Fixed generators (see https://github.com/didix21/mdutils/issues/69)
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@ -170,6 +170,12 @@ Z = np.zeros((8,8),dtype=int)
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Z[1::2,::2] = 1
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Z[::2,1::2] = 1
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print(Z)
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# Alternative solution: Using reshaping
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arr = np.ones(64,dtype=int)
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arr[::2]=0
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arr = arr.reshape((8,8))
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print(arr)
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```
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#### 20. Consider a (6,7,8) shape array, what is the index (x,y,z) of the 100th element? (★☆☆)
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`hint: np.unravel_index`
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@ -615,8 +621,17 @@ print(Z[Z[:,1].argsort()])
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```python
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# Author: Warren Weckesser
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# null : 0
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Z = np.random.randint(0,3,(3,10))
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print((~Z.any(axis=0)).any())
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# null : np.nan
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Z=np.array([
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[0,1,np.nan],
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[1,2,np.nan],
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[4,5,np.nan]
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])
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print(np.isnan(Z).all(axis=0))
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```
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#### 61. Find the nearest value from a given value in an array (★★☆)
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`hint: np.abs, argmin, flat`
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@ -648,7 +663,7 @@ class NamedArray(np.ndarray):
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return obj
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def __array_finalize__(self, obj):
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if obj is None: return
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self.info = getattr(obj, 'name', "no name")
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self.name = getattr(obj, 'name', "no name")
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Z = NamedArray(np.arange(10), "range_10")
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print (Z.name)
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@ -170,6 +170,12 @@ Z = np.zeros((8,8),dtype=int)
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Z[1::2,::2] = 1
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Z[::2,1::2] = 1
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print(Z)
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# Alternative solution: Using reshaping
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arr = np.ones(64,dtype=int)
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arr[::2]=0
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arr = arr.reshape((8,8))
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print(arr)
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```
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#### 20. Consider a (6,7,8) shape array, what is the index (x,y,z) of the 100th element? (★☆☆)
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@ -615,8 +621,17 @@ print(Z[Z[:,1].argsort()])
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```python
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# Author: Warren Weckesser
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# null : 0
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Z = np.random.randint(0,3,(3,10))
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print((~Z.any(axis=0)).any())
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# null : np.nan
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Z=np.array([
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[0,1,np.nan],
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[1,2,np.nan],
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[4,5,np.nan]
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])
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print(np.isnan(Z).all(axis=0))
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```
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#### 61. Find the nearest value from a given value in an array (★★☆)
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@ -648,7 +663,7 @@ class NamedArray(np.ndarray):
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return obj
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def __array_finalize__(self, obj):
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if obj is None: return
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self.info = getattr(obj, 'name', "no name")
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self.name = getattr(obj, 'name', "no name")
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Z = NamedArray(np.arange(10), "range_10")
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print (Z.name)
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@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "markdown",
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"id": "a194d42e",
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"id": "fc29ba19",
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"metadata": {},
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"source": [
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"# 100 numpy exercises\n",
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@ -18,7 +18,7 @@
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},
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{
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"cell_type": "markdown",
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"id": "a7fd49f7",
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"id": "c71c938e",
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"metadata": {},
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"source": [
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"File automatically generated. See the documentation to update questions/answers/hints programmatically."
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@ -26,7 +26,7 @@
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},
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{
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"cell_type": "markdown",
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"id": "b702d5a2",
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"id": "9295ebad",
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"metadata": {},
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"source": [
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"Run the `initialize.py` module, then call a random question with `pick()` an hint towards its solution with\n",
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@ -36,7 +36,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "da60e1d0",
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"id": "75ba9fda",
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"metadata": {},
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"outputs": [],
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"source": [
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@ -46,7 +46,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9fb544fe",
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"id": "5e130ff3",
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"metadata": {},
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"outputs": [],
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"source": [
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@ -108,7 +108,7 @@ def create_markdown(destination_filename='100_Numpy_exercises', with_hints=False
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# Add questions (and hint or answers if required)
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for n in range(1, 101):
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mdfile.new_header(title=f"{n}. {QHA[f'q{n}']}", level=4)
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mdfile.new_header(title=f"{n}. {QHA[f'q{n}']}", level=4, add_table_of_contents="n")
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if with_hints:
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mdfile.write(f"`{QHA[f'h{n}']}`")
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if with_solutions:
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