Ejemplo n.º 1
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 def test_invalid_readers_in_frag_traj(self):
     data = [np.array([[[1, 2], [3, 4]], [0, 1]])]
     from pyemma.coordinates.data.fragmented_trajectory_reader import FragmentedTrajectoryReader
     reader = FragmentedTrajectoryReader(data)
     with self.assertRaises(ValueError) as cm:
         save_traj(reader, self.sets, None)
     self.assertIn("FeatureReader", cm.exception.args[0])
Ejemplo n.º 2
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 def test_invalid_maximum_traj_index(self):
     frag_traj = [[self.trajfiles[0], self.trajfiles[1]], self.trajfiles[2],
                  self.trajfiles[2]]
     set = [[0, 2], [0, 1], [2, 42]]
     from pyemma.coordinates.data.fragmented_trajectory_reader import FragmentedTrajectoryReader
     reader = FragmentedTrajectoryReader(frag_traj,
                                         topologyfile=self.pdbfile)
     with self.assertRaises(ValueError) as cm:
         save_traj(reader, set, None)
     self.assertIn("larger than", cm.exception.args[0])
Ejemplo n.º 3
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    def test_list_input_save_correct_frames_disk(self):

        save_traj(self.trajfiles, self.sets, self.outfile, top=self.pdbfile)

        # Reload the object to memory
        traj = md.load(self.outfile, top=self.pdbfile)

        # Check for diffs
        (found_diff,
         errmsg) = compare_coords_md_trajectory_objects(traj,
                                                        self.traj_ref,
                                                        atom=0)

        self.assertFalse(found_diff, errmsg)
Ejemplo n.º 4
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    def test_reader_input_save_correct_frames_with_stride_in_memory(self):
        # With the inmemory option = True

        for stride in self.strides[:]:
            # Since none of the trajfiles have more than 30 frames, the frames have to be re-drawn for every stride
            sets = np.copy(self.sets)
            sets[0][:, 1] = np.random.randint(0,
                                              high=30 / stride,
                                              size=np.shape(sets[0])[0])
            sets[1][:, 1] = np.random.randint(0,
                                              high=30 / stride,
                                              size=np.shape(sets[1])[0])

            traj = save_traj(self.reader,
                             sets,
                             None,
                             stride=stride,
                             verbose=False)

            # Also the reference has to be re-drawn using the stride. For this, we use the re-scale the strided
            # frame-indexes to the unstrided value
            sets[0][:, 1] *= stride
            sets[1][:, 1] *= stride
            traj_ref = save_traj_w_md_load_frame(self.reader, sets)

            # Check for diffs
            (found_diff,
             errmsg) = compare_coords_md_trajectory_objects(traj,
                                                            traj_ref,
                                                            atom=0)
            self.assertFalse(found_diff, errmsg)
Ejemplo n.º 5
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    def test_list_input_save_correct_frames_mem(self):

        # Keep object in memory
        traj = save_traj(self.trajfiles, self.sets, None, top=self.pdbfile)

        # Check for diffs
        (found_diff,
         errmsg) = compare_coords_md_trajectory_objects(traj,
                                                        self.traj_ref,
                                                        atom=0)

        self.assertFalse(found_diff, errmsg)
Ejemplo n.º 6
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    def test_with_fragmented_reader(self):
        # intenionally group bpti dataset to a fake fragmented traj
        frag_traj = [[self.trajfiles[0], self.trajfiles[1]], self.trajfiles[2]]
        reader = coor.source(frag_traj, top=self.pdbfile)

        traj = save_traj(reader, self.sets, None)
        traj_ref = save_traj_w_md_load_frame(self.reader, self.sets)

        # Check for diffs
        (found_diff, errmsg) = compare_coords_md_trajectory_objects(traj,
                                                                    traj_ref,
                                                                    atom=0)
        self.assertFalse(found_diff, errmsg)
Ejemplo n.º 7
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    def test_with_fragmented_reader_chunksize_0(self):
        # intentionally group bpti dataset to a fake fragmented traj
        frag_traj = [[self.trajfiles[0], self.trajfiles[1]], self.trajfiles[2],
                     self.trajfiles[2]]
        reader = coor.source(frag_traj, top=self.pdbfile, chunk_size=0)
        assert reader.chunksize == 0
        traj = save_traj(reader, self.sets, None)
        traj_ref = save_traj_w_md_load_frame(self.reader, self.sets)
        # Check for diffs
        (found_diff, errmsg) = compare_coords_md_trajectory_objects(traj,
                                                                    traj_ref,
                                                                    atom=0)

        np.testing.assert_equal(traj.xyz, traj_ref.xyz)
        self.assertFalse(found_diff, errmsg)
Ejemplo n.º 8
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    def test_with_fragmented_reader(self):
        from pyemma.util.files import TemporaryDirectory
        trajlen = 35
        # trajectory 0 (first trajectory, is trajfiles[2])
        #   -> skipped
        # trajectory 1 (second trajectory, is {trajfiles[0], trajfiles[1]})
        #   fragment 1:
        #       -> frames 0,1,2,10
        #   fragment 2:
        #       -> frames 1 (i.e., 36) and 34 (i.e., 69)
        # trajectory 2 (third trajectory, is trajfiles[2])
        #   -> frame 5
        ra_indices = np.array([[1, 0], [1, 1], [1, 2], [1, 10],
                               [1, trajlen + 1], [1, 2 * trajlen - 1], [2, 5]],
                              dtype=int)
        with TemporaryDirectory() as td:

            trajfiles = []
            xyzs = []
            for i in range(3):
                tf, xyz, _ = create_traj(start=i * 10, dir=td, length=trajlen)
                trajfiles.append(tf)
                xyzs.append(xyz)

            topfile = get_top()
            frag_traj = [
                trajfiles[2], [trajfiles[0], trajfiles[1]], trajfiles[2]
            ]

            expected = xyzs[0][np.array([0, 1, 2, 10]), :], xyzs[1][np.array(
                [1, 34])], np.array([(xyzs[2][5, :])])
            expected = np.vstack(expected)

            reader = coor.source(frag_traj, top=topfile)

            for cs in range(1, 10):
                traj = save_traj(reader, ra_indices, None, chunksize=cs)
                np.testing.assert_almost_equal(traj.xyz, expected)
Ejemplo n.º 9
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 def test_list_input_save_IO(self):
     # Test that we're saving to disk alright
     save_traj(self.trajfiles, self.sets, self.outfile, top=self.pdbfile)
     exist = os.stat(self.outfile)
     self.assertTrue(exist, "Could not write to disk")
Ejemplo n.º 10
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 def test_reader_input_returns_trajectory(self):
     self.assertTrue(
         isinstance(save_traj(self.reader, self.sets, None), md.Trajectory))
Ejemplo n.º 11
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 def test_reader_input_save_IO(self):
     # Test that we're saving to disk alright
     save_traj(self.reader, self.sets, self.outfile)
     exist = os.stat(self.outfile)
     self.assertTrue(exist, "Could not write to disk")
Ejemplo n.º 12
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 def test_list_input_returns_trajectory(self):
     self.assertTrue(
         isinstance(
             save_traj(self.trajfiles, self.sets, None, top=self.pdbfile),
             md.Trajectory))
Ejemplo n.º 13
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 def test_reader_input_returns_trajectory_w_image_molecules(self):
     self.assertTrue(
         isinstance(
             save_traj(self.reader, self.sets, None, image_molecules=True),
             md.Trajectory))