add exercise with hint
This commit is contained in:
matianjun1
parent
a0e4013bec
commit
453fa9fa14
@ -4,7 +4,7 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# 100 numpy exercises with suggestion\n",
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"# 100 numpy exercises with hint\n",
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"\n",
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"This is a collection of exercises that have been collected in the numpy mailing list, on stack overflow and in the numpy documentation. The goal of this collection is to offer a quick reference for both old and new users but also to provide a set of exercices for those who teach.\n",
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"\n",
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@ -16,7 +16,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 1. Import the numpy package under the name `np` (★☆☆) (suggestion: import … as ..)"
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"#### 1. Import the numpy package under the name `np` (★☆☆) \n",
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"##### (hint: import … as ..)"
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]
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},
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{
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@ -32,7 +33,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 2. Print the numpy version and the configuration (★☆☆) (suggestion: np.\\_\\_verison\\_\\_, np.show\\_config)"
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"#### 2. Print the numpy version and the configuration (★☆☆) \n",
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"##### (hint: np.\\_\\_verison\\_\\_, np.show\\_config)"
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]
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},
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{
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@ -48,7 +50,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 3. Create a null vector of size 10 (★☆☆) (suggestion: np.zeros)"
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"#### 3. Create a null vector of size 10 (★☆☆) \n",
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"##### (hint: np.zeros)"
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]
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},
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{
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@ -64,7 +67,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 4. How to find the memory size of any array (★☆☆) (suggestion: size, itemsize)"
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"#### 4. How to find the memory size of any array (★☆☆) \n",
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"##### (hint: size, itemsize)"
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]
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},
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{
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@ -80,7 +84,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 5. How to get the documentation of the numpy add function from the command line? (★☆☆) (suggestion: np.info)"
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"#### 5. How to get the documentation of the numpy add function from the command line? (★☆☆) \n",
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"##### (hint: np.info)"
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]
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},
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{
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@ -96,7 +101,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 6. Create a null vector of size 10 but the fifth value which is 1 (★☆☆) (suggestion: array\\[4\\])"
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"#### 6. Create a null vector of size 10 but the fifth value which is 1 (★☆☆) \n",
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"##### (hint: array\\[4\\])"
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]
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},
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{
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@ -112,7 +118,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 7. Create a vector with values ranging from 10 to 49 (★☆☆) (suggestion: np.arange)"
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"#### 7. Create a vector with values ranging from 10 to 49 (★☆☆) \n",
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"##### (hint: np.arange)"
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]
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},
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{
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@ -128,7 +135,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 8. Reverse a vector (first element becomes last) (★☆☆) (suggestion: array\\[::-1\\])"
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"#### 8. Reverse a vector (first element becomes last) (★☆☆) \n",
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"##### (hint: array\\[::-1\\])"
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]
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},
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{
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@ -144,7 +152,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 9. Create a 3x3 matrix with values ranging from 0 to 8 (★☆☆) (suggestion: reshape)"
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"#### 9. Create a 3x3 matrix with values ranging from 0 to 8 (★☆☆) \n",
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"##### (hint: reshape)"
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]
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},
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{
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@ -160,7 +169,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 10. Find indices of non-zero elements from \\[1,2,0,0,4,0\\] (★☆☆) (suggestion: np.nonzero)"
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"#### 10. Find indices of non-zero elements from \\[1,2,0,0,4,0\\] (★☆☆) \n",
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"##### (hint: np.nonzero)"
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]
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},
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{
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@ -176,7 +186,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 11. Create a 3x3 identity matrix (★☆☆) (suggestion: np.eye)"
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"#### 11. Create a 3x3 identity matrix (★☆☆) \n",
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"##### (hint: np.eye)"
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]
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},
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{
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@ -192,7 +203,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 12. Create a 3x3x3 array with random values (★☆☆) (suggestion: np.random.random)"
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"#### 12. Create a 3x3x3 array with random values (★☆☆) \n",
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"##### (hint: np.random.random)"
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]
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},
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{
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@ -208,7 +220,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 13. Create a 10x10 array with random values and find the minimum and maximum values (★☆☆) (suggestion: min, max)"
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"#### 13. Create a 10x10 array with random values and find the minimum and maximum values (★☆☆) \n",
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"##### (hint: min, max)"
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]
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},
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{
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@ -224,7 +237,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 14. Create a random vector of size 30 and find the mean value (★☆☆) (suggestion: mean)"
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"#### 14. Create a random vector of size 30 and find the mean value (★☆☆) \n",
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"##### (hint: mean)"
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]
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},
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{
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@ -240,7 +254,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 15. Create a 2d array with 1 on the border and 0 inside (★☆☆) (suggestion: array\\[1:-1, 1:-1\\])"
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"#### 15. Create a 2d array with 1 on the border and 0 inside (★☆☆) \n",
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"##### (hint: array\\[1:-1, 1:-1\\])"
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]
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},
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{
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@ -256,7 +271,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 16. How to add a border (filled with 0's) around an existing array? (★☆☆) (suggestion: np.pad)"
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"#### 16. How to add a border (filled with 0's) around an existing array? (★☆☆) \n",
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"##### (hint: np.pad)"
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]
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},
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{
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@ -272,7 +288,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 17. What is the result of the following expression? (★☆☆) (suggestion: NaN = not a number, inf = infinity)"
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"#### 17. What is the result of the following expression? (★☆☆) \n",
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"##### (hint: NaN = not a number, inf = infinity)"
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]
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},
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{
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@ -301,7 +318,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 18. Create a 5x5 matrix with values 1,2,3,4 just below the diagonal (★☆☆) (suggestion: np.diag)"
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"#### 18. Create a 5x5 matrix with values 1,2,3,4 just below the diagonal (★☆☆) \n",
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"##### (hint: np.diag)"
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]
