From 3fefcc4906a2f35ab30cf7ecb5a3cb7866a51019 Mon Sep 17 00:00:00 2001
From: pinyili2 <pinyili2@illinois.edu>
Date: Sun, 4 Aug 2024 17:29:14 -0500
Subject: [PATCH] a
---
.../.ipynb_checkpoints/__init__-checkpoint.py | 39 -
.../cadnano_segments-checkpoint.py | 727 ------------
.../segmentmodel_from_lists-checkpoint.py | 495 --------
...egmentmodel_from_oxdna_pinyi-checkpoint.py | 162 ---
.../.ipynb_checkpoints/test-checkpoint.ipynb | 1053 +++++++++++++++--
.../readers/.segmentmodel_from_cadnano.py.swp | Bin 0 -> 16384 bytes
mrdna/readers/cadnano_segments.py | 319 ++---
mrdna/readers/libs | 1 +
mrdna/readers/list.pdb | 14 +-
mrdna/readers/list.psf | 20 +-
mrdna/readers/test.ipynb | 1053 +++++++++++++++--
mrdna/readers/test.json.oxdna | 418 +++++++
mrdna/readers/test.json.top | 416 +++++++
mrdna/readers/test.virt2nuc | Bin 0 -> 6565 bytes
mrdna/readers/test2.ipynb | 973 +++++++++++++++
15 files changed, 3891 insertions(+), 1799 deletions(-)
delete mode 100644 mrdna/readers/.ipynb_checkpoints/__init__-checkpoint.py
delete mode 100644 mrdna/readers/.ipynb_checkpoints/cadnano_segments-checkpoint.py
delete mode 100644 mrdna/readers/.ipynb_checkpoints/segmentmodel_from_lists-checkpoint.py
delete mode 100644 mrdna/readers/.ipynb_checkpoints/segmentmodel_from_oxdna_pinyi-checkpoint.py
create mode 100644 mrdna/readers/.segmentmodel_from_cadnano.py.swp
create mode 120000 mrdna/readers/libs
create mode 100644 mrdna/readers/test.json.oxdna
create mode 100644 mrdna/readers/test.json.top
create mode 100644 mrdna/readers/test.virt2nuc
create mode 100644 mrdna/readers/test2.ipynb
diff --git a/mrdna/readers/.ipynb_checkpoints/__init__-checkpoint.py b/mrdna/readers/.ipynb_checkpoints/__init__-checkpoint.py
deleted file mode 100644
index 7e0e4db..0000000
--- a/mrdna/readers/.ipynb_checkpoints/__init__-checkpoint.py
+++ /dev/null
@@ -1,39 +0,0 @@
-## TODO: make module this package conform to a single style for input/output
-
-def read_cadnano(json_file, sequence=None, fill_sequence='T', **model_parameters):
- from .cadnano_segments import read_json_file
- from .cadnano_segments import read_model as model_from_cadnano_json
-
- data = read_json_file(json_file)
- return model_from_cadnano_json(data, sequence, fill_sequence, **model_parameters)
-
-def read_vhelix(maya_file, **model_parameters):
- from .polygon_mesh import parse_maya_file, convert_maya_bases_to_segment_model
-
- maya_bases = parse_maya_file(maya_file)
- model = convert_maya_bases_to_segment_model( maya_bases, **model_parameters )
- return model
-
-def read_list(infile,**model_parameters):
- import numpy as np
- try:
- data = np.loadtxt(infile)
- except:
- data = np.loadtxt(infile,skiprows=1) # strip header
- coords = data[:,:3]*10
- bp = data[:,3]
- stack = data[:,4]
- three_prime = data[:,5]
-
- from .segmentmodel_from_lists import model_from_basepair_stack_3prime
- return model_from_basepair_stack_3prime(coords, bp, stack, three_prime)
-
-
-def read_atomic_pdb(pdb_file, **model_parameters):
- from .segmentmodel_from_pdb import SegmentModelFromPdb
- return SegmentModelFromPdb(pdb_file)
-
-def read_oxdna(coordinate_file, topology_file, idealized_coordinate_file=None, **model_parameters):
- """ Idealized coordinate file: coordinates for detecting stacks and base pairs, defaults to coordinate_file """
- from .segmentmodel_from_oxdna import mrdna_model_from_oxdna
- return mrdna_model_from_oxdna(coordinate_file, topology_file, idealized_coordinate_file, **model_parameters)
diff --git a/mrdna/readers/.ipynb_checkpoints/cadnano_segments-checkpoint.py b/mrdna/readers/.ipynb_checkpoints/cadnano_segments-checkpoint.py
deleted file mode 100644
index b39bd2e..0000000
--- a/mrdna/readers/.ipynb_checkpoints/cadnano_segments-checkpoint.py
+++ /dev/null
@@ -1,727 +0,0 @@
-# -*- coding: utf-8 -*-
-import pdb
-import numpy as np
-import os,sys
-from glob import glob
-import re
-
-from ..arbdmodel.coords import readArbdCoords, readAvgArbdCoords, rotationAboutAxis
-from ..segmentmodel import SegmentModel, SingleStrandedSegment, DoubleStrandedSegment
-from ..model.dna_sequence import m13 as m13seq
-
-
-## TODO: separate SegmentModel from ArbdModel so multiple parts can be combined
-## TODO: catch circular strands in "get_5prime" cadnano calls
-## TODO: handle special motifs
-## - doubly-nicked helices
-## - helices that should be stacked across an empty region (crossovers from and end in the helix to another end in the helix)
-## - circular constructs
-
-def combineRegionLists(loHi1,loHi2,intersect=False):
-
- """Combines two lists of (lo,hi) pairs specifying integer
- regions a single list of regions. """
-
- ## Validate input
- for l in (loHi1,loHi2):
- ## Assert each region in lists is sorted
- for pair in l:
- assert(len(pair) == 2)
- assert(pair[0] <= pair[1])
-
- if len(loHi1) == 0:
- if intersect:
- return []
- else:
- return loHi2
- if len(loHi2) == 0:
- if intersect:
- return []
- else:
- return loHi1
-
- ## Break input into lists of compact regions
- compactRegions1,compactRegions2 = [[],[]]
- for compactRegions,loHi in zip(
- [compactRegions1,compactRegions2],
- [loHi1,loHi2]):
- tmp = []
- lastHi = loHi[0][0]-1
- for lo,hi in loHi:
- if lo-1 != lastHi:
- compactRegions.append(tmp)
- tmp = []
- tmp.append((lo,hi))
- lastHi = hi
- if len(tmp) > 0:
- compactRegions.append(tmp)
-
- ## Build result
- result = []
- region = []
- i,j = [0,0]
- compactRegions1.append([[1e10]])
- compactRegions2.append([[1e10]])
- while i < len(compactRegions1)-1 or j < len(compactRegions2)-1:
- cr1 = compactRegions1[i]
- cr2 = compactRegions2[j]
-
- ## initialize region
- if len(region) == 0:
- if cr1[0][0] <= cr2[0][0]:
- region = cr1
- i += 1
- continue
- else:
- region = cr2
- j += 1
- continue
-
- if region[-1][-1] >= cr1[0][0]:
- region = combineCompactRegionLists(region, cr1, intersect=False)
- i+=1
- elif region[-1][-1] >= cr2[0][0]:
- region = combineCompactRegionLists(region, cr2, intersect=False)
- j+=1
- else:
- result.extend(region)
- region = []
-
- assert( len(region) > 0 )
- result.extend(region)
- result = sorted(result)
-
- # print("loHi1:",loHi1)
- # print("loHi2:",loHi2)
- # print(result,"\n")
-
- if intersect:
- lo = max( [loHi1[0][0], loHi2[0][0]] )
- hi = min( [loHi1[-1][1], loHi2[-1][1]] )
- result = [r for r in result if r[0] >= lo and r[1] <= hi]
-
- return result
-
-def combineCompactRegionLists(loHi1,loHi2,intersect=False):
-
- """Combines two lists of (lo,hi) pairs specifying regions within a
- compact integer set into a single list of regions.
-
- examples:
- loHi1 = [[0,4],[5,7]]
- loHi2 = [[2,4],[5,9]]
- out = [(0, 1), (2, 4), (5, 7), (8, 9)]
-
- loHi1 = [[0,3],[5,7]]
- loHi2 = [[2,4],[5,9]]
- out = [(0, 1), (2, 3), (4, 4), (5, 7), (8, 9)]
- """
-
- ## Validate input
- for l in (loHi1,loHi2):
- ## Assert each region in lists is sorted
- for pair in l:
- assert(len(pair) == 2)
- assert(pair[0] <= pair[1])
- ## Assert lists are compact
- for pair1,pair2 in zip(l[::2],l[1::2]):
- assert(pair1[1]+1 == pair2[0])
-
- if len(loHi1) == 0:
- if intersect:
- return []
- else:
- return loHi2
- if len(loHi2) == 0:
- if intersect:
- return []
- else:
- return loHi1
-
- ## Find the ends of the region
- lo = min( [loHi1[0][0], loHi2[0][0]] )
- hi = max( [loHi1[-1][1], loHi2[-1][1]] )
-
- ## Make a list of indices where each region will be split
- splitAfter = []
- for l,h in loHi2:
- if l != lo:
- splitAfter.append(l-1)
- if h != hi:
- splitAfter.append(h)
-
- for l,h in loHi1:
- if l != lo:
- splitAfter.append(l-1)
- if h != hi:
- splitAfter.append(h)
- splitAfter = sorted(list(set(splitAfter)))
-
- # print("splitAfter:",splitAfter)
-
- split=[]
- last = -2
- for s in splitAfter:
- split.append(s)
- last = s
-
- # print("split:",split)
- returnList = [(i+1,j) if i != j else (i,j) for i,j in zip([lo-1]+split,split+[hi])]
-
- if intersect:
- lo = max( [loHi1[0][0], loHi2[0][0]] )
- hi = min( [loHi1[-1][1], loHi2[-1][1]] )
- returnList = [r for r in returnList if r[0] >= lo and r[1] <= hi]
-
- # print("loHi1:",loHi1)
- # print("loHi2:",loHi2)
- # print(returnList,"\n")
- return returnList
-
-class cadnano_part(SegmentModel):
- def __init__(self, part,
- **kwargs
- ):
- self.part = part
- self.lattice_type = _get_lattice(part)
-
- self._cadnano_part_to_segments(part)
- # SegmentModel.__init__(self,...)
- # self.segments = [seg for hid,segs in self.helices.items() for seg in segs]
- self.segments = [seg for hid,segs in sorted(self.helices.items()) for seg in segs]
- self._add_intrahelical_connections()
- self._add_crossovers()
- self._add_prime_ends()
- SegmentModel.__init__(self, self.segments,
- **kwargs)
-
- def _get_helix_angle(self, helix_id, indices):
- """ Get "start_orientation" for helix """
- # import ipdb
- # ipdb.set_trace()
-
- """ FROM CADNANO2.5
- + angle is CCW
- - angle is CW
- Right handed DNA rotates clockwise from 5' to 3'
- we use the convention the 5' end starts at 0 degrees
- and it's pair is minor_groove_angle degrees away
- direction, hence the minus signs. eulerZ
- """
-
- hp, bpr, tpr, eulerZ, mgroove = self.part.vh_properties.loc[helix_id,
- ['helical_pitch',
- 'bases_per_repeat',
- 'turns_per_repeat',
- 'eulerZ',
- 'minor_groove_angle']]
- twist_per_base = tpr*360./bpr
- # angle = eulerZ - twist_per_base*indices + 0.5*mgroove + 180
- angle = eulerZ + twist_per_base*indices - 0.5*mgroove
- return angle
-
- def _cadnano_part_to_segments(self,part):
- try:
- from cadnano.cnenum import PointType
- except:
- try:
- from cadnano.proxies.cnenum import PointType
- except:
- from cadnano.proxies.cnenum import PointEnum as PointType
-
- segments = dict()
- self.helices = helices = dict()
- self.helix_ranges = helix_ranges = dict()
-
- props = part.getModelProperties().copy()
-
- if props.get('point_type') == PointType.ARBITRARY:
- # TODO add code to encode Parts with ARBITRARY point configurations
- raise NotImplementedError("Not implemented")
- else:
- try:
- vh_props, origins = part.helixPropertiesAndOrigins()
- except:
- origins = {hid:part.getVirtualHelixOrigin(hid)[:2] for hid in part.getidNums()}
-
- self.origins = origins
-
- vh_list = []
- strand_list = []
- xover_list = []
- self.xovers_from = dict()
- self.xovers_to = dict()
-
- try:
- numHID = part.getMaxIdNum() + 1
- except:
- numHID = part.getIdNumMax() + 1
-
- for id_num in range(numHID):
- try:
- offset_and_size = part.getOffsetAndSize(id_num)
- except:
- offset_and_size = None
- if offset_and_size is None:
- ## Add a placeholder for empty helix
- vh_list.append((id_num, 0))
- strand_list.append(None)
- else:
- offset, size = offset_and_size
- vh_list.append((id_num, size))
- fwd_ss, rev_ss = part.getStrandSets(id_num)
- fwd_idxs, fwd_colors = fwd_ss.dump(xover_list)
- rev_idxs, rev_colors = rev_ss.dump(xover_list)
- strand_list.append((fwd_idxs, rev_idxs))
-
- self.xovers_from[id_num] = []
- self.xovers_to[id_num] = []
-
- for xo in xover_list:
- h1,f1,z1,h2,f2,z2 = xo
- self.xovers_from[h1].append(xo)
- self.xovers_to[h2].append(xo)
-
- ## Get lists of 5/3prime ends
- strands5 = [o.strand5p() for o in part.oligos()]
- strands3 = [o.strand3p() for o in part.oligos()]
-
- self._5prime_list = [(s.idNum(),s.isForward(),s.idx5Prime()) for s in strands5]
- self._3prime_list = [(s.idNum(),s.isForward(),s.idx3Prime()) for s in strands3]
-
- ## Get dictionary of insertions
- self.insertions = allInsertions = part.insertions()
- self.strand_occupancies = dict()
-
- ## Build helices
- for hid in range(numHID):
- # print("Working on helix",hid)
- helices[hid] = []
- helix_ranges[hid] = []
- self.strand_occupancies[hid] = []
-
- helixStrands = strand_list[hid]
- if helixStrands is None: continue
-
- ## Build list of tuples containing (idx,length) of insertions/skips
- insertions = sorted( [(i[0],i[1].length()) for i in allInsertions[hid].items()],
- key=lambda x: x[0] )
-
- ## TODO: make the following code (until "regions = ...") more readable
- ## Build list of strand ends and list of mandatory node locations
- ends1,ends2 = self._helixStrandsToEnds(helixStrands)
-
- ## Find crossovers for this helix
- reqNodeZids = sorted(list(set( ends1 + ends2 ) ) )
-
- ## Build lists of which nt sites are occupied in the helix
- strandOccupancies = [ [x for i in range(0,len(e),2)
- for x in range(e[i],e[i+1]+1)]
- for e in (ends1,ends2) ]
- self.strand_occupancies[hid] = strandOccupancies
-
- ends1,ends2 = [ [(e[i],e[i+1]) for i in range(0,len(e),2)] for e in (ends1,ends2) ]
-
- regions = combineRegionLists(ends1,ends2)
-
- ## Split regions in event of ssDNA crossover
- split_regions = []
- for zid1,zid2 in regions:
- zMid = int(0.5*(zid1+zid2))
- if zMid in strandOccupancies[0] and zMid in strandOccupancies[1]:
- split_regions.append( (zid1,zid2) )
- else:
- is_fwd = zMid in strandOccupancies[0]
- ends = [z for h,f,z in self._get_crossover_locations( hid, range(zid1+1,zid2), is_fwd )]
- z1 = zid1
- for z in sorted(ends):
- z2 = z
- if z2 > z1:
- split_regions.append( (z1,z2) )
- z1 = z2+1
- z2 = zid2
- split_regions.append( (z1,z2) )
-
- # if hid == 43:
- # import pdb
- for zid1,zid2 in split_regions:
- zMid = int(0.5*(zid1+zid2))
- assert( zMid in strandOccupancies[0] or zMid in strandOccupancies[1] )
-
- bp_to_zidx = []
- insertion_dict = {idx:length for idx,length in insertions}
- for i in range(zid1,zid2+1):
- if i in insertion_dict:
- l = insertion_dict[i]
- else:
- l = 0
- for j in range(i,i+1+l):
- bp_to_zidx.append(i)
- numBps = len(bp_to_zidx)
-
- # print("Adding helix with length",numBps,zid1,zid2)
-
- name = "%d-%d" % (hid,len(helices[hid]))
- # "H%03d" % hid
- kwargs = dict(name=name, segname=name, occupancy=hid)
-
- posargs1 = dict( start_position = self._get_cadnano_position(hid,zid1-0.25),
- end_position = self._get_cadnano_position(hid,zid2+0.25) )
- posargs2 = dict( start_position = posargs1['end_position'],
- end_position = posargs1['start_position'])
-
- ## TODO get sequence from cadnano api
- if zMid in strandOccupancies[0] and zMid in strandOccupancies[1]:
- kwargs['num_bp'] = numBps
- _angle = self._get_helix_angle(hid, zid1)
- start_orientation = rotationAboutAxis(np.array((0,0,1)), _angle)
- seg = DoubleStrandedSegment(**kwargs,**posargs1, start_orientation = start_orientation)
- elif zMid in strandOccupancies[0]:
- kwargs['num_nt'] = numBps
- seg = SingleStrandedSegment(**kwargs,**posargs1)
- elif zMid in strandOccupancies[1]:
- kwargs['num_nt'] = numBps
- seg = SingleStrandedSegment(**kwargs,**posargs2)
- else:
- raise Exception("Segment could not be found")
-
- seg._cadnano_helix = hid
- seg._cadnano_start = zid1
- seg._cadnano_end = zid2
- seg._cadnano_bp_to_zidx = bp_to_zidx
-
- def callback(segment):
- for b in segment.beads:
- bp = int(round(b.get_nt_position(segment)))
- if bp < 0: bp = 0
- if bp >= segment.num_nt: bp = segment.num_nt-1
- try:
- b.beta = segment._cadnano_bp_to_zidx[bp]
- if 'orientation_bead' in b.__dict__:
- b.orientation_bead.beta = segment._cadnano_bp_to_zidx[bp]
- except:
- pass
- seg._generate_bead_callbacks.append(callback)
-
- def atomic_callback(nucleotide, bp_to_zidx=bp_to_zidx):
- nt = nucleotide
- segment = nucleotide.parent.segment
- bp = int(round(segment.contour_to_nt_pos( nt.contour_position )))
- if bp < 0: bp = 0
- if bp >= segment.num_nt: bp = segment.num_nt-1
- try:
- nt.beta = bp_to_zidx[bp]
- nt.parent.occupancy = segment.occupancy
- except:
- pass
- seg._generate_nucleotide_callbacks.append(atomic_callback)
-
-
- helices[hid].append( seg )
- helix_ranges[hid].append( (zid1,zid2) )
-
- def _get_cadnano_position(self, hid, zid):
- return [10*a for a in self.origins[hid]] + [-3.4*zid]
-
- def _helixStrandsToEnds(self, helixStrands):
- """Utility method to convert cadnano strand lists into list of
- indices of terminal points"""
-
- endLists = [[],[]]
- for endList, strandList in zip(endLists,helixStrands):
- lastStrand = None
- for s in strandList:
- if lastStrand is None:
- ## first strand
- endList.append(s[0])
- elif lastStrand[1] != s[0]-1:
- assert( s[0] > lastStrand[1] )
- endList.extend( [lastStrand[1], s[0]] )
- lastStrand = s
- if lastStrand is not None:
- endList.append(lastStrand[1])
- return endLists
-
- def _helix_strands_to_segment_ranges(self, helix_strands):
- """Utility method to convert cadnano strand lists into list of
- indices of terminal points"""
- def _join(strands):
- ends = []
- lastEnd = None
- for start,end in strands:
- if lastEnd is None:
- ends.append([start])
- elif lastEnd != start-1:
- ends[-1].append(lastEnd)
- ends.append([start])
- lastEnd = end
- if lastEnd is not None:
- ends[-1].append(lastEnd)
- return ends
-
- s1,s2 = [_join(s) for s in helix_strands]
- i = j = 0
-
- ## iterate through strands
- while i < len(s1) and j < len(s2):
- min(s1[i][0],s2[j][0])
-
- def _get_segment(self, hid, zid):
- ## TODO: rename these variables to segments
- segs = self.helices[hid]
- ranges = self.helix_ranges[hid]
- for i in range(len(ranges)):
- zmin,zmax = ranges[i]
- if zmin <= zid and zid <= zmax:
- return segs[i]
- raise Exception("Could not find segment in helix %d at position %d" % (hid,zid))
-
- def _get_nucleotide(self, hid, zid):
- raise Exception("Deprecated")
- seg = self._get_segment(hid,zid)
- sid = self.helices[hid].index(seg)
- zmin,zmax = self.helix_ranges[hid][sid]
-
- nt = zid-zmin
-
- ## Find insertions
- # TODO: for i in range(zmin,zid+1): ?
