PyFlux on SMC

Say hello to PyFlux on SageMathCloud!

import pyflux as pf
pf.__version__

Error in lines 1-1
Traceback (most recent call last):
  File "/usr/local/lib/python2.7/dist-packages/smc_sagews/sage_server.py", line 976, in execute
    exec compile(block+'\n', '', 'single') in namespace, locals
  File "", line 1, in <module>
  File "/projects/sage/sage-7.5/local/lib/python2.7/site-packages/pyflux/__init__.py", line 17, in <module>
    from .other import *
ImportError: No module named other

import numpy as np
import pandas as pd
import pyflux as pf
from datetime import datetime
import matplotlib.pyplot as plt

data = pd.read_csv('https://vincentarelbundock.github.io/Rdatasets/csv/datasets/sunspot.year.csv')
data.index = data['time'].values

_=plt.figure(figsize=(15,5))
_=plt.plot(data.index,data['sunspot.year'])
_=plt.ylabel('Sunspots')
_=plt.title('Yearly Sunspot Data')
plt.show()

Error in lines 3-3
Traceback (most recent call last):
  File "/usr/local/lib/python2.7/dist-packages/smc_sagews/sage_server.py", line 976, in execute
    exec compile(block+'\n', '', 'single') in namespace, locals
  File "", line 1, in <module>
  File "/projects/sage/sage-7.5/local/lib/python2.7/site-packages/pyflux/__init__.py", line 3, in <module>
    from . import __check_build
ImportError: cannot import name __check_build

model = pf.ARIMA(data=data, ar=4, ma=4, target='sunspot.year', family=pf.Normal())

Error in lines 1-1
Traceback (most recent call last):
  File "/usr/local/lib/python2.7/dist-packages/smc_sagews/sage_server.py", line 976, in execute
    exec compile(block+'\n', '', 'single') in namespace, locals
  File "", line 1, in <module>
NameError: name 'pf' is not defined

x = model.fit("MLE")
x.summary()

Normal ARIMA(4,0,4)                                                                                       
======================================================= ==================================================
Dependent Variable: sunspot.year                        Method: MLE                                       
Start Date: 1704                                        Log Likelihood: -1191.3335                        
End Date: 1988                                          AIC: 2402.6669                                    
Number of observations: 285                             BIC: 2439.1918                                    
==========================================================================================================
Latent Variable                          Estimate   Std Error  z        P>|z|    95% C.I.                 
======================================== ========== ========== ======== ======== =========================
Constant                                 10.9013    2.5712     4.2397   0.0      (5.8617 | 15.9409)       
AR(1)                                    1.5132     0.0415     36.4212  0.0      (1.4318 | 1.5947)        
AR(2)                                    -0.3377    0.2406     -1.4036  0.1604   (-0.8093 | 0.1339)       
AR(3)                                    -0.8512    0.2357     -3.6111  0.0003   (-1.3133 | -0.3892)      
AR(4)                                    0.452      0.0629     7.186    0.0      (0.3287 | 0.5753)        
MA(1)                                    -0.3643    0.0385     -9.4559  0.0      (-0.4399 | -0.2888)      
MA(2)                                    -0.4585    0.1362     -3.3669  0.0008   (-0.7254 | -0.1916)      
MA(3)                                    0.2186     0.1121     1.9495   0.0512   (-0.0012 | 0.4383)       
MA(4)                                    0.2996     0.0813     3.6831   0.0002   (0.1401 | 0.459)         
Normal Scale                             15.8542                                                          
==========================================================================================================

Latent variables ...

model.plot_z(figsize=(15,5))

In-sample fit

model.plot_fit(figsize=(15,10))

Prediction

model.plot_predict(h=20,past_values=20,figsize=(15,5))