From bffecc9926f180f16e3300d27da6c2fb52b10955 Mon Sep 17 00:00:00 2001
From: Nikolaos Korasidis <nkorasid@student.ethz.ch>
Date: Thu, 12 Mar 2020 00:23:17 +0100
Subject: [PATCH 01/11] Fix hint 2

---
 source/exercises100.ktx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/source/exercises100.ktx b/source/exercises100.ktx
index 1840c420..6eefc34c 100644
--- a/source/exercises100.ktx
+++ b/source/exercises100.ktx
@@ -11,7 +11,7 @@ import numpy as np
 Print the numpy version and the configuration (★☆☆)
 
 < h2
-hint: np.__version__, np.show_config)
+hint: np.__version__, np.show_config
 
 < a2
 print(np.__version__)

From 4dd62650f53234f81bc8733dd56cbaad7f3c7f66 Mon Sep 17 00:00:00 2001
From: Nikolaos Korasidis <nkorasid@student.ethz.ch>
Date: Thu, 12 Mar 2020 00:25:24 +0100
Subject: [PATCH 02/11] Fix answer 9

---
 source/exercises100.ktx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/source/exercises100.ktx b/source/exercises100.ktx
index 6eefc34c..8cbc42bd 100644
--- a/source/exercises100.ktx
+++ b/source/exercises100.ktx
@@ -85,8 +85,8 @@ Create a 3x3 matrix with values ranging from 0 to 8 (★☆☆)
 hint: reshape
 
 < a9
-nz = np.nonzero([1,2,0,0,4,0])
-print(nz)
+Z = np.arange(9).reshape((3, 3))
+print(Z)
 
 < q10
 Find indices of non-zero elements from [1,2,0,0,4,0] (★☆☆)

From ebd2b739454a1ecf4b6d21a54d105807788759e9 Mon Sep 17 00:00:00 2001
From: Nikolaos Korasidis <nkorasid@student.ethz.ch>
Date: Thu, 12 Mar 2020 00:28:47 +0100
Subject: [PATCH 03/11] Optimize answer 18

---
 source/exercises100.ktx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/source/exercises100.ktx b/source/exercises100.ktx
index 8cbc42bd..9bbde08e 100644
--- a/source/exercises100.ktx
+++ b/source/exercises100.ktx
@@ -191,7 +191,7 @@ Create a 5x5 matrix with values 1,2,3,4 just below the diagonal (★☆☆)
 hint: np.diag
 
 < a18
-Z = np.diag(1+np.arange(4),k=-1)
+Z = np.diag(np.arange(1,5),k=-1)
 print(Z)
 
 < q19

From d3a511703bf7c1e03b329679215153e5ec084f3b Mon Sep 17 00:00:00 2001
From: Nikolaos Korasidis <nkorasid@student.ethz.ch>
Date: Thu, 12 Mar 2020 00:44:36 +0100
Subject: [PATCH 04/11] Fix alternative answer 31

---
 source/exercises100.ktx | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/source/exercises100.ktx b/source/exercises100.ktx
index 9bbde08e..e5967a84 100644
--- a/source/exercises100.ktx
+++ b/source/exercises100.ktx
@@ -371,8 +371,9 @@ Z = np.ones(1) / 0
 _ = np.seterr(**defaults)
 
 # Equivalently with a context manager
-nz = np.nonzero([1,2,0,0,4,0])
-print(nz)
+with np.errstate(all='ignore'):
+    Z = np.arange(3) / 0
+print(Z)
 
 < q32
 Is the following expressions true? (★☆☆)

From 861e5d67b9168087d08d255b1da8496d1d69f464 Mon Sep 17 00:00:00 2001
From: Nikolaos Korasidis <nkorasid@student.ethz.ch>
Date: Thu, 12 Mar 2020 00:46:50 +0100
Subject: [PATCH 05/11] Simplify setup of answer 35

