removed useless files

-#!/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")