RuntimeWarning: divide by zero encountered in divide when using evaluate_causal_model

[newbietogitdotcom]

Describe the bug My data has all the numeric columns and does not have any null, zero or infinite values. It also does not have any duplicate values but still i keep getting this error

"Evaluating causal mechanisms...: 50%|█████ | 10/20 [00:06<00:06, 1.55it/s]/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/dowhy/gcm/divergence.py:84: RuntimeWarning: divide by zero encountered in divide result = np.sum((d / n) np.log(nu / rho)) + np.log(m / (n - 1)) /Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/dowhy/gcm/divergence.py:84: RuntimeWarning: divide by zero encountered in divide result = np.sum((d / n) np.log(nu / rho)) + np.log(m / (n - 1)) Evaluating causal mechanisms...: 100%|██████████| 20/20 [00:17<00:00, 1.16it/s] /Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/dowhy/gcm/divergence.py:84: RuntimeWarning: divide by zero encountered in divide result = np.sum((d / n) * np.log(nu / rho)) + np.log(m / (n - 1))"

and also this error

""name": "RuntimeError", "message": "Got a non-finite KL divergence! This can happen if both data sets have overlapping elements. Since these are normally removed by this method, double check whether the arrays are numeric.",

Versions/3.10/lib/python3.10/concurrent/futures/_base.py:403\u001b[0m, in \u001b[0;36mFuture.__get_result\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 401\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_exception:\n\u001b[1;32m 402\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m--> 403\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_exception\n\u001b[1;32m 404\u001b[0m \u001b[39mfinally\u001b[39;00m:\n\u001b[1;32m 405\u001b[0m \u001b[39m# Break a reference cycle with the exception in self._exception\u001b[39;00m\n\u001b[1;32m 406\u001b[0m \u001b[39mself\u001b[39m \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n\n\u001b[0;31mRuntimeError\u001b[0m: Got a non-finite KL divergence! This can happen if both data sets have overlapping elements. Since these are normally removed by this method, double check whether the arrays are numeric.""

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[bloebp]

Hi, does your data have columns with only a constant?

[newbietogitdotcom]

Hi @bloebp thank you for replying to my post.

No, it does not have any column with constant value. Please find some more information regarding my data below:

<class 'pandas.core.frame.DataFrame'> RangeIndex: 29 entries, 0 to 28 Data columns (total 22 columns):

Column Non-Null Count Dtype

---

0 Date 29 non-null dbdate 1 ET 29 non-null float64 2 EOT 29 non-null float64 3 DU 29 non-null float64 4 OD 29 non-null Int64
5 ONTD 29 non-null float64 6 ST 29 non-null Int64
7 UT 29 non-null Int64
8 OT 29 non-null Int64
9 TT 29 non-null Int64
10 THT 29 non-null Int64
11 SS 29 non-null float64 12 MPH 29 non-null float64 13 OA 29 non-null float64 14 LCA 29 non-null float64 15 OTP 29 non-null float64 16 DT 29 non-null float64 17 DST 29 non-null Int64
18 PM 29 non-null float64 19 BC 29 non-null float64 20 IC 29 non-null float64 21 TIP 29 non-null float64 dtypes: Int64(7), dbdate(1), float64(14) memory usage: 5.3 KB

and below are count of unique values per column

Date 29 ET 29 EOT 29 DU 23 OD 29 ONTD 7 ST 29 UT 28 OT 29 TT 29 THT 29 SS 3 MPH 25 OA 3 LCA 29 OTP 29 DT 27 DST 10 PM 16 BC 29 IC 29 TIP 29 dtype: int64

[bloebp]

Ok interesting, is there any chance you can provide some artificially generated data that reproduces this issue? I can take a closer look then.