- for i in range(zmin,zid):
- if i in self.insertions[hid]:
- nt += self.insertions[hid][i].length()
- return nt
-
- def _get_segment_nucleotide(self, hid, zid, get_forward_location=False):
- """ returns segments and zero-based nucleotide index """
- seg = self._get_segment(hid,zid)
- sid = self.helices[hid].index(seg)
- zmin,zmax = self.helix_ranges[hid][sid]
-
- zMid = int(0.5*(zmin+zmax))
- occ = self.strand_occupancies[hid]
- ins = self.insertions[hid]
-
- ## TODO combine if/else when nested TODO is resolved
- # if zid in self.insertions[hid]:
- # import pdb
- # pdb.set_trace()
-
- if (zMid not in occ[0]) and (zMid in occ[1]):
- ## reversed ssDNA strand
- nt = zmax-zid
- # TODO: for i in range(zmin,zid+1): ?
- for i in range(zid,zmax+1):
- if i in self.insertions[hid]:
- nt += self.insertions[hid][i].length()
- else:
- ## normal condition
- if get_forward_location:
- while zid in ins and ins[zid].length() < 0 and zid <= zmax:
- zid+=1
- # else:
- # while zid in ins and ins[zid].length() > 0 and zid >= zmax:
- # zid-=1
- nt = zid-zmin
- for i in range(zmin,zid):
- if i in ins:
- nt += ins[i].length()
-
- if not get_forward_location and zid in ins:
- nt += ins[zid].length()
-
- ## Find insertions
- return seg, nt
-
-
-
- """ Routines to add connnections between helices """
- def _add_intrahelical_connections(self):
- for hid,segs in self.helices.items():
- occ = self.strand_occupancies[hid]
- for i in range(len(segs)-1):
- seg1,seg2 = [segs[j] for j in (i,i+1)]
- if isinstance(seg1,SingleStrandedSegment) and isinstance(seg2,SingleStrandedSegment):
- continue
- r1,r2 = [self.helix_ranges[hid][j] for j in (i,i+1)]
- if r1[1]+1 == r2[0]:
- ## TODO: handle nicks that are at intrahelical connections(?)
- zmid1 = int(0.5*(r1[0]+r1[1]))
- zmid2 = int(0.5*(r2[0]+r2[1]))
-
- ## TODO: validate
- if zmid1 in occ[0] and zmid2 in occ[0]:
- seg1.connect_end3(seg2.start5)
-
- if zmid1 in occ[1] and zmid2 in occ[1]:
- if zmid1 in occ[0]:
- end = seg1.end5
- else:
- end = seg1.start5
- if zmid2 in occ[0]:
- seg2.connect_start3(end)
- else:
- seg2.connect_end3(end)
-
-
- def _get_crossover_locations(self, helix_idx, nt_idx_range, fwd_strand=None):
- xos = []
- def append_if_in_range(h,f,z):
- if fwd_strand in (None,f) and z in nt_idx_range:
- xos.append((h,f,z))
-
- for xo in self.xovers_from[helix_idx]:
- ## h1,f1,z1,h2,f2,z2 = xo[3:]
-
- append_if_in_range(*xo[:3])
- for xo in self.xovers_to[helix_idx]:
- append_if_in_range(*xo[3:])
- return xos
-
- def _add_crossovers(self):
- for hid,xos in self.xovers_from.items():
- for h1,f1,z1,h2,f2,z2 in xos:
- seg1, nt1 = self._get_segment_nucleotide(h1,z1,not f1)
- seg2, nt2 = self._get_segment_nucleotide(h2,z2,f2)
- ## TODO: use different types of crossovers
- ## fwd?
- ## 5'-to-3' direction
- if isinstance(seg1, SingleStrandedSegment): f1 = True
- if isinstance(seg2, SingleStrandedSegment): f2 = True
- seg1.add_crossover(nt1,seg2,nt2,[f1,f2])
-
- def _add_prime_ends(self):
- for h,fwd,z in self._5prime_list:
- seg, nt = self._get_segment_nucleotide(h,z, fwd)
- if isinstance(seg, SingleStrandedSegment): fwd = True
- # print("adding 5prime",seg.name,nt,fwd)
- seg.add_5prime(nt,fwd)
-
- for h,fwd,z in self._3prime_list:
- seg, nt = self._get_segment_nucleotide(h,z, not fwd)
- if isinstance(seg, SingleStrandedSegment): fwd = True
- # print("adding 3prime",seg.name,nt,fwd)
- seg.add_3prime(nt,fwd)
-
- def get_bead(self, hid, zid):
- # get segment, get nucleotide,
- seg, nt = self._get_segment_nucleotide(h,z)
- # return seg.get_nearest_bead(seg,nt / seg.num_nt)
- return seg.get_nearest_bead(seg,nt / (seg.num_nt-1))
-
-def read_json_file(filename):
- import json
- import re
-
- try:
- with open(filename) as ch:
- data = json.load(ch)
- except:
- with open(filename) as ch:
- content = ""
- for l in ch:
- l = re.sub(r"'", r'"', l)
- # https://stackoverflow.com/questions/4033633/handling-lazy-json-in-python-expecting-property-name
- # l = re.sub(r"{\s*(\w)", r'{"\1', l)
- # l = re.sub(r",\s*(\w)", r',"\1', l)
- # l = re.sub(r"(\w):", r'\1":', l)
- content += l+"\n"
- data = json.loads(content)
- return data
-
-def decode_cadnano_part(json_data):
- import cadnano
- from cadnano.document import Document
-
- try:
- doc = Document()
- cadnano.fileio.v3decode.decode(doc, json_data)
- decoder = 3
- except:
- doc = Document()
- cadnano.fileio.v2decode.decode(doc, json_data)
- decoder = 2
-
- parts = [p for p in doc.getParts()]
- if len(parts) != 1:
- raise Exception("Only documents containing a single cadnano part are implemented at this time.")
- part = parts[0]
-
- if decoder == 2:
- """ It seems cadnano2.5 (as of ce6ff019) does not set the EulerZ for square lattice structures correctly, doing so here """
- l = _get_lattice(part)
- if l == 'square':
- for id_num in part.getIdNums():
- if part.vh_properties.loc[id_num,'eulerZ'] == 0:
- part.vh_properties.loc[id_num,'eulerZ'] = 360*(6/10.5)
-
- return part
-
-def _get_lattice(part):
- lattice_type = None
- _gt = part.getGridType()
- try:
- lattice_type = _gt.name.lower()
- except:
- if _gt == 1:
- lattice_type = 'square'
- elif _gt == 2:
- lattice_type = 'honeycomb'
- else:
- print("WARNING: unable to determine cadnano part lattice type")
- return lattice_type
-
-def package_archive( name, directory ):
- ...
-
-def read_model(json_data, sequence=None, fill_sequence='T', **kwargs):
- """ Read in data """
- part = decode_cadnano_part(json_data)
- model = cadnano_part(part,
- **kwargs)
-
- # TODO
- # try:
- # model.set_cadnano_sequence()
- # finally:
- # ...
- # if sequence is not None and len() :
- # model.strands[0].set_sequence(seq)
-
- if sequence is None or len(sequence) == 0:
- ## default m13mp18
- model.set_sequence(m13seq,force=False, fill_sequence=fill_sequence)
- else:
- model.set_sequence(sequence, fill_sequence=fill_sequence)
-
- return model
-
-# pynvml.nvmlInit()
-# gpus = range(pynvml.nvmlDeviceGetCount())
-# pynvml.nvmlShutdown()
-# gpus = [0,1,2]
-# print(gpus)
-
-if __name__ == '__main__':
- loHi1 = [[0,4],[5,7]]
- loHi2 = [[2,4],[5,9]]
- out = [(0, 1), (2, 4), (5, 7), (8, 9)]
- print(loHi1)
- print(loHi2)
- print(combineRegionLists(loHi1,loHi2))
- print(combineCompactRegionLists(loHi1,loHi2))
-
- loHi1 = [[0,3],[5,7]]
- loHi2 = [[2,4],[5,9]]
- out = [(0, 1), (2, 3), (4, 4), (5, 7), (8, 9)]
- print(loHi1)
- print(loHi2)
- print(combineRegionLists(loHi1,loHi2))
- print(combineCompactRegionLists(loHi1,loHi2))
-
- combineRegionLists
-
- # for f in glob('json/*'):
- # print("Working on {}".format(f))
- # out = re.match('json/(.*).json',f).group(1)
- # data = read_json_file(f)
- # run_simulation_protocol( out, "job-id", data, gpu=0 )
diff --git a/mrdna/readers/.ipynb_checkpoints/segmentmodel_from_lists-checkpoint.py b/mrdna/readers/.ipynb_checkpoints/segmentmodel_from_lists-checkpoint.py
deleted file mode 100644
index 84eb17e..0000000
--- a/mrdna/readers/.ipynb_checkpoints/segmentmodel_from_lists-checkpoint.py
+++ /dev/null
@@ -1,495 +0,0 @@
-# -*- coding: utf-8 -*-
-
-import pdb
-import numpy as np
-import os,sys
-import scipy
-
-from mrdna import logger, devlogger
-from ..segmentmodel import SegmentModel, SingleStrandedSegment, DoubleStrandedSegment
-from ..arbdmodel.coords import quaternion_from_matrix, rotationAboutAxis, quaternion_slerp
-from .. import get_resource_path
-
-ref_stack_position = np.array((-2.41851735, -0.259761333, 3.39999978))
-
-def _three_prime_list_to_five_prime(three_prime):
- five_prime = -np.ones(three_prime.shape, dtype=int)
- has_three_prime = np.where(three_prime >= 0)[0]
- five_prime[three_prime[has_three_prime]] = has_three_prime
- return five_prime
-
-def _primes_list_to_strands(three_prime, five_prime):
- five_prime_ends = np.where(five_prime < 0)[0]
- strands = []
- strand_is_circular = []
-
- idx_to_strand = -np.ones(three_prime.shape, dtype=int)
-
- def build_strand(nt_idx, conditional):
- strand = [nt_idx]
- idx_to_strand[nt_idx] = len(strands)
- while conditional(nt_idx):
- nt_idx = three_prime[nt_idx]
- strand.append(nt_idx)
- idx_to_strand[nt_idx] = len(strands)
- strands.append( np.array(strand, dtype=int) )
-
- for nt_idx in five_prime_ends:
- build_strand(nt_idx,
- lambda nt: three_prime[nt] >= 0)
- strand_is_circular.append(False)
-
- while True:
- ## print("WARNING: working on circular strand {}".format(len(strands)))
- ids = np.where(idx_to_strand < 0)[0]
- if len(ids) == 0: break
- build_strand(ids[0],
- lambda nt: three_prime[nt] >= 0 and \
- idx_to_strand[three_prime[nt]] < 0)
- strand_is_circular.append(True)
-
- return strands, strand_is_circular
-
-def find_stacks(centers, transforms):
-
- ## Find orientation and center of each nucleotide
- expected_stack_positions = []
- for R,c in zip(transforms,centers):
- expected_stack_positions.append( c + ref_stack_position.dot(R) )
-
- expected_stack_positions = np.array(expected_stack_positions, dtype=np.float32)
-
- dists = scipy.spatial.distance_matrix(expected_stack_positions, centers)
- dists = dists + 5*np.eye(len(dists))
- idx1, idx2 = np.where(dists < 3.5)
-
- ## Convert distances to stacks
- stacks_above = -np.ones(len(centers), dtype=int)
- _z = np.array((0,0,1))
- for i in np.unique(idx1):
- js = idx2[ idx1 == i ]
- with np.errstate(divide='ignore',invalid='ignore'):
- angles = [np.arccos( transforms[j].T.dot( transforms[i].dot(_z) ).dot( _z ) ) for j in js]
- angles = np.array( angles )
- tmp = np.argmin(dists[i][js] + 1.0*angles)
- j = js[tmp]
- stacks_above[i] = j
-
- return stacks_above
-
-def basepairs_and_stacks_to_helixmap(basepairs,stacks_above):
-
- helixmap = -np.ones(basepairs.shape, dtype=int)
- helixrank = -np.ones(basepairs.shape)
- is_fwd = np.ones(basepairs.shape, dtype=int)
-
- ## Remove stacks with nts lacking a basepairs
- nobp = np.where(basepairs < 0)[0]
- stacks_above[nobp] = -1
- stacks_with_nobp = np.in1d(stacks_above, nobp)
- stacks_above[stacks_with_nobp] = -1
-
- end_ids = np.where( (stacks_above < 0)*(basepairs >= 0) )[0]
-
- hid = 0
- for end in end_ids:
- if helixmap[end] >= 0:
- continue
- rank = 0
- nt = basepairs[end]
- bp = basepairs[nt]
- assert( bp == end )
- if helixmap[nt] >= 0 or helixmap[bp] >= 0:
- logger.warning(f'Ill-formed helix: problematic basepair or stacking data near nucleotide {nt} or {bp}... skipping')
- continue
- # assert(helixmap[nt] == -1)
- # assert(helixmap[bp] == -1)
- helixmap[nt] = helixmap[bp] = hid
- helixrank[nt] = helixrank[bp] = rank
- is_fwd[bp] = 0
- rank +=1
-
- _tmp = [(nt,bp)]
-
- while stacks_above[nt] >= 0:
- nt = stacks_above[nt]
- if basepairs[nt] < 0: break
- bp = basepairs[nt]
- if helixmap[nt] >= 0 or helixmap[bp] >= 0:
- logger.warning(f'Ill-formed helix: problematic basepair or stacking data near nucleotide {nt} or {bp}... skipping')
- break
- helixmap[nt] = helixmap[bp] = hid
- helixrank[nt] = helixrank[bp] = rank
- is_fwd[bp] = 0
- _tmp.append((nt,bp))
- rank +=1
-
- hid += 1
-
- ## Create "helix" for each circular segment
- intrahelical = []
- processed = set()
- unclaimed_bases = np.where( (basepairs >= 0)*(helixmap == -1) )[0]
- for nt0 in unclaimed_bases:
- if nt0 in processed: continue
-
- nt = nt0
- all_nts = [nt]
-
- rank = 0
- nt = nt0
- bp = basepairs[nt]
- if helixmap[nt] >= 0 or helixmap[bp] >= 0:
- logger.warning(f'Ill-formed cylic helix: problematic basepair or stacking data near nucleotide {nt} or {bp}... skipping')
- continue
- helixmap[nt] = helixmap[bp] = hid
- helixrank[nt] = helixrank[bp] = rank
- is_fwd[bp] = 0
- rank +=1
- processed.add(nt)
- processed.add(bp)
-
- counter = 0
- while stacks_above[nt] >= 0:
- lastnt = nt
- nt = stacks_above[nt]
- bp = basepairs[nt]
- if nt == nt0 or nt == basepairs[nt0]:
- intrahelical.append((lastnt,nt0))
- break
-
- assert( bp >= 0 )
- if helixmap[nt] >= 0 or helixmap[bp] >= 0:
- logger.warning(f'Ill-formed cyclic helix: problematic basepair or stacking data near nucleotide {nt} or {bp}... skipping')
- break
-
- helixmap[nt] = helixmap[bp] = hid
- helixrank[nt] = helixrank[bp] = rank
- is_fwd[bp] = 0
- processed.add(nt)
- processed.add(bp)
- rank +=1
- hid += 1
-
- return helixmap, helixrank, is_fwd, intrahelical
-
-
-def set_splines(seg, coordinate, hid, hmap, hrank, fwd, basepair, orientation=None):
- maxrank = np.max( hrank[hmap==hid] )
- if maxrank == 0:
- ids = np.where((hmap == hid))[0]
- pos = np.mean( [coordinate[r,:] for r in ids ], axis=0 )
- coords = [pos,pos]
- contours = [0,1]
- if orientation is not None:
- ids = np.where((hmap == hid) * fwd)[0]
- assert( len(ids) == 1 )
- q = quaternion_from_matrix( orientation[ids[0]] )
- quats = [q, q]
- coords[-1] = pos + orientation[ids[0]].dot(np.array((0,0,1)))
-
- else:
- coords,contours,quats = [[],[],[]]
- last_q = None
- for rank in range(int(maxrank)+1):
- ids = np.where((hmap == hid) * (hrank == rank))[0]
-
- coords.append(np.mean( [coordinate[r,:] for r in ids ], axis=0 ))
- contours.append( float(rank+0.5)/(maxrank+1) )
- if orientation is not None:
- ids = np.where((hmap == hid) * (hrank == rank) * fwd)[0]
- assert(len(ids) == 1)
- q = quaternion_from_matrix( orientation[ids[0]] )
-
- if last_q is not None and last_q.dot(q) < 0:
- q = -q
-
- ## Average quaterion with reverse direction
- bp = basepair[ids[0]]
- if bp >= 0:
- bp_o = orientation[bp].dot(rotationAboutAxis(np.array((1,0,0)),180))
- q2 = quaternion_from_matrix( bp_o )
- if q.dot(q2) < 0:
- q2 = -q2
-
- ## probably good enough, but slerp is better: q = (q + q2)*0.5
- q = quaternion_slerp(q,q2,0.5)
-
- quats.append(q)
- last_q = q
-
- coords = np.array(coords)
- seg.set_splines(contours,coords)
- if orientation is not None:
- quats = np.array(quats)
- seg.set_orientation_splines(contours,quats)
-
- seg.start_position = coords[0,:]
- seg.end_position = coords[-1,:]
-
-
-def model_from_basepair_stack_3prime(coordinate, basepair, stack, three_prime,
- sequence=None, orientation=None,
- max_basepairs_per_bead = 5,
- max_nucleotides_per_bead = 5,
- local_twist = False,
- dimensions=(5000,5000,5000),
- **model_parameters):
- """
- Creates a SegmentModel object from lists of each nucleotide's
- basepair, its stack (on 3' side) and its 3'-connected nucleotide
-
- The first argument should be an N-by-3 numpy array containing the
- coordinate of each nucleotide, where N is the number of
- nucleotides. The following three arguments should be integer lists
- where the i-th element corresponds to the i-th nucleotide; the
- list element should the integer index of the corresponding
- basepaired / stacked / phosphodiester-bonded nucleotide. If there
- is no such nucleotide, the value should be -1.