---
 source/exercises100.ktx | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/source/exercises100.ktx b/source/exercises100.ktx
index e5967a84..ebb9e452 100644
--- a/source/exercises100.ktx
+++ b/source/exercises100.ktx
@@ -415,9 +415,9 @@ How to compute ((A+B)*(-A/2)) in place (without copy)? (★★☆)
 hint: np.add(out=), np.negative(out=), np.multiply(out=), np.divide(out=)
 
 < a35
-A = np.ones(3)*1
-B = np.ones(3)*2
-C = np.ones(3)*3
+A = np.ones(3)
+B = np.full(3, 2)
+
 np.add(A,B,out=B)
 np.divide(A,2,out=A)
 np.negative(A,out=A)

From e5a13fdb4d10bbd95c3ce06ab13f3f6369a8b41e Mon Sep 17 00:00:00 2001
From: Nikolaos Korasidis <nkorasid@student.ethz.ch>
Date: Thu, 12 Mar 2020 00:55:10 +0100
Subject: [PATCH 06/11] Simplify answer 44 using np.hypot

---
 source/exercises100.ktx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/source/exercises100.ktx b/source/exercises100.ktx
index ebb9e452..f57c279c 100644
--- a/source/exercises100.ktx
+++ b/source/exercises100.ktx
@@ -527,12 +527,12 @@ Z[0] = 1
 Consider a random 10x2 matrix representing cartesian coordinates, convert them to polar coordinates (★★☆)
 
 < h44
-hint: np.sqrt, np.arctan2
+hint: np.hypot, np.arctan2
 
 < a44
 Z = np.random.random((10,2))
 X,Y = Z[:,0], Z[:,1]
-R = np.sqrt(X**2+Y**2)
+R = np.hypot(Y,X)
 T = np.arctan2(Y,X)
 print(R)
 print(T)

From c36f064ab37fcb47b31bd5619564b226e5d1b0d1 Mon Sep 17 00:00:00 2001
From: Nikolaos Korasidis <nkorasid@student.ethz.ch>
Date: Thu, 12 Mar 2020 01:10:46 +0100
Subject: [PATCH 07/11] Simplify answer 52 using np.hypot

---
 source/exercises100.ktx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/source/exercises100.ktx b/source/exercises100.ktx
index f57c279c..affd45ee 100644
--- a/source/exercises100.ktx
+++ b/source/exercises100.ktx
@@ -635,7 +635,7 @@ hint: np.atleast_2d, T, np.sqrt
 < a52
 Z = np.random.random((10,2))
 X,Y = np.atleast_2d(Z[:,0], Z[:,1])
-D = np.sqrt( (X-X.T)**2 + (Y-Y.T)**2)
+D = np.hypot(X-X.T, Y-Y.T)
 print(D)
 
 # Much faster with scipy

From 7d40613daaa8c2b27bbbc53a701ea2dd6ee39fa4 Mon Sep 17 00:00:00 2001
From: Nikolaos Korasidis <nkorasid@student.ethz.ch>
Date: Thu, 12 Mar 2020 01:18:34 +0100
Subject: [PATCH 08/11] Simplify answer 56 using np.hypot

---
 source/exercises100.ktx | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/source/exercises100.ktx b/source/exercises100.ktx
index affd45ee..ab1855a0 100644
--- a/source/exercises100.ktx
+++ b/source/exercises100.ktx
@@ -706,7 +706,7 @@ hint: np.meshgrid, np.exp
 
 < a56
 X, Y = np.meshgrid(np.linspace(-1,1,10), np.linspace(-1,1,10))
-D = np.sqrt(X*X+Y*Y)
+D = np.hypot(X, Y)
 sigma, mu = 1.0, 0.0
 G = np.exp(-( (D-mu)**2 / ( 2.0 * sigma**2 ) ) )
 print(G)

From d43e2086339d233c79a715da001102896e8e7332 Mon Sep 17 00:00:00 2001
From: Nikolaos Korasidis <nkorasid@student.ethz.ch>
Date: Fri, 13 Mar 2020 15:10:43 +0100
Subject: [PATCH 09/11] Fix answer 66

