def plot_2D(d, scale, numb2, resdir):
fiddir = op.dirname(numb2)
basedir, fidname = op.split(fiddir)
base, manip = op.split(basedir)
exptype = bk.read_param(bk.find_acqu(fiddir))['$PULPROG']
exptype = exptype[1:-1] # removes the <...>
d.display(scale=scale)
plt.savefig(
op.join(resdir, '2D', exptype + '_' + fidname +
'.pdf')) # Creates a PDF of the 2D spectrum without peaks
d.display_peaks(color="g")
plt.savefig(
op.join(resdir, '2D', exptype + '_' + fidname +
'_pp.pdf')) # Creates a PDF of the 2D spectrum with peaks
plt.close()
return d
def Dprocess_2D(numb2, resdir):
"Performs DOSY processing of experiment 'numb2' and produces the spectrum with and without peaks"
fiddir = op.dirname(numb2)
basedir, fidname = op.split(fiddir)
base, manip = op.split(basedir)
exptype = bk.read_param(bk.find_acqu(fiddir))['$PULPROG']
exptype = exptype[1:-1] # removes the <...>
ppm_offset, ph0, ph1 = get_config(base, manip, fidname)
d = bk.Import_2D(numb2)
d.unit = 'ppm'
if 'ste' in exptype or 'led' in exptype:
print("DOSY")
d = process_DOSY(numb2, ppm_offset, lazy=DOSY_LAZY)
scale = 50.0
else:
raise Exception("This is not a DOSY: " + numb2)
dd = analyze_2D(d, name=op.join(resdir, '2D', exptype + '_' + fidname))
d.save(op.join(fiddir, "processed.gs2"))
return dd, scale
def process_2D(xarg):
"Performs all processing of experiment 'numb2' and produces the spectrum with and without peaks"
numb2, resdir = xarg
fiddir = op.dirname(numb2)
basedir, fidname = op.split(fiddir)
base, manip = op.split(basedir)
exptype = bk.read_param(bk.find_acqu(fiddir))['$PULPROG']
exptype = exptype[1:-1] # removes the <...>
ppm_offset, ph0, ph1 = get_config(base, manip, fidname)
d = bk.Import_2D(numb2)
d.unit = 'ppm'
scale = 10.0
sanerank = SANERANK
#1. If TOCSY
if 'dipsi' in exptype:
print("TOCSY")
# print exptype
if 'dipsi2ph' in exptype:
d.apod_sin(maxi=0.5, axis=2).zf(zf2=2).ft_sim()
if sanerank != 0:
d.sane(rank=sanerank, axis=1)
d.apod_sin(maxi=0.5,
axis=1).zf(zf1=4).ft_sh_tppi().modulus().rem_ridge()
elif 'dipsi2etgpsi' in exptype:
d.apod_sin(maxi=0.5, axis=2).zf(zf2=2).ft_sim()
if sanerank != 0:
d.sane(rank=sanerank, axis=1)
d.apod_sin(maxi=0.5,
axis=1).zf(zf1=4).ft_n_p().modulus().rem_ridge()
scale = 50.0
d.axis2.offset += ppm_offset * d.axis2.frequency
if TMS:
d = autozero(d)
#2. If COSY DQF
elif 'cosy' in exptype:
print("COSY DQF")
d.apod_sin(maxi=0.5, axis=2).zf(zf2=2).ft_sim()
if sanerank != 0:
d.sane(rank=sanerank, axis=1)
d.apod_sin(maxi=0.5,
axis=1).zf(zf1=4).ft_sh_tppi().modulus().rem_ridge()
scale = 20.0
d.axis2.offset += ppm_offset * d.axis2.frequency
if TMS:
d = autozero(d)
#3. If HSQC
elif 'hsqc' in exptype:
print("HSQC")
if 'ml' in exptype:
print("TOCSY-HSQC")
d.apod_sin(maxi=0.5, axis=2).zf(zf2=2).ft_sim().conv_n_p()
if sanerank != 0:
d.sane(rank=sanerank, axis=1)
d.apod_sin(maxi=0.5, axis=1).zf(zf1=4).ft_sh().modulus().rem_ridge()
scale = 10.0
d.axis2.offset += ppm_offset * d.axis2.frequency
if TMS:
d = autozero(d, z1=(5, -5))
#4. If HMBC
elif 'hmbc' in exptype:
print("HMBC")
if 'hmbc' in exptype:
print("HMBC")
d.apod_sin(maxi=0.5, axis=2).zf(zf2=2).ft_sim()
if 'et' in exptype:
d.conv_n_p()
if sanerank != 0:
d.sane(rank=sanerank, axis=1)
d.apod_sin(maxi=0.5, axis=1).zf(
zf1=4).bk_ftF1().modulus().rem_ridge() # For Pharma MB1-X-X series
scale = 10.0
d.axis2.offset += ppm_offset * d.axis2.frequency
if TMS:
d = autozero(d, z1=(5, -5))
#5. If DOSY - Processed in process_DOSY
elif 'ste' in exptype or 'led' in exptype:
print("DOSY")
d = process_DOSY(numb2, ppm_offset, lazy=DOSY_LAZY)
scale = 50.0
analyze_2D(d, name=op.join(resdir, '2D', exptype + '_' + fidname))
d.save(op.join(fiddir, "processed.gs2"))
return d, scale