✨ new interface

[jvdd]

In this PR we transfer from pandas.Series as representation for time series to a purely np.ndarray based representation
(pandas.Series its index can at this time not represent most numeric dtypes, e.g. int16)

The signature for the downsample methdod is changed to:

downsample([x], y, n_out, **kwargs)

Note the following:

• x is optional, allowing the same (memory) efficient runtime as with pd.RangeIndex
• x and y are both positional arguments (this is in line with how the matplotlib,pyplot.plot signature is)
• n_out is a mandatory keyword argument

Example:

from tsdownsample import MinMaxLTTBDownsampler
import numpy as np

# Create a time series
y = np.random.randn(10_000_000)

# Downsample to 1000 points
s_ds = MinMaxLTTBDownsampler().downsample(y, n_out=1000)

---

Other aspects of this PR

• support x and y datetime64: view the array as np.int64
• support x and y timedelta64: view the array as np.int64
• support y bool: view the array as np.int8 (under the hood numpy represents a bool as 8 bits)
• support y int8 & uint8
• support categorical data => out of scope for this PR, would mostly be some Python code converting it to an encoding (which is perhaps not the responsibility of this library...) - also not really sure how numpy would represent categorical data

Major TODOs:

• documentation 📒 => will leave this for another PR
• do not assume fixed sampling rate => will leave this for another PR

[jonasvdd]

I find it a little cleaner to import the concrete methods/variables in tsdownsample/__init__.py than applying from .downsamplers import *

[jonasvdd]

LGTM, see those comments!

[jvdd]

Will merge this if you approve @jonasvdd & then I can make first real release! 🚀

Besides documentation, the (afaik) only major TODO is getting rid of the assumption of fixed sampling rate 🤔

[jonasvdd]

Has this been checked? @jvdd

[jvdd]

Not yet, but will leave this to another PR (that thoroughly profiles the code)

[jonasvdd]

🔝

[jonasvdd]

Could you just provide me with an answer to the questions? If these are resolved. I think this PR is ready to merge!

Impressive work 💪🏼

[jvdd]

Will merge this if you approve @jonasvdd & then I can make first real release! rocket

Besides documentation, the (afaik) only major TODO is getting rid of the assumption of fixed sampling rate thinking

Guess we won't make a first real release yet as the distribution is not 100% watertight (see #9)

[jonasvdd]

@jvdd, I think we can tackle the M2 building in a new PR and merge this one? 🙏🏼

[jvdd]

Ready to squash and merge 🚀