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},
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{
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@ -317,7 +335,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 19. Create a 8x8 matrix and fill it with a checkerboard pattern (★☆☆) (suggestion: array\\[::2\\])"
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"#### 19. Create a 8x8 matrix and fill it with a checkerboard pattern (★☆☆) \n",
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"##### (hint: array\\[::2\\])"
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]
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},
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{
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@ -333,7 +352,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 20. Consider a (6,7,8) shape array, what is the index (x,y,z) of the 100th element? (suggestion: np.unravel_index)"
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"#### 20. Consider a (6,7,8) shape array, what is the index (x,y,z) of the 100th element? \n",
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"##### (hint: np.unravel_index)"
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]
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},
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{
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@ -349,7 +369,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 21. Create a checkerboard 8x8 matrix using the tile function (★☆☆) (suggestion: np.tile)"
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"#### 21. Create a checkerboard 8x8 matrix using the tile function (★☆☆) \n",
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"##### (hint: np.tile)"
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]
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},
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{
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@ -365,7 +386,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 22. Normalize a 5x5 random matrix (★☆☆) (suggestion: (x - min) / (max - min))"
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"#### 22. Normalize a 5x5 random matrix (★☆☆) \n",
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"##### (hint: (x - min) / (max - min))"
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]
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},
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{
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@ -381,7 +403,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 23. Create a custom dtype that describes a color as four unsigned bytes (RGBA) (★☆☆) (suggestion: np.dtype)"
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"#### 23. Create a custom dtype that describes a color as four unsigned bytes (RGBA) (★☆☆) \n",
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"##### (hint: np.dtype)"
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]
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},
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{
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@ -397,7 +420,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 24. Multiply a 5x3 matrix by a 3x2 matrix (real matrix product) (★☆☆) (suggestion: np.dot | @)"
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"#### 24. Multiply a 5x3 matrix by a 3x2 matrix (real matrix product) (★☆☆) \n",
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"##### (hint: np.dot | @)"
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]
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},
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{
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@ -413,7 +437,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 25. Given a 1D array, negate all elements which are between 3 and 8, in place. (★☆☆) (suggestion: >, <=)"
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"#### 25. Given a 1D array, negate all elements which are between 3 and 8, in place. (★☆☆) \n",
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"##### (hint: >, <=)"
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]
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},
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{
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@ -429,7 +454,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 26. What is the output of the following script? (★☆☆) (suggestion: np.sum)"
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"#### 26. What is the output of the following script? (★☆☆) \n",
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"##### (hint: np.sum)"
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]
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},
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{
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@ -515,7 +541,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 29. How to round away from zero a float array ? (★☆☆) (suggestion: np.uniform, np.copysign, np.ceil, np.abs)"
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"#### 29. How to round away from zero a float array ? (★☆☆) \n",
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"##### (hint: np.uniform, np.copysign, np.ceil, np.abs)"
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]
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},
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{
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@ -531,7 +558,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 30. How to find common values between two arrays? (★☆☆) (suggestion: np.intersect1d)"
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"#### 30. How to find common values between two arrays? (★☆☆) \n",
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"##### (hint: np.intersect1d)"
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]
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},
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{
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@ -547,7 +575,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 31. How to ignore all numpy warnings (not recommended)? (★☆☆) (suggestion: np.seterr, np.errstate)"
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"#### 31. How to ignore all numpy warnings (not recommended)? (★☆☆) \n",
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"##### (hint: np.seterr, np.errstate)"
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]
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},
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{
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@ -563,7 +592,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 32. Is the following expressions true? (★☆☆) (suggestion: imaginary number)"
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"#### 32. Is the following expressions true? (★☆☆) \n",
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"##### (hint: imaginary number)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 33. How to get the dates of yesterday, today and tomorrow? (★☆☆) (suggestion: np.datetime64, np.timedelta64)"
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"#### 33. How to get the dates of yesterday, today and tomorrow? (★☆☆) \n",
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"##### (hint: np.datetime64, np.timedelta64)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 34. How to get all the dates corresponding to the month of July 2016? (★★☆) (suggestion: np.arange(dtype=datetime64\\['D'\\]))"
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"#### 34. How to get all the dates corresponding to the month of July 2016? (★★☆) \n",
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"##### (hint: np.arange(dtype=datetime64\\['D'\\]))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 35. How to compute ((A+B)\\*(-A/2)) in place (without copy)? (★★☆) (suggestion: np.add(out=), np.negative(out=), np.multiply(out=), np.divide(out=))"
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"#### 35. How to compute ((A+B)\\*(-A/2)) in place (without copy)? (★★☆) \n",
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"##### (hint: np.add(out=), np.negative(out=), np.multiply(out=), np.divide(out=))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 36. Extract the integer part of a random array using 5 different methods (★★☆) (suggestion: %, np.floor, np.ceil, astype, np.trunc)"
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"#### 36. Extract the integer part of a random array using 5 different methods (★★☆) \n",
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"##### (hint: %, np.floor, np.ceil, astype, np.trunc)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 37. Create a 5x5 matrix with row values ranging from 0 to 4 (★★☆) (suggestion: np.arange)"
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"#### 37. Create a 5x5 matrix with row values ranging from 0 to 4 (★★☆) \n",
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"##### (hint: np.arange)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 38. Consider a generator function that generates 10 integers and use it to build an array (★☆☆) (suggestion: np.fromiter)"
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"#### 38. Consider a generator function that generates 10 integers and use it to build an array (★☆☆) \n",
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"##### (hint: np.fromiter)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 39. Create a vector of size 10 with values ranging from 0 to 1, both excluded (★★☆) (suggestion: np.linespace)"
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"#### 39. Create a vector of size 10 with values ranging from 0 to 1, both excluded (★★☆) \n",
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"##### (hint: np.linespace)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 40. Create a random vector of size 10 and sort it (★★☆) (suggestion: sort)"
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"#### 40. Create a random vector of size 10 and sort it (★★☆) \n",
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"##### (hint: sort)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 41. How to sum a small array faster than np.sum? (★★☆) (suggestion: np.add.reduce)"
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"#### 41. How to sum a small array faster than np.sum? (★★☆) \n",
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"##### (hint: np.add.reduce)"
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]
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},
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{
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@ -732,7 +771,8 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 42. Consider two random array A and B, check if they are equal (★★☆) (suggestion: np.allclose, np.array\\_equal)"
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"#### 42. Consider two random array A and B, check if they are equal (★★☆) \n",
