ztests_alex_timestamps.py

from chrony import timestamps
import numpy as np
import pandas as pd
import random
import matplotlib.pyplot as plt

print('Test for library timestamps')
print('============================')

ts = pd.date_range(start='2015-09-01',end='2015-09-30',freq='D')
y = list(map(lambda x:np.sin(4*np.pi*x/len(ts)),range(len(ts))))
y = [yy+0.5*random.random() for yy in y] # add noise
for i in [4,5,6,10,20,21,-1,-2,-3]:
    y[i] = np.nan # add holes

df=pd.DataFrame({'ts':ts,'data':y})
print('df=')
print(df)
df_initial = df

fig, ax = plt.subplots(figsize=(10,5))
ax.plot(df.ts,df.data,'-o',lw=2)
ax.set_ylim([-1.5,1.5])
ax.set_xlim([df.ts.values[0],df.ts.values[-1]])
ax.set_xlabel('ts',fontsize=20)
ax.set_ylabel('data',fontsize=20)
for t in ax.get_xticklabels():
    t.set_fontsize(16)
for t in ax.get_yticklabels():
    t.set_fontsize(16)
fig.autofmt_xdate()
#fig.savefig('images/plot_fake_timeseries.svg',bbox_inches='tight', pad_inches=0.5)


print('')
print('find_holes(df.ts, df.data)')
print(timestamps.find_holes(df.ts,df.data))

print('')
print('timestamps.audit(df.ts, df.data,talk_to_me=True):')
timestamps.audit(df.ts, df.data,talk_to_me=True)

print('')
print('timestamps.describe(df.ts, df.data):')
timestamps.describe(df.ts, df.data)

print('')
print('timestamps.trim(df.ts, df.data):')
df=timestamps.trim(df.ts,df.data)
print(df)

print('')
print('timestamps.fill_data(df.ts, df.data,max_hole_duration=2):')
df = timestamps.fill_data(df.ts, df.data, max_hole_duration=2)
print(df)

fig, ax = plt.subplots(figsize=(10,5))
ax.plot(df.ts,df.data,'r--o',lw=2,label='Filled')
ax.plot(df_initial.ts,df_initial.data,'-o',lw=2,label='Initial')
ax.set_ylim([-1.5,1.5])
ax.set_xlabel('ts',fontsize=20)
ax.set_ylabel('data',fontsize=20)
ax.legend()
for t in ax.get_xticklabels():
    t.set_fontsize(16)
for t in ax.get_yticklabels():
    t.set_fontsize(16)
fig.autofmt_xdate()
#fig.savefig('images/plot_fake_timeseries_aftershave.svg',bbox_inches='tight', pad_inches=0.5)


print('')
print('timestamps.describe(df.ts,df.data):')
print(timestamps.describe(df.ts, df.data))

print('')
print('timestamps.cut(df.ts,df.data,min_hole_duration=2):')
time_series=timestamps.cut(df.ts, df.data, min_hole_duration=2)
print(time_series)

j=0
for df in time_series:
    j+=1
    fig, ax = plt.subplots(figsize=(10,5))
    ax.plot(df.ts,df.data,'-o',lw=2)
    ax.set_xlabel('ts',fontsize=20)
    ax.set_ylabel('data',fontsize=20)
    ax.legend()
    ax.set_xlim([df_initial.ts.values[0],df_initial.ts.values[-1]])
    ax.set_ylim([-1.5,1.5])
    for t in ax.get_xticklabels():
        t.set_fontsize(16)
    for t in ax.get_yticklabels():
        t.set_fontsize(16)
    fig.autofmt_xdate()
   # fig.savefig('images/plot_fake_timeseries_cut'+str(j)+'.svg',bbox_inches='tight', pad_inches=0.5)

print('')
print('Done.')