* Treating `I` as `np.ubyte` causes multiplication with 256 to
overflow.
* There is no need to apply `np.unique` to `I.
---
 source/exercises100.ktx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/source/exercises100.ktx b/source/exercises100.ktx
index ab1855a0..7f51da0b 100644
--- a/source/exercises100.ktx
+++ b/source/exercises100.ktx
@@ -857,10 +857,10 @@ hint: np.unique
 # Author: Nadav Horesh
 
 w,h = 16,16
-I = np.random.randint(0,2,(h,w,3)).astype(np.ubyte)
+I = np.random.randint(0,2,(h,w,3))
 F = I[...,0]*256*256 + I[...,1]*256 +I[...,2]
 n = len(np.unique(F))
-print(np.unique(I))
+print(n)
 
 < q67
 Considering a four dimensions array, how to get sum over the last two axis at once? (★★★)

From 02b7c17c42d017b9f598d9f42743c6300899b532 Mon Sep 17 00:00:00 2001
From: Nikolaos Korasidis <nkorasid@student.ethz.ch>
Date: Sat, 14 Mar 2020 02:06:12 +0100
Subject: [PATCH 10/11] Simplify answer 78

---
 source/exercises100.ktx | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/source/exercises100.ktx b/source/exercises100.ktx
index 7f51da0b..4b40217f 100644
--- a/source/exercises100.ktx
+++ b/source/exercises100.ktx
@@ -1046,9 +1046,9 @@ No hints provided...
 def distance(P0, P1, p):
     T = P1 - P0
     L = (T**2).sum(axis=1)
-    U = -((P0[:,0]-p[...,0])*T[:,0] + (P0[:,1]-p[...,1])*T[:,1]) / L
+    U = ((P0 - p)*T).sum(axis=1) / L
     U = U.reshape(len(U),1)
-    D = P0 + U*T - p
+    D = P0 - U*T - p
     return np.sqrt((D**2).sum(axis=1))
 
 P0 = np.random.uniform(-10,10,(10,2))

From 52fa50ed82ba00175dee8ae378955bb2780598b3 Mon Sep 17 00:00:00 2001
From: Nikolaos Korasidis <nkorasid@student.ethz.ch>
Date: Sat, 14 Mar 2020 02:09:01 +0100
Subject: [PATCH 11/11] Run generators

---
 100_Numpy_exercises.ipynb                     |  2 +-
 100_Numpy_exercises.md                        |  2 +-
 100_Numpy_exercises_with_hints.md             |  8 ++--
 ...mpy_exercises_with_hints_with_solutions.md | 40 +++++++++----------
 100_Numpy_exercises_with_solutions.md         | 36 ++++++++---------
 5 files changed, 44 insertions(+), 44 deletions(-)

diff --git a/100_Numpy_exercises.ipynb b/100_Numpy_exercises.ipynb
index 2e4a30ee..7ecf4200 100644
--- a/100_Numpy_exercises.ipynb
+++ b/100_Numpy_exercises.ipynb
@@ -564,7 +564,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### 36. Extract the integer part of a random array using 5 different methods (★★☆)"
+    "#### 36. Extract the integer part of a random array of positive numbers using 4 different methods (★★☆)"
    ]
   },
   {
diff --git a/100_Numpy_exercises.md b/100_Numpy_exercises.md
index 1e7ce709..85c1eac4 100644
--- a/100_Numpy_exercises.md
+++ b/100_Numpy_exercises.md
@@ -113,7 +113,7 @@ np.sqrt(-1) == np.emath.sqrt(-1)
 
 #### 35. How to compute ((A+B)*(-A/2)) in place (without copy)? (★★☆)
 
-#### 36. Extract the integer part of a random array using 5 different methods (★★☆)
+#### 36. Extract the integer part of a random array of positive numbers using 4 different methods (★★☆)
 
