Import numpy as np from re import Atom, Molecule, crystal from re import subsystem_from_atoms, merge_systems from aphics import display_system # Make water crystal wat = Molecule (), Atom ( 'H', ), Atom ( 'H', )]) water_crystal = crystal (],, 225, cellpar =, # unit cell parameters repetitions = ) # unit cell repetitions in each direction # Make nacl crystal na = Molecule ()]) cl = Molecule ()]) nacl_crystal = crystal (, ],, 225, cellpar =, repetitions = ) water_half = subsystem_from_atoms ( water_crystal, water_crystal. There is also a _bonds() method toĪutomatically set the intramolecular bonds. Supported and setting them will result in an unexpected behaviour. System.bonds bonds between molecules are currently not
System, but the fastest way (in terms of processing time) is toīuild the system by passing ready-made arrays, this is done by using Preallocating and adding molecules is a pretty fast way to build a You can move it around and keep adding it to the System. Since the data is copied, the wat molecule acts as a template so add ( wat ) # data gets copied each time display_system ( s ) rand ( 3 )) # randomly displace the water molecule s. empty ( 4, 12 ) # 4 molecules, 12 atoms for i in range ( 4 ): wat. Import numpy as np from re import Atom, Molecule, System from aphics import display_system # Template molecule wat = Molecule (), Atom ( 'H', ), Atom ( 'H', )]) # Initialize a system with four water molecules. Integers of dimensions (nbonds, 2) where the integer value
#CHEMLAB TSHIRT CODE#
Unnatural, this approach limits side effects and makes the code moreīonds between atoms can be set or retrieved by using the Not reflected in the Molecule and vice-versa. This feature comes at a cost: the data is copied between atomsĪnd molecules, in other words the changes in the costituents atoms are More straightforward integration with C libraries thanks to the numpyĪrrays. The array-based API provides a massive increase in performance and a
dot ( M, r ) # numpy efficient way to do the same: # wat.r_array = np.dot(wat.r_array, M.T) array ()) # slow, readable way for i, r in enumerate ( wat. From import rotation_matrix # The transformation module returns 4x4 matrices M = rotation_matrix ( np.
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