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test_sizes_buffer_manager.py
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70 lines (54 loc) · 2.12 KB
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import numpy as np
from numpy import testing as npt
import pytest
from fastplotlib.graphics.features import PointsSizesFeature
from .utils import generate_slice_indices
def generate_data(input_type: str) -> np.ndarray | float:
"""
Point sizes varying with a sine wave
Parameters
----------
input_type: str
one of "sine", "cosine", or "float"
"""
if input_type == "float":
return 10.0
xs = np.linspace(0, 10 * np.pi, 10)
if input_type == "sine":
return np.abs(np.sin(xs)).astype(np.float32)
if input_type == "cosine":
return np.abs(np.cos(xs)).astype(np.float32)
@pytest.mark.parametrize("data", [generate_data(v) for v in ["float", "sine"]])
def test_create_buffer(data):
sizes = PointsSizesFeature(data, n_datapoints=10)
if isinstance(data, float):
npt.assert_almost_equal(sizes[:], generate_data("float"))
elif isinstance(data, np.ndarray):
npt.assert_almost_equal(sizes[:], generate_data("sine"))
@pytest.mark.parametrize(
"slice_method", [generate_slice_indices(i) for i in range(0, 16)]
)
@pytest.mark.parametrize("user_input", ["float", "cosine"])
def test_slice(slice_method: dict, user_input: str):
data = generate_data("sine")
s = slice_method["slice"]
indices = slice_method["indices"]
offset = slice_method["offset"]
size = slice_method["size"]
others = slice_method["others"]
sizes = PointsSizesFeature(data, n_datapoints=10)
match user_input:
case "float":
sizes[s] = 20.0
truth = np.full(len(indices), 20.0)
npt.assert_almost_equal(sizes[s], truth)
npt.assert_almost_equal(sizes[indices], truth)
# make sure other sizes not modified
npt.assert_almost_equal(sizes[others], data[others])
case "cosine":
cosine = generate_data("cosine")
sizes[s] = cosine[s]
npt.assert_almost_equal(sizes[s], cosine[s])
npt.assert_almost_equal(sizes[indices], cosine[s])
# make sure other sizes not modified
npt.assert_almost_equal(sizes[others], data[others])