import sys, os, math, re import numpy as np import matplotlib.pyplot as plt import pylab sys.path.insert(0, os.path.abspath('..')) from sasmodels import generate, core from sasmodels.direct_model import DirectModel from sasmodels.data import empty_data1D, empty_data2D # Convert ../sasmodels/models/name.py to name model_name = os.path.basename(sys.argv[1])[:-3] model_info = core.load_model_info(model_name) model = core.build_model(model_info) # Load the doc string from the module definition file and store it in rst docstr = generate.make_doc(model_info) # Calculate 1D curve for default parameters pars = dict((p.name, p.default) for p in model_info['parameters']) # Plotting ranges and options opts = { 'xscale' : 'log', 'yscale' : 'log' if not model_info['structure_factor'] else 'linear', 'zscale' : 'log' if not model_info['structure_factor'] else 'linear', 'q_min' : 0.001, 'q_max' : 1.0, 'nq' : 1000, 'nq2d' : 1000, 'vmin' : 1e-3, # floor for the 2D data results 'qx_max' : 0.5, #'colormap' : 'gist_ncar', 'colormap' : 'nipy_spectral', #'colormap' : 'jet', } def plot_1d(model, opts, ax): q_min, q_max, nq = opts['q_min'], opts['q_max'], opts['nq'] q_min = math.log10(q_min) q_max = math.log10(q_max) q = np.logspace(q_min, q_max, nq) data = empty_data1D(q) calculator = DirectModel(data, model) Iq1D = calculator() ax.plot(q, Iq1D, color='blue', lw=2, label=model_info['name']) ax.set_xlabel(r'$Q \/(\AA^{-1})$') ax.set_ylabel(r'$I(Q) \/(\mathrm{cm}^{-1})$') ax.set_xscale(opts['xscale']) ax.set_yscale(opts['yscale']) #ax.legend(loc='best') def plot_2d(model, opts, ax): qx_max, nq2d = opts['qx_max'], opts['nq2d'] q = np.linspace(-qx_max, qx_max, nq2d) data2d = empty_data2D(q, resolution=0.0) calculator = DirectModel(data2d, model) Iq2D = calculator() #background=0) Iq2D = Iq2D.reshape(nq2d, nq2d) if opts['zscale'] == 'log': Iq2D = np.log(np.clip(Iq2D, opts['vmin'], np.inf)) ax.imshow(Iq2D, interpolation='nearest', aspect=1, origin='lower', extent=[-qx_max, qx_max, -qx_max, qx_max], cmap=opts['colormap']) ax.set_xlabel(r'$Q_x \/(\AA^{-1})$') ax.set_ylabel(r'$Q_y \/(\AA^{-1})$') # Generate image fig_height = 3.0 # in fig_left = 0.6 # in fig_right = 0.5 # in fig_top = 0.6*0.25 # in fig_bottom = 0.6*0.75 if model_info['has_2d']: plot_height = fig_height - (fig_top+fig_bottom) plot_width = plot_height fig_width = 2*(plot_width + fig_left + fig_right) aspect = (fig_width, fig_height) ratio = aspect[0]/aspect[1] ax_left = fig_left/fig_width ax_bottom = fig_bottom/fig_height ax_height = plot_height/fig_height ax_width = ax_height/ratio # square axes fig = plt.figure(figsize=aspect) ax2d = fig.add_axes([0.5+ax_left, ax_bottom, ax_width, ax_height]) plot_2d(model, opts, ax2d) ax1d = fig.add_axes([ax_left, ax_bottom, ax_width, ax_height]) plot_1d(model, opts, ax1d) #ax.set_aspect('square') else: plot_height = fig_height - (fig_top+fig_bottom) plot_width = (1+np.sqrt(5))/2*fig_height fig_width = plot_width + fig_left + fig_right ax_left = fig_left/fig_width ax_bottom = fig_bottom/fig_height ax_width = plot_width/fig_width ax_height = plot_height/fig_height aspect = (fig_width, fig_height) fig = plt.figure(figsize=aspect) ax1d = fig.add_axes([ax_left, ax_bottom, ax_width, ax_height]) plot_1d(model, opts, ax1d) # Save image in model/img figname = model_name + '_autogenfig.png' filename = os.path.join('model', 'img', figname) plt.savefig(filename, bbox_inches='tight') #print "figure saved in",filename # Auto caption for figure captionstr = '\n' captionstr += '.. figure:: img/' + model_info['id'] + '_autogenfig.png\n' captionstr += '\n' if model_info['has_2d']: captionstr += ' 1D and 2D plots corresponding to the default parameters of the model.\n' else: captionstr += ' 1D plot corresponding to the default parameters of the model.\n' captionstr += '\n' # Add figure reference and caption to documentation (at end, before References) pattern = '\*\*REFERENCE' m = re.search(pattern, docstr.upper()) if m: docstr1 = docstr[:m.start()] docstr2 = docstr[m.start():] docstr = docstr1 + captionstr + docstr2 else: print '------------------------------------------------------------------' print 'References NOT FOUND for model: ', model_info['id'] print '------------------------------------------------------------------' docstr = docstr + captionstr open(sys.argv[2],'w').write(docstr)