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[numpy, scipy] Edits and Corrections #122

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Merged
mmcky merged 9 commits into from
Sep 20, 2021
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[numpy, scipy] Edits and Corrections #122

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cd59cd9
[numba] trial, please ignore
Jan 14, 2021
7dbc29c
[numba] typo
Jan 14, 2021
76a3c3d
[scipy] add usful feature of Numpy comparing to other libraries
Jan 15, 2021
b6cfffd
[numpy] 11.8 Recursion
Jan 15, 2021
0dd8919
[scipy] Recursion
Jan 15, 2021
bb56dd0
[scipy] ammended previous PR
Jan 16, 2021
23cddf2
remove Chapter 16
mmcky Sep 20, 2021
385f8de
Merge branch 'main' into horace
mmcky Sep 20, 2021
bc8998e
Update scipy.md
jstac Sep 20, 2021
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2 changes: 1 addition & 1 deletion lectures/numba.md
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Expand Up @@ -555,7 +555,7 @@ Now let's see how fast it runs:
%time calculate_pi()
```

If we switch of JIT compilation by removing `@njit`, the code takes around
If we switch off JIT compilation by removing `@njit`, the code takes around
150 times as long on our machine.

So we get a speed gain of 2 orders of magnitude--which is huge--by adding four
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5 changes: 3 additions & 2 deletions lectures/scipy.md
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Expand Up @@ -63,7 +63,8 @@ from numpy.fft import fft, ifft
from numpy.lib.scimath import *
```

However, it's more common and better practice to use NumPy functionality explicitly
However, it's more common and better practice to use NumPy functionality explicitly.


```{code-cell} python3
import numpy as np
Expand Down Expand Up @@ -442,7 +443,7 @@ We leave you to investigate the [set of available routines](http://docs.scipy.or
(sp_ex1)=
### Exercise 1

Previously we discussed the concept of {ref}`recursive function calls <recursive_functions>`.
In {ref}`this lecture <python_advanced_features>`, we will discuss the concept of {ref}`recursive function calls <recursive_functions>`.

Try to write a recursive implementation of homemade bisection function {ref}`described above <bisect_func>`.

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