-
- Args:
- basepair: List of each nucleotide's basepair's index
- stack: List containing index of the nucleotide stacked on the 3' of each nucleotide
- three_prime: List of each nucleotide's the 3' end of each nucleotide
-
- Returns:
- SegmentModel
- """
-
- """ Validate Input """
- inputs = (basepair,three_prime)
- try:
- basepair,three_prime = [np.array(a,dtype=int) for a in inputs]
- except:
- raise TypeError("One or more of the input lists could not be converted into a numpy array")
- inputs = (basepair,three_prime)
- coordinate = np.array(coordinate)
-
- if np.any( [len(a.shape) > 1 for a in inputs] ):
- raise ValueError("One or more of the input lists has the wrong dimensionality")
-
- if len(coordinate.shape) != 2:
- raise ValueError("Coordinate array has the wrong dimensionality")
-
- inputs = (coordinate,basepair,three_prime)
- if not np.all(np.diff([len(a) for a in inputs]) == 0):
- raise ValueError("Inputs are not the same length")
-
- num_nt = len(basepair)
- if sequence is not None and len(sequence) != num_nt:
- raise ValueError("The 'sequence' parameter is the wrong length {} != {}".format(len(sequence),num_nt))
-
- if orientation is not None:
- orientation = np.array(orientation)
- if len(orientation.shape) != 3:
- raise ValueError("The 'orientation' array has the wrong dimensionality (should be Nx3x3)")
- if orientation.shape != (num_nt,3,3):
- raise ValueError("The 'orientation' array is not properly formatted")
-
- if stack is None:
- if orientation is not None:
- stack = find_stacks(coordinate, orientation)
- else:
- ## Guess stacking based on 3' connectivity
- stack = np.array(three_prime,dtype=int) # Assume nts on 3' ends are stacked
- _stack_below = _three_prime_list_to_five_prime(stack)
- _has_bp = (basepair >= 0)
- _nostack = np.where( (stack == -1)*_has_bp )[0]
- _has_stack_below = _stack_below[basepair[_nostack]] >= 0
- _nostack2 = _nostack[_has_stack_below]
- stack[_nostack2] = basepair[_stack_below[basepair[_nostack2]]]
-
- else:
- try:
- stack = np.array(stack,dtype=int)
- except:
- raise TypeError("The 'stack' array could not be converted into a numpy integer array")
-
- if len(stack.shape) != 1:
- raise ValueError("The 'stack' array has the wrong dimensionality")
-
- if len(stack) != num_nt:
- raise ValueError("The length of the 'stack' array does not match other inputs")
-
- bps = basepair # alias
-
- """ Fix stacks: require that the stack of a bp of a base's stack is its bp """
- _has_bp = (bps >= 0)
- _has_stack = (stack >= 0)
- _stack_has_basepair = (bps[stack] >= 0) * _has_stack
- stack = np.where( (stack[bps[stack]] == bps) * _has_bp * _has_stack * _has_bp,
- stack, -np.ones(len(stack),dtype=int) )
-
- five_prime = _three_prime_list_to_five_prime(three_prime)
-
- """ Build map of dsDNA helices and strands """
- hmap,hrank,fwd,intrahelical = basepairs_and_stacks_to_helixmap(bps,stack)
- double_stranded_helices = np.unique(hmap[hmap >= 0])
- strands, strand_is_circular = _primes_list_to_strands(three_prime, five_prime)
-
- """ Add ssDNA to hmap """
- if len(double_stranded_helices) > 0:
- hid = double_stranded_helices[-1]+1
- else:
- hid = 0
- ss_residues = hmap < 0
- #
- if np.any(bps[ss_residues] != -1):
- logger.warning(f'{np.sum(bps[ss_residues] != -1)} ssDNA nucleotides appear to have basepairs... ignoring')
-
- for s,c in zip(strands, strand_is_circular):
- strand_segment_ends = [i for i in np.where( np.diff(hmap[s]) != 0 )[0]] + [len(s)-1]
- seg_start = 0
- for i in strand_segment_ends:
- if hmap[s[i]] < 0:
- ## Found single-stranded segment
- ids = s[seg_start:i+1]
- assert( np.all(hmap[ids] == -1) )
- hmap[ids] = hid
- hrank[ids] = np.arange(i+1-seg_start)
- hid+=1
- seg_start = i+1
-
- if len(double_stranded_helices) > 0:
- single_stranded_helices = np.arange(double_stranded_helices[-1]+1,hid)
- else:
- single_stranded_helices = np.arange(hid)
-
- ## Create double-stranded segments
- doubleSegments = []
- for hid in double_stranded_helices:
- seg = DoubleStrandedSegment(name=str(hid),
- num_bp = np.sum(hmap==hid)//2)
- set_splines(seg, coordinate, hid, hmap, hrank, fwd, basepair, orientation)
-
- assert(hid == len(doubleSegments))
- doubleSegments.append(seg)
-
- ## Create single-stranded segments
- singleSegments = []
- for hid in single_stranded_helices:
- seg = SingleStrandedSegment(name=str(hid),
- num_nt = np.sum(hmap==hid))
- set_splines(seg, coordinate, hid, hmap, hrank, fwd, basepair, orientation)
-
- assert(hid == len(doubleSegments) + len(singleSegments))
- singleSegments.append(seg)
-
- ## Find crossovers and 5prime/3prime ends
- crossovers,prime5,prime3 = [[],[],[]]
- for s,c in zip(strands,strand_is_circular):
- tmp = np.where(np.diff(hmap[s]) != 0)[0]
- for i in tmp:
- crossovers.append( (s[i],s[i+1]) )
- if c:
- if hmap[s[-1]] != hmap[s[0]]:
- crossovers.append( (s[-1],s[0]) )
- else:
- prime5.append(s[0])
- prime3.append(s[-1])
-
- ## Add connections
- allSegments = doubleSegments+singleSegments
-
- for r1,r2 in crossovers:
- seg1,seg2 = [allSegments[hmap[i]] for i in (r1,r2)]
- nt1,nt2 = [hrank[i] for i in (r1,r2)]
- f1,f2 = [fwd[i] for i in (r1,r2)]
-
- ## Handle connections at the ends
- is_terminal1 = (nt1,f1) in ((0,0),(seg1.num_nt-1,1))
- is_terminal2 = (nt2,f2) in ((0,1),(seg2.num_nt-1,0))
-
- print(seg1,seg2, r1, r2, is_terminal1, is_terminal2)
- if is_terminal1 or is_terminal2:
- """ Ensure that we don't have three-way dsDNA junctions """
- if is_terminal1 and (bps[r1] >= 0) and (five_prime[bps[r1]] >= 0) and (three_prime[r1] >= 0):
- if (bps[five_prime[bps[r1]]] >= 0) and (bps[three_prime[r1]] >= 0):
- # is_terminal1 = (three_prime[r1] == bps[five_prime[bps[r1]]])
- is_terminal1 = hmap[five_prime[bps[r1]]] == hmap[three_prime[r1]]
- if is_terminal2 and (bps[r2] >= 0) and (three_prime[bps[r2]] >= 0) and (five_prime[r2] >= 0):
- if (bps[three_prime[bps[r2]]] >= 0) and (bps[five_prime[r2]] >= 0):
- # is_terminal2 = (five_prime[r2] == bps[three_prime[bps[r2]]])
- is_terminal2 = hmap[three_prime[bps[r2]]] == hmap[five_prime[r2]]
-
- """ Place connection """
- if is_terminal1 and is_terminal2:
- end1 = seg1.end3 if f1 else seg1.start3
- end2 = seg2.start5 if f2 else seg2.end5
- seg1._connect_ends( end1, end2, type_='intrahelical')
- else:
- seg1.add_crossover(nt1,seg2,nt2,[f1,f2],type_="terminal_crossover")
- else:
- seg1.add_crossover(nt1,seg2,nt2,[f1,f2])
-
- ## Add 5prime/3prime ends
- for r in prime5:
- seg = allSegments[hmap[r]]
- seg.add_5prime(hrank[r],fwd[r])
- for r in prime3:
- seg = allSegments[hmap[r]]
- seg.add_3prime(hrank[r],fwd[r])
-
- ## Add intrahelical connections to circular helical sections
- for nt0,nt1 in intrahelical:
- seg = allSegments[hmap[nt0]]
- assert( seg is allSegments[hmap[nt1]] )
- if three_prime[nt0] >= 0:
- if hmap[nt0] == hmap[three_prime[nt0]]:
- seg.connect_end3(seg.start5)
-
- bp0,bp1 = [bps[nt] for nt in (nt0,nt1)]
- if three_prime[bp1] >= 0:
- if hmap[bp1] == hmap[three_prime[bp1]]:
- seg.connect_start3(seg.end5)
-
- ## Assign sequence
- if sequence is not None:
- for hid in range(len(allSegments)):
- resids = np.where( (hmap==hid)*(fwd==1) )[0]
- s = allSegments[hid]
- s.sequence = [sequence[r] for r in sorted(resids,key=lambda x: hrank[x])]
-
-
- ## Build model
- model = SegmentModel( allSegments,
- max_basepairs_per_bead = max_basepairs_per_bead,
- max_nucleotides_per_bead = max_nucleotides_per_bead,
- local_twist = local_twist,
- dimensions = dimensions,
- **model_parameters )
-
-
- model._reader_list_coordinates = coordinate
- model._reader_list_basepair = basepair
- model._reader_list_stack = stack
- model._reader_list_three_prime = three_prime
- model._reader_list_five_prime = five_prime
- model._reader_list_sequence = sequence
- model._reader_list_orientation = orientation
- model._reader_list_hmap = hmap
- model._reader_list_fwd = fwd
- model._reader_list_hrank = hrank
-
- if sequence is None:
- for s in model.segments:
- s.randomize_unset_sequence()
-
- return model
-
-def UNIT_circular():
- """ Make a circular DNA strand, with dsDNA in the middle """
- coordinate = [(0,0,3.4*i) for i in range(7)]
- stack = -1*np.ones(len(coordinate))
- three_prime = [ 1, 2, 4,-1, 6, 3, 0]
- basepair = [-1,-1, 3, 2, 5, 4,-1]
- stack = [-1,-1, 4,-1,-1, 3,-1]
- for i in [3,5]:
- coordinate[i] = (1,0,3.4*i)
-
- model = model_from_basepair_stack_3prime(coordinate, basepair, stack, three_prime,
- max_basepairs_per_bead=1,
- max_nucleotides_per_bead=1,
- local_twist=True)
-
- model.simulate(output_name='circular', directory='unittest')
diff --git a/mrdna/readers/.ipynb_checkpoints/segmentmodel_from_oxdna_pinyi-checkpoint.py b/mrdna/readers/.ipynb_checkpoints/segmentmodel_from_oxdna_pinyi-checkpoint.py
deleted file mode 100644
index b107283..0000000
--- a/mrdna/readers/.ipynb_checkpoints/segmentmodel_from_oxdna_pinyi-checkpoint.py
+++ /dev/null
@@ -1,162 +0,0 @@
-from mrdna import logger, devlogger
-from .segmentmodel_from_lists import model_from_basepair_stack_3prime
-from ..arbdmodel.coords import rotationAboutAxis
-
-from oxlibs import *
-import numpy as np
-from scipy.spatial import distance_matrix
-
-_seq_to_int_dict = dict(A=0,T=1,C=2,G=3)
-_seq_to_int_dict = {k:str(v) for k,v in _seq_to_int_dict.items()}
-
-_yrot = rotationAboutAxis(axis=(0,1,0), angle=180).dot(rotationAboutAxis(axis=(0,0,1),angle=-40))
-
-def mrdna_model_from_oxdna(coordinate_file, topology_file, virt2nuc=None, **model_parameters):
- """ Construct an mrdna model from oxDNA coordinate and topology files """
- top_data = np.loadtxt(topology_file, skiprows=1,
- unpack=True,
- dtype=np.dtype('i4,U1,i4,i4')
- )
- conf_data = np.loadtxt(idealized_coordinate_file, skiprows=3)
-
- if idealized_coordinate_file is not None:
- import pickle
- df = pickle.load(virt2nuc)
- vh_vb2nuc_rev, vhelix_pattern=df
-
-
-
- ## Reverse direction so indices run 5'-to-3'
- top_data = [a[::-1] for a in top_data]
- conf_data = conf_data[::-1,:]
-
- r = conf_data[:,:3] * 8.518
- base_dir = conf_data[:,3:6]
- # basepair_pos = r + base_dir*6.0
- basepair_pos = r + base_dir*10.0
- normal_dir = -conf_data[:,6:9]
- perp_dir = np.cross(base_dir, normal_dir)
- orientation = np.array([np.array(o).T.dot(_yrot) for o in zip(perp_dir,-base_dir,-normal_dir)])
-
- def _get_bp(sequence=None):
- dists = distance_matrix(r,basepair_pos) + np.eye(len(r))*1000
- dists = 0.5*(dists + dists.T)
-
- bp = np.array([np.argmin(da) for da in dists])
-
- for i,j in enumerate(bp):
- if j == -1: continue
- # devlogger.info(f'bp {i} {j} {dists[i,j]}')
- if dists[i,j] > 2:
- bp[i] = -1
- elif bp[j] != i:
- bpj = bp[j]
- logger.warning( " ".join([str(_x) for _x in ["Bad pair", i, j, bp[i], bp[j], dists[i,j], dists[j,i], dists[bpj,j], dists[j,bpj]]]) )
-
- for i,j in enumerate(bp):
- if j == -1: continue
- if bp[j] != i:
- bpj = bp[j]
- logger.warning( " ".join([str(_x) for _x in ["Bad pair2", i, j, bp[i], bp[j], dists[i,j], dists[j,i], dists[bpj,j], dists[j,bpj]]]) )
- raise Exception
-
- if sequence is not None:
- seq = sequence
- bp_seq = sequence[bp]
- bp_seq[bp==-1] = 'X'
- bad_bps = np.where( (bp >= 0) &
- (((seq == 'C') & (bp_seq != 'G')) |
- ((seq == 'G') & (bp_seq != 'C')) |
- ((seq == 'T') & (bp_seq != 'A')) |
- ((seq == 'U') & (bp_seq != 'A')) |
- ((seq == 'A') & ((bp_seq != 'T') | (bp_seq != 'U')))
- ) )[0]
- bp[bp[bad_bps]] = -1
- bp[bad_bps] = -1
-
- return bp
-
- def _get_stack():
- dists = distance_matrix( r + 3.5*normal_dir + 2.1*perp_dir -1*base_dir, r ) + np.eye(len(r))*1000
- stack = np.array([np.argmin(da) for da in dists])
- for i,j in enumerate(stack):
- if dists[i,j] > 8:
- stack[i] = -1
- elif i < 10:
- ## development info
- # devlogger.info([i,j,dists[i,j]])
- # dr = r[j] - (r[i] - normal_dir[i]*3.4 + perp_dir[i]*1 + base_dir[i]*1)
- dr = r[j] - r[i]
- # devlogger.info([normal_dir[i].dot(dr), perp_dir[i].dot(dr), base_dir[i].dot(dr)])
- return np.array(stack)
-
- seq = top_data[1]
- bp = _get_bp(seq)
- stack = _get_stack()
-
- three_prime = len(r) - top_data[2] -1
- five_prime = len(r) - top_data[3] -1
- three_prime[three_prime >= len(r)] = -1
- five_prime[five_prime >= len(r)] = -1
-
- def _debug_write_bonds():
- from ..arbdmodel import ParticleType, PointParticle, ArbdModel, Group
- bond = tuple()
- b_t = ParticleType('BASE')
- p_t = ParticleType('PHOS')
-
- parts = []
- for i,(r0,r_bp,three_prime0,bp0,stack0,seq0) in enumerate(zip(r,basepair_pos, three_prime, bp, stack, seq)):
- p = PointParticle(p_t, name='PHOS', position = r0, resid=i)
- b = PointParticle(b_t, name=seq0, position = 0.5*(r0+r_bp), resid=i)
- parts.extend((p,b))
-
- model = ArbdModel(parts)
- model.writePdb('test.pdb')
-
- for i,(r0,r_bp,three_prime0,bp0,stack0) in enumerate(zip(r,basepair_pos, three_prime, bp, stack)):
- model.add_bond(parts[2*i],parts[2*i+1],bond)
- j = three_prime0
- if j >= 0:
- model.add_bond(parts[2*i],parts[2*j],bond)
- j = bp0
- if j >= 0:
- model.add_bond(parts[2*i+1],parts[2*j+1],bond)
- model.writePsf('test.psf')
-
- model.bonds = []
- for i,(r0,r_bp,three_prime0,bp0,stack0) in enumerate(zip(r,basepair_pos, three_prime, bp, stack)):
- j = stack0
- if j >= 0:
- model.add_bond(parts[2*i],parts[2*j],bond)
- model.writePsf('test.stack.psf')
- ## _debug_write_bonds()
-
- logger.info(f'mrdna_model_from_oxdna: num_bp, num_ss_nt, num_stacked: {np.sum(bp>=0)//2} {np.sum(bp<0)} {np.sum(stack >= 0)}')
-
- if coordinate_file != idealized_coordinate_file:
- conf_data = conf_data[::-1,:]
-
- r = conf_data[:,:3] * 8.518
- base_dir = conf_data[:,3:6]
- basepair_pos = r + base_dir*10.0
- normal_dir = -conf_data[:,6:9]
- perp_dir = np.cross(base_dir, normal_dir)
- orientation = np.array([np.array(o).T.dot(_yrot) for o in zip(perp_dir,-base_dir,-normal_dir)])
-
- model = model_from_basepair_stack_3prime( r, bp, stack, three_prime, seq, orientation, **model_parameters )
-
- """
- model.DEBUG = True
- model.generate_bead_model(1,1,False,True,one_bead_per_monomer=True)
- for seg in model.segments:
- for bead in seg.beads:
- bead.position = bead.position + np.random.standard_normal(3)
-
- simulate( model, output_name='test', directory='test4' )
- """
- return model
-
-if __name__ == "__main__":
- mrdna_model_from_oxdna("0-from-collab/nanopore.oxdna","0-from-collab/nanopore.top")
- # mrdna_model_from_oxdna("2-oxdna.manual/output/from_mrdna-oxdna-min.last.conf","0-from-collab/nanopore.top")
diff --git a/mrdna/readers/.ipynb_checkpoints/test-checkpoint.ipynb b/mrdna/readers/.ipynb_checkpoints/test-checkpoint.ipynb
index 8e5ae43..2b75bca 100644
--- a/mrdna/readers/.ipynb_checkpoints/test-checkpoint.ipynb
+++ b/mrdna/readers/.ipynb_checkpoints/test-checkpoint.ipynb
@@ -2,97 +2,765 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 20,
- "id": "ef4ed889-492f-4ba3-8c1d-a0fc607b1f57",
- "metadata": {},
+ "execution_count": 124,
+ "id": "767c8226",
+ "metadata": {
+ "scrolled": true
+ },
"outputs": [
{
"data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>name</th>\n",
- " <th>vstrands</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>test.json</td>\n",
- " <td>{'row': 12, 'col': 16, 'num': 0, 'scaf': [[-1,...</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>test.json</td>\n",
- " <td>{'row': 12, 'col': 15, 'num': 1, 'scaf': [[-1,...</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>test.json</td>\n",
- " <td>{'row': 13, 'col': 15, 'num': 2, 'scaf': [[-1,...</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>test.json</td>\n",
- " <td>{'row': 13, 'col': 16, 'num': 3, 'scaf': [[-1,...</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>test.json</td>\n",
- " <td>{'row': 13, 'col': 17, 'num': 4, 'scaf': [[-1,...</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>5</th>\n",
- " <td>test.json</td>\n",
- " <td>{'row': 12, 'col': 17, 'num': 5, 'scaf': [[5, ...</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
"text/plain": [
- " name vstrands\n",
- "0 test.json {'row': 12, 'col': 16, 'num': 0, 'scaf': [[-1,...\n",
- "1 test.json {'row': 12, 'col': 15, 'num': 1, 'scaf': [[-1,...\n",
- "2 test.json {'row': 13, 'col': 15, 'num': 2, 'scaf': [[-1,...\n",
- "3 test.json {'row': 13, 'col': 16, 'num': 3, 'scaf': [[-1,...\n",
- "4 test.json {'row': 13, 'col': 17, 'num': 4, 'scaf': [[-1,...\n",
- "5 test.json {'row': 12, 'col': 17, 'num': 5, 'scaf': [[5, ..."
