, coord[0], (yloc+104,xloc+78)
else:
print("no position found")
if count > 10:
print("Too many tries: aborting" )
happy = True
im = ''
try:
lss = 1.0
band = obs['band']
caldb = os.getenv('CALDB')
command = "quzcif swift uvota - "+band.upper()+\
" SKYFLAT "+\
obs['dateobs'].split('T')[0]+" "+\
obs['dateobs'].split('T')[1]+" - > lssfile.1234.tmp"
print(command)
os.system(command)
f = open('lssfile.1234.tmp')
lssfile = f.readline()
f.close()
f = fits.getdata(lssfile.split()[0],ext=int(lssfile.split()[1]))
lss = f[ yloc,xloc]
print("lss correction = ",lss," coords=",coord[0], (yloc+104,xloc+78))
return lss, coord[0], (yloc+104,xloc+78)
except:
print("LSS correction cannot be determined.")
return 1.0, (0,0), (1100.5,1100.5)