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"##### (hint: np.allclose, np.array\\_equal)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### 43. Make an array immutable (read-only) (★★☆) (suggestion: flags.writeable)"
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"#### 43. Make an array immutable (read-only) (★★☆) \n",
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"##### (hint: flags.writeable)"
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]
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},
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{
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||||
@ -764,7 +805,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 44. Consider a random 10x2 matrix representing cartesian coordinates, convert them to polar coordinates (★★☆) (suggestion: np.sqrt, np.arctan2)"
|
||||
"#### 44. Consider a random 10x2 matrix representing cartesian coordinates, convert them to polar coordinates (★★☆) \n",
|
||||
"##### (hint: np.sqrt, np.arctan2)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -780,7 +822,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 45. Create random vector of size 10 and replace the maximum value by 0 (★★☆) (suggestion: argmax)"
|
||||
"#### 45. Create random vector of size 10 and replace the maximum value by 0 (★★☆) \n",
|
||||
"##### (hint: argmax)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -796,7 +839,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 46. Create a structured array with `x` and `y` coordinates covering the \\[0,1\\]x\\[0,1\\] area (★★☆) (suggestion: np.meshgrid)"
|
||||
"#### 46. Create a structured array with `x` and `y` coordinates covering the \\[0,1\\]x\\[0,1\\] area (★★☆) \n",
|
||||
"##### (hint: np.meshgrid)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -812,7 +856,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 47. Given two arrays, X and Y, construct the Cauchy matrix C (Cij =1/(xi - yj)) (suggestion: np.subtract.outer)"
|
||||
"#### 47. Given two arrays, X and Y, construct the Cauchy matrix C (Cij =1/(xi - yj)) \n",
|
||||
"##### (hint: np.subtract.outer)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -828,7 +873,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 48. Print the minimum and maximum representable value for each numpy scalar type (★★☆) (suggestion: np.iinfo, np.finfo, eps)"
|
||||
"#### 48. Print the minimum and maximum representable value for each numpy scalar type (★★☆) \n",
|
||||
"##### (hint: np.iinfo, np.finfo, eps)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -844,7 +890,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 49. How to print all the values of an array? (★★☆) (suggestion: np.set\\_printoptions)"
|
||||
"#### 49. How to print all the values of an array? (★★☆) \n",
|
||||
"##### (hint: np.set\\_printoptions)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -860,7 +907,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 50. How to find the closest value (to a given scalar) in a vector? (★★☆) (suggestion: argmin)"
|
||||
"#### 50. How to find the closest value (to a given scalar) in a vector? (★★☆) \n",
|
||||
"##### (hint: argmin)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -876,7 +924,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 51. Create a structured array representing a position (x,y) and a color (r,g,b) (★★☆) (suggestion: dtype)"
|
||||
"#### 51. Create a structured array representing a position (x,y) and a color (r,g,b) (★★☆) \n",
|
||||
"##### (hint: dtype)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -892,7 +941,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 52. Consider a random vector with shape (100,2) representing coordinates, find point by point distances (★★☆) (suggestion: np.atleast\\_2d, T, np.sqrt)"
|
||||
"#### 52. Consider a random vector with shape (100,2) representing coordinates, find point by point distances (★★☆) \n",
|
||||
"##### (hint: np.atleast\\_2d, T, np.sqrt)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -908,7 +958,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 53. How to convert a float (32 bits) array into an integer (32 bits) in place? (suggestion: astype(copy=False))"
|
||||
"#### 53. How to convert a float (32 bits) array into an integer (32 bits) in place? \n",
|
||||
"##### (hint: astype(copy=False))"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -924,7 +975,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 54. How to read the following file? (★★☆) (suggestion: np.genfromtxt)"
|
||||
"#### 54. How to read the following file? (★★☆) \n",
|
||||
"##### (hint: np.genfromtxt)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -951,7 +1003,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 55. What is the equivalent of enumerate for numpy arrays? (★★☆) (suggestion: np.ndenumerate, np.ndindex)"
|
||||
"#### 55. What is the equivalent of enumerate for numpy arrays? (★★☆) \n",
|
||||
"##### (hint: np.ndenumerate, np.ndindex)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -967,7 +1020,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 56. Generate a generic 2D Gaussian-like array (★★☆) (suggestion: np.meshgrid, np.exp)"
|
||||
"#### 56. Generate a generic 2D Gaussian-like array (★★☆) \n",
|
||||
"##### (hint: np.meshgrid, np.exp)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -983,7 +1037,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 57. How to randomly place p elements in a 2D array? (★★☆) (suggestion: np.put, np.random.choice)"
|
||||
"#### 57. How to randomly place p elements in a 2D array? (★★☆) \n",
|
||||
"##### (hint: np.put, np.random.choice)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -999,7 +1054,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 58. Subtract the mean of each row of a matrix (★★☆) (suggestion: mean(axis=,keepdims=))"
|
||||
"#### 58. Subtract the mean of each row of a matrix (★★☆) \n",
|
||||
"##### (hint: mean(axis=,keepdims=))"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1015,7 +1071,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 59. How to sort an array by the nth column? (★★☆) (suggestion: argsort)"
|
||||
"#### 59. How to sort an array by the nth column? (★★☆) \n",
|
||||
"##### (hint: argsort)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1031,7 +1088,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 60. How to tell if a given 2D array has null columns? (★★☆) (suggestion: any, ~)"
|
||||
"#### 60. How to tell if a given 2D array has null columns? (★★☆) \n",
|
||||
"##### (hint: any, ~)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1047,7 +1105,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 61. Find the nearest value from a given value in an array (★★☆) (suggestion: np.abs, argmin, flat)"
|
||||
"#### 61. Find the nearest value from a given value in an array (★★☆) \n",
|
||||
"##### (hint: np.abs, argmin, flat)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1063,7 +1122,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 62. Considering two arrays with shape (1,3) and (3,1), how to compute their sum using an iterator? (★★☆) (suggestion: np.nditer)"
|
||||
"#### 62. Considering two arrays with shape (1,3) and (3,1), how to compute their sum using an iterator? (★★☆) \n",
|
||||
"##### (hint: np.nditer)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1079,7 +1139,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 63. Create an array class that has a name attribute (★★☆) (suggestion: class method)"
|
||||
"#### 63. Create an array class that has a name attribute (★★☆) \n",
|
||||
"##### (hint: class method)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1095,7 +1156,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 64. Consider a given vector, how to add 1 to each element indexed by a second vector (be careful with repeated indices)? (★★★) (suggestion: np.bincount | np.add.at)"
|
||||
"#### 64. Consider a given vector, how to add 1 to each element indexed by a second vector (be careful with repeated indices)? (★★★) \n",
|
||||
"##### (hint: np.bincount | np.add.at)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1111,7 +1173,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 65. How to accumulate elements of a vector (X) to an array (F) based on an index list (I)? (★★★) (suggestion: np.bincount)"
|
||||
"#### 65. How to accumulate elements of a vector (X) to an array (F) based on an index list (I)? (★★★) \n",
|
||||
"##### (hint: np.bincount)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1127,7 +1190,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 66. Considering a (w,h,3) image of (dtype=ubyte), compute the number of unique colors (★★★) (suggestion: np.unique)"
|
||||
"#### 66. Considering a (w,h,3) image of (dtype=ubyte), compute the number of unique colors (★★★) \n",
|
||||
"##### (hint: np.unique)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1143,7 +1207,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 67. Considering a four dimensions array, how to get sum over the last two axis at once? (★★★) (suggestion: sum(axis=(-2,-1)))"
|
||||
"#### 67. Considering a four dimensions array, how to get sum over the last two axis at once? (★★★) \n",
|
||||
"##### (hint: sum(axis=(-2,-1)))"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1159,7 +1224,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 68. Considering a one-dimensional vector D, how to compute means of subsets of D using a vector S of same size describing subset indices? (★★★) (suggestion: np.bincount)"
|
||||
"#### 68. Considering a one-dimensional vector D, how to compute means of subsets of D using a vector S of same size describing subset indices? (★★★) \n",
|
||||
"##### (hint: np.bincount)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1175,7 +1241,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 69. How to get the diagonal of a dot product? (★★★) (suggestion: np.diag)"
|
||||
"#### 69. How to get the diagonal of a dot product? (★★★) \n",
|
||||
"##### (hint: np.diag)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1191,7 +1258,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 70. Consider the vector \\[1, 2, 3, 4, 5\\], how to build a new vector with 3 consecutive zeros interleaved between each value? (★★★) (suggestion: array\\[::4\\])"
|
||||
"#### 70. Consider the vector \\[1, 2, 3, 4, 5\\], how to build a new vector with 3 consecutive zeros interleaved between each value? (★★★) \n",
|
||||
"##### (hint: array\\[::4\\])"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1207,7 +1275,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 71. Consider an array of dimension (5,5,3), how to mulitply it by an array with dimensions (5,5)? (★★★) (suggestion: array\\[:, :, None\\])"
|
||||
"#### 71. Consider an array of dimension (5,5,3), how to mulitply it by an array with dimensions (5,5)? (★★★) \n",
|
||||
"##### (hint: array\\[:, :, None\\])"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1223,7 +1292,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 72. How to swap two rows of an array? (★★★) (suggestion: array\\[\\[\\]\\] = array\\[\\[\\]\\])"
|
||||
