aesthetics, comments, and statistics on the produced data

+# execution outputs:
+nohup.out
+jobstats.csv
+log_of_the_run.sh
+
 # Byte-compiled / optimized / DLL files
 # Byte-compiled / optimized / DLL files
 __pycache__/
 __pycache__/
 *.py[cod]
 *.py[cod]

+#!/usr/bin/python3.8
+import os
+import numpy as np
+import pandas as pd
+import scipy.stats as st
+import matplotlib.pyplot as plt
+import matplotlib.patches as ptch
+from mpl_toolkits.mplot3d import axes3d
+from matplotlib import cm 
+from tqdm import tqdm
+
+
+if os.path.isdir("/home/ubuntu/"): # this is the IFB-core cloud
+    path_to_3D_data = "/mnt/Data/RNA/3D/"
+    path_to_seq_data = "/mnt/Data/RNA/sequences/"
+elif os.path.isdir("/home/persalteas"): # this is my personal workstation
+    path_to_3D_data = "/home/persalteas/Data/RNA/3D/"
+    path_to_seq_data = "/home/persalteas/Data/RNA/sequences/"
+elif os.path.isdir("/home/lbecquey"): # this is the IBISC server
+    path_to_3D_data = "/home/lbecquey/Data/RNA/3D/"
+    path_to_seq_data = "/home/lbecquey/Data/RNA/sequences/"
+elif os.path.isdir("/nhome/siniac/lbecquey"): # this is the office PC
+    path_to_3D_data = "/nhome/siniac/lbecquey/Data/RNA/3D/"
+    path_to_seq_data = "/nhome/siniac/lbecquey/Data/RNA/sequences/"
+else:
+    print("I don't know that machine... I'm shy, maybe you should introduce yourself ?")
+    exit(1)
+
+if __name__ == "__main__":
+
+    #TODO: compute nt frequencies, chain lengths
+
+    print("loading CSV files...")
+    rna_points = []
+    all_etas = []
+    all_thetas = []
+    for csvfile in tqdm(os.listdir(path_to_3D_data + "pseudotorsions")):
+        df = pd.read_csv(path_to_3D_data + "pseudotorsions/" + csvfile).drop('Unnamed: 0', axis=1)
+        all_etas += list(df['eta'].values)
+        all_thetas += list(df['theta'].values)
+        rna_points.append(df)
+
+    print("combining etas and thetas...")
+    # increase all the angles by 180°
+    alldata = [ ((e+360)%360-180, (t+360)%360-180) 
+                for e, t in zip(all_etas, all_thetas) 
+                if ('nan' not in str((e,t))) 
+                and not(e<-150 and t<-110) and not (e>160 and t<-110) ]
+    print(len(alldata), "couples of nts found.")
+
+    x = np.array([ p[0] for p in alldata ])
+    y = np.array([ p[1] for p in alldata ])
+    xmin, xmax = min(x), max(x)
+    ymin, ymax = min(y), max(y)
+    xx, yy = np.mgrid[xmin:xmax:100j, ymin:ymax:100j]
+    positions = np.vstack([xx.ravel(), yy.ravel()])
+    values = np.vstack([x, y])
+    kernel = st.gaussian_kde(values)
+    f = np.reshape(kernel(positions).T, xx.shape)
+
+    # histogram : 
+    fig, axs = plt.subplots(1,3, figsize=(18, 6))
+    ax = fig.add_subplot(131)
+    
+    plt.axhline(y=0, alpha=0.5, color='black')
+    plt.axvline(x=0, alpha=0.5, color='black')
+    plt.scatter(x, y, s=1, alpha=0.1)
+    plt.contourf(xx, yy, f, cmap=cm.BuPu, alpha=0.5)
+    ax.set_xlabel("$\\eta'=C_1'^{i-1}-P^i-C_1'^i-P^{i+1}$")
+    ax.set_ylabel("$\\theta'=P^i-C_1'^i-P^{i+1}-C_1'^{i+1}$")
+    ax.add_patch(ptch.Rectangle((-20,0),50,70, linewidth=1, edgecolor='r', facecolor='#ff000080'))
+
+    ax = fig.add_subplot(132, projection='3d')
+    ax.plot_surface(xx, yy, f, cmap=cm.coolwarm, linewidth=0, antialiased=False)
+    ax.set_title("\"Wadley plot\"\n$\\eta'$, $\\theta'$ pseudotorsions in 3D RNA structures\n(Massive peak removed in the red zone, = double helices)")
+    ax.set_xlabel("$\\eta'=C_1'^{i-1}-P^i-C_1'^i-P^{i+1}$")
+    ax.set_ylabel("$\\theta'=P^i-C_1'^i-P^{i+1}-C_1'^{i+1}$")
+
+    ax = fig.add_subplot(133, projection='3d')
+    hist, xedges, yedges = np.histogram2d(x, y, bins=300, range=[[xmin, xmax], [ymin, ymax]])
+    xpos, ypos = np.meshgrid(xedges[:-1], yedges[:-1], indexing="ij")
+    ax.bar3d(xpos.ravel(), ypos.ravel(), 0, 0.5, 0.5, hist.ravel(), zsort='average')
+    ax.set_xlabel("$\\eta'=C_1'^{i-1}-P^i-C_1'^i-P^{i+1}$")
+    ax.set_ylabel("$\\theta'=P^i-C_1'^i-P^{i+1}-C_1'^{i+1}$")
+    plt.savefig("results/clusters_rot180.png")
+    plt.show()