+ "dict_keys(['row', 'col', 'num', 'scaf', 'stap', 'loop', 'skip', 'scafLoop', 'stapLoop', 'stap_colors'])"
]
},
- "execution_count": 20,
+ "execution_count": 124,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
- "\n",
- "\n",
+ "import pickle\n",
+ "import numpy as np\n",
"df=pd.read_json(\"test.json\")\n",
- "df"
+ "df[\"vstrands\"][0].keys()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 164,
+ "id": "bf2d37ca",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[[-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [0, 3, -1, -1],\n",
+ " [0, 4, 0, 2],\n",
+ " [0, 5, 0, 3],\n",
+ " [0, 6, 0, 4],\n",
+ " [0, 7, 0, 5],\n",
+ " [0, 8, 0, 6],\n",
+ " [0, 9, 0, 7],\n",
+ " [0, 10, 0, 8],\n",
+ " [0, 11, 0, 9],\n",
+ " [0, 12, 0, 10],\n",
+ " [0, 13, 0, 11],\n",
+ " [0, 14, 0, 12],\n",
+ " [0, 15, 0, 13],\n",
+ " [0, 16, 0, 14],\n",
+ " [0, 17, 0, 15],\n",
+ " [0, 18, 0, 16],\n",
+ " [0, 19, 0, 17],\n",
+ " [0, 20, 0, 18],\n",
+ " [1, 20, 0, 19],\n",
+ " [0, 22, 1, 21],\n",
+ " [0, 23, 0, 21],\n",
+ " [-1, -1, 0, 22],\n",
+ " [0, 25, -1, -1],\n",
+ " [0, 26, 0, 24],\n",
+ " [0, 27, 0, 25],\n",
+ " [5, 27, 0, 26],\n",
+ " [0, 29, 5, 28],\n",
+ " [0, 30, 0, 28],\n",
+ " [0, 31, 0, 29],\n",
+ " [0, 32, 0, 30],\n",
+ " [0, 33, 0, 31],\n",
+ " [0, 34, 0, 32],\n",
+ " [0, 35, 0, 33],\n",
+ " [0, 36, 0, 34],\n",
+ " [0, 37, 0, 35],\n",
+ " [0, 38, 0, 36],\n",
+ " [-1, -1, 0, 37],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1]]"
+ ]
+ },
+ "execution_count": 164,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df[\"vstrands\"][0][\"stap\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 65,
+ "id": "4ce8f67f",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "UnicodeDecodeError",
+ "evalue": "'utf-8' codec can't decode byte 0x80 in position 0: invalid start byte",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mUnicodeDecodeError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-65-71f198107f5e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"test.virt2nuc\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\"r\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;32m/data/server1/cmaffeo2/miniconda3/lib/python3.8/codecs.py\u001b[0m in \u001b[0;36mdecode\u001b[0;34m(self, input, final)\u001b[0m\n\u001b[1;32m 320\u001b[0m \u001b[0;31m# decode input (taking the buffer into account)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 321\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuffer\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 322\u001b[0;31m \u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconsumed\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_buffer_decode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfinal\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 323\u001b[0m \u001b[0;31m# keep undecoded input until the next call\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 324\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuffer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mconsumed\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mUnicodeDecodeError\u001b[0m: 'utf-8' codec can't decode byte 0x80 in position 0: invalid start byte"
+ ]
+ }
+ ],
+ "source": [
+ "f=open(\"test.virt2nuc\",\"r\")\n",
+ "pickle.load(f)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 119,
+ "id": "625c831b",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "210"
+ ]
+ },
+ "execution_count": 119,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "vh_vb,pattern=pd.read_pickle(\"test.virt2nuc\")\n",
+ "len(vh_vb._scaf)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 66,
+ "id": "6a4129c2",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{0: (12, 16), 1: (12, 15), 2: (13, 15), 3: (13, 16), 4: (13, 17), 5: (12, 17)}"
+ ]
+ },
+ "execution_count": 66,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "pattern"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 141,
+ "id": "f85af2e4",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "(0, 40)\n",
+ "(0, 41)\n"
+ ]
+ },
+ {
+ "ename": "AttributeError",
+ "evalue": "'NoneType' object has no attribute 'append'",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-141-a0e59df19136>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ms\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdecode_vh_vb\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"test.virt2nuc\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_dict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m<ipython-input-140-99891f72666f>\u001b[0m in \u001b[0;36mdecode_vh_vb\u001b[0;34m(virt2nuc)\u001b[0m\n\u001b[1;32m 21\u001b[0m \u001b[0mscafs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvh_vb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_scaf\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 22\u001b[0m \u001b[0mstaps\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvh_vb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_stap\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 23\u001b[0;31m \u001b[0mscaf_strands\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfind_segs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscafs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 24\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 25\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mvh_list\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m<ipython-input-140-99891f72666f>\u001b[0m in \u001b[0;36mfind_segs\u001b[0;34m(vir2nuc_scaf)\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvir2nuc_scaf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m \u001b[0moligos\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0moligo\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0moligos\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0moligo\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvir2nuc_scaf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 11\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0moligos\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mAttributeError\u001b[0m: 'NoneType' object has no attribute 'append'"
+ ]
+ }
+ ],
+ "source": [
+ "s=decode_vh_vb(\"test.virt2nuc\")[0]\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 165,
+ "id": "aefe656e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "class strands():\n",
+ " def __init__(self):\n",
+ " self.row=0 \n",
+ " self.col=0\n",
+ " self.num=0\n",
+ " self.scaf=[]\n",
+ " self.stap=[]\n",
+ " self.loop=[]\n",
+ " self.skip=[]\n",
+ " self.scafLoop=[]\n",
+ " self.stapLoop=[]\n",
+ " self.stap_colors=[]\n",
+ " self.scaf_contact={}\n",
+ " self.stap_connect={}\n",
+ " def to_dict(self):\n",
+ " d={}\n",
+ " d['row']=self.row\n",
+ " d['col']=self.col\n",
+ " d['num']=self.num\n",
+ " d['scaf']=self.scaf\n",
+ " d['stap']=self.stap\n",
+ " d['loop']=self.loop\n",
+ " d['skip']=self.skip\n",
+ " d['scafLoop']=self.scafLoop\n",
+ " d['stapLoop']=self.stapLoop\n",
+ " d['stap_colors']=self.stap_colors\n",
+ " return d\n",
+ " \n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 160,
+ "id": "e154a8c3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def find_segs(vir2nuc_scaf):\n",
+ " oligos={}\n",
+ " for i in range(len(vir2nuc_scaf)):\n",
+ " oligo,ox_ind=list(vir2nuc_scaf.values())[i]\n",
+ " if oligo not in oligos.keys():\n",
+ " oligos[oligo]=[]\n",
+ " oligos[oligo].append(list(vir2nuc_scaf.keys())[i])\n",
+ " return oligos\n",
+ " \n",
+ "def decode_vh_vb(virt2nuc):\n",
+ " vh_list=[]\n",
+ " vh_vb,pattern=pd.read_pickle(virt2nuc)\n",
+ " for i in pattern.keys():\n",
+ " s=strands()\n",
+ " s.row,s.col=pattern[i]\n",
+ " s.num=i\n",
+ " vh_list.append(s)\n",
+ " scafs=vh_vb._scaf\n",
+ " staps=vh_vb._stap\n",
+ " scaf_strands=find_segs(scafs)\n",
+ " scaf_oligos=list(scaf_strands.keys())\n",
+ " for i in scaf_oligos:\n",
+ " bases=len(scaf_oligos)\n",
+ " vh0,vb0=scaf_oligos[i][0]\n",
+ " vh1,vb1=scaf_oligos[i][1]\n",
+ " if vb0>vb1:#53\n",
+ " scaf_contact\n",
+ " else: #35\n",
+ " \n",
+ " \n",
+ " return vh_list"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 163,
+ "id": "09619e4e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{0: [(0, 39), (0, 40), (0, 41)],\n",
+ " 1: [(1, 41), (1, 40), (1, 39)],\n",
+ " 2: [(2, 39), (2, 40), (2, 41)],\n",
+ " 4: [(3, 41), (3, 40), (3, 39), (3, 38), (3, 37)],\n",
+ " 5: [(4, 0), (4, 1), (4, 2), (4, 3)],\n",
+ " 6: [(5, 3), (5, 2), (5, 1), (5, 0)],\n",
+ " 7: [(5, 22),\n",
+ " (5, 21),\n",
+ " (5, 20),\n",
+ " (5, 19),\n",
+ " (5, 18),\n",
+ " (5, 17),\n",
+ " (5, 16),\n",
+ " (5, 15),\n",
+ " (5, 14),\n",
+ " (5, 13),\n",
+ " (5, 12),\n",
+ " (5, 11),\n",
+ " (5, 10),\n",
+ " (5, 9),\n",
+ " (4, 9),\n",
+ " (4, 10),\n",
+ " (4, 11),\n",
+ " (4, 12),\n",
+ " (4, 13),\n",
+ " (4, 14),\n",
+ " (4, 15),\n",
+ " (3, 15),\n",
+ " (3, 14),\n",
+ " (3, 13),\n",
+ " (3, 12),\n",
+ " (3, 11),\n",
+ " (3, 10),\n",
+ " (3, 9),\n",
+ " (3, 8),\n",
+ " (3, 7),\n",
+ " (3, 6),\n",
+ " (3, 5),\n",
+ " (3, 4),\n",
+ " (3, 3),\n",
+ " (3, 2),\n",
+ " (2, 2),\n",
+ " (2, 3),\n",
+ " (2, 4),\n",
+ " (2, 5),\n",
+ " (2, 6),\n",
+ " (2, 7),\n",
+ " (2, 8),\n",
+ " (2, 9),\n",
+ " (2, 10),\n",
+ " (2, 11),\n",
+ " (2, 12),\n",
+ " (2, 13),\n",
+ " (2, 14),\n",
+ " (2, 15),\n",
+ " (2, 16),\n",
+ " (2, 17),\n",
+ " (2, 18),\n",
+ " (1, 18),\n",
+ " (1, 17),\n",
+ " (1, 16),\n",
+ " (1, 15),\n",
+ " (1, 14),\n",
+ " (1, 13),\n",
+ " (1, 12),\n",
+ " (1, 11),\n",
+ " (1, 10),\n",
+ " (1, 9),\n",
+ " (1, 8),\n",
+ " (1, 7),\n",
+ " (1, 6),\n",
+ " (1, 5),\n",
+ " (0, 5),\n",
+ " (0, 6),\n",
+ " (0, 7),\n",
+ " (0, 8),\n",
+ " (0, 9),\n",
+ " (0, 10),\n",
+ " (0, 11),\n",
+ " (0, 12),\n",
+ " (0, 13),\n",
+ " (0, 14),\n",
+ " (0, 15),\n",
+ " (0, 16),\n",
+ " (0, 17),\n",
+ " (0, 18),\n",
+ " (0, 19),\n",
+ " (0, 20),\n",
+ " (0, 21),\n",
+ " (0, 22),\n",
+ " (0, 23),\n",
+ " (0, 24),\n",
+ " (0, 25),\n",
+ " (0, 26),\n",
+ " (0, 27),\n",
+ " (0, 28),\n",
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+ " (0, 31),\n",
+ " (0, 32),\n",
+ " (0, 33),\n",
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+ " (0, 35),\n",
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+ " (1, 36),\n",
+ " (1, 35),\n",
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+ " (1, 33),\n",
+ " (1, 32),\n",
+ " (1, 31),\n",
+ " (1, 30),\n",
+ " (1, 29),\n",
+ " (1, 28),\n",
+ " (1, 27),\n",
+ " (1, 26),\n",
+ " (1, 25),\n",
+ " (1, 24),\n",
+ " (1, 23),\n",
+ " (1, 22),\n",
+ " (1, 21),\n",
+ " (1, 20),\n",
+ " (1, 19),\n",
+ " (2, 19),\n",
+ " (2, 20),\n",
+ " (2, 21),\n",
+ " (2, 22),\n",
+ " (2, 23),\n",
+ " (2, 24),\n",
+ " (2, 25),\n",
+ " (2, 26),\n",
+ " (2, 27),\n",
+ " (2, 28),\n",
+ " (2, 29),\n",
+ " (2, 30),\n",
+ " (2, 31),\n",
+ " (2, 32),\n",
+ " (3, 32),\n",
+ " (3, 31),\n",
+ " (3, 30),\n",
+ " (3, 29),\n",
+ " (3, 28),\n",
+ " (3, 27),\n",
+ " (3, 26),\n",
+ " (3, 25),\n",
+ " (3, 24),\n",
+ " (3, 23),\n",
+ " (3, 22),\n",
+ " (3, 21),\n",
+ " (3, 20),\n",
+ " (3, 19),\n",
+ " (3, 18),\n",
+ " (3, 17),\n",
+ " (3, 16),\n",
+ " (4, 16),\n",
+ " (4, 17),\n",
+ " (4, 18),\n",
+ " (4, 19),\n",
+ " (4, 20),\n",
+ " (4, 21),\n",
+ " (4, 22),\n",
+ " (4, 23),\n",
+ " (4, 24),\n",
+ " (4, 25),\n",
+ " (4, 26),\n",
+ " (4, 27),\n",
+ " (4, 28),\n",
+ " (4, 29),\n",
+ " (4, 30),\n",
+ " (4, 31),\n",
+ " (4, 32),\n",
+ " (4, 33),\n",
+ " (4, 34),\n",
+ " (4, 35),\n",
+ " (4, 36),\n",
+ " (4, 37),\n",
+ " (4, 38),\n",
+ " (4, 39),\n",
+ " (5, 39),\n",
+ " (5, 38),\n",
+ " (5, 37),\n",
+ " (5, 36),\n",
+ " (5, 35),\n",
+ " (5, 34),\n",
+ " (5, 33),\n",
+ " (5, 32),\n",
+ " (5, 31),\n",
+ " (5, 30),\n",
+ " (5, 29),\n",
+ " (5, 28),\n",
+ " (5, 27),\n",
+ " (5, 26),\n",
+ " (5, 25),\n",
+ " (5, 24),\n",
+ " (5, 23)]}"
+ ]
+ },
+ "execution_count": 163,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "scafs=vh_vb._scaf\n",
+ "s=list(scafs.values())\n",
+ "len(scafs)\n",
+ "find_segs(scafs)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 157,
+ "id": "88d989b9",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[(1, 2)]"
+ ]
+ },
+ "execution_count": 157,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "oligos[0]=[]\n",
+ "L=[]\n",
+ "L.append((1,2))\n",
+ "L"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 152,
+ "id": "2909c273",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(0, 39)"
+ ]
+ },
+ "execution_count": 152,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "list(scafs.keys())[0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 62,
+ "id": "422e2b48",
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
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+ " (5, 25): (10, [309]),\n",
+ " (5, 26): (10, [308]),\n",
+ " (5, 27): (10, [307]),\n",
+ " (0, 27): (10, [306]),\n",
+ " (0, 26): (10, [305]),\n",
+ " (0, 25): (10, [304]),\n",
+ " (0, 24): (10, [303]),\n",
+ " (0, 38): (11, [348]),\n",
+ " (0, 37): (11, [347]),\n",
+ " (0, 36): (11, [346]),\n",
+ " (0, 35): (11, [345]),\n",
+ " (0, 34): (11, [344]),\n",
+ " (0, 33): (11, [343]),\n",
+ " (0, 32): (11, [342]),\n",
+ " (0, 31): (11, [341]),\n",
+ " (0, 30): (11, [340]),\n",
+ " (0, 29): (11, [339]),\n",
+ " (0, 28): (11, [338]),\n",
+ " (5, 28): (11, [337]),\n",
+ " (5, 29): (11, [336]),\n",
+ " (5, 30): (11, [335]),\n",
+ " (5, 31): (11, [334]),\n",
+ " (5, 32): (11, [333]),\n",
+ " (5, 33): (11, [332]),\n",
+ " (5, 34): (11, [331]),\n",
+ " (5, 35): (11, [330]),\n",
+ " (5, 36): (11, [329]),\n",
+ " (5, 37): (11, [328]),\n",
+ " (5, 38): (11, [327]),\n",
+ " (5, 39): (11, [326]),\n",
+ " (3, 0): (12, [381]),\n",
+ " (3, 1): (12, [380]),\n",
+ " (3, 2): (12, [379]),\n",
+ " (3, 3): (12, [378]),\n",
+ " (3, 4): (12, [377]),\n",
+ " (3, 5): (12, [376]),\n",
+ " (3, 6): (12, [375]),\n",
+ " (3, 7): (12, [374]),\n",
+ " (3, 8): (12, [373]),\n",
+ " (3, 9): (12, [372]),\n",
+ " (3, 10): (12, [371]),\n",
+ " (3, 11): (12, [370]),\n",
+ " (3, 12): (12, [369]),\n",
+ " (3, 13): (12, [368]),\n",
+ " (3, 14): (12, [367]),\n",
+ " (3, 15): (12, [366]),\n",
+ " (3, 16): (12, [365]),\n",
+ " (3, 17): (12, [364]),\n",
+ " (3, 18): (12, [363]),\n",
+ " (3, 19): (12, [362]),\n",
+ " (3, 20): (12, [361]),\n",
+ " (4, 20): (12, [360]),\n",
+ " (4, 19): (12, [359]),\n",
+ " (4, 18): (12, [358]),\n",
+ " (4, 17): (12, [357]),\n",
+ " (4, 16): (12, [356]),\n",
+ " (4, 15): (12, [355]),\n",
+ " (4, 14): (12, [354]),\n",
+ " (4, 13): (12, [353]),\n",
+ " (4, 12): (12, [352]),\n",
+ " (4, 11): (12, [351]),\n",
+ " (4, 10): (12, [350]),\n",
+ " (4, 9): (12, [349]),\n",
+ " (4, 39): (13, [414]),\n",
+ " (4, 38): (13, [413]),\n",
+ " (4, 37): (13, [412]),\n",
+ " (4, 36): (13, [411]),\n",
+ " (4, 35): (13, [410]),\n",
+ " (4, 34): (13, [409]),\n",
+ " (4, 33): (13, [408]),\n",
+ " (4, 32): (13, [407]),\n",
+ " (4, 31): (13, [406]),\n",
+ " (4, 30): (13, [405]),\n",
+ " (4, 29): (13, [404]),\n",
+ " (4, 28): (13, [403]),\n",
+ " (4, 27): (13, [402]),\n",
+ " (4, 26): (13, [401]),\n",
+ " (4, 25): (13, [400]),\n",
+ " (4, 24): (13, [399]),\n",
+ " (4, 23): (13, [398]),\n",
