Updated MSTUMP tutorial with subspace

Author: seanlaw

docs/Tutorial_Multidimensional_Motif_Discovery.ipynb

@@ -283,6 +283,7 @@
     "mdtype = mdata.dtype\n",
     "\n",
     "df = pd.DataFrame(mdata, dtype=mdtype, columns=['T3', 'T2', 'T1'])\n",
+    "df = df[['T1', 'T2', 'T3']]\n",
     "df.to_csv(\"toy.csv\", index=False)"
    ]
   }

docs/Zenodo.ipynb

@@ -185,7 +185,7 @@ def transpose_dataframe(df):  # pragma: no cover
     Returns
     -------
     output : df
-        If a is a Pandas `DataFrame` then return `a.T`. Otherwise, return `a`
+        If `df` is a Pandas `DataFrame` then return `df.T`. Otherwise, return `df`
     """
     if type(df).__name__ == "DataFrame":
         return df.T
@@ -1235,6 +1235,7 @@ def preprocess(T, m):
         Rolling standard deviation
     """
     T = T.copy()
+    T = transpose_dataframe(T)
     T = np.asarray(T)
     check_dtype(T)
 
@@ -1273,6 +1274,7 @@ def preprocess_non_normalized(T, m):
         `np.nan`/`np.inf` value (False)
     """
     T = T.copy()
+    T = transpose_dataframe(T)
     T = np.asarray(T)
     check_dtype(T)
 

stumpy/core.py

@@ -693,7 +693,7 @@ def mstump(T, m, include=None, discords=False):
 
     See mSTAMP Algorithm
     """
-    T_A = core.transpose_dataframe(T)
+    T_A = T
     T_B = T_A
 
     T_A, M_T, Σ_T = core.preprocess(T_A, m)

stumpy/mstump.py

@@ -70,7 +70,7 @@ def mstumped(dask_client, T, m, include=None, discords=False):
 
     See mSTAMP Algorithm
     """
-    T_A = core.transpose_dataframe(T)
+    T_A = T
     T_B = T_A
 
     T_A, M_T, Σ_T = core.preprocess(T_A, m)