From d931b008a3ab2cf7e266a93d6080c12f904e2405 Mon Sep 17 00:00:00 2001
From: Fisher Wang <kingwfsh@163.com>
Date: Tue, 9 Mar 2021 21:42:18 +0800
Subject: [PATCH] Give another solution of problem #66, and fix the old
 solution as #142 did

---
 100_Numpy_exercises_with_hints_with_solutions.md | 12 +++++++++++-
 100_Numpy_exercises_with_solutions.md            |  9 +++++++++
 source/exercises100.ktx                          | 12 +++++++++++-
 3 files changed, 31 insertions(+), 2 deletions(-)

diff --git a/100_Numpy_exercises_with_hints_with_solutions.md b/100_Numpy_exercises_with_hints_with_solutions.md
index bd311ce..e08ac98 100644
--- a/100_Numpy_exercises_with_hints_with_solutions.md
+++ b/100_Numpy_exercises_with_hints_with_solutions.md
@@ -682,9 +682,19 @@ print(F)
 
 w,h = 16,16
 I = np.random.randint(0,2,(h,w,3)).astype(np.ubyte)
-F = I[...,0]*256*256 + I[...,1]*256 +I[...,2]
+# The parenthesis around 256*256 ensure the dtpye promoted to uint32 properly.Otherwise the first term will overflow.
+F = I[...,0]*(256*256) + I[...,1]*256 +I[...,2]
 n = len(np.unique(F))
 print(np.unique(I))
+
+# Another solution
+# Author: Fisher Wang
+
+w, h = 16, 16
+img = np.random.randint(0, 256, (w, h, 3)).astype(np.ubyte)
+colors = np.unique(img.reshape(-1, 3), axis=0)
+n = len(colors)
+print(n)
 ```
 #### 67. Considering a four dimensions array, how to get sum over the last two axis at once? (★★★)
 `hint: sum(axis=(-2,-1))`
diff --git a/100_Numpy_exercises_with_solutions.md b/100_Numpy_exercises_with_solutions.md
index 12c658a..35cf3a8 100644
--- a/100_Numpy_exercises_with_solutions.md
+++ b/100_Numpy_exercises_with_solutions.md
@@ -686,6 +686,15 @@ I = np.random.randint(0,2,(h,w,3)).astype(np.ubyte)
 F = I[...,0]*(256*256) + I[...,1]*256 +I[...,2]
 n = len(np.unique(F))
 print(np.unique(I))
+
+# Another solution
+# Author: Fisher Wang
+
+w, h = 16, 16
+img = np.random.randint(0, 256, (w, h, 3)).astype(np.ubyte)
+colors = np.unique(img.reshape(-1, 3), axis=0)
+n = len(colors)
+print(n)
 ```
 #### 67. Considering a four dimensions array, how to get sum over the last two axis at once? (★★★)
 
diff --git a/source/exercises100.ktx b/source/exercises100.ktx
index 5f392a7..bf0b807 100644
--- a/source/exercises100.ktx
+++ b/source/exercises100.ktx
@@ -865,10 +865,20 @@ hint: np.unique
 
 w,h = 16,16
 I = np.random.randint(0,2,(h,w,3)).astype(np.ubyte)
-F = I[...,0]*256*256 + I[...,1]*256 +I[...,2]
+# The parenthesis around 256*256 ensure the dtpye promoted to uint32 properly.Otherwise the first term will overflow.
+F = I[...,0]*(256*256) + I[...,1]*256 +I[...,2]
 n = len(np.unique(F))
 print(np.unique(I))
 
+# Another solution
+# Author: Fisher Wang
+
+w, h = 16, 16
+img = np.random.randint(0, 256, (w, h, 3)).astype(np.ubyte)
+colors = np.unique(img.reshape(-1, 3), axis=0)
+n = len(colors)
+print(n)
+
 < q67
 Considering a four dimensions array, how to get sum over the last two axis at once? (★★★)