+ " (4, 22): (13, [397]),\n",
+ " (4, 21): (13, [396]),\n",
+ " (3, 21): (13, [395]),\n",
+ " (3, 22): (13, [394]),\n",
+ " (3, 23): (13, [393]),\n",
+ " (3, 24): (13, [392]),\n",
+ " (3, 25): (13, [391]),\n",
+ " (3, 26): (13, [390]),\n",
+ " (3, 27): (13, [389]),\n",
+ " (3, 28): (13, [388]),\n",
+ " (3, 29): (13, [387]),\n",
+ " (3, 30): (13, [386]),\n",
+ " (3, 31): (13, [385]),\n",
+ " (3, 32): (13, [384]),\n",
+ " (3, 33): (13, [383]),\n",
+ " (3, 34): (13, [382])}"
+ ]
+ },
+ "execution_count": 62,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "s=vh_vb.__dict__\n",
+ "scafs=s[\"_scaf\"]\n",
+ "staps=s[\"_stap\"]\n",
+ "staps"
]
},
{
"cell_type": "code",
- "execution_count": 30,
- "id": "051eb3b8-2bf1-4482-9815-19937f66e09d",
+ "execution_count": 3,
+ "id": "69c011ff",
"metadata": {},
"outputs": [],
"source": [
@@ -217,8 +885,8 @@
},
{
"cell_type": "code",
- "execution_count": 43,
- "id": "6e88e214-c870-47d1-9a47-504caa411530",
+ "execution_count": 4,
+ "id": "f2693e7a",
"metadata": {},
"outputs": [],
"source": [
@@ -238,30 +906,215 @@
},
{
"cell_type": "code",
- "execution_count": 57,
- "id": "326f70c5-6a80-4802-847a-ae0de82f0eda",
+ "execution_count": 20,
+ "id": "a4594752",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "'{\\n\"stapLoop\":[],\\n\"skip\":[],\\n\"loop\":[],\\n\"stap_colors\":[],\\n\"row\":0,\\n\"col\":0,\\n\"num\":0,\\n\"scafLoop\":[],\\n\"stap\":[[5, 1, -1, -1],[5, 2, 5, 0],[5, 3, 5, 1],[-1, -1, 5, 2],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[5, 10, 4, 9],[5, 11, 5, 9],[5, 12, 5, 10],[5, 13, 5, 11],[5, 14, 5, 12],[5, 15, 5, 13],[5, 16, 5, 14],[5, 17, 5, 15],[5, 18, 5, 16],[5, 19, 5, 17],[5, 20, 5, 18],[5, 21, 5, 19],[5, 22, 5, 20],[-1, -1, 5, 21],[5, 24, -1, -1],[5, 25, 5, 23],[5, 26, 5, 24],[5, 27, 5, 25],[5, 28, 5, 26],[5, 29, 5, 27],[5, 30, 5, 28],[5, 31, 5, 29],[5, 32, 5, 30],[5, 33, 5, 31],[5, 34, 5, 32],[5, 35, 5, 33],[5, 36, 5, 34],[5, 37, 5, 35],[5, 38, 5, 36],[5, 39, 5, 37],[4, 39, 5, 38],[-1, -1, -1, -1],[-1, -1, -1, -1]],\\n\"scaf\":[[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, 5, 10],[5, 9, 5, 11],[5, 10, 5, 12],[5, 11, 5, 13],[5, 12, 5, 14],[5, 13, 5, 15],[5, 14, 5, 16],[5, 15, 5, 17],[5, 16, 5, 18],[5, 17, 5, 19],[5, 18, 5, 20],[5, 19, 5, 21],[5, 20, 5, 22],[5, 21, 5, 23],[5, 22, 5, 24],[5, 23, 5, 25],[5, 24, 5, 26],[5, 25, 5, 27],[5, 26, 0, 27],[0, 28, 5, 29],[5, 28, 5, 30],[5, 29, 5, 31],[5, 30, 5, 32],[5, 31, 5, 33],[5, 32, 5, 34],[5, 33, 5, 35],[5, 34, 5, 36],[5, 35, 5, 37],[5, 36, 5, 38],[5, 37, 5, 39],[5, 38, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1]]\\n}'"
+ "['__class__',\n",
+ " '__delattr__',\n",
+ " '__dict__',\n",
+ " '__dir__',\n",
+ " '__doc__',\n",
+ " '__eq__',\n",
+ " '__format__',\n",
+ " '__ge__',\n",
+ " '__getattribute__',\n",
+ " '__gt__',\n",
+ " '__hash__',\n",
+ " '__init__',\n",
+ " '__init_subclass__',\n",
+ " '__le__',\n",
+ " '__lt__',\n",
+ " '__module__',\n",
+ " '__ne__',\n",
+ " '__new__',\n",
+ " '__reduce__',\n",
+ " '__reduce_ex__',\n",
+ " '__repr__',\n",
+ " '__setattr__',\n",
+ " '__sizeof__',\n",
+ " '__str__',\n",
+ " '__subclasshook__',\n",
+ " '__weakref__',\n",
+ " 'add_square',\n",
+ " 'cad_index',\n",
+ " 'col',\n",
+ " 'get_length',\n",
+ " 'len',\n",
+ " 'loop',\n",
+ " 'num',\n",
+ " 'row',\n",
+ " 'scaf',\n",
+ " 'scafLoop',\n",
+ " 'skip',\n",
+ " 'skiploop_bases',\n",
+ " 'stap',\n",
+ " 'stapLoop',\n",
+ " 'stap_colors']"
]
},
- "execution_count": 57,
+ "execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"s0=cadsys.vhelices[0]\n",
- "s0.__str__()"
+ "dir(s0)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "id": "ca071163",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[[-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, 5, 10],\n",
+ " [5, 9, 5, 11],\n",
+ " [5, 10, 5, 12],\n",
+ " [5, 11, 5, 13],\n",
+ " [5, 12, 5, 14],\n",
+ " [5, 13, 5, 15],\n",
+ " [5, 14, 5, 16],\n",
+ " [5, 15, 5, 17],\n",
+ " [5, 16, 5, 18],\n",
+ " [5, 17, 5, 19],\n",
+ " [5, 18, 5, 20],\n",
+ " [5, 19, 5, 21],\n",
+ " [5, 20, 5, 22],\n",
+ " [5, 21, 5, 23],\n",
+ " [5, 22, 5, 24],\n",
+ " [5, 23, 5, 25],\n",
+ " [5, 24, 5, 26],\n",
+ " [5, 25, 5, 27],\n",
+ " [5, 26, 0, 27],\n",
+ " [0, 28, 5, 29],\n",
+ " [5, 28, 5, 30],\n",
+ " [5, 29, 5, 31],\n",
+ " [5, 30, 5, 32],\n",
+ " [5, 31, 5, 33],\n",
+ " [5, 32, 5, 34],\n",
+ " [5, 33, 5, 35],\n",
+ " [5, 34, 5, 36],\n",
+ " [5, 35, 5, 37],\n",
+ " [5, 36, 5, 38],\n",
+ " [5, 37, 5, 39],\n",
+ " [5, 38, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1]]"
+ ]
+ },
+ "execution_count": 25,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "s0.scaf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "e5913163",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "for s in s0.scaf:\n",
+ " if s[0]==-1 and s[1]==-1:\n",
+ " pass\n",
+ " elif s[2]==len(s0.scaf) and abs(s[3])==1"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "3eefca8f",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[-1, -1, -1, -1]"
+ ]
+ },
+ "execution_count": 13,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "s0.scaf[0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "268d5c04",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "['__class__',\n",
+ " '__delattr__',\n",
+ " '__dict__',\n",
+ " '__dir__',\n",
+ " '__doc__',\n",
+ " '__eq__',\n",
+ " '__format__',\n",
+ " '__ge__',\n",
+ " '__getattribute__',\n",
+ " '__gt__',\n",
+ " '__hash__',\n",
+ " '__init__',\n",
+ " '__init_subclass__',\n",
+ " '__le__',\n",
+ " '__lt__',\n",
+ " '__module__',\n",
+ " '__ne__',\n",
+ " '__new__',\n",
+ " '__reduce__',\n",
+ " '__reduce_ex__',\n",
+ " '__repr__',\n",
+ " '__setattr__',\n",
+ " '__sizeof__',\n",
+ " '__str__',\n",
+ " '__subclasshook__',\n",
+ " '__weakref__',\n",
+ " 'add_vhelix',\n",
+ " 'bbox',\n",
+ " 'vhelices']"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "dir(cadsys)"
]
},
{
"cell_type": "code",
"execution_count": 36,
- "id": "7b552911-d7de-4079-ab4d-e859f2281f36",
+ "id": "d3d42e33",
"metadata": {},
"outputs": [
{
@@ -323,7 +1176,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "94113dfa",
+ "id": "2cc3f477",
"metadata": {},
"outputs": [
{
@@ -349,7 +1202,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "ec7f1e22-6a95-41f9-8c23-7603cc165837",
+ "id": "5d50f58a",
"metadata": {},
"outputs": [],
"source": []
@@ -357,7 +1210,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "id": "40d7cdcf",
+ "id": "3b40b71b",
"metadata": {},
"outputs": [
{
@@ -377,7 +1230,7 @@
{
"cell_type": "code",
"execution_count": 13,
- "id": "4b3748a8",
+ "id": "6915bad6",
"metadata": {},
"outputs": [
{
@@ -398,7 +1251,7 @@
{
"cell_type": "code",
"execution_count": 15,
- "id": "aa8a8cd9",
+ "id": "1c16c59d",
"metadata": {},
"outputs": [
{
@@ -468,7 +1321,7 @@
{
"cell_type": "code",
"execution_count": 16,
- "id": "e0cab15d",
+ "id": "c61d9586",
"metadata": {},
"outputs": [],
"source": [
@@ -479,7 +1332,7 @@
{
"cell_type": "code",
"execution_count": 26,
- "id": "9811bf9a",
+ "id": "aeca0546",
"metadata": {},
"outputs": [
{
@@ -588,7 +1441,7 @@
{
"cell_type": "code",
"execution_count": 25,
- "id": "86403b4b",
+ "id": "90a54834",
"metadata": {},
"outputs": [
{
@@ -609,7 +1462,7 @@
{
"cell_type": "code",
"execution_count": 10,
- "id": "5c7cea80",
+ "id": "de00fb7e",
"metadata": {},
"outputs": [
{
@@ -640,7 +1493,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "136dcf08",
+ "id": "716ff2ed",
"metadata": {},
"outputs": [
{
@@ -1137,7 +1990,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "id": "88f7d20e",
+ "id": "766d0ecd",
"metadata": {},
"outputs": [
{
@@ -1171,7 +2024,7 @@
{
"cell_type": "code",
"execution_count": 4,
- "id": "69d29f1e",
+ "id": "05456be4",
"metadata": {},
"outputs": [
{
@@ -1191,7 +2044,7 @@
{
"cell_type": "code",
"execution_count": 5,
- "id": "e103e8b4",
+ "id": "cd1a5604",
"metadata": {},
"outputs": [],
"source": [
@@ -1201,7 +2054,7 @@
{
"cell_type": "code",
"execution_count": 6,
- "id": "a30b582d",
+ "id": "4346f1fc",
"metadata": {},
"outputs": [
{
@@ -1222,7 +2075,7 @@
{
"cell_type": "code",
"execution_count": 7,
- "id": "dcd8bf8a",
+ "id": "294094f9",
"metadata": {},
"outputs": [
{
@@ -1249,7 +2102,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "bf20c9ef",
+ "id": "b3d29c52",
"metadata": {},
"outputs": [],
"source": []
@@ -1257,7 +2110,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3 (ipykernel)",
+ "display_name": "Python 3",
"language": "python",
"name": "python3"
},
@@ -1271,7 +2124,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.19"
+ "version": "3.8.18"
}
},
"nbformat": 4,
diff --git a/mrdna/readers/.segmentmodel_from_cadnano.py.swp b/mrdna/readers/.segmentmodel_from_cadnano.py.swp
new file mode 100644
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diff --git a/mrdna/readers/cadnano_segments.py b/mrdna/readers/cadnano_segments.py
index b39bd2e..47cf148 100644
--- a/mrdna/readers/cadnano_segments.py
+++ b/mrdna/readers/cadnano_segments.py
@@ -17,166 +17,7 @@ from ..model.dna_sequence import m13 as m13seq
## - helices that should be stacked across an empty region (crossovers from and end in the helix to another end in the helix)
## - circular constructs
-def combineRegionLists(loHi1,loHi2,intersect=False):
-
- """Combines two lists of (lo,hi) pairs specifying integer
- regions a single list of regions. """
-
- ## Validate input
- for l in (loHi1,loHi2):
- ## Assert each region in lists is sorted
- for pair in l:
- assert(len(pair) == 2)
- assert(pair[0] <= pair[1])
-
- if len(loHi1) == 0:
- if intersect:
- return []
- else:
- return loHi2
- if len(loHi2) == 0:
- if intersect:
- return []
- else:
- return loHi1
-
- ## Break input into lists of compact regions
- compactRegions1,compactRegions2 = [[],[]]
- for compactRegions,loHi in zip(
- [compactRegions1,compactRegions2],
- [loHi1,loHi2]):
- tmp = []
- lastHi = loHi[0][0]-1
- for lo,hi in loHi:
- if lo-1 != lastHi:
- compactRegions.append(tmp)
- tmp = []
- tmp.append((lo,hi))
- lastHi = hi
- if len(tmp) > 0:
- compactRegions.append(tmp)
-
- ## Build result
- result = []
- region = []
- i,j = [0,0]
- compactRegions1.append([[1e10]])
- compactRegions2.append([[1e10]])
- while i < len(compactRegions1)-1 or j < len(compactRegions2)-1:
- cr1 = compactRegions1[i]
- cr2 = compactRegions2[j]
-
- ## initialize region
- if len(region) == 0:
- if cr1[0][0] <= cr2[0][0]:
- region = cr1
- i += 1
- continue
- else:
- region = cr2
- j += 1
- continue
-
- if region[-1][-1] >= cr1[0][0]:
- region = combineCompactRegionLists(region, cr1, intersect=False)
- i+=1
- elif region[-1][-1] >= cr2[0][0]:
- region = combineCompactRegionLists(region, cr2, intersect=False)
- j+=1
- else:
- result.extend(region)
- region = []
-
- assert( len(region) > 0 )
- result.extend(region)
- result = sorted(result)
-
- # print("loHi1:",loHi1)
- # print("loHi2:",loHi2)
- # print(result,"\n")
-
- if intersect:
- lo = max( [loHi1[0][0], loHi2[0][0]] )
- hi = min( [loHi1[-1][1], loHi2[-1][1]] )
- result = [r for r in result if r[0] >= lo and r[1] <= hi]
-
- return result
-
-def combineCompactRegionLists(loHi1,loHi2,intersect=False):
-
- """Combines two lists of (lo,hi) pairs specifying regions within a
- compact integer set into a single list of regions.
-
- examples:
- loHi1 = [[0,4],[5,7]]
- loHi2 = [[2,4],[5,9]]
- out = [(0, 1), (2, 4), (5, 7), (8, 9)]
-
- loHi1 = [[0,3],[5,7]]
- loHi2 = [[2,4],[5,9]]
- out = [(0, 1), (2, 3), (4, 4), (5, 7), (8, 9)]
- """
-
- ## Validate input
- for l in (loHi1,loHi2):
- ## Assert each region in lists is sorted
- for pair in l:
- assert(len(pair) == 2)
- assert(pair[0] <= pair[1])
- ## Assert lists are compact
- for pair1,pair2 in zip(l[::2],l[1::2]):
- assert(pair1[1]+1 == pair2[0])
-
- if len(loHi1) == 0:
- if intersect:
- return []
- else:
- return loHi2
- if len(loHi2) == 0:
- if intersect:
- return []
- else:
- return loHi1
- ## Find the ends of the region
- lo = min( [loHi1[0][0], loHi2[0][0]] )
- hi = max( [loHi1[-1][1], loHi2[-1][1]] )
-
- ## Make a list of indices where each region will be split
- splitAfter = []
- for l,h in loHi2:
- if l != lo:
- splitAfter.append(l-1)
- if h != hi:
- splitAfter.append(h)
-
- for l,h in loHi1:
- if l != lo:
- splitAfter.append(l-1)
- if h != hi:
- splitAfter.append(h)
- splitAfter = sorted(list(set(splitAfter)))
-
- # print("splitAfter:",splitAfter)
-
- split=[]
- last = -2
- for s in splitAfter:
- split.append(s)
- last = s
-
- # print("split:",split)
- returnList = [(i+1,j) if i != j else (i,j) for i,j in zip([lo-1]+split,split+[hi])]
-
- if intersect:
- lo = max( [loHi1[0][0], loHi2[0][0]] )
- hi = min( [loHi1[-1][1], loHi2[-1][1]] )
- returnList = [r for r in returnList if r[0] >= lo and r[1] <= hi]
-
- # print("loHi1:",loHi1)
- # print("loHi2:",loHi2)
- # print(returnList,"\n")
- return returnList
class cadnano_part(SegmentModel):
def __init__(self, part,
@@ -700,6 +541,166 @@ def read_model(json_data, sequence=None, fill_sequence='T', **kwargs):
# pynvml.nvmlShutdown()
# gpus = [0,1,2]
# print(gpus)
+def combineRegionLists(loHi1,loHi2,intersect=False):
+
+ """Combines two lists of (lo,hi) pairs specifying integer
+ regions a single list of regions. """
+
+ ## Validate input
+ for l in (loHi1,loHi2):
+ ## Assert each region in lists is sorted
+ for pair in l:
+ assert(len(pair) == 2)
+ assert(pair[0] <= pair[1])
+
+ if len(loHi1) == 0:
+ if intersect:
+ return []
+ else:
+ return loHi2
+ if len(loHi2) == 0:
+ if intersect:
+ return []
+ else:
+ return loHi1
+
+ ## Break input into lists of compact regions
+ compactRegions1,compactRegions2 = [[],[]]
+ for compactRegions,loHi in zip(
+ [compactRegions1,compactRegions2],
+ [loHi1,loHi2]):
+ tmp = []
+ lastHi = loHi[0][0]-1
+ for lo,hi in loHi:
+ if lo-1 != lastHi:
+ compactRegions.append(tmp)
+ tmp = []
+ tmp.append((lo,hi))
+ lastHi = hi
+ if len(tmp) > 0:
+ compactRegions.append(tmp)
+
+ ## Build result
+ result = []
+ region = []
+ i,j = [0,0]
+ compactRegions1.append([[1e10]])
+ compactRegions2.append([[1e10]])
+ while i < len(compactRegions1)-1 or j < len(compactRegions2)-1:
+ cr1 = compactRegions1[i]
+ cr2 = compactRegions2[j]
+
+ ## initialize region
+ if len(region) == 0:
+ if cr1[0][0] <= cr2[0][0]:
+ region = cr1
+ i += 1
+ continue
+ else:
+ region = cr2
+ j += 1
+ continue
+
+ if region[-1][-1] >= cr1[0][0]:
+ region = combineCompactRegionLists(region, cr1, intersect=False)
+ i+=1
+ elif region[-1][-1] >= cr2[0][0]:
+ region = combineCompactRegionLists(region, cr2, intersect=False)
+ j+=1
+ else:
+ result.extend(region)
+ region = []
+
+ assert( len(region) > 0 )
+ result.extend(region)
+ result = sorted(result)
+
+ # print("loHi1:",loHi1)
+ # print("loHi2:",loHi2)
+ # print(result,"\n")
+
+ if intersect:
+ lo = max( [loHi1[0][0], loHi2[0][0]] )
+ hi = min( [loHi1[-1][1], loHi2[-1][1]] )
+ result = [r for r in result if r[0] >= lo and r[1] <= hi]
+
+ return result
+
+def combineCompactRegionLists(loHi1,loHi2,intersect=False):
+
+ """Combines two lists of (lo,hi) pairs specifying regions within a
+ compact integer set into a single list of regions.