"#### 72. How to swap two rows of an array? (★★★) \n",
|
||||
"##### (hint: array\\[\\[\\]\\] = array\\[\\[\\]\\])"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1239,7 +1309,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 73. Consider a set of 10 triplets describing 10 triangles (with shared vertices), find the set of unique line segments composing all the triangles (★★★) (suggestion: repeat, np.roll, np.sort, view, np.unique)"
|
||||
"#### 73. Consider a set of 10 triplets describing 10 triangles (with shared vertices), find the set of unique line segments composing all the triangles (★★★) \n",
|
||||
"##### (hint: repeat, np.roll, np.sort, view, np.unique)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1255,7 +1326,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 74. Given an array C that is a bincount, how to produce an array A such that np.bincount(A) == C? (★★★) (suggestion: np.repeat)"
|
||||
"#### 74. Given an array C that is a bincount, how to produce an array A such that np.bincount(A) == C? (★★★) \n",
|
||||
"##### (hint: np.repeat)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1271,7 +1343,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 75. How to compute averages using a sliding window over an array? (★★★) (suggestion: np.cumsum)"
|
||||
"#### 75. How to compute averages using a sliding window over an array? (★★★) \n",
|
||||
"##### (hint: np.cumsum)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1287,7 +1360,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 76. Consider a one-dimensional array Z, build a two-dimensional array whose first row is (Z\\[0\\],Z\\[1\\],Z\\[2\\]) and each subsequent row is shifted by 1 (last row should be (Z\\[-3\\],Z\\[-2\\],Z\\[-1\\]) (★★★) (suggestion: from numpy.lib import stride_tricks)"
|
||||
"#### 76. Consider a one-dimensional array Z, build a two-dimensional array whose first row is (Z\\[0\\],Z\\[1\\],Z\\[2\\]) and each subsequent row is shifted by 1 (last row should be (Z\\[-3\\],Z\\[-2\\],Z\\[-1\\]) (★★★) \n",
|
||||
"##### (hint: from numpy.lib import stride_tricks)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1303,7 +1377,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 77. How to negate a boolean, or to change the sign of a float inplace? (★★★) (suggestion: np.logical_not, np.negative)"
|
||||
"#### 77. How to negate a boolean, or to change the sign of a float inplace? (★★★) \n",
|
||||
"##### (hint: np.logical_not, np.negative)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1351,7 +1426,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 80. Consider an arbitrary array, write a function that extract a subpart with a fixed shape and centered on a given element (pad with a `fill` value when necessary) (★★★) (suggestion: minimum, maximum)"
|
||||
"#### 80. Consider an arbitrary array, write a function that extract a subpart with a fixed shape and centered on a given element (pad with a `fill` value when necessary) (★★★) \n",
|
||||
"##### (hint: minimum, maximum)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1367,7 +1443,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 81. Consider an array Z = \\[1,2,3,4,5,6,7,8,9,10,11,12,13,14\\], how to generate an array R = \\[\\[1,2,3,4\\], \\[2,3,4,5\\], \\[3,4,5,6\\], ..., \\[11,12,13,14\\]\\]? (★★★) (suggestion: stride\\_tricks.as\\_strided)"
|
||||
"#### 81. Consider an array Z = \\[1,2,3,4,5,6,7,8,9,10,11,12,13,14\\], how to generate an array R = \\[\\[1,2,3,4\\], \\[2,3,4,5\\], \\[3,4,5,6\\], ..., \\[11,12,13,14\\]\\]? (★★★) \n",
|
||||
"##### (hint: stride\\_tricks.as\\_strided)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1383,7 +1460,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 82. Compute a matrix rank (★★★) (suggestion: np.linalg.svd) (suggestion: np.linalg.svd)"
|
||||
"#### 82. Compute a matrix rank (★★★) \n",
|
||||
"##### (hint: np.linalg.svd) (suggestion: np.linalg.svd)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1399,7 +1477,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 83. How to find the most frequent value in an array? (suggestion: np.bincount, argmax)"
|
||||
"#### 83. How to find the most frequent value in an array? \n",
|
||||
"##### (hint: np.bincount, argmax)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1415,7 +1494,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 84. Extract all the contiguous 3x3 blocks from a random 10x10 matrix (★★★) (suggestion: stride\\_tricks.as\\_strided)"
|
||||
"#### 84. Extract all the contiguous 3x3 blocks from a random 10x10 matrix (★★★) \n",
|
||||
"##### (hint: stride\\_tricks.as\\_strided)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1431,7 +1511,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 85. Create a 2D array subclass such that Z\\[i,j\\] == Z\\[j,i\\] (★★★) (suggestion: class method)"
|
||||
"#### 85. Create a 2D array subclass such that Z\\[i,j\\] == Z\\[j,i\\] (★★★) \n",
|
||||
"##### (hint: class method)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1447,7 +1528,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 86. Consider a set of p matrices wich shape (n,n) and a set of p vectors with shape (n,1). How to compute the sum of of the p matrix products at once? (result has shape (n,1)) (★★★) (suggestion: np.tensordot)"
|
||||
"#### 86. Consider a set of p matrices wich shape (n,n) and a set of p vectors with shape (n,1). How to compute the sum of of the p matrix products at once? (result has shape (n,1)) (★★★) \n",
|
||||
"##### (hint: np.tensordot)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1463,7 +1545,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 87. Consider a 16x16 array, how to get the block-sum (block size is 4x4)? (★★★) (suggestion: np.add.reduceat)"
|
||||
"#### 87. Consider a 16x16 array, how to get the block-sum (block size is 4x4)? (★★★) \n",
|
||||
"##### (hint: np.add.reduceat)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1495,7 +1578,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 89. How to get the n largest values of an array (★★★) (suggestion: np.argsort | np.argpartition)"
|
||||
"#### 89. How to get the n largest values of an array (★★★) \n",
|
||||
"##### (hint: np.argsort | np.argpartition)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1511,7 +1595,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 90. Given an arbitrary number of vectors, build the cartesian product (every combinations of every item) (★★★) (suggestion: np.indices)"
|
||||
"#### 90. Given an arbitrary number of vectors, build the cartesian product (every combinations of every item) (★★★) \n",
|
||||
"##### (hint: np.indices)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1528,7 +1613,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 91. How to create a record array from a regular array? (★★★) (suggestion: np.core.records.fromarrays)"
|
||||
"#### 91. How to create a record array from a regular array? (★★★) \n",
|
||||
"##### (hint: np.core.records.fromarrays)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1544,7 +1630,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 92. Consider a large vector Z, compute Z to the power of 3 using 3 different methods (★★★) (suggestion: np.power, \\*, np.einsum)"
|
||||
"#### 92. Consider a large vector Z, compute Z to the power of 3 using 3 different methods (★★★) \n",
|
||||
"##### (hint: np.power, \\*, np.einsum)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1560,7 +1647,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 93. Consider two arrays A and B of shape (8,3) and (2,2). How to find rows of A that contain elements of each row of B regardless of the order of the elements in B? (★★★) (suggestion: np.where)"
|
||||
"#### 93. Consider two arrays A and B of shape (8,3) and (2,2). How to find rows of A that contain elements of each row of B regardless of the order of the elements in B? (★★★) \n",
|
||||
"##### (hint: np.where)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1592,7 +1680,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 95. Convert a vector of ints into a matrix binary representation (★★★) (suggestion: np.unpackbits)"
|
||||
"#### 95. Convert a vector of ints into a matrix binary representation (★★★) \n",
|
||||
"##### (hint: np.unpackbits)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1608,7 +1697,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 96. Given a two dimensional array, how to extract unique rows? (★★★) (suggestion: np.ascontiguousarray)"
|
||||
"#### 96. Given a two dimensional array, how to extract unique rows? (★★★) \n",
|
||||
"##### (hint: np.ascontiguousarray)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1624,7 +1714,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 97. Considering 2 vectors A & B, write the einsum equivalent of inner, outer, sum, and mul function (★★★) (suggestion: np.einsum)"
|
||||
"#### 97. Considering 2 vectors A & B, write the einsum equivalent of inner, outer, sum, and mul function (★★★) \n",
|
||||
"##### (hint: np.einsum)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1640,7 +1731,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 98. Considering a path described by two vectors (X,Y), how to sample it using equidistant samples (★★★)? (suggestion: np.cumsum, np.interp)"
|
||||
"#### 98. Considering a path described by two vectors (X,Y), how to sample it using equidistant samples (★★★)? \n",
|
||||
"##### (hint: np.cumsum, np.interp)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1656,7 +1748,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 99. Given an integer n and a 2D array X, select from X the rows which can be interpreted as draws from a multinomial distribution with n degrees, i.e., the rows which only contain integers and which sum to n. (★★★) (suggestion: np.logical\\_and.reduce, np.mod)"
|
||||
"#### 99. Given an integer n and a 2D array X, select from X the rows which can be interpreted as draws from a multinomial distribution with n degrees, i.e., the rows which only contain integers and which sum to n. (★★★) \n",
|
||||
"##### (hint: np.logical\\_and.reduce, np.mod)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1672,7 +1765,8 @@
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"#### 100. Compute bootstrapped 95% confidence intervals for the mean of a 1D array X (i.e., resample the elements of an array with replacement N times, compute the mean of each sample, and then compute percentiles over the means). (★★★) (suggestion: np.percentile)"
|
||||
"#### 100. Compute bootstrapped 95% confidence intervals for the mean of a 1D array X (i.e., resample the elements of an array with replacement N times, compute the mean of each sample, and then compute percentiles over the means). (★★★) \n",
|
||||
"##### (hint: np.percentile)"
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -1,5 +1,5 @@
|
||||
|
||||
# 100 numpy exercises with suggestion
|
||||
# 100 numpy exercises with hint
|
||||
|
||||
This is a collection of exercises that have been collected in the numpy mailing
|
||||
list, on stack overflow and in the numpy documentation. I've also created some
|
||||
@ -10,71 +10,105 @@ those who teach.
