def calc_fret_deltas(residues): delta_dict = {} # --- First, fit Bid data --- bid_fit_results = nba.plot_3conf_fits(df_pre, residues, 'Bid', dtype='FRET', do_plot=False) for fr in bid_fit_results: # Calculate the difference key = (fr.activator, fr.measurement, fr.nbd_site, fr.rep_index) delta_fret = np.max(fr.y) - fr.y[-1] delta_dict[key] = delta_fret # --- Now do Bim --- bim_fit_results = nba.plot_3conf_fits(df_pre, residues, 'Bim', dtype='FRET', do_plot=False) for fr in bim_fit_results: # Calculate the difference key = (fr.activator, fr.measurement, fr.nbd_site, fr.rep_index) delta_fret = np.max(fr.y) - fr.y[-1] delta_dict[key] = delta_fret # Cache the results with open('fret_deltas.pck', 'w') as f: cPickle.dump(delta_dict, f) return delta_dict
from tbidbaxlipo.plots.nbd_bax_analysis import plot_2conf_fits, plot_3conf_fits from tbidbaxlipo.plots.bid_bim_fret_nbd_release.preprocess_data \ import df_pre, df, nbd_residues from matplotlib import pyplot as plt plt.ion() nbd_residues=['184'] fret_fr = plot_2conf_fits(df_pre, nbd_residues, activator='Bim', dtype='FRET', replicates=(1, 2, 3)) #plt.show() nbd_fr = plot_3conf_fits(df_pre, nbd_residues, activator='Bim', dtype='NBD', replicates=(1, 2, 3)) #plt.show() fret_k1 = [fret_fr[i].param_dict['c0_to_c1_k'] for i in range(3)] nbd_k1 = [nbd_fr[i].param_dict['c0_to_c1_k'] for i in range(3)] print "FRET", fret_k1 print "NBD", nbd_k1