Changeset 3003

Timestamp:

Aug 12, 2017 4:23:31 PM (6 years ago)

Author:

vondreele

Message:

more development of protein validation - still not correct
substitute old "paired" & "Paired-r" continuous colors for the installed one (16 discrete colors in mpl 2.0.X
trap use of tick_label in barh (not in mpl <2.0)

Location:

trunk

Files:

• GSASIImath.py (modified) (6 diffs)
• GSASIIplot.py (modified) (3 diffs)

trunk/GSASIImath.py

@@ -2574 +2574 @@
     resNames = ['ALA','ARG','ASN','ASP','CYS','GLN','GLU','GLY','HIS','ILE',
         'LEU','LYS','MET','PHE','PRO','SER','THR','TRP','TYR','VAL','MSE']
+    old = True          #use errat version 1 math
+# data from errat.f
+    b1_old = np.array([ 
+        [1154.343,  600.213, 1051.018, 1132.885,  960.738],
+        [600.213, 1286.818, 1282.042,  957.156,  612.789],
+        [1051.018, 1282.042, 3519.471,  991.974, 1226.491],
+        [1132.885,  957.156,  991.974, 1798.672,  820.355],
+        [960.738,  612.789, 1226.491,  820.355, 2428.966]
+        ])
+    avg_old = np.array([ 0.225, 0.281, 0.071, 0.237, 0.044])    #Table 1 3.5A Obsd. Fr. p 1513
 # data taken from erratv2.ccp
-    b1 = np.array([     [0,0,0,0,0,0],
-          [0,   5040.279078850848200,   3408.805141583649400,   4152.904423767300600,   4236.200004171890200,   5054.781210204625500],  
-          [0,   3408.805141583648900,   8491.906094010220800,   5958.881777877950300,   1521.387352718486200,   4304.078200827221700],  
-          [0,   4152.904423767301500,   5958.881777877952100,   7637.167089335050100,   6620.715738223072500,   5287.691183798410700],  
-          [0,   4236.200004171890200,   1521.387352718486200,   6620.715738223072500,   18368.343774298410000,  4050.797811118806700],  
-          [0,   5054.781210204625500,   4304.078200827220800,   5287.691183798409800,   4050.797811118806700,   6666.856740479164700]])
-    avg = np.array([0.,0.192765509919262, 0.195575208778518, 0.275322406824210, 0.059102357035642, 0.233154192767480])
+    b1 = np.array([
+          [5040.279078850848200,        3408.805141583649400,   4152.904423767300600,   4236.200004171890200,   5054.781210204625500],  
+          [3408.805141583648900,        8491.906094010220800,   5958.881777877950300,   1521.387352718486200,   4304.078200827221700],  
+          [4152.904423767301500,        5958.881777877952100,   7637.167089335050100,   6620.715738223072500,   5287.691183798410700],  
+          [4236.200004171890200,        1521.387352718486200,   6620.715738223072500,   18368.343774298410000,  4050.797811118806700],  
+          [5054.781210204625500,        4304.078200827220800,   5287.691183798409800,   4050.797811118806700,   6666.856740479164700]])
+    avg = np.array([0.192765509919262, 0.195575208778518, 0.275322406824210, 0.059102357035642, 0.233154192767480])
     General = Phase['General']
     Amat,Bmat = G2lat.cell2AB(General['Cell'][1:7])
@@ -2594 +2604 @@
             if atom[4].strip() in ['S','Se']:
                 atom[4] = 'O'
-            if atom[3].strip() in ['C','N']:    #skip main chain C & N atoms
-                continue
+#            if atom[3].strip() in ['C','N']:    #skip main chain C & N atoms
+#                continue
             cartAtoms.append(atom[:cx+3])
             cartAtoms[-1][cx:cx+3] = np.inner(Amat,cartAtoms[-1][cx:cx+3])
