File generation for Aleksandar

filegen.py

+# kernel e.g. datascience_py37
+import numpy as np
+import matplotlib.pyplot as plt
+import pandas as pd
+
+# ?np.zeros
+
+rot_radius = 13
+rot_std = 6
+
+nrPoints = 100
+angleStep = 1
+particles = np.zeros((nrPoints * 360//angleStep,6))
+
+# +
+wobble_angle = (rot_radius/2)*10**-3 
+pi = np.arccos(-1)
+
+for i,angle in enumerate(np.arange(0,360,angleStep)):
+    x0=np.cos(pi*angle/180)*rot_radius
+    y0=np.sin(pi*angle/180)*rot_radius
+    x = np.random.default_rng().normal(x0, rot_std, nrPoints)
+    y = np.random.default_rng().normal(y0, rot_std, nrPoints)
+    xp = x0 / rot_radius * wobble_angle
+    yp = y0 / rot_radius * wobble_angle
+    xp = np.sin(xp)
+    yp = np.sin(yp)
+    zp = np.cos(wobble_angle) 
+    particles[i*nrPoints:(i+1)*nrPoints,:] = np.array([x,np.zeros(nrPoints),y,np.ones(nrPoints)*xp,np.ones(nrPoints)*zp, np.ones(nrPoints)*yp]).T
+# -
+## beam travelling in z but y in MCNP 
+
+
+#plt.hist(zp);
+
+plt.xlabel('${radius\ [mm]}$',size=11)
+plt.ylabel('$norm.\ beam\ intensity$',size=11)
+plt.title('Sliced beam distribution')
+
+np.savetxt("flattened.csv", particles, delimiter=",")
+df = pd.read_csv('flattened.csv', sep=" ", header=None)
+df.columns = ["x", "y", "z", "xp","yp","zp"]
+df['x'] = df['x'].div(10)
+df['y'] = df['y'].div(10)
+df['z'] = df['z'].div(10)
+data = ['DS2 L']
+df3 = pd.DataFrame(data)
+df=df.append(df3)
+
+df2 = df[["xp", "yp","zp"]]
+df = df.drop('xp', 1)
+df = df.drop('yp', 1)
+df = df.drop('zp', 1)
+df=df.append(df2)
+df.style.set_properties(**{'text-align': 'left'})
+
+df.to_csv('flat.txt', sep=' ', index=False, header=None)
+lines = ['SDEF PAR=h POS=D1 VEC=FPOS D2 DIR=-1 ERG=590 wgt=1', 'SP1 1 35999r','SI1 L']
+
+with open("flat.txt", 'r+') as file:
+    readcontent = file.read()                                  
+    file.seek(0, 0) 
+    for i in lines:        
+        file.write(str(i) + "\n")
+        file.write('   '.join(i.split()))
+                                  
+    file.write(readcontent) 
+
+
+plt.hist(particles[:,3]);
+
+#plt.hist2d(particles[:,0], particles[:,2], bins = 50);
+
+#plt.hist2d(particles[:,3], particles[:,5], bins = 50);
+
+#plt.hist(particles[:,0]);
+
+
+
+plt.show()
+
+
+
+print(particles[:,3])