Adjusted tests
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@ -4,7 +4,7 @@ import pytest
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import numpy as np
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import mdevaluate
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from mdevaluate import free_energy_landscape as fel
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import mdevaluate.extra.free_energy_landscape as fel
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@pytest.fixture
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@ -15,40 +15,40 @@ def trajectory(request):
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def test_get_fel(trajectory):
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test_array = np.array(
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[
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0.0,
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12.87438176,
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4.95868203,
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11.02055197,
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5.44195534,
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6.73933442,
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3.30971789,
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6.10424055,
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8.56153733,
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5.45777331,
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5.64545817,
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8.42100423,
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6.28132121,
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7.4777172,
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11.64839354,
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4.52566354,
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40.84730838,
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93.86241602,
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140.3039937,
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173.55970021,
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174.46253634,
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174.60905476,
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178.57658092,
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182.43001192,
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180.57916378,
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176.49886217,
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178.96018547,
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181.13561782,
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178.31026314,
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176.08903996,
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180.71215345,
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181.59703135,
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180.34329368,
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187.02474488,
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197.99167477,
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214.05788031,
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245.58571282,
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287.52457507,
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331.53492965,
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]
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)
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oxygens_water = trajectory.subset(atom_name="OW", residue_name="SOL")
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r, energy_differences = fel.get_fel(
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oxygens_water,
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os.path.join(os.path.dirname(__file__), "data/pore"),
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"cylindrical",
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225,
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edge=0.05,
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radiusmin=0.05,
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radiusmax=2.05,
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z=[-np.inf, np.inf],
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overwrite=True,
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)
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OW = trajectory.subset(atom_name="OW")
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assert (np.round(energy_differences) == np.round(test_array)).all()
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box = np.diag(trajectory[0].box)
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box_voxels = (box // [0.05, 0.05, 0.05] + [1, 1, 1]) * [0.05, 0.05, 0.05]
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occupation_matrix = fel.occupation_matrix(OW, skip=0, segments=1000)
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maxima_matrix = fel.find_maxima(occupation_matrix, box=box_voxels, edge_length=0.05)
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maxima_matrix = fel.add_distances(maxima_matrix, "cylindrical", box / 2)
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r_bins = np.arange(0, 2, 0.02)
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distance_bins = np.arange(0.05, 2.05, 0.1)
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energy_df = fel.distance_resolved_energies(
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maxima_matrix, distance_bins, r_bins, box, 225
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)
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result = fel.find_energy_maxima(energy_df, r_min=0.05, r_max=0.15)
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assert (np.round(np.array(result["energy"])) == np.round(test_array)).all()
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@ -31,16 +31,3 @@ def test_filon_fourier_transformation(logdata):
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xdata, xdata, frequencies=freqs, derivative='linear', imag=False
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)
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assert np.isclose(filon_imag.real, filon_real).all()
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def test_histogram():
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data = np.random.rand(100)
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bins = np.linspace(0, 1)
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np_hist = np.histogram(data, bins=bins)[0]
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ut_hist = utils.histogram(data, bins=bins)[0]
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assert (np_hist == ut_hist).all()
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bins = np.linspace(0.3, 1.5)
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np_hist = np.histogram(data, bins=bins)[0]
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ut_hist = utils.histogram(data, bins=bins)[0]
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assert (np_hist == ut_hist).all()
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