 #### 37. Create a 5x5 matrix with row values ranging from 0 to 4 (★★☆)
 
diff --git a/100_Numpy_exercises_with_hints.md b/100_Numpy_exercises_with_hints.md
index 96fa44af..58f97702 100644
--- a/100_Numpy_exercises_with_hints.md
+++ b/100_Numpy_exercises_with_hints.md
@@ -15,7 +15,7 @@ File automatically generated. See the documentation to update questions/answers/
 #### 1. Import the numpy package under the name `np` (★☆☆)
 `hint: import … as`
 #### 2. Print the numpy version and the configuration (★☆☆)
-`hint: np.__version__, np.show_config)`
+`hint: np.__version__, np.show_config`
 #### 3. Create a null vector of size 10 (★☆☆)
 `hint: np.zeros`
 #### 4. How to find the memory size of any array (★☆☆)
@@ -113,8 +113,8 @@ np.sqrt(-1) == np.emath.sqrt(-1)
 `hint: np.arange(dtype=datetime64['D'])`
 #### 35. How to compute ((A+B)*(-A/2)) in place (without copy)? (★★☆)
 `hint: np.add(out=), np.negative(out=), np.multiply(out=), np.divide(out=)`
-#### 36. Extract the integer part of a random array using 5 different methods (★★☆)
-`hint: %, np.floor, np.ceil, astype, np.trunc`
+#### 36. Extract the integer part of a random array of positive numbers using 4 different methods (★★☆)
+`hint: %, np.floor, astype, np.trunc`
 #### 37. Create a 5x5 matrix with row values ranging from 0 to 4 (★★☆)
 `hint: np.arange`
 #### 38. Consider a generator function that generates 10 integers and use it to build an array (★☆☆)
@@ -130,7 +130,7 @@ np.sqrt(-1) == np.emath.sqrt(-1)
 #### 43. Make an array immutable (read-only) (★★☆)
 `hint: flags.writeable`
 #### 44. Consider a random 10x2 matrix representing cartesian coordinates, convert them to polar coordinates (★★☆)
-`hint: np.sqrt, np.arctan2`
+`hint: np.hypot, np.arctan2`
 #### 45. Create random vector of size 10 and replace the maximum value by 0 (★★☆)
 `hint: argmax`
 #### 46. Create a structured array with `x` and `y` coordinates covering the [0,1]x[0,1] area (★★☆)
diff --git a/100_Numpy_exercises_with_hints_with_solutions.md b/100_Numpy_exercises_with_hints_with_solutions.md
index 8319fdbf..f9fb8f6d 100644
--- a/100_Numpy_exercises_with_hints_with_solutions.md
+++ b/100_Numpy_exercises_with_hints_with_solutions.md
@@ -19,7 +19,7 @@ File automatically generated. See the documentation to update questions/answers/
 import numpy as np
 ```
 #### 2. Print the numpy version and the configuration (★☆☆)
-`hint: np.__version__, np.show_config)`
+`hint: np.__version__, np.show_config`
 
 ```python
 print(np.__version__)
@@ -72,8 +72,8 @@ print(Z)
 `hint: reshape`
 
 ```python
-nz = np.nonzero([1,2,0,0,4,0])
-print(nz)
+Z = np.arange(9).reshape((3, 3))
+print(Z)
 ```
 #### 10. Find indices of non-zero elements from [1,2,0,0,4,0] (★☆☆)
 `hint: np.nonzero`
@@ -151,7 +151,7 @@ print(0.3 == 3 * 0.1)
 `hint: np.diag`
 
 ```python
-Z = np.diag(1+np.arange(4),k=-1)
+Z = np.diag(np.arange(1,5),k=-1)
 print(Z)
 ```
 #### 19. Create a 8x8 matrix and fill it with a checkerboard pattern (★☆☆)
@@ -292,8 +292,9 @@ Z = np.ones(1) / 0
 _ = np.seterr(**defaults)
 