+
+ examples:
+ loHi1 = [[0,4],[5,7]]
+ loHi2 = [[2,4],[5,9]]
+ out = [(0, 1), (2, 4), (5, 7), (8, 9)]
+
+ loHi1 = [[0,3],[5,7]]
+ loHi2 = [[2,4],[5,9]]
+ out = [(0, 1), (2, 3), (4, 4), (5, 7), (8, 9)]
+ """
+
+ ## Validate input
+ for l in (loHi1,loHi2):
+ ## Assert each region in lists is sorted
+ for pair in l:
+ assert(len(pair) == 2)
+ assert(pair[0] <= pair[1])
+ ## Assert lists are compact
+ for pair1,pair2 in zip(l[::2],l[1::2]):
+ assert(pair1[1]+1 == pair2[0])
+
+ if len(loHi1) == 0:
+ if intersect:
+ return []
+ else:
+ return loHi2
+ if len(loHi2) == 0:
+ if intersect:
+ return []
+ else:
+ return loHi1
+
+ ## Find the ends of the region
+ lo = min( [loHi1[0][0], loHi2[0][0]] )
+ hi = max( [loHi1[-1][1], loHi2[-1][1]] )
+
+ ## Make a list of indices where each region will be split
+ splitAfter = []
+ for l,h in loHi2:
+ if l != lo:
+ splitAfter.append(l-1)
+ if h != hi:
+ splitAfter.append(h)
+
+ for l,h in loHi1:
+ if l != lo:
+ splitAfter.append(l-1)
+ if h != hi:
+ splitAfter.append(h)
+ splitAfter = sorted(list(set(splitAfter)))
+
+ # print("splitAfter:",splitAfter)
+
+ split=[]
+ last = -2
+ for s in splitAfter:
+ split.append(s)
+ last = s
+
+ # print("split:",split)
+ returnList = [(i+1,j) if i != j else (i,j) for i,j in zip([lo-1]+split,split+[hi])]
+
+ if intersect:
+ lo = max( [loHi1[0][0], loHi2[0][0]] )
+ hi = min( [loHi1[-1][1], loHi2[-1][1]] )
+ returnList = [r for r in returnList if r[0] >= lo and r[1] <= hi]
+
+ # print("loHi1:",loHi1)
+ # print("loHi2:",loHi2)
+ # print(returnList,"\n")
+ return returnList
if __name__ == '__main__':
loHi1 = [[0,4],[5,7]]
diff --git a/mrdna/readers/libs b/mrdna/readers/libs
new file mode 120000
index 0000000..8266af3
--- /dev/null
+++ b/mrdna/readers/libs
@@ -0,0 +1 @@
+/home/pinyili2/server5/tacoxDNA/src/libs/
\ No newline at end of file
diff --git a/mrdna/readers/list.pdb b/mrdna/readers/list.pdb
index e402a34..a986d3d 100644
--- a/mrdna/readers/list.pdb
+++ b/mrdna/readers/list.pdb
@@ -1,8 +1,8 @@
CRYST1 5000.000 5000.000 5000.000 90.00 90.00 90.00 P 1 1
-ATOM 1 DNA DNA A 1 0.50000 0.00000 5.10000 0.00 0.00 0 0
-ATOM 2 DNA DNA A 2 0.50000 0.00000 11.9000 0.00 0.00 0 0
-ATOM 3 DNA DNA A 3 0.50000 0.00000 18.7000 0.00 0.00 0 0
-ATOM 4 NAS NAS A 4 0.00000 0.00000-1.70000 0.00 0.00 0 1
-ATOM 5 NAS NAS A 5 0.00000 0.00000 1.70000 0.00 0.00 0 1
-ATOM 6 NAS NAS A 6 0.00000 0.00000 5.10000 0.00 0.00 0 1
-ATOM 7 NAS NAS A 7 0.00000 0.00000 20.4000 0.00 0.00 0 2
+ATOM 1 DNA DNA A 1 0.50000 0.00000 8.50000 0.00 0.00 0 0
+ATOM 2 DNA DNA A 2 0.50000 0.00000 15.3000 0.00 0.00 0 1
+ATOM 3 DNA DNA A 3 0.50000 0.00000 15.3000 0.00 0.00 0 1
+ATOM 4 NAS NAS A 4 0.00000 0.00000-1.70000 0.00 0.00 0 2
+ATOM 5 NAS NAS A 5 0.00000 0.00000 1.70000 0.00 0.00 0 2
+ATOM 6 NAS NAS A 6 0.00000 0.00000 5.10000 0.00 0.00 0 2
+ATOM 7 NAS NAS A 7 0.00000 0.00000 20.4000 0.00 0.00 0 3
diff --git a/mrdna/readers/list.psf b/mrdna/readers/list.psf
index 89e10e7..828fb57 100644
--- a/mrdna/readers/list.psf
+++ b/mrdna/readers/list.psf
@@ -3,20 +3,20 @@ PSF NAMD
0 !NTITLE
7 !NATOM
- 1 0 1 DNA DNA D000 0.000000 150.0000 0
- 2 0 2 DNA DNA D001 0.000000 300.0000 0
- 3 0 3 DNA DNA D001 0.000000 300.0000 0
- 4 1 4 NAS NAS S000 0.000000 150.0000 0
- 5 1 5 NAS NAS S000 0.000000 150.0000 0
- 6 1 6 NAS NAS S001 0.000000 75.0000 0
- 7 2 7 NAS NAS S000 0.000000 150.0000 0
+ 1 0 1 DNA DNA D000 0.000000 225.0000 0
+ 2 1 2 DNA DNA D001 0.000000 300.0000 0
+ 3 1 3 DNA DNA D002 0.000000 375.0000 0
+ 4 2 4 NAS NAS S000 0.000000 150.0000 0
+ 5 2 5 NAS NAS S000 0.000000 150.0000 0
+ 6 2 6 NAS NAS S001 0.000000 75.0000 0
+ 7 3 7 NAS NAS S000 0.000000 150.0000 0
7 !NBOND
- 4 7 3 7 1 2 1 6
- 2 3 4 5 5 6
+ 1 6 4 5 5 6 4 7
+ 1 3 2 3 2 7
3 !NTHETA
- 5 4 7 4 5 6 1 2 3
+ 4 5 6 5 4 7 1 3 2
0 !NPHI
diff --git a/mrdna/readers/test.ipynb b/mrdna/readers/test.ipynb
index 8e5ae43..2b75bca 100644
--- a/mrdna/readers/test.ipynb
+++ b/mrdna/readers/test.ipynb
@@ -2,97 +2,765 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 20,
- "id": "ef4ed889-492f-4ba3-8c1d-a0fc607b1f57",
- "metadata": {},
+ "execution_count": 124,
+ "id": "767c8226",
+ "metadata": {
+ "scrolled": true
+ },
"outputs": [
{
"data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>name</th>\n",
- " <th>vstrands</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>test.json</td>\n",
- " <td>{'row': 12, 'col': 16, 'num': 0, 'scaf': [[-1,...</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>test.json</td>\n",
- " <td>{'row': 12, 'col': 15, 'num': 1, 'scaf': [[-1,...</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>test.json</td>\n",
- " <td>{'row': 13, 'col': 15, 'num': 2, 'scaf': [[-1,...</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>test.json</td>\n",
- " <td>{'row': 13, 'col': 16, 'num': 3, 'scaf': [[-1,...</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>test.json</td>\n",
- " <td>{'row': 13, 'col': 17, 'num': 4, 'scaf': [[-1,...</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>5</th>\n",
- " <td>test.json</td>\n",
- " <td>{'row': 12, 'col': 17, 'num': 5, 'scaf': [[5, ...</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
"text/plain": [
- " name vstrands\n",
- "0 test.json {'row': 12, 'col': 16, 'num': 0, 'scaf': [[-1,...\n",
- "1 test.json {'row': 12, 'col': 15, 'num': 1, 'scaf': [[-1,...\n",
- "2 test.json {'row': 13, 'col': 15, 'num': 2, 'scaf': [[-1,...\n",
- "3 test.json {'row': 13, 'col': 16, 'num': 3, 'scaf': [[-1,...\n",
- "4 test.json {'row': 13, 'col': 17, 'num': 4, 'scaf': [[-1,...\n",
- "5 test.json {'row': 12, 'col': 17, 'num': 5, 'scaf': [[5, ..."
+ "dict_keys(['row', 'col', 'num', 'scaf', 'stap', 'loop', 'skip', 'scafLoop', 'stapLoop', 'stap_colors'])"
]
},
- "execution_count": 20,
+ "execution_count": 124,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
- "\n",
- "\n",
+ "import pickle\n",
+ "import numpy as np\n",
"df=pd.read_json(\"test.json\")\n",
- "df"
+ "df[\"vstrands\"][0].keys()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 164,
+ "id": "bf2d37ca",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[[-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [0, 3, -1, -1],\n",
+ " [0, 4, 0, 2],\n",
+ " [0, 5, 0, 3],\n",
+ " [0, 6, 0, 4],\n",
+ " [0, 7, 0, 5],\n",
+ " [0, 8, 0, 6],\n",
+ " [0, 9, 0, 7],\n",
+ " [0, 10, 0, 8],\n",
+ " [0, 11, 0, 9],\n",
+ " [0, 12, 0, 10],\n",
+ " [0, 13, 0, 11],\n",
+ " [0, 14, 0, 12],\n",
+ " [0, 15, 0, 13],\n",
+ " [0, 16, 0, 14],\n",
+ " [0, 17, 0, 15],\n",
+ " [0, 18, 0, 16],\n",
+ " [0, 19, 0, 17],\n",
+ " [0, 20, 0, 18],\n",
+ " [1, 20, 0, 19],\n",
+ " [0, 22, 1, 21],\n",
+ " [0, 23, 0, 21],\n",
+ " [-1, -1, 0, 22],\n",
+ " [0, 25, -1, -1],\n",
+ " [0, 26, 0, 24],\n",
+ " [0, 27, 0, 25],\n",
+ " [5, 27, 0, 26],\n",
+ " [0, 29, 5, 28],\n",
+ " [0, 30, 0, 28],\n",
+ " [0, 31, 0, 29],\n",
+ " [0, 32, 0, 30],\n",
+ " [0, 33, 0, 31],\n",
+ " [0, 34, 0, 32],\n",
+ " [0, 35, 0, 33],\n",
+ " [0, 36, 0, 34],\n",
+ " [0, 37, 0, 35],\n",
+ " [0, 38, 0, 36],\n",
+ " [-1, -1, 0, 37],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1]]"
+ ]
+ },
+ "execution_count": 164,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df[\"vstrands\"][0][\"stap\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 65,
+ "id": "4ce8f67f",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "UnicodeDecodeError",
+ "evalue": "'utf-8' codec can't decode byte 0x80 in position 0: invalid start byte",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mUnicodeDecodeError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-65-71f198107f5e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"test.virt2nuc\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\"r\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;32m/data/server1/cmaffeo2/miniconda3/lib/python3.8/codecs.py\u001b[0m in \u001b[0;36mdecode\u001b[0;34m(self, input, final)\u001b[0m\n\u001b[1;32m 320\u001b[0m \u001b[0;31m# decode input (taking the buffer into account)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 321\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuffer\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 322\u001b[0;31m \u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconsumed\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_buffer_decode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfinal\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 323\u001b[0m \u001b[0;31m# keep undecoded input until the next call\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 324\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuffer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mconsumed\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mUnicodeDecodeError\u001b[0m: 'utf-8' codec can't decode byte 0x80 in position 0: invalid start byte"
+ ]
+ }
+ ],
+ "source": [
+ "f=open(\"test.virt2nuc\",\"r\")\n",
+ "pickle.load(f)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 119,
+ "id": "625c831b",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "210"
+ ]
+ },
+ "execution_count": 119,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "vh_vb,pattern=pd.read_pickle(\"test.virt2nuc\")\n",
+ "len(vh_vb._scaf)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 66,
+ "id": "6a4129c2",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{0: (12, 16), 1: (12, 15), 2: (13, 15), 3: (13, 16), 4: (13, 17), 5: (12, 17)}"
+ ]
+ },
+ "execution_count": 66,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "pattern"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 141,
+ "id": "f85af2e4",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "(0, 40)\n",
+ "(0, 41)\n"
+ ]
+ },
+ {
+ "ename": "AttributeError",
+ "evalue": "'NoneType' object has no attribute 'append'",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-141-a0e59df19136>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ms\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdecode_vh_vb\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"test.virt2nuc\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_dict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m<ipython-input-140-99891f72666f>\u001b[0m in \u001b[0;36mdecode_vh_vb\u001b[0;34m(virt2nuc)\u001b[0m\n\u001b[1;32m 21\u001b[0m \u001b[0mscafs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvh_vb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_scaf\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 22\u001b[0m \u001b[0mstaps\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvh_vb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_stap\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 23\u001b[0;31m \u001b[0mscaf_strands\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfind_segs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscafs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 24\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 25\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mvh_list\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m<ipython-input-140-99891f72666f>\u001b[0m in \u001b[0;36mfind_segs\u001b[0;34m(vir2nuc_scaf)\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvir2nuc_scaf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m \u001b[0moligos\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0moligo\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0moligos\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0moligo\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvir2nuc_scaf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 11\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0moligos\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mAttributeError\u001b[0m: 'NoneType' object has no attribute 'append'"
+ ]
+ }
+ ],
+ "source": [
+ "s=decode_vh_vb(\"test.virt2nuc\")[0]\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 165,
+ "id": "aefe656e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "class strands():\n",
+ " def __init__(self):\n",
+ " self.row=0 \n",
+ " self.col=0\n",
+ " self.num=0\n",
+ " self.scaf=[]\n",
+ " self.stap=[]\n",
+ " self.loop=[]\n",
+ " self.skip=[]\n",
+ " self.scafLoop=[]\n",
+ " self.stapLoop=[]\n",
+ " self.stap_colors=[]\n",
+ " self.scaf_contact={}\n",
+ " self.stap_connect={}\n",
+ " def to_dict(self):\n",
+ " d={}\n",
+ " d['row']=self.row\n",
+ " d['col']=self.col\n",
+ " d['num']=self.num\n",
+ " d['scaf']=self.scaf\n",
+ " d['stap']=self.stap\n",
+ " d['loop']=self.loop\n",
+ " d['skip']=self.skip\n",
+ " d['scafLoop']=self.scafLoop\n",
+ " d['stapLoop']=self.stapLoop\n",
+ " d['stap_colors']=self.stap_colors\n",
+ " return d\n",
+ " \n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 160,
+ "id": "e154a8c3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def find_segs(vir2nuc_scaf):\n",
+ " oligos={}\n",
+ " for i in range(len(vir2nuc_scaf)):\n",
+ " oligo,ox_ind=list(vir2nuc_scaf.values())[i]\n",
+ " if oligo not in oligos.keys():\n",
+ " oligos[oligo]=[]\n",
+ " oligos[oligo].append(list(vir2nuc_scaf.keys())[i])\n",
+ " return oligos\n",
+ " \n",
+ "def decode_vh_vb(virt2nuc):\n",
+ " vh_list=[]\n",
+ " vh_vb,pattern=pd.read_pickle(virt2nuc)\n",
+ " for i in pattern.keys():\n",
+ " s=strands()\n",
+ " s.row,s.col=pattern[i]\n",
+ " s.num=i\n",
+ " vh_list.append(s)\n",
+ " scafs=vh_vb._scaf\n",
+ " staps=vh_vb._stap\n",
+ " scaf_strands=find_segs(scafs)\n",
+ " scaf_oligos=list(scaf_strands.keys())\n",
+ " for i in scaf_oligos:\n",
+ " bases=len(scaf_oligos)\n",
+ " vh0,vb0=scaf_oligos[i][0]\n",
+ " vh1,vb1=scaf_oligos[i][1]\n",
+ " if vb0>vb1:#53\n",
+ " scaf_contact\n",
+ " else: #35\n",
+ " \n",
+ " \n",
+ " return vh_list"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 163,
+ "id": "09619e4e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{0: [(0, 39), (0, 40), (0, 41)],\n",
+ " 1: [(1, 41), (1, 40), (1, 39)],\n",
+ " 2: [(2, 39), (2, 40), (2, 41)],\n",
+ " 4: [(3, 41), (3, 40), (3, 39), (3, 38), (3, 37)],\n",
+ " 5: [(4, 0), (4, 1), (4, 2), (4, 3)],\n",
+ " 6: [(5, 3), (5, 2), (5, 1), (5, 0)],\n",
+ " 7: [(5, 22),\n",
+ " (5, 21),\n",
+ " (5, 20),\n",
+ " (5, 19),\n",
+ " (5, 18),\n",
+ " (5, 17),\n",
+ " (5, 16),\n",
+ " (5, 15),\n",
+ " (5, 14),\n",
+ " (5, 13),\n",
+ " (5, 12),\n",
+ " (5, 11),\n",
+ " (5, 10),\n",
+ " (5, 9),\n",
+ " (4, 9),\n",
+ " (4, 10),\n",
+ " (4, 11),\n",
+ " (4, 12),\n",
+ " (4, 13),\n",
+ " (4, 14),\n",
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+ " (3, 15),\n",
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+ " (3, 11),\n",
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+ " (3, 6),\n",
+ " (3, 5),\n",
+ " (3, 4),\n",
+ " (3, 3),\n",
+ " (3, 2),\n",
+ " (2, 2),\n",
+ " (2, 3),\n",
+ " (2, 4),\n",
+ " (2, 5),\n",
+ " (2, 6),\n",
+ " (2, 7),\n",
+ " (2, 8),\n",
+ " (2, 9),\n",
+ " (2, 10),\n",
+ " (2, 11),\n",
+ " (2, 12),\n",
+ " (2, 13),\n",
+ " (2, 14),\n",
+ " (2, 15),\n",
+ " (2, 16),\n",
+ " (2, 17),\n",
+ " (2, 18),\n",
+ " (1, 18),\n",
+ " (1, 17),\n",
+ " (1, 16),\n",
+ " (1, 15),\n",
+ " (1, 14),\n",
+ " (1, 13),\n",
+ " (1, 12),\n",
+ " (1, 11),\n",
+ " (1, 10),\n",
+ " (1, 9),\n",
+ " (1, 8),\n",
+ " (1, 7),\n",
+ " (1, 6),\n",
+ " (1, 5),\n",
+ " (0, 5),\n",
+ " (0, 6),\n",
+ " (0, 7),\n",
+ " (0, 8),\n",
+ " (0, 9),\n",
+ " (0, 10),\n",
