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Compare.py
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Compare.py
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import matplotlib
matplotlib.use('WXAgg', False)
from matplotlib.figure import Figure
from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigCanvas
import wx
import os
import pickle
import re
import glob
import math
from Tab import Tab
from PDBTools import PDBTools
class Compare(Tab):
def __init__(self, nb):
Tab.__init__(self, nb)
self.fig = Figure((5.0, 4.0), dpi=100)
col = wx.SystemSettings.GetColour(wx.SYS_COLOUR_BACKGROUND)
self.fig.patch.set_facecolor((col[0]/255.0, col[1]/255.0, col[2]/255.0))
self.canvas = FigCanvas(self, -1, self.fig)
self.canvas.mpl_connect('button_press_event', self._on_click)
self.ax1 = self.fig.add_subplot(111)
self.ax1.set_position([0.10,0.153,0.80,0.81])
#self.ax2 = self.ax1.twinx()
self.ax1.tick_params(labelsize=8)
#self.ax2.tick_params(labelsize=8)
self.hist_fig = Figure((2,1.5), dpi=100)
self.hist_fig.set_facecolor((col[0]/255.0, col[1]/255.0, col[2]/255.0))
self.hist_canvas = FigCanvas(self, -1, self.hist_fig)
self.hist_ax1 = self.hist_fig.add_subplot(111)
self.shist_fig = Figure((2,1.5), dpi=100)
self.shist_fig.set_facecolor((col[0]/255.0, col[1]/255.0, col[2]/255.0))
self.shist_canvas = FigCanvas(self, -1, self.shist_fig)
self.shist_ax1 = self.shist_fig.add_subplot(111)
self.refinements = wx.ListBox(self, 26, wx.DefaultPosition, (60, 100), [], wx.LB_MULTIPLE)
self.refinements.Bind(wx.EVT_LISTBOX, self._set_refinements)
self.res_sizer = wx.BoxSizer(wx.HORIZONTAL)
self.res_sizer.Add(wx.StaticText(self, -1, 'Residue Type'), 0, wx.EXPAND)
self.res_type = wx.ComboBox(self, -1, choices=[], style=wx.CB_READONLY)
self.res_type.Bind(wx.EVT_COMBOBOX, self._set_residue_type)
self.res_sizer.Add(self.res_type, 0, wx.EXPAND)
self._flds = [ wx.StaticText(self, -1, '') for i in range(4) ]
self.avg_info = wx.FlexGridSizer(rows=0, cols=2, vgap=5, hgap=5)
self.avg_info.Add(wx.StaticText(self, -1, 'Average Std Dev'), 0, wx.EXPAND)
self.avg_info.Add(self._flds[0], 0, wx.EXPAND)
#self.avg_info.Add(wx.StaticText(self, -1, 'Number of Vals'), wx.EXPAND|wx.ALL, 5)
#self.avg_info.Add(self._flds[1], wx.EXPAND|wx.ALL, 5)
self.res_info = wx.FlexGridSizer(rows=0, cols=2, vgap=5, hgap=5)
self.res_info.Add(wx.StaticText(self, -1, 'Average Values'), 0, wx.EXPAND)
self.res_info.Add(self._flds[1], 0, wx.EXPAND)
self.res_info.Add(wx.StaticText(self, -1, 'Standard Dev'), 0, wx.EXPAND)
self.res_info.Add(self._flds[2], 0, wx.EXPAND)
#self.res_info.Add(wx.StaticText(self, -1, 'Number of Vals'), wx.EXPAND|wx.ALL, 5)
#self.res_info.Add(self._flds[3], wx.EXPAND|wx.ALL, 5)
self.side_sizer = wx.BoxSizer(wx.VERTICAL)
self.side_sizer.Add(wx.StaticText(self, -1, 'Refinements'), 0, wx.EXPAND|wx.LEFT, 5)
self.side_sizer.Add(self.refinements, 0, wx.EXPAND|wx.LEFT, 5)
self.side_sizer.Add(self.res_sizer, 0, wx.EXPAND|wx.LEFT, 5)
self.side_sizer.Add(self.avg_info, 0, wx.EXPAND|wx.LEFT, 5)
self.side_sizer.Add(self.shist_canvas, 1, wx.EXPAND|wx.LEFT, 5)
self.side_sizer.Add(self.res_info, 0, wx.EXPAND|wx.LEFT, 5)
self.side_sizer.Add(self.hist_canvas, 1, wx.EXPAND|wx.LEFT, 5)
self.sizer = wx.BoxSizer(wx.HORIZONTAL)
self.sizer.Add(self.side_sizer, 0, wx.EXPAND|wx.ALL, 5)
self.sizer.Add(self.canvas, 1, wx.EXPAND|wx.ALL, 5)
self._rtypes = ['Aspartate', 'Glutamate', 'Histidine', 'Arginine']
self._rtypess = ['Asp', 'Glu', 'His', 'Arg']
self._residue_type = 0
self._highlight = -1
self._selected_residue = -1
self._residue_types = []
self._all_data = []
self._averaged = []
self._files = []
self.SetSizer(self.sizer)
self.Fit()
def _on_click(self,event):
self._highlight = -1
if event.xdata:
self._highlight = int(round(event.xdata, 0))
t = self._rtypess[self._residue_type].lower()
x = sorted(self._averaged[t].keys())
if self._highlight < len(x):
self._selected_residue = x[self._highlight]
self._plot()
self._show_residue()
def _set_residue_type(self, event):
self._residue_type = self._rtypes.index(self.res_type.GetValue())