 # Equivalently with a context manager
-nz = np.nonzero([1,2,0,0,4,0])
-print(nz)
+with np.errstate(all='ignore'):
+    Z = np.arange(3) / 0
+print(Z)
 ```
 #### 32. Is the following expressions true? (★☆☆)
 ```python
@@ -323,23 +324,22 @@ print(Z)
 `hint: np.add(out=), np.negative(out=), np.multiply(out=), np.divide(out=)`
 
 ```python
-A = np.ones(3)*1
-B = np.ones(3)*2
-C = np.ones(3)*3
+A = np.ones(3)
+B = np.full(3, 2)
+
 np.add(A,B,out=B)
 np.divide(A,2,out=A)
 np.negative(A,out=A)
 np.multiply(A,B,out=A)
 ```
-#### 36. Extract the integer part of a random array using 5 different methods (★★☆)
-`hint: %, np.floor, np.ceil, astype, np.trunc`
+#### 36. Extract the integer part of a random array of positive numbers using 4 different methods (★★☆)
+`hint: %, np.floor, astype, np.trunc`
 
 ```python
 Z = np.random.uniform(0,10,10)
 
 print (Z - Z%1)
 print (np.floor(Z))
-print (np.ceil(Z)-1)
 print (Z.astype(int))
 print (np.trunc(Z))
 ```
@@ -409,12 +409,12 @@ Z.flags.writeable = False
 Z[0] = 1
 ```
 #### 44. Consider a random 10x2 matrix representing cartesian coordinates, convert them to polar coordinates (★★☆)
-`hint: np.sqrt, np.arctan2`
+`hint: np.hypot, np.arctan2`
 
 ```python
 Z = np.random.random((10,2))
 X,Y = Z[:,0], Z[:,1]
-R = np.sqrt(X**2+Y**2)
+R = np.hypot(Y,X)
 T = np.arctan2(Y,X)
 print(R)
 print(T)
@@ -493,7 +493,7 @@ print(Z)
 ```python
 Z = np.random.random((10,2))
 X,Y = np.atleast_2d(Z[:,0], Z[:,1])
-D = np.sqrt( (X-X.T)**2 + (Y-Y.T)**2)
+D = np.hypot(X-X.T, Y-Y.T)
 print(D)
 
 # Much faster with scipy
@@ -552,7 +552,7 @@ for index in np.ndindex(Z.shape):
 
 ```python
 X, Y = np.meshgrid(np.linspace(-1,1,10), np.linspace(-1,1,10))
-D = np.sqrt(X*X+Y*Y)
+D = np.hypot(X, Y)
 sigma, mu = 1.0, 0.0
 G = np.exp(-( (D-mu)**2 / ( 2.0 * sigma**2 ) ) )
 print(G)
@@ -673,10 +673,10 @@ print(F)
 # Author: Nadav Horesh
 
 w,h = 16,16
-I = np.random.randint(0,2,(h,w,3)).astype(np.ubyte)
+I = np.random.randint(0,2,(h,w,3))
 F = I[...,0]*256*256 + I[...,1]*256 +I[...,2]
 n = len(np.unique(F))
-print(np.unique(I))
+print(n)
 ```
 #### 67. Considering a four dimensions array, how to get sum over the last two axis at once? (★★★)
 `hint: sum(axis=(-2,-1))`
@@ -826,9 +826,9 @@ np.negative(Z, out=Z)
 def distance(P0, P1, p):
     T = P1 - P0
     L = (T**2).sum(axis=1)
-    U = -((P0[:,0]-p[...,0])*T[:,0] + (P0[:,1]-p[...,1])*T[:,1]) / L
+    U = ((P0 - p)*T).sum(axis=1) / L
     U = U.reshape(len(U),1)
-    D = P0 + U*T - p
+    D = P0 - U*T - p
     return np.sqrt((D**2).sum(axis=1))
 
 P0 = np.random.uniform(-10,10,(10,2))
diff --git a/100_Numpy_exercises_with_solutions.md b/100_Numpy_exercises_with_solutions.md
index aaafa807..86ad9293 100644
--- a/100_Numpy_exercises_with_solutions.md
+++ b/100_Numpy_exercises_with_solutions.md
@@ -72,8 +72,8 @@ print(Z)
 
 
 ```python
-nz = np.nonzero([1,2,0,0,4,0])
-print(nz)
+Z = np.arange(9).reshape((3, 3))
+print(Z)
 ```
 #### 10. Find indices of non-zero elements from [1,2,0,0,4,0] (★☆☆)
 
@@ -151,7 +151,7 @@ print(0.3 == 3 * 0.1)
 
 
 ```python
-Z = np.diag(1+np.arange(4),k=-1)
+Z = np.diag(np.arange(1,5),k=-1)
 print(Z)
 ```
 #### 19. Create a 8x8 matrix and fill it with a checkerboard pattern (★☆☆)
@@ -211,7 +211,7 @@ print(Z)
 # Author: Evgeni Burovski
 
 Z = np.arange(11)
-Z[(3 < Z) & (Z < 8)] *= -1
+Z[(3 < Z) & (Z <= 8)] *= -1
 print(Z)
 ```
 #### 26. What is the output of the following script? (★☆☆)
@@ -292,8 +292,9 @@ Z = np.ones(1) / 0
 _ = np.seterr(**defaults)
 
