https://github.com/saravanabalagi/sampling_utils
Python tools to sample randomly with dont pick closest n elements constraints. Also contains a batch generator for the same to sample with replacement and with repeats if necessary.
https://github.com/saravanabalagi/sampling_utils
conditional-sampling constrained-sampling dont-pick-closest sampling sampling-methods sampling-with-constraints
Last synced: 8 months ago
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Python tools to sample randomly with dont pick closest n elements constraints. Also contains a batch generator for the same to sample with replacement and with repeats if necessary.
- Host: GitHub
- URL: https://github.com/saravanabalagi/sampling_utils
- Owner: saravanabalagi
- License: mit
- Created: 2019-11-22T12:55:53.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-12-02T15:23:39.000Z (about 6 years ago)
- Last Synced: 2025-06-03T15:39:42.848Z (9 months ago)
- Topics: conditional-sampling, constrained-sampling, dont-pick-closest, sampling, sampling-methods, sampling-with-constraints
- Language: Python
- Homepage: https://pypi.org/project/sampling-utils/
- Size: 14.6 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Sampling Utils
Python tools to sample randomly with dont pick closest `n` elements constraints.
Also contains a batch generator for the same to sample with replacement and with repeats if necessary.
## Installation
Simply install using `pip`
```sh
pip install sampling_utils
```
## Usage
### Dont Pick Closest
```python
from sampling_utils import sample_from_list
sample_from_list([1,2,3,4,5,6,7,8], dont_pick_closest=2)
```
You are guaranteed to get samples that are at least `dont_pick_closest` apart# (in value, not in indices).
Here you will get samples where `sample` - `any_other_sample` is always greater than 2.
For example, if 2 is picked, no other item in range [2+`dont_pick_closest` and 2-`dont_pick_closest`] will be picked
Another example looped 5 times:
```python
for _ in range(5):
sample_from_list([1,2,3,4,5,6,8,9,10,12,14], dont_pick_closest=2)
# Output
# [5, 10, 2, 14]
# [9, 6, 14, 1]
# [3, 8, 12]
# [10, 3, 6, 14]
# [2, 5, 8, 12]
```
If 12 is sampled, sampling 10 and 14 are not allowed since `dont_pick_closest` is 2.
In other words, if `n` is sampled, then sampling anything from `[n-dont_pick_closest, ... n-1, n , n+1, ... n+dont_pick_closest]`
is not allowed (if present in the list).
#Will be called as **dont_pick_closest rule** hereafter.
### Number of samples
You can also specify how many samples you want from the list using `number_of_samples` parameter.
By default, you get maximum possible samples (without replacement).
```python
for _ in range(5):
sample_from_list([1,2,3,4,5,6,8,9,10,12,14], dont_pick_closest=2, num_samples=2)
# Output
# [8, 2]
# [6, 3]
# [12, 1]
# [4, 10]
# [9, 1]
```
If you try to sample more than what's possible, you will get an error saying that it's not possible.
### Min and max samples
You may want to just know how much you can sample from a given list obeying the **dont_pick_closest rule**
```python
from sampling_utils import get_min_samples, get_max_samples
print(get_min_samples([1,2,3,4,5,6,8,9,10,12,14], dont_pick_closest=2))
print(get_max_samples([1,2,3,4,5,6,8,9,10,12,14], dont_pick_closest=2))
# Output
# Min 3
# Max 4
```
### Sampling without replacement successively / Generating batches of samples for one epoch
If you want to successively sample without replacement i.e. sample as many samples from the list without repeating,
you can use `batch_rand_generator` as shown below.
This is particularly useful to generate batches of data
until no more batches can be generated (equivalent to one epoch).
```python
from sampling_utils import batch_rand_generator
from sampling_utils import get_batch_generator_elements
batch_size = 2
brg = batch_rand_generator([1,2,3,4,5,6,8,9,10,12,14], batch_size=batch_size, dont_pick_closest=2)
print(get_batch_generator_elements(brg, batch_size=batch_size))
# Output
# [[1, 4], [8, 5], [14, 3], [2, 6]]
```
Notice that the elements
- within each batch obey the **dont_pick_closest rule** _(e.g. 1 and 4 from batch 1)_
- from different batches need not obey the rule _(e.g. 4 and 5 from batch 1 and 2 respectively)._
## Contributing
Pull requests are very welcome.
1. Fork the repo
1. Create new branch with feature name as branch name
1. Check if things work with a jupyter notebook
1. Raise a pull request
## Licence
Please see attached [Licence](LICENCE)