I'm stupid and I deleted the previous repository...

So, code is working, this case reproduce a Diko's peak with Poisson
equation by changing the boundary conditions over time.

scripts_python/plotCumF.py

@@ -0,0 +1,41 @@
+import readPhi
+import readF
+import matplotlib.pyplot as plt
+import glob
+import numpy as np
+from scipy.constants import e, k
+
+
+m_i = 1.9712e-25
+
+paths = ['../quasiNeutral_fullAblation/','../Poisson_fullAblation/']
+#  paths = ['../quasiNeutral_partialAblation/','../Poisson_partialAblation/']
+for path in paths:
+    filesCum_i = sorted(glob.glob(path+'time_*_fCum_i.csv'))
+    start = 0
+    end   = len(filesCum_i)
+    every = 100
+
+    for fileCum_i in filesCum_i[start:end:every]:
+        time, x, v, f_i = readF.read(fileCum_i)
+
+        plt.plot(v**2*m_i*0.5/e, f_i[0]*e/m_i/v, label='{:.3f} ns'.format(time*1e9))
+
+    time, x, v, f_i = readF.read(filesCum_i[-1])
+
+    plt.plot(v**2*m_i*0.5/e, f_i[0]*e/m_i/v, label='{:.3f} ns'.format(time*1e9), color='k')
+
+    plt.yscale('log')
+    plt.ylim([1e18,1e24])
+    plt.ylabel('Sum f(e) / sqrt(e) (m^-3 eV^-1)')
+    plt.xscale('log')
+    plt.xlim([1e0,1e4])
+    plt.xlabel('e (eV)')
+
+    plt.legend()
+
+    plt.title('r = {:.1f} mm, time_max={:.1f} ns '.format(x[0]*1e3, time*1e9) + path)
+
+    plt.show()
+ 
+

scripts_python/plotF.py

@@ -0,0 +1,22 @@
+import readPhi
+import readF
+import matplotlib.pyplot as plt
+from matplotlib.colors import Normalize
+import glob
+import numpy as np
+from scipy.constants import e, k
+
+path = '../2024-09-26_11.48.04/'
+
+filesF_i = sorted(glob.glob(path+'time_*_f_i.csv'))
+start = 0
+end   = len(filesF_i)
+every = 50
+ 
+time, x, v, f_i = readF.read(filesF_i[-1])
+plt.title('t = {:.3f} ns'.format(time*1e9))
+norm = Normalize(vmin=4., vmax=20., clip=False)
+plt.imshow(np.log10(f_i), cmap='cividis', interpolation='None', aspect='auto', origin='lower', extent=[v[0],v[-1],x[0],x[-1]], norm=norm)
+
+plt.show()
+

scripts_python/plotMom.py

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+import readPhi
+import readMom
+import readF
+import matplotlib.pyplot as plt
+import glob
+import numpy as np
+from scipy.constants import e, k
+
+#  paths = ['../quasiNeutral_fullAblation/','../2024-09-26_11.48.04/']
+#  paths = ['../2024-09-26_12.47.11/']
+paths = ['../quasiNeutral_partialAblation/','../2024-09-26_13.58.24/']
+#  path = '../quasiNeutral_fullAblation/'
+#  path = '../quasiNeutral_partialAblatio/'
+
+
+for path in paths:
+    filesPhi   = sorted(glob.glob(path+'time_*_phi.csv'))
+    filesMom_i = sorted(glob.glob(path+'time_*_mom_i.csv'))
+    start = 0
+    end   = len(filesMom_i)
+    every = 100
+    fig, ax = plt.subplots(4, sharex='all')
+    for fileMom_i, filePhi in zip(filesMom_i[start:end+1:every], filesPhi[start:end+1:every]):
+        time, r, phi, n_e            = readPhi.read(filePhi)
+        time, r, n_i, u_i, T_i, Zave = readMom.read(fileMom_i)
+
+        ax[0].plot(r, phi, label='t = {:.3f} ns'.format(time*1e9))
+        ax[1].set_yscale('log')
+        ax[1].set_ylim([1e14,2e25])
+        ax[1].plot(r, Zave*n_i)
+        ax[1].plot(r,      n_e, color='k', linestyle='dashed')
+        ax[2].plot(r,      u_i)
+        ax[3].plot(r,      T_i)
+
+    ax[0].set_title(path)
+    ax[0].legend()
+
+    plt.show()

scripts_python/readF.py

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+import pandas
+
+def read(filename):
+    # Get time
+    df = pandas.read_csv(filename,skiprows=0,nrows=1)
+    time = df['t (s)'].to_numpy()[0]
+
+    df = pandas.read_csv(filename,skiprows=2,nrows=1,header=None)
+    x = df.to_numpy()[0][1:]
+    df = pandas.read_csv(filename,skiprows=3,header=None)
+    f = []
+    for col in df:
+        if col == 0:
+            v = df[col].to_numpy()
+        else:
+            f.append(df[col].to_numpy())
+
+    return time, x, v, f

scripts_python/readMom.py

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+import pandas
+
+def read(filename):
+    # Get time
+    df = pandas.read_csv(filename,skiprows=0,nrows=1)
+    time = df['t (s)'].to_numpy()[0]
+
+    df = pandas.read_csv(filename,skiprows=2)
+    x   = df['r (m)'].to_numpy()
+    n_i = df['n_i (m^-3)'].to_numpy()
+    u_i = df['u_i (m s^-1)'].to_numpy()
+    T_i = df['T_i (eV)'].to_numpy()
+    Z   = df['Zave'].to_numpy()
+
+    return time, x, n_i, u_i, T_i, Z
+
+

scripts_python/readPhi.py

@@ -0,0 +1,15 @@
+import pandas
+
+def read(filename):
+    # Get time
+    df = pandas.read_csv(filename,skiprows=0,nrows=1)
+    time = df['t (s)'].to_numpy()[0]
+
+    df = pandas.read_csv(filename,skiprows=2)
+    x   = df['r (m)'].to_numpy()
+    phi = df['phi (V)'].to_numpy()
+    n_e = df['n_e (m^-3)'].to_numpy()
+
+    return time, x, phi, n_e
+
+