+ " (0, 11),\n",
+ " (0, 12),\n",
+ " (0, 13),\n",
+ " (0, 14),\n",
+ " (0, 15),\n",
+ " (0, 16),\n",
+ " (0, 17),\n",
+ " (0, 18),\n",
+ " (0, 19),\n",
+ " (0, 20),\n",
+ " (0, 21),\n",
+ " (0, 22),\n",
+ " (0, 23),\n",
+ " (0, 24),\n",
+ " (0, 25),\n",
+ " (0, 26),\n",
+ " (0, 27),\n",
+ " (0, 28),\n",
+ " (0, 29),\n",
+ " (0, 30),\n",
+ " (0, 31),\n",
+ " (0, 32),\n",
+ " (0, 33),\n",
+ " (0, 34),\n",
+ " (0, 35),\n",
+ " (0, 36),\n",
+ " (1, 36),\n",
+ " (1, 35),\n",
+ " (1, 34),\n",
+ " (1, 33),\n",
+ " (1, 32),\n",
+ " (1, 31),\n",
+ " (1, 30),\n",
+ " (1, 29),\n",
+ " (1, 28),\n",
+ " (1, 27),\n",
+ " (1, 26),\n",
+ " (1, 25),\n",
+ " (1, 24),\n",
+ " (1, 23),\n",
+ " (1, 22),\n",
+ " (1, 21),\n",
+ " (1, 20),\n",
+ " (1, 19),\n",
+ " (2, 19),\n",
+ " (2, 20),\n",
+ " (2, 21),\n",
+ " (2, 22),\n",
+ " (2, 23),\n",
+ " (2, 24),\n",
+ " (2, 25),\n",
+ " (2, 26),\n",
+ " (2, 27),\n",
+ " (2, 28),\n",
+ " (2, 29),\n",
+ " (2, 30),\n",
+ " (2, 31),\n",
+ " (2, 32),\n",
+ " (3, 32),\n",
+ " (3, 31),\n",
+ " (3, 30),\n",
+ " (3, 29),\n",
+ " (3, 28),\n",
+ " (3, 27),\n",
+ " (3, 26),\n",
+ " (3, 25),\n",
+ " (3, 24),\n",
+ " (3, 23),\n",
+ " (3, 22),\n",
+ " (3, 21),\n",
+ " (3, 20),\n",
+ " (3, 19),\n",
+ " (3, 18),\n",
+ " (3, 17),\n",
+ " (3, 16),\n",
+ " (4, 16),\n",
+ " (4, 17),\n",
+ " (4, 18),\n",
+ " (4, 19),\n",
+ " (4, 20),\n",
+ " (4, 21),\n",
+ " (4, 22),\n",
+ " (4, 23),\n",
+ " (4, 24),\n",
+ " (4, 25),\n",
+ " (4, 26),\n",
+ " (4, 27),\n",
+ " (4, 28),\n",
+ " (4, 29),\n",
+ " (4, 30),\n",
+ " (4, 31),\n",
+ " (4, 32),\n",
+ " (4, 33),\n",
+ " (4, 34),\n",
+ " (4, 35),\n",
+ " (4, 36),\n",
+ " (4, 37),\n",
+ " (4, 38),\n",
+ " (4, 39),\n",
+ " (5, 39),\n",
+ " (5, 38),\n",
+ " (5, 37),\n",
+ " (5, 36),\n",
+ " (5, 35),\n",
+ " (5, 34),\n",
+ " (5, 33),\n",
+ " (5, 32),\n",
+ " (5, 31),\n",
+ " (5, 30),\n",
+ " (5, 29),\n",
+ " (5, 28),\n",
+ " (5, 27),\n",
+ " (5, 26),\n",
+ " (5, 25),\n",
+ " (5, 24),\n",
+ " (5, 23)]}"
+ ]
+ },
+ "execution_count": 163,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "scafs=vh_vb._scaf\n",
+ "s=list(scafs.values())\n",
+ "len(scafs)\n",
+ "find_segs(scafs)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 157,
+ "id": "88d989b9",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[(1, 2)]"
+ ]
+ },
+ "execution_count": 157,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "oligos[0]=[]\n",
+ "L=[]\n",
+ "L.append((1,2))\n",
+ "L"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 152,
+ "id": "2909c273",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(0, 39)"
+ ]
+ },
+ "execution_count": 152,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "list(scafs.keys())[0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 62,
+ "id": "422e2b48",
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{(2, 34): (3, [43]),\n",
+ " (2, 33): (3, [42]),\n",
+ " (2, 32): (3, [41]),\n",
+ " (2, 31): (3, [40]),\n",
+ " (2, 30): (3, [39]),\n",
+ " (2, 29): (3, [38]),\n",
+ " (2, 28): (3, [37]),\n",
+ " (2, 27): (3, [36]),\n",
+ " (2, 26): (3, [35]),\n",
+ " (2, 25): (3, [34]),\n",
+ " (2, 24): (3, [33]),\n",
+ " (2, 23): (3, [32]),\n",
+ " (2, 22): (3, [31]),\n",
+ " (2, 21): (3, [30]),\n",
+ " (2, 20): (3, [29]),\n",
+ " (2, 19): (3, [28]),\n",
+ " (2, 18): (3, [27]),\n",
+ " (2, 17): (3, [26]),\n",
+ " (2, 16): (3, [25]),\n",
+ " (2, 15): (3, [24]),\n",
+ " (2, 14): (3, [23]),\n",
+ " (2, 13): (3, [22]),\n",
+ " (2, 12): (3, [21]),\n",
+ " (2, 11): (3, [20]),\n",
+ " (2, 10): (3, [19]),\n",
+ " (2, 9): (3, [18]),\n",
+ " (2, 8): (3, [17]),\n",
+ " (2, 7): (3, [16]),\n",
+ " (2, 6): (3, [15]),\n",
+ " (2, 5): (3, [14]),\n",
+ " (2, 4): (3, [13]),\n",
+ " (2, 3): (3, [12]),\n",
+ " (2, 2): (3, [11]),\n",
+ " (2, 1): (3, [10]),\n",
+ " (2, 0): (3, [9]),\n",
+ " (1, 3): (8, [281]),\n",
+ " (1, 4): (8, [280]),\n",
+ " (1, 5): (8, [279]),\n",
+ " (1, 6): (8, [278]),\n",
+ " (1, 7): (8, [277]),\n",
+ " (1, 8): (8, [276]),\n",
+ " (1, 9): (8, [275]),\n",
+ " (1, 10): (8, [274]),\n",
+ " (1, 11): (8, [273]),\n",
+ " (1, 12): (8, [272]),\n",
+ " (1, 13): (8, [271]),\n",
+ " (1, 14): (8, [270]),\n",
+ " (1, 15): (8, [269]),\n",
+ " (1, 16): (8, [268]),\n",
+ " (1, 17): (8, [267]),\n",
+ " (1, 18): (8, [266]),\n",
+ " (1, 19): (8, [265]),\n",
+ " (1, 20): (8, [264]),\n",
+ " (0, 20): (8, [263]),\n",
+ " (0, 19): (8, [262]),\n",
+ " (0, 18): (8, [261]),\n",
+ " (0, 17): (8, [260]),\n",
+ " (0, 16): (8, [259]),\n",
+ " (0, 15): (8, [258]),\n",
+ " (0, 14): (8, [257]),\n",
+ " (0, 13): (8, [256]),\n",
+ " (0, 12): (8, [255]),\n",
+ " (0, 11): (8, [254]),\n",
+ " (0, 10): (8, [253]),\n",
+ " (0, 9): (8, [252]),\n",
+ " (0, 8): (8, [251]),\n",
+ " (0, 7): (8, [250]),\n",
+ " (0, 6): (8, [249]),\n",
+ " (0, 5): (8, [248]),\n",
+ " (0, 4): (8, [247]),\n",
+ " (0, 3): (8, [246]),\n",
+ " (0, 2): (8, [245]),\n",
+ " (0, 23): (9, [302]),\n",
+ " (0, 22): (9, [301]),\n",
+ " (0, 21): (9, [300]),\n",
+ " (1, 21): (9, [299]),\n",
+ " (1, 22): (9, [298]),\n",
+ " (1, 23): (9, [297]),\n",
+ " (1, 24): (9, [296]),\n",
+ " (1, 25): (9, [295]),\n",
+ " (1, 26): (9, [294]),\n",
+ " (1, 27): (9, [293]),\n",
+ " (1, 28): (9, [292]),\n",
+ " (1, 29): (9, [291]),\n",
+ " (1, 30): (9, [290]),\n",
+ " (1, 31): (9, [289]),\n",
+ " (1, 32): (9, [288]),\n",
+ " (1, 33): (9, [287]),\n",
+ " (1, 34): (9, [286]),\n",
+ " (1, 35): (9, [285]),\n",
+ " (1, 36): (9, [284]),\n",
+ " (1, 37): (9, [283]),\n",
+ " (1, 38): (9, [282]),\n",
+ " (5, 9): (10, [325]),\n",
+ " (5, 10): (10, [324]),\n",
+ " (5, 11): (10, [323]),\n",
+ " (5, 12): (10, [322]),\n",
+ " (5, 13): (10, [321]),\n",
+ " (5, 14): (10, [320]),\n",
+ " (5, 15): (10, [319]),\n",
+ " (5, 16): (10, [318]),\n",
+ " (5, 17): (10, [317]),\n",
+ " (5, 18): (10, [316]),\n",
+ " (5, 19): (10, [315]),\n",
+ " (5, 20): (10, [314]),\n",
+ " (5, 21): (10, [313]),\n",
+ " (5, 22): (10, [312]),\n",
+ " (5, 23): (10, [311]),\n",
+ " (5, 24): (10, [310]),\n",
+ " (5, 25): (10, [309]),\n",
+ " (5, 26): (10, [308]),\n",
+ " (5, 27): (10, [307]),\n",
+ " (0, 27): (10, [306]),\n",
+ " (0, 26): (10, [305]),\n",
+ " (0, 25): (10, [304]),\n",
+ " (0, 24): (10, [303]),\n",
+ " (0, 38): (11, [348]),\n",
+ " (0, 37): (11, [347]),\n",
+ " (0, 36): (11, [346]),\n",
+ " (0, 35): (11, [345]),\n",
+ " (0, 34): (11, [344]),\n",
+ " (0, 33): (11, [343]),\n",
+ " (0, 32): (11, [342]),\n",
+ " (0, 31): (11, [341]),\n",
+ " (0, 30): (11, [340]),\n",
+ " (0, 29): (11, [339]),\n",
+ " (0, 28): (11, [338]),\n",
+ " (5, 28): (11, [337]),\n",
+ " (5, 29): (11, [336]),\n",
+ " (5, 30): (11, [335]),\n",
+ " (5, 31): (11, [334]),\n",
+ " (5, 32): (11, [333]),\n",
+ " (5, 33): (11, [332]),\n",
+ " (5, 34): (11, [331]),\n",
+ " (5, 35): (11, [330]),\n",
+ " (5, 36): (11, [329]),\n",
+ " (5, 37): (11, [328]),\n",
+ " (5, 38): (11, [327]),\n",
+ " (5, 39): (11, [326]),\n",
+ " (3, 0): (12, [381]),\n",
+ " (3, 1): (12, [380]),\n",
+ " (3, 2): (12, [379]),\n",
+ " (3, 3): (12, [378]),\n",
+ " (3, 4): (12, [377]),\n",
+ " (3, 5): (12, [376]),\n",
+ " (3, 6): (12, [375]),\n",
+ " (3, 7): (12, [374]),\n",
+ " (3, 8): (12, [373]),\n",
+ " (3, 9): (12, [372]),\n",
+ " (3, 10): (12, [371]),\n",
+ " (3, 11): (12, [370]),\n",
+ " (3, 12): (12, [369]),\n",
+ " (3, 13): (12, [368]),\n",
+ " (3, 14): (12, [367]),\n",
+ " (3, 15): (12, [366]),\n",
+ " (3, 16): (12, [365]),\n",
+ " (3, 17): (12, [364]),\n",
+ " (3, 18): (12, [363]),\n",
+ " (3, 19): (12, [362]),\n",
+ " (3, 20): (12, [361]),\n",
+ " (4, 20): (12, [360]),\n",
+ " (4, 19): (12, [359]),\n",
+ " (4, 18): (12, [358]),\n",
+ " (4, 17): (12, [357]),\n",
+ " (4, 16): (12, [356]),\n",
+ " (4, 15): (12, [355]),\n",
+ " (4, 14): (12, [354]),\n",
+ " (4, 13): (12, [353]),\n",
+ " (4, 12): (12, [352]),\n",
+ " (4, 11): (12, [351]),\n",
+ " (4, 10): (12, [350]),\n",
+ " (4, 9): (12, [349]),\n",
+ " (4, 39): (13, [414]),\n",
+ " (4, 38): (13, [413]),\n",
+ " (4, 37): (13, [412]),\n",
+ " (4, 36): (13, [411]),\n",
+ " (4, 35): (13, [410]),\n",
+ " (4, 34): (13, [409]),\n",
+ " (4, 33): (13, [408]),\n",
+ " (4, 32): (13, [407]),\n",
+ " (4, 31): (13, [406]),\n",
+ " (4, 30): (13, [405]),\n",
+ " (4, 29): (13, [404]),\n",
+ " (4, 28): (13, [403]),\n",
+ " (4, 27): (13, [402]),\n",
+ " (4, 26): (13, [401]),\n",
+ " (4, 25): (13, [400]),\n",
+ " (4, 24): (13, [399]),\n",
+ " (4, 23): (13, [398]),\n",
+ " (4, 22): (13, [397]),\n",
+ " (4, 21): (13, [396]),\n",
+ " (3, 21): (13, [395]),\n",
+ " (3, 22): (13, [394]),\n",
+ " (3, 23): (13, [393]),\n",
+ " (3, 24): (13, [392]),\n",
+ " (3, 25): (13, [391]),\n",
+ " (3, 26): (13, [390]),\n",
+ " (3, 27): (13, [389]),\n",
+ " (3, 28): (13, [388]),\n",
+ " (3, 29): (13, [387]),\n",
+ " (3, 30): (13, [386]),\n",
+ " (3, 31): (13, [385]),\n",
+ " (3, 32): (13, [384]),\n",
+ " (3, 33): (13, [383]),\n",
+ " (3, 34): (13, [382])}"
+ ]
+ },
+ "execution_count": 62,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "s=vh_vb.__dict__\n",
+ "scafs=s[\"_scaf\"]\n",
+ "staps=s[\"_stap\"]\n",
+ "staps"
]
},
{
"cell_type": "code",
- "execution_count": 30,
- "id": "051eb3b8-2bf1-4482-9815-19937f66e09d",
+ "execution_count": 3,
+ "id": "69c011ff",
"metadata": {},
"outputs": [],
"source": [
@@ -217,8 +885,8 @@
},
{
"cell_type": "code",
- "execution_count": 43,
- "id": "6e88e214-c870-47d1-9a47-504caa411530",
+ "execution_count": 4,
+ "id": "f2693e7a",
"metadata": {},
"outputs": [],
"source": [
@@ -238,30 +906,215 @@
},
{
"cell_type": "code",
- "execution_count": 57,
- "id": "326f70c5-6a80-4802-847a-ae0de82f0eda",
+ "execution_count": 20,
+ "id": "a4594752",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "'{\\n\"stapLoop\":[],\\n\"skip\":[],\\n\"loop\":[],\\n\"stap_colors\":[],\\n\"row\":0,\\n\"col\":0,\\n\"num\":0,\\n\"scafLoop\":[],\\n\"stap\":[[5, 1, -1, -1],[5, 2, 5, 0],[5, 3, 5, 1],[-1, -1, 5, 2],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[5, 10, 4, 9],[5, 11, 5, 9],[5, 12, 5, 10],[5, 13, 5, 11],[5, 14, 5, 12],[5, 15, 5, 13],[5, 16, 5, 14],[5, 17, 5, 15],[5, 18, 5, 16],[5, 19, 5, 17],[5, 20, 5, 18],[5, 21, 5, 19],[5, 22, 5, 20],[-1, -1, 5, 21],[5, 24, -1, -1],[5, 25, 5, 23],[5, 26, 5, 24],[5, 27, 5, 25],[5, 28, 5, 26],[5, 29, 5, 27],[5, 30, 5, 28],[5, 31, 5, 29],[5, 32, 5, 30],[5, 33, 5, 31],[5, 34, 5, 32],[5, 35, 5, 33],[5, 36, 5, 34],[5, 37, 5, 35],[5, 38, 5, 36],[5, 39, 5, 37],[4, 39, 5, 38],[-1, -1, -1, -1],[-1, -1, -1, -1]],\\n\"scaf\":[[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1],[-1, -1, 5, 10],[5, 9, 5, 11],[5, 10, 5, 12],[5, 11, 5, 13],[5, 12, 5, 14],[5, 13, 5, 15],[5, 14, 5, 16],[5, 15, 5, 17],[5, 16, 5, 18],[5, 17, 5, 19],[5, 18, 5, 20],[5, 19, 5, 21],[5, 20, 5, 22],[5, 21, 5, 23],[5, 22, 5, 24],[5, 23, 5, 25],[5, 24, 5, 26],[5, 25, 5, 27],[5, 26, 0, 27],[0, 28, 5, 29],[5, 28, 5, 30],[5, 29, 5, 31],[5, 30, 5, 32],[5, 31, 5, 33],[5, 32, 5, 34],[5, 33, 5, 35],[5, 34, 5, 36],[5, 35, 5, 37],[5, 36, 5, 38],[5, 37, 5, 39],[5, 38, -1, -1],[-1, -1, -1, -1],[-1, -1, -1, -1]]\\n}'"
+ "['__class__',\n",
+ " '__delattr__',\n",
+ " '__dict__',\n",
+ " '__dir__',\n",
+ " '__doc__',\n",
+ " '__eq__',\n",
+ " '__format__',\n",
+ " '__ge__',\n",
+ " '__getattribute__',\n",
+ " '__gt__',\n",
+ " '__hash__',\n",
+ " '__init__',\n",
+ " '__init_subclass__',\n",
+ " '__le__',\n",
+ " '__lt__',\n",
+ " '__module__',\n",
+ " '__ne__',\n",
+ " '__new__',\n",
+ " '__reduce__',\n",
+ " '__reduce_ex__',\n",
+ " '__repr__',\n",
+ " '__setattr__',\n",
+ " '__sizeof__',\n",
+ " '__str__',\n",
+ " '__subclasshook__',\n",
+ " '__weakref__',\n",
+ " 'add_square',\n",
+ " 'cad_index',\n",
+ " 'col',\n",
+ " 'get_length',\n",
+ " 'len',\n",
+ " 'loop',\n",
+ " 'num',\n",
+ " 'row',\n",
+ " 'scaf',\n",
+ " 'scafLoop',\n",
+ " 'skip',\n",
+ " 'skiploop_bases',\n",
+ " 'stap',\n",
+ " 'stapLoop',\n",
+ " 'stap_colors']"
]
},
- "execution_count": 57,
+ "execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"s0=cadsys.vhelices[0]\n",
- "s0.__str__()"
+ "dir(s0)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "id": "ca071163",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[[-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, 5, 10],\n",
+ " [5, 9, 5, 11],\n",
+ " [5, 10, 5, 12],\n",
+ " [5, 11, 5, 13],\n",
+ " [5, 12, 5, 14],\n",
+ " [5, 13, 5, 15],\n",
+ " [5, 14, 5, 16],\n",
+ " [5, 15, 5, 17],\n",
+ " [5, 16, 5, 18],\n",
+ " [5, 17, 5, 19],\n",
+ " [5, 18, 5, 20],\n",
+ " [5, 19, 5, 21],\n",
+ " [5, 20, 5, 22],\n",
+ " [5, 21, 5, 23],\n",
+ " [5, 22, 5, 24],\n",
+ " [5, 23, 5, 25],\n",
+ " [5, 24, 5, 26],\n",
+ " [5, 25, 5, 27],\n",
+ " [5, 26, 0, 27],\n",
+ " [0, 28, 5, 29],\n",
+ " [5, 28, 5, 30],\n",
+ " [5, 29, 5, 31],\n",
+ " [5, 30, 5, 32],\n",
+ " [5, 31, 5, 33],\n",
+ " [5, 32, 5, 34],\n",
+ " [5, 33, 5, 35],\n",
+ " [5, 34, 5, 36],\n",
+ " [5, 35, 5, 37],\n",
+ " [5, 36, 5, 38],\n",
+ " [5, 37, 5, 39],\n",
+ " [5, 38, -1, -1],\n",
+ " [-1, -1, -1, -1],\n",
+ " [-1, -1, -1, -1]]"
+ ]
+ },
+ "execution_count": 25,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "s0.scaf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "e5913163",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "for s in s0.scaf:\n",
+ " if s[0]==-1 and s[1]==-1:\n",
+ " pass\n",
+ " elif s[2]==len(s0.scaf) and abs(s[3])==1"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "3eefca8f",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[-1, -1, -1, -1]"
+ ]
+ },
+ "execution_count": 13,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "s0.scaf[0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "268d5c04",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "['__class__',\n",
+ " '__delattr__',\n",
+ " '__dict__',\n",
+ " '__dir__',\n",
+ " '__doc__',\n",
+ " '__eq__',\n",
+ " '__format__',\n",
+ " '__ge__',\n",
+ " '__getattribute__',\n",
+ " '__gt__',\n",
+ " '__hash__',\n",
+ " '__init__',\n",
+ " '__init_subclass__',\n",
+ " '__le__',\n",
+ " '__lt__',\n",
+ " '__module__',\n",
+ " '__ne__',\n",
+ " '__new__',\n",
+ " '__reduce__',\n",
+ " '__reduce_ex__',\n",
+ " '__repr__',\n",
+ " '__setattr__',\n",
+ " '__sizeof__',\n",
+ " '__str__',\n",
+ " '__subclasshook__',\n",
+ " '__weakref__',\n",
+ " 'add_vhelix',\n",
+ " 'bbox',\n",
+ " 'vhelices']"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "dir(cadsys)"
]
},
{
"cell_type": "code",
"execution_count": 36,
- "id": "7b552911-d7de-4079-ab4d-e859f2281f36",
+ "id": "d3d42e33",
"metadata": {},
"outputs": [
{
@@ -323,7 +1176,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "94113dfa",
+ "id": "2cc3f477",
"metadata": {},
"outputs": [
{
@@ -349,7 +1202,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "ec7f1e22-6a95-41f9-8c23-7603cc165837",
+ "id": "5d50f58a",
"metadata": {},
"outputs": [],
"source": []
@@ -357,7 +1210,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "id": "40d7cdcf",
+ "id": "3b40b71b",
"metadata": {},
"outputs": [
{
@@ -377,7 +1230,7 @@
{
"cell_type": "code",
"execution_count": 13,
- "id": "4b3748a8",
+ "id": "6915bad6",
"metadata": {},
"outputs": [
{
@@ -398,7 +1251,7 @@
{
"cell_type": "code",
"execution_count": 15,
- "id": "aa8a8cd9",
+ "id": "1c16c59d",
"metadata": {},
"outputs": [
{
@@ -468,7 +1321,7 @@
{
"cell_type": "code",
"execution_count": 16,
- "id": "e0cab15d",
+ "id": "c61d9586",
"metadata": {},
"outputs": [],
"source": [
@@ -479,7 +1332,7 @@
{
