This example shows how to use nmrglue and matplotlib to create figures for examining data or publication. In this example the assignments used in integration example: integrate_2d are graphically examined. A contour plot of the spectrum with the boxes and assignments is created. To examine the box limit more closely see plotting example: plot_2d_boxes.
#! /usr/bin/env python
# Create contour plots of a spectrum with each peak in limits.in labeled
import nmrglue as ng
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm
# plot parameters
cmap = matplotlib.cm.Blues_r # contour map (colors to use for contours)
contour_start = 30000 # contour level start value
contour_num = 20 # number of contour levels
contour_factor = 1.20 # scaling factor between contour levels
textsize = 6 # text size of labels
# calculate contour levels
cl = [contour_start*contour_factor**x for x in xrange(contour_num)]
# read in the data from a NMRPipe file
dic,data = ng.pipe.read("../../common_data/2d_pipe/test.ft2")
# read in the integration limits
peak_list = np.recfromtxt("limits.in")
# create the figure
fig = plt.figure()
ax = fig.add_subplot(111)
# plot the contours
ax.contour(data,cl,cmap=cmap,extent=(0,data.shape[1]-1,0,data.shape[0]-1))
# loop over the peaks
for name,x0,y0,x1,y1 in peak_list:
if x0>x1:
x0,x1 = x1,x0
if y0>y1:
y0,y1 = y1,y0
# plot a box around each peak and label
ax.plot([x0,x1,x1,x0,x0],[y0,y0,y1,y1,y0],'k')
ax.text(x1+1,y0,name,size=textsize,color='r')
# set limits
ax.set_xlim(1900,2200)
ax.set_ylim(750,1400)
# save the figure
fig.savefig("assignments.png")
#Peak X0 Y0 X1 Y1
# Peak defines 15N resonance in 2D NCO spectra.
# Limits are in term of points from 0 to length-1.
# These can determined from nmrDraw by subtracting 1 from the X and Y
# values reported.
#Peak X0 Y0 X1 Y1
T49 1992 1334 2003 1316
T11 1996 1302 2008 1284
# comments can appear anywhere in this file just start the line with #
G14 2032 1314 2044 1293
E15 2077 1025 2087 1004
W43 2008 952 2019 933
Result: