script to measure angles + details

@@ -4,6 +4,7 @@ log_of_the_run.sh
 
 
 # results
 # results
 results/*
 results/*
+archive/*
 logs/*
 logs/*
 
 
 # temporary results files
 # temporary results files
@@ -13,4 +14,4 @@ esl*
 # environment stuff
 # environment stuff
 .vscode/
 .vscode/
 *.pyc
 *.pyc
-__pycache__/
\ No newline at end of file
+__pycache__/

@@ -1206,7 +1206,7 @@ class Pipeline:
                     self.known_issues = [ x[:-1] for x in issues.readlines() if not '-' in x ]
                     self.known_issues = [ x[:-1] for x in issues.readlines() if not '-' in x ]
             if self.USE_KNOWN_ISSUES:
             if self.USE_KNOWN_ISSUES:
                 print("\t> Ignoring known issues:")
                 print("\t> Ignoring known issues:")
-                print(" ".join(self.known_issues")
+                print(" ".join(self.known_issues))
 
 
         if self.HOMOLOGY:
         if self.HOMOLOGY:
             # Ask Rfam if some are mapped to Rfam families
             # Ask Rfam if some are mapped to Rfam families
@@ -1263,8 +1263,7 @@ class Pipeline:
             conn.close()
             conn.close()
 
 
         if self.SELECT_ONLY is not None:
         if self.SELECT_ONLY is not None:
-            self.update = [
-                c for c in self.update if c.chain_label == self.SELECT_ONLY]
+            self.update = [ c for c in self.update if c.chain_label == self.SELECT_ONLY ]
 
 
         self.n_chains = len(self.update)
         self.n_chains = len(self.update)
         print(str(self.n_chains) + " RNA chains of interest.")
         print(str(self.n_chains) + " RNA chains of interest.")

@@ -1611,3 +1611,15 @@
 7jz0_1_F
 7jz0_1_F
 7k00_1_5
 7k00_1_5
 7k00_1_B
 7k00_1_B
+1qzb_1_B_1-73
+1qza_1_B_1-73
+5zzm_1_M_3-118
+5zzm_1_N_1-2904
+3dg2_1_B_1-2904
+3dg0_1_B_1-2904
+3dg4_1_B_1-2904
+3dg5_1_B_1-2904
+3dg2_1_A_1-1542
+3dg0_1_A_1-1542
+3dg4_1_A_1-1542
+3dg5_1_A_1-1542

@@ -4837,3 +4837,39 @@ Sequence is too short. (< 5 resolved nts)
 5hjz_1_C
 5hjz_1_C
 Sequence is too short. (< 5 resolved nts)
 Sequence is too short. (< 5 resolved nts)
 
 
+1qzb_1_B_1-73
+DSSR warning 1qzb.json: no nucleotides found. Ignoring 1qzb_1_B_1-73.
+
+1qza_1_B_1-73
+DSSR warning 1qza.json: no nucleotides found. Ignoring 1qza_1_B_1-73.
+
+5zzm_1_M_3-118
+DSSR warning 5zzm.json: no nucleotides found. Ignoring 5zzm_1_M_3-118.
+
+5zzm_1_N_1-2904
+DSSR warning 5zzm.json: no nucleotides found. Ignoring 5zzm_1_N_1-2904.
+
+3dg2_1_B_1-2904
+DSSR warning 3dg2.json: no nucleotides found. Ignoring 3dg2_1_B_1-2904.
+
+3dg0_1_B_1-2904
+DSSR warning 3dg0.json: no nucleotides found. Ignoring 3dg0_1_B_1-2904.
+
+3dg4_1_B_1-2904
+DSSR warning 3dg4.json: no nucleotides found. Ignoring 3dg4_1_B_1-2904.
+
+3dg5_1_B_1-2904
+DSSR warning 3dg5.json: no nucleotides found. Ignoring 3dg5_1_B_1-2904.
+
+3dg2_1_A_1-1542
+DSSR warning 3dg2.json: no nucleotides found. Ignoring 3dg2_1_A_1-1542.
+
+3dg0_1_A_1-1542
+DSSR warning 3dg0.json: no nucleotides found. Ignoring 3dg0_1_A_1-1542.
+
+3dg4_1_A_1-1542
+DSSR warning 3dg4.json: no nucleotides found. Ignoring 3dg4_1_A_1-1542.
+
+3dg5_1_A_1-1542
+DSSR warning 3dg5.json: no nucleotides found. Ignoring 3dg5_1_A_1-1542.
+

