.ipynb

Use Built-in Datasets#

ktch includes example datasets for learning and testing. Datasets are divided into two categories: bundled datasets shipped with the package, and remote datasets downloaded on first use.

Available datasets#

Bundled datasets#

These are included in the package and require no extra dependencies.

Function

Type

Description

load_landmark_mosquito_wings

Landmarks

18 landmarks from 127 mosquito wings

load_landmark_trilobite_cephala

Landmarks + Curves

16 landmarks and 4 curves from 301 trilobite cephala

load_outline_mosquito_wings

Outlines

100-point outlines from 126 mosquito wings

load_outline_leaf_bending

Outlines (3D)

200-point 3D outlines from 60 simulated leaves

Remote datasets#

These are downloaded and cached locally on first use. Install the optional data extras first:

pip install ktch[data]

Function

Type

Description

load_image_passiflora_leaves

Images

25 leaf scan images of 10 Passiflora species

Load landmark data#

from ktch.datasets import load_landmark_mosquito_wings

data = load_landmark_mosquito_wings()

print(f"Coordinates shape: {data.coords.shape}")  # (n_specimens * n_landmarks, n_dim)
print(f"Metadata keys: {list(data.meta.keys())}")

Coordinates shape: (2286, 2)
Metadata keys: ['genus']

Load as pandas DataFrame#

data = load_landmark_mosquito_wings(as_frame=True)

print("Coordinates DataFrame:")
print(data.coords.head())

Coordinates DataFrame:
                           x       y
specimen_id coord_id                
1           0        -0.4933  0.0130
            1        -0.0777  0.0832
            2         0.2231  0.0861
            3         0.2641  0.0462
            4         0.2645  0.0261

Load outline data#

from ktch.datasets import load_outline_mosquito_wings

data = load_outline_mosquito_wings()
print(f"Outlines shape: {data.coords.shape}")  # (n_specimens * n_points, n_dim)

Outlines shape: (12600, 2)

Load remote datasets#

Remote datasets support version pinning via the version parameter. When omitted, the default version for the current ktch release is used.

from ktch.datasets import load_image_passiflora_leaves

# Use the default version
data = load_image_passiflora_leaves()

# Pin to a specific version
data = load_image_passiflora_leaves(version="2")

The dataset is downloaded once and cached locally. Subsequent calls load from the cache.

Dataset description#

Each dataset includes a description accessible via data.DESCR:

data = load_landmark_mosquito_wings()
print(data.DESCR[:200] + "...")

Mosquito Wing Landmark Dataset
======================================

...

See also