@@ -2607 +2617 @@
         Boxes[box[0],box[1],box[2],0] += 1
         Boxes[box[0],box[1],box[2],Boxes[box[0],box[1],box[2],0]] = ib
+    #Box content checks with errat.f ibox1 array
     indices = (-1,0,1)
     Units = np.array([[h,k,l] for h in indices for k in indices for l in indices]) 
     dsmax = 3.75**2
+    if old:
+        dsmax = 3.5**2
     chains = []
     resIntAct = []
@@ -2631 +2644 @@
                 newChain = True
         if atom[0] not in res:  #new residue, get residue no.
+            if len(res): print res[-1],resname[-1],intact
             res.append(atom[0])
             resname.append('%s-%s%s'%(atom[2],atom[0],atom[1]))
@@ -2645 +2659 @@
         tgts = list(set(tgts))
         tgts = [tgt for tgt in tgts if atom[1:3] != cartAtoms[tgt][1:3]]    #exclude same residue
-        tgts = [tgt for tgt in tgts if cartAtoms[tgt][3].strip() not in ['C','N']]  #exclude main chain
+        if atom[3].strip() in ['C',]:
+            tgts = [tgt for tgt in tgts if cartAtoms[tgt][3].strip() not in ['N',]]  #exclude main chain C-N
+        if atom[3].strip() in ['N',]:
+            tgts = [tgt for tgt in tgts if cartAtoms[tgt][3].strip() not in ['C',]]  #exclude main chain N-C
         tgts = [tgt for tgt in tgts if np.sum((XYZ[ia]-XYZ[tgt])**2) <= dsmax]
         for tgt in tgts:
             dsqt = np.sqrt(np.sum((XYZ[ia]-XYZ[tgt])**2))
             mult = 1.0
-            if dsqt > 3.25:
+            if dsqt > 3.25 and not old:
                 mult = 2.*(3.75-dsqt)
             intype = atom[4].strip()+cartAtoms[tgt][4].strip()
@@ -2663 +2680 @@
         Probs = [0.,0.,0.,0.]
         for i in range(4,nRes-4):
-            mtrx = np.zeros(6)
+            print i,IntAct[i]
+            mtrx = np.zeros(5)
             summ = 0.
-            for j in range(i-4,i+4):
+            for j in range(i-4,i+5):
                 summ += np.sum(np.array(IntAct[j].values()))
-                print 'CC',IntAct[j]['CC'],'CN',IntAct[j]['CN'],'CO',IntAct[j]['CO']
-                print 'NN',IntAct[j]['NN'],'NO',IntAct[j]['NO'],'OO',IntAct[j]['OO']
-                mtrx[1] += IntAct[j]['CC']
-                mtrx[2] += IntAct[j]['CN']
-                mtrx[3] += IntAct[j]['CO']
-                mtrx[4] += IntAct[j]['NN']
-                mtrx[5] += IntAct[j]['NO']
+                if old:
+                    mtrx[0] += IntAct[j]['CC']
+                    mtrx[1] += IntAct[j]['CO']
+                    mtrx[2] += IntAct[j]['NN']
+                    mtrx[3] += IntAct[j]['NO']
+                    mtrx[4] += IntAct[j]['OO']
+                else:
+                    mtrx[0] += IntAct[j]['CC']
+                    mtrx[1] += IntAct[j]['CN']
+                    mtrx[2] += IntAct[j]['CO']
+                    mtrx[3] += IntAct[j]['NN']
+                    mtrx[4] += IntAct[j]['NO']
+            print mtrx,np.sum(mtrx)
+            print summ
             mtrx /= summ
-            mtrx -= avg
-            prob = np.inner(np.inner(mtrx,b1),mtrx)/36.
+            if old:
+                mtrx -= avg_old
+                prob = np.inner(np.inner(mtrx,b1_old),mtrx)
+            else:
+                mtrx -= avg
+                prob = np.inner(np.inner(mtrx,b1),mtrx)
             print i, mtrx
             Probs.append(prob)

