X should be a numpy array

[mlhossen]

Hi, I am trying to calculate the TE where my data is a matrix obtained from a molecular dynamics simulation. I tried following:

import pandas as pd
import seaborn
import matplotlib.pyplot as plt
from PyIF import te_compute as te
import numpy as np
X_1000 = pd.read_csv("1.csv")(6, 1).flatten() # 1.csv is my data
Y_1000 = pd.read_csv("1.csv")(6, 1).flatten()

And I got the following error message:

---

TypeError Traceback (most recent call last)
in
----> 1 X_1000 = pd.read_csv("1.csv")(6, 1).flatten()
2 Y_1000 = pd.read_csv("1.csv")(6, 1).flatten()

TypeError: 'DataFrame' object is not callable

Further, when I typed
TE = te.te_compute(X_1000, Y_1000, k=1, embedding=1, safetyCheck=True, GPU=False)
I got following message:

---

AssertionError Traceback (most recent call last)
in
----> 1 TE = te.te_compute(X_1000, Y_1000, k=1, embedding=1, safetyCheck=True, GPU=False)

~/opt/anaconda3/lib/python3.8/site-packages/PyIF/te_compute.py in te_compute(X, Y, k, embedding, safetyCheck, GPU)
27 assert_true(k>=1, msg="K should be greater than or equal to 1")
28 assert_true(embedding >= 1, msg='The embedding must be greater than or equal to 1')
---> 29 assert_true(type(X) == np.ndarray, msg='X should be a numpy array')
30 assert_true(type(Y) == np.ndarray, msg='Y should be a numpy array')
31 assert_true(len(X) == len(Y), msg='The length of X & Y are not equal')

~/opt/anaconda3/lib/python3.8/unittest/case.py in assertTrue(self, expr, msg)
763 if not expr:
764 msg = self._formatMessage(msg, "%s is not true" % safe_repr(expr))
--> 765 raise self.failureException(msg)
766
767 def _formatMessage(self, msg, standardMsg):

AssertionError: False is not true : X should be a numpy array
What am I missing here? What could be possible action overcoming the issues?