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cleanup old code
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@BradyAJohnston
BradyAJohnston committed Nov 25, 2024
1 parent 7223bf7 commit 2699873
Showing 1 changed file with 1 addition and 311 deletions.
312 changes: 1 addition & 311 deletions molecularnodes/entities/trajectory/dna.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,4 @@
from MDAnalysis import Universe
import numpy as np
import bpy
from ... import color
from ...blender import coll, nodes
Expand Down Expand Up @@ -42,9 +41,8 @@ def __init__(self, universe: Universe, world_scale: float = 0.01):

def create_object(
self,
style: str = "vdw",
style: str = "oxdna",
name: str = "NewUniverseObject",
subframes: int = 0,
):
bob = bpyd.create_bob(
name=name,
Expand Down Expand Up @@ -117,311 +115,3 @@ def panel(layout, scene):
col = layout.column(align=True)
col.prop(scene, "MN_import_oxdna_topology")
col.prop(scene, "MN_import_oxdna_trajectory")


# def base_to_int(bases: np.array) -> np.array:
# """
# Convert an array of DNA bases to their corresponding MN integer values.

# Parameters
# ----------
# bases : np.array
# Array of DNA bases.

# Returns
# -------
# np.array
# Array of corresponding integer values for the DNA bases.
# """
# # Values for internal Molecular Nodes use. Defined in data.py
# base_lookup = {"A": 30, "C": 31, "G": 32, "T": 33}

# ints = np.array([base_lookup.get(base, -1) for base in bases])

# return ints


# def is_new_topology(filepath):
# with open(filepath) as f:
# firstline = f.readline()

# return "5 -> 3" in firstline


# def read_topology_new(filepath):
# with open(filepath, "r") as file:
# contents = file.read()

# lines = np.array(contents.split("\n"))

# def read_seq_line(line):
# sequence = line.split(" ")[0]
# return np.array([c for c in sequence])

# strands = []
# counter = 0

# for i, line in enumerate(lines[1:]):
# bases = read_seq_line(line)
# arr = np.zeros((len(bases), 4), dtype=int)
# idx = np.array(range(len(bases)), dtype=int)
# arr[:, 0] = i + 1 # strand ID
# arr[:, 1] = base_to_int(bases) # base
# bond_3 = idx - 1 + counter
# bond_5 = idx + 1 + counter
# bond_3[0] = -1
# bond_5[-1] = -1
# arr[:, 2] = bond_3
# arr[:, 3] = bond_5

# strands.append(arr)
# counter += len(bases)

# return np.vstack(strands)


# def read_topology_old(filepath):
# """
# Read the topology from a file and convert it to a numpy array.


# Strand assignment
# | Base assignment
# | | 3' Bonded base to the current base (index based on row)
# | | | 5' Bonded base to the current base (index based on row)
# | | | |
# S B 3' 5'
# S B 3' 5'
# S B 3' 5'

# Parameters
# ----------
# filepath : str
# The path to the file containing the topology.

# Returns
# -------
# numpy.ndarray
# The topology as a integer numpy array. Base assignment is (30, 31, 32, 33) where
# this corresponds to (A, C, G, T) for use inside of Molecular Nodes.

# """

# with open(filepath, "r") as file:
# contents = file.read()

# lines = np.array(contents.split("\n"))
# # metadata = lines[0]

# # read the topology from the file sans the first metadata line
# # have to initially read as strings, then convert bases to numeric later
# array_str = np.loadtxt(lines[1:], dtype=str)

# # convert the columns to numeric
# array_int = np.zeros(array_str.shape, dtype=int)
# array_int[:, (0, 2, 3)] = array_str[:, (0, 2, 3)].astype(
# int
# ) # easy convert numeric columns to int
# # convert bases (A, C, G, T) to (30, 31, 32, 33)
# array_int[:, 1] = base_to_int(array_str[:, 1])

# return array_int


# def read_trajectory(filepath):
# """
# Read an oxDNA trajectory file and return an array of frames.

# Each frame becomes a 2D array in a stack. Each frame has 5 three-component vectors.
# The vectors are: (position, base_vector, base_normal, veclocity, angular_velocity),
# which totals 15 columns in the array. The (velocity, angular_velocity) are optional
# and can sometimes not appear in the trajectory.

# Parameters
# ----------
# filepath : str
# The path to the trajectory file.

# Returns
# -------
# frames : ndarray
# An array of frames, where each frame is a 2D array of positions

# """
# # Open the file and read its contents
# with open(filepath, "r") as file:
# contents = file.read()

# # Split the contents into lines
# lines = np.array(contents.split("\n"))
# is_meta = np.char.find(lines, "=") > 0

# group_id = np.cumsum(np.append([True], np.diff(is_meta)))
# groups = np.unique(group_id)

# frames = []

# for group in groups:
# mask = group == group_id
# if "=" in lines[mask][0]:
# continue

# arr = np.loadtxt(lines[mask])
# frames.append(arr)

# return np.stack(frames)


# def store_named_attributes_to_dna_mol(obj, frame, scale_dna=0.1):
# attributes = ("base_vector", "base_normal", "velocity", "angular_velocity")
# for i, att in enumerate(attributes):
# col_idx = np.array([3, 4, 5]) + i * 3

# try:
# data = frame[:, col_idx]
# except IndexError as e:
# print(f"Unable to get {att} attribute from coordinates. Error: {e}")
# continue

# if att != "angular_velocity":
# data *= scale_dna

# bpyd.store_named_attribute(
# obj=obj, data=data, name=att, atype=AttributeTypes.FLOAT_VECTOR
# )


# def toplogy_to_bond_idx_pairs(topology: np.ndarray):
# """
# Convert the given topology array into pairs of indices representing each distinct bond.

