Added new function for calculating the occupation matrix
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@ -9,10 +9,61 @@ import cmath
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import pandas as pd
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import multiprocessing as mp
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VALID_GEOMETRY = {"cylindrical", "slab"}
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def occupation_matrix(trajectory, edge_length=0.05, segments=1000, skip=0.1, nodes=8):
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frame_indices = np.unique(
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np.int_(np.linspace(len(trajectory) * skip, len(trajectory) - 1, num=segments))
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)
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box = trajectory[0].box
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x_bins = np.arange(0, box[0][0] + edge_length, edge_length)
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y_bins = np.arange(0, box[1][1] + edge_length, edge_length)
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z_bins = np.arange(0, box[2][2] + edge_length, edge_length)
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bins = [x_bins, y_bins, z_bins]
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# Trajectory is split for parallel computing
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size = math.ceil(len(frame_indices) / nodes)
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indices = [
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np.arange(len(frame_indices))[i : i + size]
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for i in range(0, len(frame_indices), size)
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]
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pool = mp.Pool(nodes)
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results = pool.map(
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partial(_calc_histogram, trajectory=trajectory, bins=bins), indices
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)
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pool.close()
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matbin = np.sum(results, axis=0)
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x = (x_bins[:-1] + x_bins[1:]) / 2
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y = (y_bins[:-1] + y_bins[1:]) / 2
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z = (z_bins[:-1] + z_bins[1:]) / 2
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coords = np.array(np.meshgrid(x, y, z, indexing="ij"))
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coords = np.array([x.flatten() for x in coords])
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matbin_new = matbin.flatten()
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occupation_df = pd.DataFrame(
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{"x": coords[0], "y": coords[1], "z": coords[2], "occupation": matbin_new}
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)
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occupation_df = occupation_df.query("occupation != 0")
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return occupation_df
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def _calc_histogram(numberlist, trajectory, bins):
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matbin = None
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for index in range(0, len(numberlist), 1000):
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try:
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indices = numberlist[index : index + 1000]
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except IndexError:
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indices = numberlist[index:]
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frames = np.concatenate(np.array([trajectory.pbc[i] for i in indices]))
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hist, _ = np.histogramdd(frames, bins=bins)
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if matbin is None:
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matbin = hist
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else:
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matbin += hist
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return matbin
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def get_fel(
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traj,
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path,
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@ -9,39 +9,39 @@ from mdevaluate import free_energy_landscape as fel
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@pytest.fixture
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def trajectory(request):
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return mdevaluate.open(os.path.join(os.path.dirname(__file__), 'data/pore'))
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return mdevaluate.open(os.path.join(os.path.dirname(__file__), "data/pore"))
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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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13.162354034697204,
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5.327100985208421,
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9.558746399158396,
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4.116475238453127,
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6.305715728953043,
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3.231102391108276,
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5.896478799115712,
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8.381981206446293,
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5.1191684352849816,
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5.361112857237105,
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8.053932845998895,
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6.895396051256847,
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7.588888886900885,
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11.223429636542576,
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3.779149304024221,
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40.64319010769286,
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93.1120609754045,
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136.99287780099627,
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171.4403749377496,
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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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]
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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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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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@ -51,4 +51,4 @@ def test_get_fel(trajectory):
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overwrite=True,
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)
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assert (energy_differences == test_array).all()
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assert (np.round(energy_differences) == np.round(test_array)).all()
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