import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np


df = pd.read_csv("samples.csv")

walker_id = df.walker.drop_duplicates().array


fig, ax = plt.subplots(3,1,constrained_layout=True)    
for walker in walker_id:
    df_aux = df.loc[df["walker"]==walker]
    size = len(df_aux["x"].index)
    x = np.linspace(0,size,size)
    ax[0].plot(x, df_aux["y"], alpha=0.3, color = 'black')
    ax[1].plot(x, df_aux["x"], alpha=0.3, color = 'black')
    ax[2].plot(x, df_aux["z"], alpha=0.3, color = 'black')
ax[0].set_xlabel("y")
ax[1].set_xlabel("x")
ax[2].set_xlabel("z")
plt.savefig("convergence.png",dpi=300)
plt.show()


import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np


df = pd.read_csv("samples.csv")

walker_id = df.walker.drop_duplicates().array


fig, ax = plt.subplots(3,1,constrained_layout=True)    
for walker in walker_id:
    df_aux = df.loc[df["walker"]==walker]
    size = len(df_aux["x"].index)
    x = np.linspace(0,size,size)
    ax[0].plot(x, df_aux["y"], alpha=0.3, color = 'black')
    ax[1].plot(x, df_aux["x"], alpha=0.3, color = 'black')
    ax[2].plot(x, df_aux["z"], alpha=0.3, color = 'black')
ax[0].set_xlabel("y")
ax[1].set_xlabel("x")
ax[2].set_xlabel("z")
plt.savefig("convergence.png",dpi=300)
plt.show()