# Strand assignment
# | Base assignment
# | | 3' Bonded base to the current base (index based on row)
# | | | 5' Bonded base to the current base (index based on row)
# | | | |
# 1 A -1 1
# 1 G 0 2
# 1 C 1 -1

# The topology above becomes:
# np.array([[0, 1], [2, 1]])

# The order of the bond indices doesn't matter to Blender.

# Parameters:
# topology (np.ndarray): Numeric numpy array representing the topology.

# Returns:
# np.ndarray: Array of pairs of indices representing each distinct bond.
# """

# # to get pairs of indices which represent each distinct bond, which are needed for
# # edge creation in Blender, take each bonded column and create a 'bond' with itself
# idx = np.array(list(range(topology.shape[0])))
# bond_3 = np.vstack((idx, topology[:, 2])).reshape((len(idx), 2))
# bond_5 = np.vstack((idx, topology[:, 3])).reshape((len(idx), 2))
# bonds = np.vstack((bond_3, bond_5))

# # drop where either bond is -1 (not bonded) from the bond indices
# mask = bonds == -1
# mask = np.logical_not(mask.any(axis=1))

# bond_idxs = np.unique(bonds[mask, :], axis=0)

# return np.sort(bond_idxs, axis=1)


# def load(top, traj, name="oxDNA", setup_nodes=True, world_scale=0.01):
# # the scale of the oxDNA files seems to be based on nanometres rather than angstrongs
# # like most structural biology files, so currently adjusting the world_scale to
# # compensate
# scale_dna = world_scale * 10

# # read in the topology and trajectory files
# is_new_top = is_new_topology(top)
# if is_new_top:
# topology = read_topology_new(top)
# else:
# topology = read_topology_old(top)

# trajectory = read_trajectory(traj)
# n_frames = trajectory.shape[0]

# # creat toplogy object with positions of the first frame, and the bonds from the
# # topology object
# obj = bpyd.create_object(
# name=name,
# collection=coll.mn(),
# vertices=trajectory[0][:, 0:3] * scale_dna,
# edges=toplogy_to_bond_idx_pairs(topology),
# )

# # adding additional toplogy information from the topology and frames objects
# bpyd.store_named_attribute(
# obj=obj, data=topology[:, 1], name="res_name", atype=AttributeTypes.INT
# )
# bpyd.store_named_attribute(
# obj=obj, data=topology[:, 0], name="chain_id", atype=AttributeTypes.INT
# )
# bpyd.store_named_attribute(
# obj=obj,
# data=color.color_chains_equidistant(topology[:, 0]),
# name="Color",
# atype=AttributeTypes.FLOAT_COLOR,
# )
# store_named_attributes_to_dna_mol(obj, trajectory[0], scale_dna=scale_dna)

# # if the 'frames' file only contained one timepoint, return the object without creating
# # any kind of collection for storing multiple frames from a trajectory, and a None
# # object in place of the frames collection
# if n_frames == 1:
# if setup_nodes:
# nodes.create_starting_node_tree(obj, style="oxdna", color=None)
# return obj, None

# # create a collection to store all of the frame objects that are part of the trajectory
# # they will contain all of the possible attributes which can be interpolated betewen
# # frames such as position, base_vector, base_normal, velocity, angular_velocity
# collection = coll.frames(name)
# for i, frame in enumerate(trajectory):
# fill_n = int(np.ceil(np.log10(n_frames)))
# frame_name = f"{name}_frame_{str(i).zfill(fill_n)}"
# frame_obj = bpyd.create_object(
# frame[:, 0:3] * scale_dna, name=frame_name, collection=collection
# )
# store_named_attributes_to_dna_mol(frame_obj, frame, scale_dna)

# if setup_nodes:
# nodes.create_starting_node_tree(
# obj, coll_frames=collection, style="oxdna", color=None
# )

# return obj, collection


# class MN_OT_Import_OxDNA_Trajectory(bpy.types.Operator):
# bl_idname = "mn.import_oxdna"
# bl_label = "Load"
# bl_description = "Will import the given file and toplogy."
# bl_options = {"REGISTER"}

# def execute(self, context):
# s = context.scene
# load(
# top=s.MN_import_oxdna_topology,
# traj=s.MN_import_oxdna_trajectory,
# name=s.MN_import_oxdna_name,
# )
# return {"FINISHED"}


# def panel(layout, scene):
# layout.label(text="Load oxDNA File", icon="FILE_TICK")
# layout.separator()
# row = layout.row()
# row.prop(scene, "MN_import_oxdna_name")
# row.operator("mn.import_oxdna")
# col = layout.column(align=True)
# col.prop(scene, "MN_import_oxdna_topology")
# col.prop(scene, "MN_import_oxdna_trajectory")

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