+#!/usr/bin/python3.8
+
+# usage : pass as an argument a folder containing .cif files of RNA chains, like those produced by RNANet:
+# usage : ./measure_bonds_and_angles.py ~/Data/RNA/3D/rna_only
+# OR
+# usage : ./measure_bonds_and_angles.py ~/Data/RNA/3D/rna_mapped_to_Rfam
+
+from Bio.PDB import MMCIFParser
+from Bio.PDB.vectors import Vector, calc_angle
+from sys import argv
+from tqdm import tqdm
+import multiprocessing as mp
+import matplotlib.pyplot as plt
+import numpy as np
+import os, signal
+
+def measure_in_chain(f):
+    mmcif_parser = MMCIFParser()
+    s = mmcif_parser.get_structure('null', os.path.abspath(path_to_3D_data + f))
+    chain = next(s[0].get_chains()) # Assume only one chain per .cif file
+
+    c_to_p = []
+    p_to_c = []
+    c_p_c = []
+    p_c_p = []
+    last_p = None
+    last_c = None
+    nres = 0
+    for res in chain:
+        nres += 1
+
+        # Get the new c1' and p atoms
+        atom_c1p = [ atom.get_coord() for atom in res if "C1'" in atom.get_fullname() ]
+        atom_p = [ atom.get_coord() for atom in res if atom.get_name() ==  "P"]
+        if len(atom_c1p) + len(atom_p) != 2:
+            last_c = None 
+            last_p = None
+            continue
+        atom_c1p = Vector(atom_c1p[0])
+        atom_p = Vector(atom_p[0])
+
+        if last_c is not None: # There was a previous residue
+            # Get the C1'(i-1) -> P distance
+            c_to_p.append((last_c - atom_p).norm()) # the C1'(i-1) -> P bond of the theta angle
+
+            # Get the C1'(i-1)-P(i)-C1'(i) flat angle
+            c_p_c.append(calc_angle(last_c, atom_p, atom_c1p))
+            
+            # Get the P(i-1)-C1'(i-1)-P(i) flat angle
+            p_c_p.append(calc_angle(last_p, last_c, atom_p))
+        
+        p_to_c.append((atom_c1p - atom_p).norm()) # the P -> C1' bond of the eta angle
+        last_c = atom_c1p
+        last_p = atom_p
+
+    c_to_p = np.array(c_to_p, dtype=np.float16)
+    p_to_c = np.array(p_to_c, dtype=np.float16)
+    c_p_c = np.array(c_p_c, dtype=np.float16)
+    p_c_p = np.array(p_c_p, dtype=np.float16)
+    c_to_p = c_to_p[~np.isnan(c_to_p)]
+    p_to_c = p_to_c[~np.isnan(p_to_c)]
+    c_p_c = c_p_c[~np.isnan(c_p_c)]
+    p_c_p = p_c_p[~np.isnan(p_c_p)]
+    
+    return (c_to_p, p_to_c, c_p_c, p_c_p)
+
+def init_worker(tqdm_lock=None):
+    signal.signal(signal.SIGINT, signal.SIG_IGN)
+    if tqdm_lock is not None:
+        tqdm.set_lock(tqdm_lock)
+
+def measure_all_dist_angles():
+    path_to_3D_data = argv[1]
+
+    if path_to_3D_data[-1] != '/':
+        path_to_3D_data += '/'
+
+    r_cp = np.array([], dtype=np.float16)
+    r_pc = np.array([], dtype=np.float16)
+    flat_angles_cpc = np.array([], dtype=np.float16)
+    flat_angles_pcp = np.array([], dtype=np.float16)
+    p = mp.Pool(initializer=init_worker, initargs=(tqdm.get_lock(),), processes=os.cpu_count())
+    pbar = tqdm(total=len(os.listdir(path_to_3D_data)), desc="Scanning RNA chains", position=0, leave=True)
+    try:
+        nchains = 0
+        for _, r in enumerate(p.imap_unordered(measure_in_chain, os.listdir(path_to_3D_data))):
+            pbar.update(1)
+            nchains += 1
+            r_cp = np.hstack([r_cp, r[0]])
+            r_pc = np.hstack([r_pc, r[1]])
+            flat_angles_cpc = np.hstack([flat_angles_cpc, r[2]])
+            flat_angles_pcp = np.hstack([flat_angles_pcp, r[3]])
+        p.close()
+        p.join()
+        pbar.close()
+        np.savez("measures.npz", c_p=r_cp, p_c=r_pc, c_p_c=flat_angles_pcp, p_c_p=flat_angles_pcp)
+    except KeyboardInterrupt:
+        print("Caught Ctrl-C, quitting")
+        p.terminate()
+        p.join()
+        pbar.close() 
+    except Exception as e:
+        print(e)
+        p.terminate()
+        p.join()
+        pbar.close()
+        np.savez("measures_incomplete.npz", c_p=r_cp, p_c=r_pc, c_p_c=flat_angles_pcp, p_c_p=flat_angles_pcp)
+
+
+if __name__ == "__main__":
+    # Do the computations and save/reload the data
+    
+    # measure_all_dist_angles()
+
+    d = np.load("measures.npz")
+    c_p = d["c_p"]
+    p_c = d["p_c"]
+    p_c_p = d["p_c_p"]
+    c_p_c = d["c_p_c"]
+
+    # Plot stuff
+    plt.figure(figsize=(6,4), dpi=300)
+    plt.hist(c_p)
+    plt.savefig("lengths.png")
+    plt.close()
+
+    # print(f"Final values: P->C1' is \033[32m{avg[0]/10:.3f} ± {avg[1]/10:.3f} nm\033[0m, "
+    #     f"C1'->P is \033[32m{avg[2]/10:.3f} ± {avg[3]/10:.3f} nm\033[0m, "
+    #     f"angles C-P-C \033[32m{avg[4]:.2f} ± {avg[5]:.2f}\033[0m and P-C-P \033[32m{avg[6]:.2f} ± {avg[7]:.2f}\033[0m")