IPKM/mdevaluate
6
1
Fork 0
Code Issues 1 Pull Requests Activity

parse jumps now correctly uses fractional coordinates and should work for triclinic boxes. this should lead to correct behavior in all cases except for maybe changing angles in triclinic boxes. old behavior can still be used

Browse Source
This commit is contained in:
robrobo
2026-04-23 14:34:05 +02:00
parent d97863e356
commit 303bdbf9d2
1 changed files with 36 additions and 19 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/mdevaluate/reader.py
+36 -19
View File
@@ -187,35 +187,52 @@ def nojump_save_filename(reader: BaseReader):
return full_path_fallback
def parse_jumps(trajectory: Coordinates):
prev = trajectory[0].whole
def parse_jumps(trajectory: Coordinates, whole: bool=True, fractional_inverted: bool=True):
if whole:
prev = trajectory[0].whole
else:
prev = trajectory[0]
box = prev.box
if fractional_inverted:
s_prev = prev @ np.linalg.inv(box)
SparseData = namedtuple("SparseData", ["data", "row", "col"])
jump_data = (
SparseData(data=array("b"), row=array("l"), col=array("l")),
SparseData(data=array("b"), row=array("l"), col=array("l")),
SparseData(data=array("b"), row=array("l"), col=array("l")),
)
for i, curr in enumerate(trajectory):
if i % 500 == 0:
logger.debug("Parse jumps Step: %d", i)
r3 = np.subtract(curr, prev)
delta_z = np.array(np.rint(np.divide(r3[:, 2], box[2][2])), dtype=np.int8)
r2 = np.subtract(
r3,
(np.rint(np.divide(r3[:, 2], box[2][2])))[:, np.newaxis]
* box[2][np.newaxis, :],
)
delta_y = np.array(np.rint(np.divide(r2[:, 1], box[1][1])), dtype=np.int8)
r1 = np.subtract(
r2,
(np.rint(np.divide(r2[:, 1], box[1][1])))[:, np.newaxis]
* box[1][np.newaxis, :],
)
delta_x = np.array(np.rint(np.divide(r1[:, 0], box[0][0])), dtype=np.int8)
delta = np.array([delta_x, delta_y, delta_z]).T
prev = curr
box = prev.box
if not fractional_inverted:
r3 = np.subtract(curr, prev)
delta_z = np.array(np.rint(np.divide(r3[:, 2], box[2][2])), dtype=np.int8)
r2 = np.subtract(
r3,
(np.rint(np.divide(r3[:, 2], box[2][2])))[:, np.newaxis]
* box[2][np.newaxis, :],
)
delta_y = np.array(np.rint(np.divide(r2[:, 1], box[1][1])), dtype=np.int8)
r1 = np.subtract(
r2,
(np.rint(np.divide(r2[:, 1], box[1][1])))[:, np.newaxis]
* box[1][np.newaxis, :],
)
delta_x = np.array(np.rint(np.divide(r1[:, 0], box[0][0])), dtype=np.int8)
delta = np.array([delta_x, delta_y, delta_z]).T
prev = curr
box = prev.box
else:
s_curr = curr @ np.linalg.inv(curr.box)
ds = s_curr - s_prev
delta = np.array(np.rint(ds), dtype=np.int8)
s_prev = s_curr
for d in range(3):
(col,) = np.where(delta[:, d] != 0)
jump_data[d].col.extend(col)