Task: Create a "Review: " Issue template

[bmwoodruff]

Description:

We need a new template for reviewing batches of functions that have been processed.

Acceptance Criteria:

• [x] Created a new "Review template"

[bmwoodruff]

Look at https://github.com/possee-org/genai-numpy/issues/54 for ideas for the template.

[bmwoodruff]

Testing a script. This looks like it will work for large groupings.

Group Names:

• [x] Group 1
• [x] Group 2
• [x] Group 3
• [x] Group 4

Group 1	Group 2	Group 3
- [ ] Task 1	- [ ] Task 11	- [ ] Task 21
- [ ] Task 2	- [ ] Task 12	- [ ] Task 22
- [ ] Task 3	- [ ] Task 13	- [ ] Task 23
- [ ] Task 4	- [ ] Task 14	- [ ] Task 24
- [ ] Task 5	- [ ] Task 15	- [ ] Task 25
- [ ] Task 6	- [ ] Task 16	- [ ] Task 26
- [ ] Task 7	- [ ] Task 17	- [ ] Task 27
- [ ] Task 8	- [ ] Task 18	- [ ] Task 28
- [ ] Task 9	- [ ] Task 19	- [ ] Task 29
- [ ] Task 10	- [ ] Task 20	- [ ] Task 30

Group 4
- [ ] Task 31
- [ ] Task 32
- [ ] Task 33
- [ ] Task 34
- [ ] Task 35
- [ ] Task 36
- [ ] Task 37
- [ ] Task 38
- [ ] Task 39
- [ ] Task 40

[bmwoodruff]

Clearly I'll have to remove the - [ ] inside the tables.

[bmwoodruff]

Group Names:

• [x] Group 1
• [x] Group 2
• [ ] Group 3
• [ ] Group 4
• [x] Group 5
• [ ] Group 6
• [x] Group 7
• [ ] Group 8
• [ ] Group 9
• [ ] Group 10
• [ ] Group 11

Group 1	Group 2	Group 3	Group 4	Group 5
allclose	choose	fix_invalid	isMaskedArray	masked_greater
allequal	common_fill_value	flatten_mask	is_mask	masked_greater_equal
alltrue	compressed	flatten_structured_array	is_masked	masked_inside
amax	concatenate	fromflex	isarray	masked_invalid
amin	convolve	getdata	left_shift	masked_less
append	correlate	getmask	make_mask	masked_less_equal
argsort	default_fill_value	getmaskarray	make_mask_descr	masked_not_equal
array	diag	inner	make_mask_none	masked_object
asanyarray	diff	innerproduct	mask_or	masked_outside
asarray	filled	isMA	masked_equal	masked_values

Group 6	Group 7	Group 8	Group 9	Group 10
masked_where	put	sometrue	compress_cols	isin
max	putmask	sort	compress_nd	in1d
maximum_fill_value	reshape	take	compress_rowcols	intersect1d
min	resize	transpose	compress_rows	mask_cols
minimum_fill_value	right_shift	where	count_masked	mask_rowcols
ndim	round	apply_along_axis	cov	mask_rows
outer	round_	apply_over_axes	dot	masked_all
outerproduct	set_fill_value	average	ediff1d	masked_all_like
power	shape	clump_masked	flatnotmasked_contiguous	median
ptp	size	clump_unmasked	flatnotmasked_edges	ndenumerate

Group 11
notmasked_contiguous
notmasked_edges
polyfit
setdiff1d
setxor1d
unique
union1d
vander

[bmwoodruff]

I think the above look manageable.

[bmwoodruff]

This is what I'm thinking about. I wonder if it's too large.

• Claim a group by making a comment below.
• While Nebari is generating examples, spend some time with the functions to see what they do.
• Some of these functions are NOT something we need to add examples to. You'll have to decide that.
• When you've finished the group of 10, check it off.

DELETED OUTPUT to make issue readable.

[bmwoodruff]

There are 61 groups above, without np, and then another 38 from np alone.

I think I can split this into a few tracking files.

1. np alone
2. ma alone
3. polynomial types alone (These should probably be done in groups together.. I'll have to play with it).
4. char and string together (they should be looked at together. Start with string, then char (which will phase out over time).
5. random (I have a feeling the script is missing something).
6. The rest

[bmwoodruff]

We should stardardize how we log the output from Llama 3, and have a log file stored in this repo for the output from Llama 3 for each function we test. Then everything is documented.