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138 lines
3.9 KiB
Python
138 lines
3.9 KiB
Python
import numpy as np
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import pytest
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from aare import (
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FastPedestal,
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FastPedestal_d,
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FastPedestal_f,
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FastPedestal_i16,
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)
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@pytest.mark.parametrize(
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("dtype", "pedestal_type"),
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[
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(np.float64, FastPedestal_d),
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(np.float32, FastPedestal_f),
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(np.int16, FastPedestal_i16),
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],
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)
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def test_fast_pedestal_factory(dtype, pedestal_type):
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pedestal = FastPedestal(2, 3, n_samples=4, dtype=dtype)
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assert isinstance(pedestal, pedestal_type)
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assert pedestal.rows == 2
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assert pedestal.cols == 3
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assert pedestal.n_samples == 4
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def test_fast_pedestal_factory_defaults_to_double():
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assert isinstance(FastPedestal(2, 3), FastPedestal_d)
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def test_fast_pedestal_factory_rejects_unbound_dtype():
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with pytest.raises(ValueError, match="Unsupported dtype for FastPedestal"):
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FastPedestal(2, 3, dtype=np.int32)
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@pytest.mark.parametrize(
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("kwargs", "expected_n_samples"),
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[
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({"rows": 2, "cols": 3}, 1000),
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({"rows": 2, "cols": 3, "n_samples": 4}, 4),
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],
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)
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def test_fast_pedestal_binding_accepts_constructor_keywords(
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kwargs, expected_n_samples
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):
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pedestal = FastPedestal_d(**kwargs)
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assert pedestal.rows == 2
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assert pedestal.cols == 3
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assert pedestal.n_samples == expected_n_samples
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@pytest.mark.parametrize(
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("dtype", "pedestal_type", "expected_dtype"),
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[
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(np.float64, FastPedestal_d, np.float64),
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(np.float32, FastPedestal_f, np.float32),
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(np.int16, FastPedestal_i16, np.int16),
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],
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)
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def test_fast_pedestal_factory_from_file(
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tmp_path, dtype, pedestal_type, expected_dtype
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):
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frames = np.array(
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[[[100, 100]], [[2, 4]], [[4, 6]], [[5, 7]]], dtype=np.uint16
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)
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filename = tmp_path / "frames.npy"
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np.save(filename, frames)
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pedestal = FastPedestal.from_file(
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filename, n_samples=2, skip_first=1, dtype=dtype
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)
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assert isinstance(pedestal, pedestal_type)
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assert pedestal.ready
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assert pedestal.cur_samples == 2
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assert pedestal.mean().dtype == expected_dtype
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np.testing.assert_array_equal(pedestal.mean(), [[4, 6]])
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def test_fast_pedestal_factory_from_file_rejects_unbound_dtype():
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with pytest.raises(ValueError, match="Unsupported dtype for FastPedestal"):
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FastPedestal.from_file("unused.npy", dtype=np.int32)
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@pytest.mark.parametrize(
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("pedestal_type", "expected_dtype"),
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[(FastPedestal_d, np.float64), (FastPedestal_f, np.float32)],
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)
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def test_fast_pedestal_initialization(pedestal_type, expected_dtype):
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pedestal = pedestal_type(2, 3, 2)
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first = np.array([[2, 4, 6], [8, 10, 12]], dtype=np.uint16)
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second = np.array([[4, 6, 8], [10, 12, 14]], dtype=np.uint16)
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pedestal.push_init(first)
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pedestal.push_init(second)
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expected_mean = np.array(
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[[3, 5, 7], [9, 11, 13]], dtype=expected_dtype
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)
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np.testing.assert_array_equal(pedestal.mean(), expected_mean)
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np.testing.assert_array_equal(pedestal.std(), np.ones((2, 3)))
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def test_fast_pedestal_steady_state_push():
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pedestal = FastPedestal_d(1, 2, 2)
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pedestal.push_init(np.array([[2, 4]], dtype=np.uint16))
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pedestal.push_init(np.array([[4, 6]], dtype=np.uint16))
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pedestal.push(np.array([[6, 8]], dtype=np.uint16))
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np.testing.assert_array_equal(pedestal.mean(), [[4.5, 6.5]])
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def test_fast_pedestal_exposes_read_only_buffer_and_subtraction():
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pedestal = FastPedestal_d(1, 2, 1)
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pedestal.push_init(np.array([[2, 4]], dtype=np.uint16))
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view = np.asarray(pedestal)
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result = np.array([[12, 14]], dtype=np.uint16) - pedestal
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np.testing.assert_array_equal(view, [[2, 4]])
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np.testing.assert_array_equal(result, [[10, 10]])
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assert np.shares_memory(view, pedestal.view())
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assert not view.flags.writeable
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def test_fast_pedestal_rejects_wrong_shape():
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pedestal = FastPedestal_d(2, 3)
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with pytest.raises(RuntimeError, match="shape"):
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pedestal.push_init(np.zeros((2, 2), dtype=np.uint16))
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