<jupyter_start><jupyter_text>Number of A or G in bandits design<jupyter_code>df_bandit = df[df['Group'] == 'bandit'][['RBS6', 'AVERAGE', 'STD']]
num_ags = []

for rbs6 in np.asarray(df_bandit['RBS6']):
    num = 0
    for i in rbs6:
        if i == 'A' or i == 'G':
            num+=1
    num_ags.append(num)
    
plt.scatter(num_ags, np.asarray(df_bandit['AVERAGE']))
plt.xlabel('Number of A or G in Bandits design')
plt.ylabel('Average label')
plt.hist(num_ags)
plt.xlabel('Number of A or G in Bandits design')
plt.ylabel('Number of sequences')<jupyter_output><empty_output><jupyter_text>Violinplot and swarmplot with AVERAGE value<jupyter_code>df.sort_values(by = ['AVERAGE'], ascending = False).head(10)
fig, ax = plt.subplots( figsize=(18,12))
plt.axhline(56.058,color="black",ls="--")
sns.violinplot(x="Group", y="AVERAGE", data=df.drop([0]).sort_values(by = ['Group'], ascending = True),palette='viridis')
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
SMALL_SIZE = 14
MEDIUM_SIZE = 16
BIGGER_SIZE = 18

plt.rc('font', size=MEDIUM_SIZE)          # controls default text sizes
plt.rc('axes', titlesize=MEDIUM_SIZE)     # fontsize of the axes title
plt.rc('axes', labelsize=MEDIUM_SIZE)    # fontsize of the x and y labels
plt.rc('xtick', labelsize=MEDIUM_SIZE)    # fontsize of the tick labels
plt.rc('ytick', labelsize=MEDIUM_SIZE)    # fontsize of the tick labels
plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize
plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title

#dfv = df.copy(deep=True)

#for index, row in dfv.iterrows():
#    if row['Group'] == 'bps' and row['RBS6'] == 'AGGAGA':
#        row['Group'] = 'bps_ncore'
#        dfv = dfv.append(row, ignore_index=True)
#    elif row['Group'] == 'bps' and row['RBS6'] != 'AGGAGA':
#        row['Group'] = 'bps_core'
#        dfv = dfv.append(row, ignore_index=True)      
        
#dfv.sort_values(by = ['Group'], ascending = True,inplace=True) 

#dfv.head(300)

#fig, ax = plt.subplots( figsize=(18,12))
#sns.violinplot(x="Group", y="AVERAGE", data=dfv,palette='viridis')
fig, ax = plt.subplots( figsize=(18,12))
plt.axhline(56.058,color="black",ls="--")
sns.swarmplot(x="Group", y="AVERAGE", data=df.drop([0]),palette='plasma')
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
SMALL_SIZE = 14
MEDIUM_SIZE = 16
BIGGER_SIZE = 18

plt.rc('font', size=MEDIUM_SIZE)          # controls default text sizes
plt.rc('axes', titlesize=MEDIUM_SIZE)     # fontsize of the axes title
plt.rc('axes', labelsize=MEDIUM_SIZE)    # fontsize of the x and y labels
plt.rc('xtick', labelsize=MEDIUM_SIZE)    # fontsize of the tick labels
plt.rc('ytick', labelsize=MEDIUM_SIZE)    # fontsize of the tick labels
plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize
plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title<jupyter_output><empty_output><jupyter_text>Violinplot with all replications<jupyter_code>df_all_rep = pd.melt(df, id_vars=['RBS', 'Group'], value_vars=['Rep1', 'Rep2', 'Rep3'])
df_all_rep = df_all_rep.dropna()
df_all_rep.sort_values(by = ['value'], ascending = False).head(10)
sns.violinplot(x="Group", y="value", data=df_all_rep)<jupyter_output><empty_output><jupyter_text>Predict labels with baseline data as training data<jupyter_code>df.sort_values(by = ['AVERAGE'], ascending = False).head(10)
lm = sns.violinplot(x="Group", y="predict mean", data=df)
axes = lm.axes
axes.set_ylim(-2,4)
sns.violinplot(x="Group", y="value", data=df_all_rep)<jupyter_output><empty_output>
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