self._plot()
def _set_refinements(self, event):
refs = list(self.refinements.GetSelections())
self._pdbs = [ self._files[i].replace('.dat', '.pdb') for i in refs ]
print self._pdbs
self.analyse()
self._plot()
self._show_residue()
def refresh(self):
self.refinements.Clear()
ids, files, dirs = self._get_inputs()
self._files = []
for i,d in enumerate(files):
r = pickle.load(open(d))
p = r.parameters()
if p['type'] in (1,2,3):
self._files.append(files[i])
self.refinements.Append(dirs[i])
def _get_inputs(self):
id = []
files = []
dirs = []
for f in sorted(os.listdir(self._project.root()), key=self.sort_dirs):
m = re.match('(\d+)_', f)
if m:
res = sorted(glob.glob(self._project.root() + os.sep + f + os.sep + '*.dat'))
if len(res) > 0:
id.append(m.group(1))
files.append(res[0])
dirs.append(f)
return id, files, dirs
def sort_dirs(self, item):
l = item.split('_')
if l[0].isdigit():
i = int(l[0])
else:
i = item
return i
def analyse(self):
pdbt = PDBTools()
self._bond_lengths = []
for f in self._pdbs:
om, res = pdbt.get_bond_lengths(str(f))
self._bond_lengths.append(res)
combined = {}
for ty in self._bond_lengths[0].keys():
combined[ty] = {}
for pid,p in enumerate(self._bond_lengths):
for rid,r in p[ty].iteritems():
if not rid in combined[ty]:
combined[ty][rid] = {}
if type(r) == type({}):
for bl,v in r.iteritems():
#print pid, ty, rid, bl, v
if not bl in combined[ty][rid]:
combined[ty][rid][bl] = [[v[0]], [v[1]], [v[2]]]
else:
for i in range(3):
combined[ty][rid][bl][i].append(v[i])
self._all_data = dict(combined)
self._averaged = {}
for tid,res in combined.iteritems():
self._averaged[tid] = {}
for rid,r in res.iteritems():
if not rid in self._averaged[tid]:
self._averaged[tid][rid] = {}
for n,bl in r.iteritems():
tmp = []
for i in range(3):
tmp.append(self._stat(bl[i]))
self._averaged[tid][rid][n] = tmp
self._residue_types = []
self.res_type.Clear()
for k in sorted(self._averaged.keys()):
if k != 'avg' and len(self._averaged[k]) > 0:
self.res_type.Append(self._rtypes[[ x.lower() for x in self._rtypess].index(k)])
self._residue_types.append(k)
def _stat(self, list):
ret = [0,0]
if len(list) > 0:
avg = sum(list)/len(list)
var = []
for i in list:
var.append(pow(abs(i-avg),2))
ret = [avg, 1/float(len(list))*math.sqrt(sum(var))]
return ret
def _plot(self):
self.ax1.cla()
#self.ax2.cla()
#self.ax2.set_ylabel('B Factor ($A^2$)', fontsize=9)
t = self._rtypess[self._residue_type].lower()
tu = self._rtypess[self._residue_type]
x = sorted(self._averaged[t].keys())
xs = [ tu + '-' + str(k) for k in x ]
xa = range(len(x))
l1 = [self._averaged[t][k][1][0][0] for k in x ]
l2 = [self._averaged[t][k][2][0][0] for k in x ]
el1 = [self._averaged[t][k][1][0][1] for k in x ]
el2 = [self._averaged[t][k][2][0][1] for k in x ]
if len(x) > 0:
b1 = [self._averaged[t][k][1][2][0] for k in x ]
be1 = [self._averaged[t][k][2][2][1] for k in x ]
b2 = [self._averaged[t][k][1][2][0] for k in x ]
be2 = [self._averaged[t][k][2][2][1] for k in x ]
if self._residue_type == 0 or self._residue_type == 1:
self.ax1.errorbar(xa, l1, yerr=el1, fmt='ro', label='$C-O\gamma1')
self.ax1.errorbar(xa, l2, yerr=el2, fmt='b^', label='$C-O\gamma2')
#self.ax2.plot(xa, b1, 'go', xa, b2, 'y^')
#self.ax2.errorbar(xa, b1, yerr=be1, fmt='go')
#self.ax2.errorbar(xa, b2, yerr=be2, fmt='y^')
self.ax1.axhline(y=1.21, color='0.7')
self.ax1.axhline(y=1.31, color='0.7')
self.ax1.axhspan(1.327, 1.293, alpha=0.6, color='0.9')
self.ax1.axhspan(1.194, 1.226, alpha=0.6, color='0.9')
#self.ax1.set_ylim(min(l1+l2+[1.2])-0.2, max(l1+l2+[1.32])+0.05)
self.ax1.set_ylabel('C-O (A)', fontsize=9)
# his CG CD2 NE2, ND1 CE1 NE2
elif self._residue_type == 2:
self.ax1.errorbar(xa, l1, yerr=el1, fmt='ro', label='CG-CD2-NE2')
self.ax1.errorbar(xa, l2, yerr=el2, fmt='b^', label='ND1-CE1-NE2')
#self.ax2.plot(xa, b1, 'go', xa, b2, 'y^')
self.ax1.axhline(y=111.2, color='0.7')
self.ax1.axhline(y=109.3, color='0.7')
self.ax1.axhline(y=107.5, color='0.7')
self.ax1.axhline(y=107.2, color='0.7')
#self.ax1.set_ylim(95, 115)
self.ax1.set_ylabel('Angle', fontsize=9)