 # Equivalently with a context manager
-nz = np.nonzero([1,2,0,0,4,0])
-print(nz)
+with np.errstate(all='ignore'):
+    Z = np.arange(3) / 0
+print(Z)
 ```
 #### 32. Is the following expressions true? (★☆☆)
 ```python
@@ -323,15 +324,15 @@ print(Z)
 
 
 ```python
-A = np.ones(3)*1
-B = np.ones(3)*2
-C = np.ones(3)*3
+A = np.ones(3)
+B = np.full(3, 2)
+
 np.add(A,B,out=B)
 np.divide(A,2,out=A)
 np.negative(A,out=A)
 np.multiply(A,B,out=A)
 ```
-#### 36. Extract the integer part of a random array using 5 different methods (★★☆)
+#### 36. Extract the integer part of a random array of positive numbers using 4 different methods (★★☆)
 
 
 ```python
@@ -339,7 +340,6 @@ Z = np.random.uniform(0,10,10)
 
 print (Z - Z%1)
 print (np.floor(Z))
-print (np.ceil(Z)-1)
 print (Z.astype(int))
 print (np.trunc(Z))
 ```
@@ -414,7 +414,7 @@ Z[0] = 1
 ```python
 Z = np.random.random((10,2))
 X,Y = Z[:,0], Z[:,1]
-R = np.sqrt(X**2+Y**2)
+R = np.hypot(Y,X)
 T = np.arctan2(Y,X)
 print(R)
 print(T)
@@ -493,7 +493,7 @@ print(Z)
 ```python
 Z = np.random.random((10,2))
 X,Y = np.atleast_2d(Z[:,0], Z[:,1])
-D = np.sqrt( (X-X.T)**2 + (Y-Y.T)**2)
+D = np.hypot(X-X.T, Y-Y.T)
 print(D)
 
 # Much faster with scipy
@@ -552,7 +552,7 @@ for index in np.ndindex(Z.shape):
 
 ```python
 X, Y = np.meshgrid(np.linspace(-1,1,10), np.linspace(-1,1,10))
-D = np.sqrt(X*X+Y*Y)
+D = np.hypot(X, Y)
 sigma, mu = 1.0, 0.0
 G = np.exp(-( (D-mu)**2 / ( 2.0 * sigma**2 ) ) )
 print(G)
@@ -673,10 +673,10 @@ print(F)
 # Author: Nadav Horesh
 
 w,h = 16,16
-I = np.random.randint(0,2,(h,w,3)).astype(np.ubyte)
+I = np.random.randint(0,2,(h,w,3))
 F = I[...,0]*256*256 + I[...,1]*256 +I[...,2]
 n = len(np.unique(F))
-print(np.unique(I))
+print(n)
 ```
 #### 67. Considering a four dimensions array, how to get sum over the last two axis at once? (★★★)
 
@@ -826,9 +826,9 @@ np.negative(Z, out=Z)
 def distance(P0, P1, p):
     T = P1 - P0
     L = (T**2).sum(axis=1)
-    U = -((P0[:,0]-p[...,0])*T[:,0] + (P0[:,1]-p[...,1])*T[:,1]) / L
+    U = ((P0 - p)*T).sum(axis=1) / L
     U = U.reshape(len(U),1)
-    D = P0 + U*T - p
+    D = P0 - U*T - p
     return np.sqrt((D**2).sum(axis=1))
 
 P0 = np.random.uniform(-10,10,(10,2))