From 6f05fefe819824f3e2e899880d38e924e10ce1f2 Mon Sep 17 00:00:00 2001 From: kuzand Date: Fri, 2 Nov 2018 15:30:58 +0200 Subject: [PATCH 1/4] Added hint to question 96. for my solution --- 100_Numpy_exercises_with_hint.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/100_Numpy_exercises_with_hint.md b/100_Numpy_exercises_with_hint.md index 43aaccb..e926efa 100644 --- a/100_Numpy_exercises_with_hint.md +++ b/100_Numpy_exercises_with_hint.md @@ -606,7 +606,7 @@ np.sqrt(-1) == np.emath.sqrt(-1) #### 96. Given a two dimensional array, how to extract unique rows? (★★★) -(**hint**: np.ascontiguousarray) +(**hint**: np.ascontiguousarray | np.unique) From a7fc6a820bb293a8d6e9429e06cf40c78cef76f3 Mon Sep 17 00:00:00 2001 From: kuzand Date: Fri, 2 Nov 2018 15:32:10 +0200 Subject: [PATCH 2/4] Update 100_Numpy_exercises.md --- 100_Numpy_exercises.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/100_Numpy_exercises.md b/100_Numpy_exercises.md index c93c54b..1e4c220 100644 --- a/100_Numpy_exercises.md +++ b/100_Numpy_exercises.md @@ -1157,8 +1157,8 @@ _, idx = np.unique(T, return_index=True) uZ = Z[idx] print(uZ) -# Another solution, for NumPy >= 1.13 # Author: Andreas Kouzelis +# For NumPy >= 1.13 uZ = np.unique(Z, axis=0) print(uZ) ``` From 69d0e429a07f10c74fbb7b1a7b1f2fe225d66cea Mon Sep 17 00:00:00 2001 From: kuzand Date: Fri, 2 Nov 2018 15:33:41 +0200 Subject: [PATCH 3/4] Update 100_Numpy_exercises.md --- 100_Numpy_exercises.md | 1 + 1 file changed, 1 insertion(+) diff --git a/100_Numpy_exercises.md b/100_Numpy_exercises.md index 1e4c220..c0cae26 100644 --- a/100_Numpy_exercises.md +++ b/100_Numpy_exercises.md @@ -1159,6 +1159,7 @@ print(uZ) # Author: Andreas Kouzelis # For NumPy >= 1.13 + uZ = np.unique(Z, axis=0) print(uZ) ``` From b7530ee580f03761decddd5b051fcb4cc2645f07 Mon Sep 17 00:00:00 2001 From: kuzand Date: Fri, 2 Nov 2018 15:36:09 +0200 Subject: [PATCH 4/4] Update 100_Numpy_exercises.md --- 100_Numpy_exercises.md | 1 - 1 file changed, 1 deletion(-) diff --git a/100_Numpy_exercises.md b/100_Numpy_exercises.md index c0cae26..1e4c220 100644 --- a/100_Numpy_exercises.md +++ b/100_Numpy_exercises.md @@ -1159,7 +1159,6 @@ print(uZ) # Author: Andreas Kouzelis # For NumPy >= 1.13 - uZ = np.unique(Z, axis=0) print(uZ) ```