# arg CZ NH2, CZ NE, CZ NH1, CD NE?
elif self._residue_type == 3:
l3 = [self._averaged[t][k][3][0][0] for k in x ]
#b3 = [self._residues[t][k][3][2] for k in x ]
el3 = [self._averaged[t][k][3][0][1] for k in x ]
self.ax1.errorbar(xa, l1, yerr=el1, fmt='ro', label='CZ-NH2')
self.ax1.errorbar(xa, l2, yerr=el2, fmt='b^', label='CZ-NE')
self.ax1.errorbar(xa, l3, yerr=el3, fmt='b^', label='CZ-NH1')
#self.ax2.plot(xa, b1, 'go', xa, b2, 'y^', xa, b3)
#self.ax1.set_ylim(min(l1+l2)-0.2, max(l1+l2)+0.05)
self.ax1.set_ylabel('NZ-X (A)', fontsize=9)
self.ax1.axhline(y=1.326, color='0.7')
self.ax1.axhline(y=1.41, color='0.7')
#self.ax2.axhline(y=self._averaged['avg']['b'], color=(0.5,0.5,0), ls='--')
#self.ax2.set_ylim(min(b1+b2)-2, max(b1+b2)+20)
self.ax1.set_xlim(-1, len(x))
self.ax1.set_xticks(xa)
self.ax1.set_xticklabels(xs, rotation='vertical', size=8)
self.ax1.tick_params(labelsize=8)
#self.ax2.tick_params(labelsize=8)
if self._highlight > -1:
self.ax1.axvspan(self._highlight-0.5, self._highlight+0.5, alpha=0.3, color='0.9')
#handles, labels = self.ax1.get_legend_handles_labels()
#handles2, labels2 = self.ax2.get_legend_handles_labels()
#self.ax2.legend(handles+handles2, labels+labels2)
self.canvas.draw()
self._hist_stds()
def _hist_stds(self):
t = self._rtypess[self._residue_type].lower()
tu = self._rtypess[self._residue_type]
#print self._averaged[t]
l1 = [ self._averaged[t][rid][1][0][1] for rid in self._averaged[t].keys() ] + [ self._averaged[t][rid][2][0][1] for rid in self._averaged[t].keys() ]
#print l1
self.shist_ax1.cla()
if len(l1) > 0:
avg = sum(l1)/len(l1)
self.shist_ax1.axvline(x=avg, color='blue')
self._flds[0].SetLabel('%.3f' % avg)
#self._flds[1].SetLabel(str(len(l1)))
self.shist_ax1.tick_params(labelsize=8)
self.shist_ax1.hist(l1, 10, normed=1, facecolor='green', alpha=0.75)
self.shist_canvas.draw()
def _show_residue(self):
if self._highlight > -1:
t = self._rtypess[self._residue_type].lower()
tu = self._rtypess[self._residue_type]
l1 = self._all_data[t][self._selected_residue][1][0]
l2 = self._all_data[t][self._selected_residue][2][0]
vals = [ '%.3f' % x[0] for x in [self._stat(l1), self._stat(l2)] ]
stds = [ '%.3f' % x[1] for x in [self._stat(l1), self._stat(l2)] ]
self._flds[1].SetLabel(' '.join(vals))
self._flds[2].SetLabel(' '.join(stds))
self.hist_ax1.cla()
self.hist_ax1.tick_params(labelsize=8)
self.hist_ax1.hist(l1, 5, normed=0, facecolor='red', alpha=0.75)
self.hist_ax1.hist(l2, 5, normed=0, facecolor='blue', alpha=0.75)
self.hist_canvas.draw()