trunk/GSASIIplot.py

@@ -70 +70 @@
 #    GSASIIpath.IPyBreak()
 plotDebug = False
-    
+#matplotlib 2.0.x dumbed down Paired to 16 colors - 
+#   this restores the pre 2.0 Paired color map found in matplotlib._cm.py
+_Old_Paired_data = {'blue': [(0.0, 0.89019608497619629,
+0.89019608497619629), (0.090909090909090912, 0.70588237047195435,
+0.70588237047195435), (0.18181818181818182, 0.54117649793624878,
+0.54117649793624878), (0.27272727272727271, 0.17254902422428131,
+0.17254902422428131), (0.36363636363636365, 0.60000002384185791,
+0.60000002384185791), (0.45454545454545453, 0.10980392247438431,
+0.10980392247438431), (0.54545454545454541, 0.43529412150382996,
+0.43529412150382996), (0.63636363636363635, 0.0, 0.0),
+(0.72727272727272729, 0.83921569585800171, 0.83921569585800171),
+(0.81818181818181823, 0.60392159223556519, 0.60392159223556519),
+(0.90909090909090906, 0.60000002384185791, 0.60000002384185791), (1.0,
+0.15686275064945221, 0.15686275064945221)],
+
+    'green': [(0.0, 0.80784314870834351, 0.80784314870834351),
+    (0.090909090909090912, 0.47058823704719543, 0.47058823704719543),
+    (0.18181818181818182, 0.87450981140136719, 0.87450981140136719),
+    (0.27272727272727271, 0.62745100259780884, 0.62745100259780884),
+    (0.36363636363636365, 0.60392159223556519, 0.60392159223556519),
+    (0.45454545454545453, 0.10196078568696976, 0.10196078568696976),
+    (0.54545454545454541, 0.74901962280273438, 0.74901962280273438),
+    (0.63636363636363635, 0.49803921580314636, 0.49803921580314636),
+    (0.72727272727272729, 0.69803923368453979, 0.69803923368453979),
+    (0.81818181818181823, 0.23921568691730499, 0.23921568691730499),
+    (0.90909090909090906, 1.0, 1.0), (1.0, 0.3490196168422699,
+    0.3490196168422699)],
+
+    'red': [(0.0, 0.65098041296005249, 0.65098041296005249),
+    (0.090909090909090912, 0.12156862765550613, 0.12156862765550613),
+    (0.18181818181818182, 0.69803923368453979, 0.69803923368453979),
+    (0.27272727272727271, 0.20000000298023224, 0.20000000298023224),
+    (0.36363636363636365, 0.9843137264251709, 0.9843137264251709),
+    (0.45454545454545453, 0.89019608497619629, 0.89019608497619629),
+    (0.54545454545454541, 0.99215686321258545, 0.99215686321258545),
+    (0.63636363636363635, 1.0, 1.0), (0.72727272727272729,
+    0.7921568751335144, 0.7921568751335144), (0.81818181818181823,
+    0.41568627953529358, 0.41568627953529358), (0.90909090909090906,
+    1.0, 1.0), (1.0, 0.69411766529083252, 0.69411766529083252)]}
+mpl.cm.register_cmap('Paired',data=_Old_Paired_data,lut=128)
+mpl.cm.register_cmap('Paired_r',data=mpl.cm._reverse_cmap_spec(_Old_Paired_data),lut=128)
+#This can be done on request for other colors
+
 class _tabPlotWin(wx.Panel):    
     'Creates a basic tabbed plot window for GSAS-II graphics'
@@ -3111 +3153 @@
         Plot.set_xlabel(r'Error score',fontsize=14)
         Plot.set_ylabel(r'Residue',fontsize=14)
-        colors=['b','r','g','c','m','k']
-        Plot.barh(np.arange(len(resNames)),Probs,tick_label=resNames,)
+        try:
+            Plot.barh(np.arange(len(resNames)),Probs,tick_label=resNames,)
+        except AttributeError:  #tick_label not in mpl 1.4
+            Plot.barh(np.arange(len(resNames)),Probs)
         if thresh is not None:
             for item in thresh:
@@ -3126 +3170 @@
         else:
             Page.canvas.draw()
-            
     
     new,plotNum,Page,Plot,lim = G2frame.G2plotNB.FindPlotTab(Title,'mpl')