|
||||
If you find an error or think you've a better way to solve some of them, feel
|
||||
free to open an issue at <https://github.com/rougier/numpy-100>
|
||||
|
||||
#### 1. Import the numpy package under the name `np` (★☆☆) (suggestion: import … as ..)
|
||||
#### 1. Import the numpy package under the name `np` (★☆☆)
|
||||
|
||||
##### (hint: import … as ..)
|
||||
|
||||
|
||||
|
||||
#### 2. Print the numpy version and the configuration (★☆☆) (suggestion: np.\_\_verison\_\_, np.show\_config)
|
||||
#### 2. Print the numpy version and the configuration (★☆☆)
|
||||
|
||||
##### (hint: np.\_\_verison\_\_, np.show\_config)
|
||||
|
||||
|
||||
|
||||
#### 3. Create a null vector of size 10 (★☆☆) (suggestion: np.zeros)
|
||||
#### 3. Create a null vector of size 10 (★☆☆)
|
||||
|
||||
##### (hint: np.zeros)
|
||||
|
||||
|
||||
|
||||
#### 4. How to find the memory size of any array (★☆☆) (suggestion: size, itemsize)
|
||||
#### 4. How to find the memory size of any array (★☆☆)
|
||||
|
||||
##### (hint: size, itemsize)
|
||||
|
||||
|
||||
|
||||
#### 5. How to get the documentation of the numpy add function from the command line? (★☆☆) (suggestion: np.info)
|
||||
#### 5. How to get the documentation of the numpy add function from the command line? (★☆☆)
|
||||
|
||||
##### (hint: np.info)
|
||||
|
||||
|
||||
|
||||
#### 6. Create a null vector of size 10 but the fifth value which is 1 (★☆☆) (suggestion: array\[4\])
|
||||
#### 6. Create a null vector of size 10 but the fifth value which is 1 (★☆☆)
|
||||
|
||||
##### (hint: array\[4\])
|
||||
|
||||
|
||||
|
||||
#### 7. Create a vector with values ranging from 10 to 49 (★☆☆) (suggestion: np.arange)
|
||||
#### 7. Create a vector with values ranging from 10 to 49 (★☆☆)
|
||||
|
||||
##### (hint: np.arange)
|
||||
|
||||
|
||||
|
||||
#### 8. Reverse a vector (first element becomes last) (★☆☆) (suggestion: array\[::-1\])
|
||||
#### 8. Reverse a vector (first element becomes last) (★☆☆)
|
||||
|
||||
##### (hint: array\[::-1\])
|
||||
|
||||
|
||||
|
||||
#### 9. Create a 3x3 matrix with values ranging from 0 to 8 (★☆☆) (suggestion: reshape)
|
||||
#### 9. Create a 3x3 matrix with values ranging from 0 to 8 (★☆☆)
|
||||
|
||||
##### (hint: reshape)
|
||||
|
||||
|
||||
|
||||
#### 10. Find indices of non-zero elements from \[1,2,0,0,4,0\] (★☆☆) (suggestion: np.nonzero)
|
||||
#### 10. Find indices of non-zero elements from \[1,2,0,0,4,0\] (★☆☆)
|
||||
|
||||
##### (hint: np.nonzero)
|
||||
|
||||
|
||||
|
||||
#### 11. Create a 3x3 identity matrix (★☆☆) (suggestion: np.eye)
|
||||
#### 11. Create a 3x3 identity matrix (★☆☆)
|
||||
|
||||
##### (hint: np.eye)
|
||||
|
||||
|
||||
|
||||
#### 12. Create a 3x3x3 array with random values (★☆☆) (suggestion: np.random.random)
|
||||
#### 12. Create a 3x3x3 array with random values (★☆☆)
|
||||
|
||||
##### (hint: np.random.random)
|
||||
|
||||
|
||||
|
||||
#### 13. Create a 10x10 array with random values and find the minimum and maximum values (★☆☆) (suggestion: min, max)
|
||||
#### 13. Create a 10x10 array with random values and find the minimum and maximum values (★☆☆)
|
||||
|
||||
##### (hint: min, max)
|
||||
|
||||
|
||||
|
||||
#### 14. Create a random vector of size 30 and find the mean value (★☆☆) (suggestion: mean)
|
||||
#### 14. Create a random vector of size 30 and find the mean value (★☆☆)
|
||||
|
||||
##### (hint: mean)
|
||||
|
||||
|
||||
|
||||
#### 15. Create a 2d array with 1 on the border and 0 inside (★☆☆) (suggestion: array\[1:-1, 1:-1\])
|
||||
#### 15. Create a 2d array with 1 on the border and 0 inside (★☆☆)
|
||||
|
||||
##### (hint: array\[1:-1, 1:-1\])
|
||||
|
||||
|
||||
|
||||
#### 16. How to add a border (filled with 0's) around an existing array? (★☆☆) (suggestion: np.pad)
|
||||
#### 16. How to add a border (filled with 0's) around an existing array? (★☆☆)
|
||||
|
||||
##### (hint: np.pad)
|
||||
|
||||
|
||||
|
||||
#### 17. What is the result of the following expression? (★☆☆) (suggestion: NaN = not a number, inf = infinity)
|
||||
#### 17. What is the result of the following expression? (★☆☆)
|
||||
|
||||
##### (hint: NaN = not a number, inf = infinity)
|
||||
|
||||
|
||||
```python
|
||||
@ -85,39 +119,57 @@ np.nan - np.nan
|
||||
0.3 == 3 * 0.1
|
||||
```
|
||||
|
||||
#### 18. Create a 5x5 matrix with values 1,2,3,4 just below the diagonal (★☆☆) (suggestion: np.diag)
|
||||
#### 18. Create a 5x5 matrix with values 1,2,3,4 just below the diagonal (★☆☆)
|
||||
|
||||
##### (hint: np.diag)
|
||||
|
||||
|
||||
|
||||
#### 19. Create a 8x8 matrix and fill it with a checkerboard pattern (★☆☆) (suggestion: array\[::2\])
|
||||
#### 19. Create a 8x8 matrix and fill it with a checkerboard pattern (★☆☆)
|
||||
|
||||
##### (hint: array\[::2\])
|
||||
|
||||
|
||||
|
||||
#### 20. Consider a (6,7,8) shape array, what is the index (x,y,z) of the 100th element? (suggestion: np.unravel\_index)
|
||||
#### 20. Consider a (6,7,8) shape array, what is the index (x,y,z) of the 100th element?
|
||||
|
||||
##### (hint: np.unravel\_index)
|
||||
|
||||
|
||||
|
||||
#### 21. Create a checkerboard 8x8 matrix using the tile function (★☆☆) (suggestion: np.tile)
|
||||
#### 21. Create a checkerboard 8x8 matrix using the tile function (★☆☆)
|
||||
|
||||
##### (hint: np.tile)
|
||||
|
||||
|
||||
|
||||
#### 22. Normalize a 5x5 random matrix (★☆☆) (suggestion: (x - min) / (max - min))
|
||||
#### 22. Normalize a 5x5 random matrix (★☆☆)
|
||||
|
||||
##### (hint: (x - min) / (max - min))
|
||||
|
||||
|
||||
|
||||
#### 23. Create a custom dtype that describes a color as four unsigned bytes (RGBA) (★☆☆) (suggestion: np.dtype)
|
||||
#### 23. Create a custom dtype that describes a color as four unsigned bytes (RGBA) (★☆☆)
|
||||
|
||||
##### (hint: np.dtype)
|
||||
|
||||
|
||||
|
||||
#### 24. Multiply a 5x3 matrix by a 3x2 matrix (real matrix product) (★☆☆) (suggestion: np.dot | @)
|
||||
#### 24. Multiply a 5x3 matrix by a 3x2 matrix (real matrix product) (★☆☆)
|
||||
|
||||
##### (hint: np.dot | @)
|
||||
|
||||
|
||||
|
||||
#### 25. Given a 1D array, negate all elements which are between 3 and 8, in place. (★☆☆) (suggestion: >, <=)
|
||||
#### 25. Given a 1D array, negate all elements which are between 3 and 8, in place. (★☆☆)
|
||||
|
||||
##### (hint: >, <=)
|
||||
|
||||
|
||||
|
||||
#### 26. What is the output of the following script? (★☆☆) (suggestion: np.sum)
|
||||
#### 26. What is the output of the following script? (★☆☆)
|
||||
|
||||
##### (hint: np.sum)
|
||||
|
||||
|
||||
```python
|
||||
@ -149,110 +201,162 @@ np.array(0) // np.array(0)
|
||||
np.array([np.nan]).astype(int).astype(float)
|
||||
```
|
||||
|
||||
#### 29. How to round away from zero a float array ? (★☆☆) (suggestion: np.uniform, np.copysign, np.ceil, np.abs)
|
||||
#### 29. How to round away from zero a float array ? (★☆☆)
|
||||
|
||||
##### (hint: np.uniform, np.copysign, np.ceil, np.abs)
|
||||
|
||||
|
||||
|
||||
#### 30. How to find common values between two arrays? (★☆☆) (suggestion: np.intersect1d)
|
||||
#### 30. How to find common values between two arrays? (★☆☆)
|
||||
|
||||
##### (hint: np.intersect1d)
|
||||
|
||||
|
||||
|
||||
#### 31. How to ignore all numpy warnings (not recommended)? (★☆☆) (suggestion: np.seterr, np.errstate)
|
||||
#### 31. How to ignore all numpy warnings (not recommended)? (★☆☆)
|
||||
|
||||
##### (hint: np.seterr, np.errstate)
|
||||
|
||||
|
||||
|
||||
#### 32. Is the following expressions true? (★☆☆) (suggestion: imaginary number)
|
||||
#### 32. Is the following expressions true? (★☆☆)
|
||||
|
||||
##### (hint: imaginary number)
|
||||
|
||||
|
||||
```python
|
||||
np.sqrt(-1) == np.emath.sqrt(-1)
|
||||
```
|
||||
|
||||
#### 33. How to get the dates of yesterday, today and tomorrow? (★☆☆) (suggestion: np.datetime64, np.timedelta64)
|
||||
#### 33. How to get the dates of yesterday, today and tomorrow? (★☆☆)
|
||||
|
||||
##### (hint: np.datetime64, np.timedelta64)
|
||||
|
||||
|
||||
|
||||
#### 34. How to get all the dates corresponding to the month of July 2016? (★★☆) (suggestion: np.arange(dtype=datetime64\['D'\]))
|
||||
#### 34. How to get all the dates corresponding to the month of July 2016? (★★☆)
|
||||
|
||||
##### (hint: np.arange(dtype=datetime64\['D'\]))
|
||||
|
||||
|
||||
|
||||
#### 35. How to compute ((A+B)\*(-A/2)) in place (without copy)? (★★☆) (suggestion: np.add(out=), np.negative(out=), np.multiply(out=), np.divide(out=))
|
||||
#### 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 (★★☆) (suggestion: %, np.floor, np.ceil, astype, np.trunc)
|
||||
#### 36. Extract the integer part of a random array using 5 different methods (★★☆)
|
||||
|
||||
##### (hint: %, np.floor, np.ceil, astype, np.trunc)
|
||||
|
||||
|
||||
|
||||
#### 37. Create a 5x5 matrix with row values ranging from 0 to 4 (★★☆) (suggestion: np.arange)
|
||||
#### 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 (★☆☆) (suggestion: np.fromiter)
|
||||
#### 38. Consider a generator function that generates 10 integers and use it to build an array (★☆☆)
|
||||
|
||||
##### (hint: np.fromiter)
|
||||
|
||||
|
||||
|
||||
#### 39. Create a vector of size 10 with values ranging from 0 to 1, both excluded (★★☆) (suggestion: np.linespace)
|
||||
#### 39. Create a vector of size 10 with values ranging from 0 to 1, both excluded (★★☆)
|
||||
|
||||
##### (hint: np.linespace)
|
||||
|
||||
|
||||
|
||||
#### 40. Create a random vector of size 10 and sort it (★★☆) (suggestion: sort)
|
||||
#### 40. Create a random vector of size 10 and sort it (★★☆)
|
||||
|
||||
##### (hint: sort)
|
||||
|
||||
|
||||
|
||||
#### 41. How to sum a small array faster than np.sum? (★★☆) (suggestion: np.add.reduce)
|
||||
#### 41. How to sum a small array faster than np.sum? (★★☆)
|
||||
|
||||
##### (hint: np.add.reduce)
|
||||
|
||||
|
||||
|
||||
#### 42. Consider two random array A and B, check if they are equal (★★☆) (suggestion: np.allclose, np.array\_equal)
|
||||
#### 42. Consider two random array A and B, check if they are equal (★★☆)
|
||||
|
||||
##### (hint: np.allclose, np.array\_equal)
|
||||
|
||||
|
||||
|
||||
#### 43. Make an array immutable (read-only) (★★☆) (suggestion: flags.writeable)
|
||||
#### 43. Make an array immutable (read-only) (★★☆)
|
||||
|
||||
##### (hint: flags.writeable)
|
||||
|
||||
|
||||
|
||||
#### 44. Consider a random 10x2 matrix representing cartesian coordinates, convert them to polar coordinates (★★☆) (suggestion: np.sqrt, np.arctan2)
|
||||
#### 44. Consider a random 10x2 matrix representing cartesian coordinates, convert them to polar coordinates (★★☆)
|
||||
|
||||
##### (hint: np.sqrt, np.arctan2)
|
||||
|
||||
|
||||
|
||||
#### 45. Create random vector of size 10 and replace the maximum value by 0 (★★☆) (suggestion: argmax)
|
||||
#### 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 (★★☆) (suggestion: np.meshgrid)
|
||||
#### 46. Create a structured array with `x` and `y` coordinates covering the \[0,1\]x\[0,1\] area (★★☆)
|
||||
|
||||
##### (hint: np.meshgrid)
|
||||
|
||||
|
||||
|
||||
#### 47. Given two arrays, X and Y, construct the Cauchy matrix C (Cij =1/(xi - yj)) (suggestion: np.subtract.outer)
|
||||
#### 47. Given two arrays, X and Y, construct the Cauchy matrix C (Cij =1/(xi - yj))
|
||||
|
||||
##### (hint: np.subtract.outer)
|
||||
|
||||
|
||||
|
||||
#### 48. Print the minimum and maximum representable value for each numpy scalar type (★★☆) (suggestion: np.iinfo, np.finfo, eps)
|
||||
#### 48. Print the minimum and maximum representable value for each numpy scalar type (★★☆)
|
||||
|
||||
##### (hint: np.iinfo, np.finfo, eps)
|
||||
|
||||
|
||||
|
||||
#### 49. How to print all the values of an array? (★★☆) (suggestion: np.set\_printoptions)
|
||||
#### 49. How to print all the values of an array? (★★☆)
|
||||
|
||||
##### (hint: np.set\_printoptions)
|
||||
|
||||
|
||||
|
||||
#### 50. How to find the closest value (to a given scalar) in a vector? (★★☆) (suggestion: argmin)
|
||||
#### 50. How to find the closest value (to a given scalar) in a vector? (★★☆)
|
||||
|
||||
##### (hint: argmin)
|
||||
|
||||
|
||||
|
||||
#### 51. Create a structured array representing a position (x,y) and a color (r,g,b) (★★☆) (suggestion: dtype)
|
||||
#### 51. Create a structured array representing a position (x,y) and a color (r,g,b) (★★☆)
|
||||
|
||||
##### (hint: dtype)
|
||||
|
||||
|
||||
|
||||
#### 52. Consider a random vector with shape (100,2) representing coordinates, find point by point distances (★★☆) (suggestion: np.atleast\_2d, T, np.sqrt)
|
||||
#### 52. Consider a random vector with shape (100,2) representing coordinates, find point by point distances (★★☆)
|
||||
|
||||
##### (hint: np.atleast\_2d, T, np.sqrt)
|
||||
|
||||
|
||||
|
||||
#### 53. How to convert a float (32 bits) array into an integer (32 bits) in place? (suggestion: astype(copy=False))
|
||||
#### 53. How to convert a float (32 bits) array into an integer (32 bits) in place?
|
||||
|
||||
##### (hint: astype(copy=False))
|
||||
|
||||
|
||||
|
||||
#### 54. How to read the following file? (★★☆) (suggestion: np.genfromtxt)
|
||||
#### 54. How to read the following file? (★★☆)
|
||||
|
||||
##### (hint: np.genfromtxt)
|
||||
|
||||
|
||||
```
|
||||
@ -261,95 +365,141 @@ np.sqrt(-1) == np.emath.sqrt(-1)
|
||||
, , 9,10,11
|
||||
```
|
||||
|
||||
#### 55. What is the equivalent of enumerate for numpy arrays? (★★☆) (suggestion: np.ndenumerate, np.ndindex)
|
||||
#### 55. What is the equivalent of enumerate for numpy arrays? (★★☆)
|
||||
|
||||
##### (hint: np.ndenumerate, np.ndindex)
|
||||
|
||||
|
||||
#### 56. Generate a generic 2D Gaussian-like array (★★☆) (suggestion: np.meshgrid, np.exp)
|
||||
|
||||
#### 56. Generate a generic 2D Gaussian-like array (★★☆)
|
||||
|
||||
##### (hint: np.meshgrid, np.exp)
|
||||
|
||||
#### 57. How to randomly place p elements in a 2D array? (★★☆) (suggestion: np.put, np.random.choice)
|
||||
|
||||
|
||||
#### 57. How to randomly place p elements in a 2D array? (★★☆)
|
||||
|
||||
#### 58. Subtract the mean of each row of a matrix (★★☆) (suggestion: mean(axis=,keepdims=))
|
||||
##### (hint: np.put, np.random.choice)
|
||||
|
||||
|
||||
|
||||
#### 59. How to sort an array by the nth column? (★★☆) (suggestion: argsort)
|
||||
#### 58. Subtract the mean of each row of a matrix (★★☆)
|
||||
|
||||
##### (hint: mean(axis=,keepdims=))
|
||||
|
||||
|
||||
#### 60. How to tell if a given 2D array has null columns? (★★☆) (suggestion: any, ~)
|
||||
|
||||
#### 59. How to sort an array by the nth column? (★★☆)
|
||||
|
||||
##### (hint: argsort)
|
||||
|
||||
#### 61. Find the nearest value from a given value in an array (★★☆) (suggestion: np.abs, argmin, flat)
|
||||
|
||||
|
||||
#### 60. How to tell if a given 2D array has null columns? (★★☆)
|
||||
|
||||
#### 62. Considering two arrays with shape (1,3) and (3,1), how to compute their sum using an iterator? (★★☆) (suggestion: np.nditer)
|
||||
##### (hint: any, ~)
|
||||
|
||||
|
||||
|
||||
#### 63. Create an array class that has a name attribute (★★☆) (suggestion: class method)
|
||||
#### 61. Find the nearest value from a given value in an array (★★☆)
|
||||
|
||||
##### (hint: np.abs, argmin, flat)
|
||||
|
||||
|
||||
#### 64. Consider a given vector, how to add 1 to each element indexed by a second vector (be careful with repeated indices)? (★★★) (suggestion: np.bincount | np.add.at)
|
||||
|
||||
#### 62. Considering two arrays with shape (1,3) and (3,1), how to compute their sum using an iterator? (★★☆)
|
||||
|
||||
##### (hint: np.nditer)
|
||||
|
||||
#### 65. How to accumulate elements of a vector (X) to an array (F) based on an index list (I)? (★★★) (suggestion: np.bincount)
|
||||
|
||||
|
||||
#### 63. Create an array class that has a name attribute (★★☆)
|
||||
|
||||
#### 66. Considering a (w,h,3) image of (dtype=ubyte), compute the number of unique colors (★★★) (suggestion: np.unique)
|
||||
##### (hint: class method)
|
||||
|
||||
|
||||
|
||||
#### 67. Considering a four dimensions array, how to get sum over the last two axis at once? (★★★) (suggestion: sum(axis=(-2,-1)))
|
||||
#### 64. Consider a given vector, how to add 1 to each element indexed by a second vector (be careful with repeated indices)? (★★★)
|
||||
|
||||
##### (hint: np.bincount | np.add.at)
|
||||
|
||||
|
||||
#### 68. Considering a one-dimensional vector D, how to compute means of subsets of D using a vector S of same size describing subset indices? (★★★) (suggestion: np.bincount)
|
||||
|
||||
#### 65. How to accumulate elements of a vector (X) to an array (F) based on an index list (I)? (★★★)
|
||||
|
||||
##### (hint: np.bincount)
|
||||
|
||||
#### 69. How to get the diagonal of a dot product? (★★★) (suggestion: np.diag)
|
||||
|
||||
|
||||
#### 66. Considering a (w,h,3) image of (dtype=ubyte), compute the number of unique colors (★★★)
|
||||
|
||||
#### 70. Consider the vector \[1, 2, 3, 4, 5\], how to build a new vector with 3 consecutive zeros interleaved between each value? (★★★) (suggestion: array\[::4\])
|
||||
##### (hint: np.unique)
|
||||
|
||||
|
||||
|
||||
#### 71. Consider an array of dimension (5,5,3), how to mulitply it by an array with dimensions (5,5)? (★★★) (suggestion: array\[:, :, None\])
|
||||
#### 67. Considering a four dimensions array, how to get sum over the last two axis at once? (★★★)
|
||||
|
||||
##### (hint: sum(axis=(-2,-1)))
|
||||
|
||||
|
||||
#### 72. How to swap two rows of an array? (★★★) (suggestion: array\[\[\]\] = array\[\[\]\])
|
||||
|
||||
#### 68. Considering a one-dimensional vector D, how to compute means of subsets of D using a vector S of same size describing subset indices? (★★★)
|
||||
|
||||
##### (hint: np.bincount)
|
||||
|
||||
#### 73. Consider a set of 10 triplets describing 10 triangles (with shared vertices), find the set of unique line segments composing all the triangles (★★★) (suggestion: repeat, np.roll, np.sort, view, np.unique)
|
||||
|
||||
|
||||
#### 69. How to get the diagonal of a dot product? (★★★)
|
||||
|
||||
#### 74. Given an array C that is a bincount, how to produce an array A such that np.bincount(A) == C? (★★★) (suggestion: np.repeat)
|
||||
##### (hint: np.diag)
|
||||
|
||||
|
||||
|
||||
#### 75. How to compute averages using a sliding window over an array? (★★★) (suggestion: np.cumsum)
|
||||
#### 70. Consider the vector \[1, 2, 3, 4, 5\], how to build a new vector with 3 consecutive zeros interleaved between each value? (★★★)
|
||||
|
||||
##### (hint: array\[::4\])
|
||||
|
||||
|
||||
#### 76. Consider a one-dimensional array Z, build a two-dimensional array whose first row is (Z\[0\],Z\[1\],Z\[2\]) and each subsequent row is shifted by 1 (last row should be (Z\[-3\],Z\[-2\],Z\[-1\]) (★★★) (suggestion: from numpy.lib import stride\_tricks)
|
||||
|
||||
#### 71. Consider an array of dimension (5,5,3), how to mulitply it by an array with dimensions (5,5)? (★★★)
|
||||
|
||||
##### (hint: array\[:, :, None\])
|
||||
|
||||
#### 77. How to negate a boolean, or to change the sign of a float inplace? (★★★) (suggestion: np.logical_not, np.negative)
|
||||
|
||||
|
||||
#### 72. How to swap two rows of an array? (★★★)
|
||||
|
||||
##### (hint: array\[\[\]\] = array\[\[\]\])
|
||||
|
||||
|
||||
|
||||
#### 73. Consider a set of 10 triplets describing 10 triangles (with shared vertices), find the set of unique line segments composing all the triangles (★★★)
|
||||
|
||||
##### (hint: repeat, np.roll, np.sort, view, np.unique)
|
||||
|
||||
|
||||
|
||||
#### 74. Given an array C that is a bincount, how to produce an array A such that np.bincount(A) == C? (★★★)
|
||||
|
||||
##### (hint: np.repeat)
|
||||
|
||||
|
||||
|
||||
#### 75. How to compute averages using a sliding window over an array? (★★★)
|
||||
|
||||
##### (hint: np.cumsum)
|
||||
|
||||
|
||||
|
||||
#### 76. Consider a one-dimensional array Z, build a two-dimensional array whose first row is (Z\[0\],Z\[1\],Z\[2\]) and each subsequent row is shifted by 1 (last row should be (Z\[-3\],Z\[-2\],Z\[-1\]) (★★★)
|
||||
|
||||
##### (hint: from numpy.lib import stride\_tricks)
|
||||
|
||||
|
||||
|
||||
#### 77. How to negate a boolean, or to change the sign of a float inplace? (★★★)
|
||||
|
||||
##### (hint: np.logical_not, np.negative)
|
||||
|
||||
|
||||
|
||||
@ -361,35 +511,51 @@ np.sqrt(-1) == np.emath.sqrt(-1)
|
||||
|
||||
|
||||
|
||||
#### 80. Consider an arbitrary array, write a function that extract a subpart with a fixed shape and centered on a given element (pad with a `fill` value when necessary) (★★★) (suggestion: minimum, maximum)
|
||||
#### 80. Consider an arbitrary array, write a function that extract a subpart with a fixed shape and centered on a given element (pad with a `fill` value when necessary) (★★★)
|
||||
|
||||
##### (hint: minimum, maximum)
|
||||
|
||||
|
||||
|
||||
#### 81. Consider an array Z = \[1,2,3,4,5,6,7,8,9,10,11,12,13,14\], how to generate an array R = \[\[1,2,3,4\], \[2,3,4,5\], \[3,4,5,6\], ..., \[11,12,13,14\]\]? (★★★) (suggestion: stride\_tricks.as\_strided)
|
||||
#### 81. Consider an array Z = \[1,2,3,4,5,6,7,8,9,10,11,12,13,14\], how to generate an array R = \[\[1,2,3,4\], \[2,3,4,5\], \[3,4,5,6\], ..., \[11,12,13,14\]\]? (★★★)
|
||||
|
||||
##### (hint: stride\_tricks.as\_strided)
|
||||
|
||||
|
||||
|
||||
#### 82. Compute a matrix rank (★★★) (suggestion: np.linalg.svd)
|
||||
#### 82. Compute a matrix rank (★★★)
|
||||
|
||||
##### (hint: np.linalg.svd)
|
||||
|
||||
|
||||
|
||||
#### 83. How to find the most frequent value in an array? (suggestion: np.bincount, argmax)
|
||||
#### 83. How to find the most frequent value in an array?
|
||||
|
||||
##### (hint: np.bincount, argmax)
|
||||
|
||||
|
||||
|
||||
#### 84. Extract all the contiguous 3x3 blocks from a random 10x10 matrix (★★★) (suggestion: stride\_tricks.as\_strided)
|
||||
#### 84. Extract all the contiguous 3x3 blocks from a random 10x10 matrix (★★★)
|
||||
|
||||
##### (hint: stride\_tricks.as\_strided)
|
||||
|
||||
|
||||
|
||||
#### 85. Create a 2D array subclass such that Z\[i,j\] == Z\[j,i\] (★★★) (suggestion: class method)
|
||||
#### 85. Create a 2D array subclass such that Z\[i,j\] == Z\[j,i\] (★★★)
|
||||
|
||||
##### (hint: class method)
|
||||
|
||||
|
||||
|
||||
#### 86. Consider a set of p matrices wich shape (n,n) and a set of p vectors with shape (n,1). How to compute the sum of of the p matrix products at once? (result has shape (n,1)) (★★★) (suggestion: np.tensordot)
|
||||
#### 86. Consider a set of p matrices wich shape (n,n) and a set of p vectors with shape (n,1). How to compute the sum of of the p matrix products at once? (result has shape (n,1)) (★★★)
|
||||
|
||||
##### (hint: np.tensordot)
|
||||
|
||||
|
||||
|
||||
#### 87. Consider a 16x16 array, how to get the block-sum (block size is 4x4)? (★★★) (suggestion: np.add.reduceat)
|
||||
#### 87. Consider a 16x16 array, how to get the block-sum (block size is 4x4)? (★★★)
|
||||
|
||||
##### (hint: np.add.reduceat)
|
||||
|
||||
|
||||
|
||||
@ -397,23 +563,33 @@ np.sqrt(-1) == np.emath.sqrt(-1)
|
||||
|
||||
|
||||
|
||||
#### 89. How to get the n largest values of an array (★★★) (suggestion: np.argsort | np.argpartition)
|
||||
#### 89. How to get the n largest values of an array (★★★)
|
||||
|
||||
##### (hint: np.argsort | np.argpartition)
|
||||
|
||||
|
||||
|
||||
#### 90. Given an arbitrary number of vectors, build the cartesian product (every combinations of every item) (★★★) (suggestion: np.indices)
|
||||
#### 90. Given an arbitrary number of vectors, build the cartesian product (every combinations of every item) (★★★)
|
||||
|
||||
##### (hint: np.indices)
|
||||
|
||||
|
||||
|
||||
#### 91. How to create a record array from a regular array? (★★★) (suggestion: np.core.records.fromarrays)
|
||||
#### 91. How to create a record array from a regular array? (★★★)
|
||||
|
||||
##### (hint: np.core.records.fromarrays)
|
||||
|
||||
|
||||
|
||||
#### 92. Consider a large vector Z, compute Z to the power of 3 using 3 different methods (★★★) (suggestion: np.power, \*, np.einsum)
|
||||
#### 92. Consider a large vector Z, compute Z to the power of 3 using 3 different methods (★★★)
|
||||
|
||||
##### (hint: np.power, \*, np.einsum)
|
||||
|
||||
|
||||
|
||||
#### 93. Consider two arrays A and B of shape (8,3) and (2,2). How to find rows of A that contain elements of each row of B regardless of the order of the elements in B? (★★★) (suggestion: np.where)
|
||||
#### 93. Consider two arrays A and B of shape (8,3) and (2,2). How to find rows of A that contain elements of each row of B regardless of the order of the elements in B? (★★★)
|
||||
|
||||
##### (hint: np.where)
|
||||
|
||||
|
||||
|
||||
@ -421,25 +597,37 @@ np.sqrt(-1) == np.emath.sqrt(-1)
|
||||
|
||||
|
||||
|
||||
#### 95. Convert a vector of ints into a matrix binary representation (★★★) (suggestion: np.unpackbits)
|
||||
#### 95. Convert a vector of ints into a matrix binary representation (★★★)
|
||||
|
||||
##### (hint: np.unpackbits)
|
||||
|
||||
|
||||
|
||||
#### 96. Given a two dimensional array, how to extract unique rows? (★★★) (suggestion: np.ascontiguousarray)
|
||||
#### 96. Given a two dimensional array, how to extract unique rows? (★★★)
|
||||
|
||||
##### (hint: np.ascontiguousarray)
|
||||
|
||||
|
||||
|
||||
#### 97. Considering 2 vectors A & B, write the einsum equivalent of inner, outer, sum, and mul function (★★★) (suggestion: np.einsum)
|
||||
#### 97. Considering 2 vectors A & B, write the einsum equivalent of inner, outer, sum, and mul function (★★★)
|
||||
|
||||
##### (hint: np.einsum)
|
||||
|
||||
|
||||
|
||||
#### 98. Considering a path described by two vectors (X,Y), how to sample it using equidistant samples (★★★)? (suggestion: np.cumsum, np.interp)
|
||||
#### 98. Considering a path described by two vectors (X,Y), how to sample it using equidistant samples (★★★)?
|
||||
|
||||
##### (hint: np.cumsum, np.interp)
|
||||
|
||||
|
||||
|
||||
#### 99. Given an integer n and a 2D array X, select from X the rows which can be interpreted as draws from a multinomial distribution with n degrees, i.e., the rows which only contain integers and which sum to n. (★★★) (suggestion: np.logical\_and.reduce, np.mod)
|
||||
#### 99. Given an integer n and a 2D array X, select from X the rows which can be interpreted as draws from a multinomial distribution with n degrees, i.e., the rows which only contain integers and which sum to n. (★★★)
|
||||
|
||||
##### (hint: np.logical\_and.reduce, np.mod)
|
||||
|
||||
|
||||
|
||||
#### 100. Compute bootstrapped 95% confidence intervals for the mean of a 1D array X (i.e., resample the elements of an array with replacement N times, compute the mean of each sample, and then compute percentiles over the means). (★★★) (suggestion: np.percentile)
|
||||
#### 100. Compute bootstrapped 95% confidence intervals for the mean of a 1D array X (i.e., resample the elements of an array with replacement N times, compute the mean of each sample, and then compute percentiles over the means). (★★★)
|
||||
|
||||
##### (hint: np.percentile)
|
||||
|
||||
Loading…
Reference in New Issue
Block a user