"cell_type": "code",
"execution_count": 26,
- "id": "9811bf9a",
+ "id": "aeca0546",
"metadata": {},
"outputs": [
{
@@ -588,7 +1441,7 @@
{
"cell_type": "code",
"execution_count": 25,
- "id": "86403b4b",
+ "id": "90a54834",
"metadata": {},
"outputs": [
{
@@ -609,7 +1462,7 @@
{
"cell_type": "code",
"execution_count": 10,
- "id": "5c7cea80",
+ "id": "de00fb7e",
"metadata": {},
"outputs": [
{
@@ -640,7 +1493,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "136dcf08",
+ "id": "716ff2ed",
"metadata": {},
"outputs": [
{
@@ -1137,7 +1990,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "id": "88f7d20e",
+ "id": "766d0ecd",
"metadata": {},
"outputs": [
{
@@ -1171,7 +2024,7 @@
{
"cell_type": "code",
"execution_count": 4,
- "id": "69d29f1e",
+ "id": "05456be4",
"metadata": {},
"outputs": [
{
@@ -1191,7 +2044,7 @@
{
"cell_type": "code",
"execution_count": 5,
- "id": "e103e8b4",
+ "id": "cd1a5604",
"metadata": {},
"outputs": [],
"source": [
@@ -1201,7 +2054,7 @@
{
"cell_type": "code",
"execution_count": 6,
- "id": "a30b582d",
+ "id": "4346f1fc",
"metadata": {},
"outputs": [
{
@@ -1222,7 +2075,7 @@
{
"cell_type": "code",
"execution_count": 7,
- "id": "dcd8bf8a",
+ "id": "294094f9",
"metadata": {},
"outputs": [
{
@@ -1249,7 +2102,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "bf20c9ef",
+ "id": "b3d29c52",
"metadata": {},
"outputs": [],
"source": []
@@ -1257,7 +2110,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3 (ipykernel)",
+ "display_name": "Python 3",
"language": "python",
"name": "python3"
},
@@ -1271,7 +2124,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.19"
+ "version": "3.8.18"
}
},
"nbformat": 4,
diff --git a/mrdna/readers/test.json.oxdna b/mrdna/readers/test.json.oxdna
new file mode 100644
index 0000000..22b3082
--- /dev/null
+++ b/mrdna/readers/test.json.oxdna
@@ -0,0 +1,418 @@
+t = 0
+b = 59.840000 59.840000 59.840000
+E = 0.000000 0.000000 0.000000
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diff --git a/mrdna/readers/test.json.top b/mrdna/readers/test.json.top
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diff --git a/mrdna/readers/test.virt2nuc b/mrdna/readers/test.virt2nuc
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diff --git a/mrdna/readers/test2.ipynb b/mrdna/readers/test2.ipynb
new file mode 100644
index 0000000..2fcb4e5
--- /dev/null
+++ b/mrdna/readers/test2.ipynb
@@ -0,0 +1,973 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "9ea65628",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " _\n",
+ " _____ ___ _| |___ ___\n",
+ "| | _| . | | .'|\n",
+ "|_|_|_|_| |___|_|_|__,| v1.0a.dev74 \n",
+ "it/its\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "\n",
+ "\n",
+ "from mrdna.readers.cadnano_segments import *\n",
+ "from cadnano.document import Document\n",
+ "import cadnano"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 27,
+ "id": "f07e1b32",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Found cadnano version 2 file\n"
+ ]
+ }
+ ],
+ "source": [
+ "json_data=read_json_file(\"test.json\")\n",
+ "part=decode_cadnano_part(json_data)\n",
+ "model=cadnano_part(part)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "id": "a4d48fe0",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Found cadnano version 2 file\n"
+ ]
+ }
+ ],
+ "source": [
+ "doc=Document()\n",
+ "cadnano.fileio.v2decode.decode(doc, json_data)\n",
+ "parts = [p for p in doc.getParts()]\n",
+ "part=parts[0]\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "id": "03d8b6e7",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Oligo_(5.1[22])_2224\t188\t'None\n",
+ "Oligo_(4.1[39])_7104\t33\t'None\n",
+ "Oligo_(2.1[34])_8976\t35\t'None\n",
+ "Oligo_(5.0[9])_4592\t23\t'None\n",
+ "Oligo_(0.0[39])_2544\t3\t'None\n",
+ "Oligo_(3.1[41])_5568\t5\t'None\n",
+ "Oligo_(1.0[3])_3184\t37\t'None\n",
+ "Oligo_(0.1[38])_5296\t23\t'None\n",
+ "Oligo_(4.0[0])_8128\t4\t'None\n",
+ "Oligo_(3.0[0])_6400\t33\t'None\n",
+ "Oligo_(2.0[39])_8208\t3\t'None\n",
+ "Oligo_(1.1[41])_1888\t3\t'None\n",
+ "Oligo_(0.1[23])_3888\t21\t'None\n",
+ "Oligo_(5.1[3])_1120\t4\t'None\n",
+ "VH0\n",
+ "\t <fwd_StrandSet(0)> \t [(5, 36), (39, 41)] \n",
+ "\t\t\t\t ['#0066cc', '#0066cc']\n",
+ "\t <rev_StrandSet(0)> \t [(2, 20), (21, 23), (24, 27), (28, 38)] \n",
+ "\t\t\t\t ['#cc0000', '#b8056c', '#f74308', '#1700de']\n",
+ "VH1\n",
+ "\t <fwd_StrandSet(1)> \t [(3, 20), (21, 38)] \n",
+ "\t\t\t\t ['#cc0000', '#b8056c']\n",
+ "\t <rev_StrandSet(1)> \t [(5, 18), (19, 36), (39, 41)] \n",
+ "\t\t\t\t ['#0066cc', '#0066cc', '#0066cc']\n",
+ "VH2\n",
+ "\t <fwd_StrandSet(2)> \t [(2, 18), (19, 32), (39, 41)] \n",
+ "\t\t\t\t ['#0066cc', '#0066cc', '#0066cc']\n",
+ "\t <rev_StrandSet(2)> \t [(0, 34)] \n",
+ "\t\t\t\t ['#888888']\n",
+ "VH3\n",
+ "\t <fwd_StrandSet(3)> \t [(0, 20), (21, 34)] \n",
+ "\t\t\t\t ['#cc0000', '#888888']\n",
+ "\t <rev_StrandSet(3)> \t [(2, 15), (16, 32), (37, 41)] \n",
+ "\t\t\t\t ['#0066cc', '#0066cc', '#0066cc']\n",
+ "VH4\n",
+ "\t <fwd_StrandSet(4)> \t [(0, 3), (9, 15), (16, 39)] \n",
+ "\t\t\t\t ['#0066cc', '#0066cc', '#0066cc']\n",
+ "\t <rev_StrandSet(4)> \t [(9, 20), (21, 39)] \n",
+ "\t\t\t\t ['#cc0000', '#888888']\n",
+ "VH5\n",
+ "\t <fwd_StrandSet(5)> \t [(9, 27), (28, 39)] \n",
+ "\t\t\t\t ['#f74308', '#1700de']\n",
+ "\t <rev_StrandSet(5)> \t [(0, 3), (9, 22), (23, 39)] \n",
+ "\t\t\t\t ['#0066cc', '#0066cc', '#0066cc']\n"
+ ]
+ }
+ ],
+ "source": [
+ "part.__dict__.keys()\n",
+ "\n",
+ "oligos = part.oligos()\n",
+ "for oligo in oligos:\n",
+ " print(\"{0}\\t{1}\\t\\'{2}\".format(oligo,\n",
+ " oligo.length(),\n",
+ " oligo.sequence()))\n",
+ "\n",
+ "vhs = list(part.getIdNums()) # convert set to list\n",
+ "for vh_id in vhs: # display first 3 vhs\n",
+ " fwd_ss, rev_ss = part.getStrandSets(vh_id)\n",
+ " print('VH{0}'.format(vh_id))\n",
+ " print('\\t', fwd_ss, '\\t', [s.idxs() for s in fwd_ss.strands()], '\\n\\t\\t\\t\\t',\n",
+ " [s.getColor() for s in fwd_ss.strands()])\n",
+ " print('\\t', rev_ss, '\\t', [s.idxs() for s in rev_ss.strands()], '\\n\\t\\t\\t\\t',\n",
+ " [s.getColor() for s in rev_ss.strands()])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "884f07ed",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "id": "1e934f2b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "strands5 = [o.strand5p() for o in part.oligos()]\n",
+ "strands3 = [o.strand3p() for o in part.oligos()]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 35,
+ "id": "e5b59a91",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{'_part': NucleicAcidPart_-1_7520,\n",
+ " '_strand5p': <rev_StrandSet(4)>.<Strand(21, 39)>,\n",
+ " '_is_circular': False,\n",
+ " '_props': {'name': 'oligo7104',\n",
+ " 'color': '#888888',\n",
+ " 'length': 33,\n",
+ " 'is_visible': True}}"
+ ]
+ },
+ "execution_count": 35,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "L=[o for o in part.oligos()]\n",
+ "\n",
+ "L[1].__dict__"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 36,
+ "id": "78ecf1e1",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "['__class__',\n",
+ " '__delattr__',\n",
+ " '__dict__',\n",
+ " '__dir__',\n",
+ " '__doc__',\n",
+ " '__eq__',\n",
+ " '__format__',\n",
+ " '__ge__',\n",
+ " '__getattribute__',\n",
+ " '__gt__',\n",
+ " '__hash__',\n",
+ " '__init__',\n",
+ " '__init_subclass__',\n",
+ " '__le__',\n",
+ " '__lt__',\n",
+ " '__module__',\n",
+ " '__ne__',\n",
+ " '__new__',\n",
+ " '__reduce__',\n",
+ " '__reduce_ex__',\n",
+ " '__repr__',\n",
+ " '__setattr__',\n",
+ " '__sizeof__',\n",
+ " '__slots__',\n",
+ " '__str__',\n",
+ " '__subclasshook__',\n",
+ " '__weakref__',\n",
+ " '_decrementLength',\n",
+ " '_incrementLength',\n",
+ " '_is_circular',\n",
+ " '_parent',\n",
+ " '_part',\n",
+ " '_props',\n",
+ " '_setColor',\n",
+ " '_setLength',\n",
+ " '_setLoop',\n",
+ " '_setProperty',\n",
+ " '_signals',\n",
+ " '_strand5p',\n",
+ " '_strandMergeUpdate',\n",
+ " '_strandSplitUpdate',\n",
+ " 'addToPart',\n",
+ " 'applyAbstractSequences',\n",
+ " 'applyColor',\n",
+ " 'applySequence',\n",
+ " 'applySequenceCMD',\n",
+ " 'clearAbstractSequences',\n",
+ " 'connect',\n",
+ " 'deleteLater',\n",
+ " 'destroy',\n",
+ " 'disconnect',\n",
+ " 'displayAbstractSequences',\n",
+ " 'dump',\n",
+ " 'editable_properties',\n",
+ " 'getAbsolutePositionAtLength',\n",
+ " 'getColor',\n",
+ " 'getModelProperties',\n",
+ " 'getName',\n",
+ " 'getNumberOfBasesToEachXover',\n",
+ " 'getOutlineProperties',\n",
+ " 'getProperty',\n",
+ " 'getStrandLengths',\n",
+ " 'isCircular',\n",
+ " 'length',\n",
+ " 'locString',\n",
+ " 'oligoPropertyChangedSignal',\n",
+ " 'oligoRemovedSignal',\n",
+ " 'oligoSelectedChangedSignal',\n",
+ " 'oligoSequenceAddedSignal',\n",
+ " 'oligoSequenceClearedSignal',\n",
+ " 'parent',\n",
+ " 'part',\n",
+ " 'refreshLength',\n",
+ " 'remove',\n",
+ " 'removeFromPart',\n",
+ " 'sequence',\n",
+ " 'sequenceExport',\n",
+ " 'setParent',\n",
+ " 'setPart',\n",
+ " 'setProperty',\n",
+ " 'setStrand5p',\n",
+ " 'shallowCopy',\n",
+ " 'shouldHighlight',\n",
+ " 'signals',\n",
+ " 'splitAtAbsoluteLengths',\n",
+ " 'strand3p',\n",
+ " 'strand5p',\n",
+ " 'undoStack']"
+ ]
+ },
+ "execution_count": 36,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "dir(L[0])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "680d09ca",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{'name': 'NaPart1',\n",
+ " 'color': '#0066cc',\n",
+ " 'is_visible': True,\n",
+ " 'active_phos': None,\n",
+ " 'crossover_span_angle': 45,\n",
+ " 'max_vhelix_length': 42,\n",
+ " 'neighbor_active_angle': '',\n",
+ " 'grid_type': <GridEnum.HONEYCOMB: 2>,\n",
+ " 'virtual_helix_order': [0, 1, 2, 3, 4, 5],\n",
+ " 'is_lattice': True,\n",
+ " <GridEnum.HONEYCOMB: 2>: <GridEnum.NONE: 0>}"
+ ]
+ },
+ "execution_count": 10,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "part.getModelProperties()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "190a91a3",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " _\n",
+ " _____ ___ _| |___ ___\n",
+ "| | _| . | | .'|\n",
+ "|_|_|_|_| |___|_|_|__,| v1.0a.dev74 \n",
+ "it/its\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "import pdb\n",
+ "import numpy as np\n",
+ "import os,sys\n",
+ "import scipy\n",
+ "\n",
+ "from mrdna import logger, devlogger\n",
+ "from mrdna.segmentmodel import SegmentModel, SingleStrandedSegment, DoubleStrandedSegment\n",
+ "from mrdna.arbdmodel.coords import quaternion_from_matrix, rotationAboutAxis, quaternion_slerp\n",
+ "from mrdna import get_resource_path\n",
+ "\n",
+ "ref_stack_position = np.array((-2.41851735, -0.259761333, 3.39999978))\n",
+ "\n",
+ "def _three_prime_list_to_five_prime(three_prime):\n",
+ " five_prime = -np.ones(three_prime.shape, dtype=int)\n",
+ " has_three_prime = np.where(three_prime >= 0)[0]\n",
+ " five_prime[three_prime[has_three_prime]] = has_three_prime\n",
+ " return five_prime \n",
+ "def _primes_list_to_strands(three_prime, five_prime):\n",
+ " five_prime_ends = np.where(five_prime < 0)[0]\n",
+ " strands = []\n",
+ " strand_is_circular = []\n",
+ " \n",
+ " idx_to_strand = -np.ones(three_prime.shape, dtype=int)\n",
+ "\n",
+ " def build_strand(nt_idx, conditional):\n",
+ " strand = [nt_idx]\n",
+ " idx_to_strand[nt_idx] = len(strands)\n",
+ " while conditional(nt_idx):\n",
+ " nt_idx = three_prime[nt_idx]\n",
+ " strand.append(nt_idx)\n",
+ " idx_to_strand[nt_idx] = len(strands)\n",
+ " strands.append( np.array(strand, dtype=int) )\n",
+ "\n",
+ " for nt_idx in five_prime_ends:\n",
+ " build_strand(nt_idx,\n",
+ " lambda nt: three_prime[nt] >= 0)\n",
+ " strand_is_circular.append(False)\n",
+ "\n",
+ " while True:\n",
+ " ## print(\"WARNING: working on circular strand {}\".format(len(strands)))\n",
+ " ids = np.where(idx_to_strand < 0)[0]\n",
+ " if len(ids) == 0: break\n",
+ " build_strand(ids[0],\n",
+ " lambda nt: three_prime[nt] >= 0 and \\\n",
+ " idx_to_strand[three_prime[nt]] < 0)\n",
+ " strand_is_circular.append(True)\n",
+ "\n",
+ " return strands, strand_is_circular\n",
+ "\n",
+ "def find_stacks(centers, transforms):\n",
+ "\n",
+ " ## Find orientation and center of each nucleotide\n",
+ " expected_stack_positions = []\n",
+ " for R,c in zip(transforms,centers):\n",
+ " expected_stack_positions.append( c + ref_stack_position.dot(R) )\n",
+ "\n",
+ " expected_stack_positions = np.array(expected_stack_positions, dtype=np.float32)\n",
+ "\n",
+ " dists = scipy.spatial.distance_matrix(expected_stack_positions, centers)\n",
+ " dists = dists + 5*np.eye(len(dists))\n",
+ " idx1, idx2 = np.where(dists < 3.5)\n",
+ "\n",
+ " ## Convert distances to stacks\n",
+ " stacks_above = -np.ones(len(centers), dtype=int)\n",
+ " _z = np.array((0,0,1))\n",
+ " for i in np.unique(idx1):\n",
+ " js = idx2[ idx1 == i ]\n",
+ " with np.errstate(divide='ignore',invalid='ignore'):\n",
+ " angles = [np.arccos( transforms[j].T.dot( transforms[i].dot(_z) ).dot( _z ) ) for j in js]\n",
+ " angles = np.array( angles )\n",
+ " tmp = np.argmin(dists[i][js] + 1.0*angles)\n",
+ " j = js[tmp]\n",
+ " stacks_above[i] = j\n",
+ "\n",
+ " return stacks_above\n",
+ "\n",
+ "def basepairs_and_stacks_to_helixmap(basepairs,stacks_above):\n",
+ "\n",
+ " helixmap = -np.ones(basepairs.shape, dtype=int)\n",
+ " helixrank = -np.ones(basepairs.shape)\n",
+ " is_fwd = np.ones(basepairs.shape, dtype=int)\n",
+ " \n",
+ " ## Remove stacks with nts lacking a basepairs\n",
+ " nobp = np.where(basepairs < 0)[0]\n",
+ " stacks_above[nobp] = -1\n",
+ " stacks_with_nobp = np.in1d(stacks_above, nobp)\n",
+ " stacks_above[stacks_with_nobp] = -1\n",
+ "\n",
+ " end_ids = np.where( (stacks_above < 0)*(basepairs >= 0) )[0]\n",
+ "\n",
+ " hid = 0\n",
+ " for end in end_ids:\n",
+ " if helixmap[end] >= 0:\n",
+ " continue\n",
+ " rank = 0\n",
+ " nt = basepairs[end]\n",
+ " bp = basepairs[nt]\n",
+ " assert( bp == end )\n",
+ " if helixmap[nt] >= 0 or helixmap[bp] >= 0:\n",
+ " logger.warning(f'Ill-formed helix: problematic basepair or stacking data near nucleotide {nt} or {bp}... skipping')\n",
+ " continue\n",
+ " # assert(helixmap[nt] == -1)\n",
+ " # assert(helixmap[bp] == -1)\n",
+ " helixmap[nt] = helixmap[bp] = hid\n",
+ " helixrank[nt] = helixrank[bp] = rank\n",
+ " is_fwd[bp] = 0\n",
+ " rank +=1\n",
+ "\n",
+ " _tmp = [(nt,bp)]\n",
+ " \n",
+ " while stacks_above[nt] >= 0:\n",
+ " nt = stacks_above[nt]\n",
+ " if basepairs[nt] < 0: break\n",
+ " bp = basepairs[nt]\n",
+ " if helixmap[nt] >= 0 or helixmap[bp] >= 0:\n",
+ " logger.warning(f'Ill-formed helix: problematic basepair or stacking data near nucleotide {nt} or {bp}... skipping')\n",
+ " break\n",
+ " helixmap[nt] = helixmap[bp] = hid\n",
+ " helixrank[nt] = helixrank[bp] = rank\n",
+ " is_fwd[bp] = 0\n",
+ " _tmp.append((nt,bp))\n",
+ " rank +=1\n",
+ "\n",
+ " hid += 1\n",
+ "\n",
+ " ## Create \"helix\" for each circular segment\n",
+ " intrahelical = []\n",
+ " processed = set()\n",
+ " unclaimed_bases = np.where( (basepairs >= 0)*(helixmap == -1) )[0]\n",
+ " for nt0 in unclaimed_bases:\n",
+ " if nt0 in processed: continue\n",
+ "\n",
+ " nt = nt0\n",
+ " all_nts = [nt]\n",
+ "\n",
+ " rank = 0\n",
+ " nt = nt0\n",
+ " bp = basepairs[nt]\n",
+ " if helixmap[nt] >= 0 or helixmap[bp] >= 0:\n",
+ " logger.warning(f'Ill-formed cylic helix: problematic basepair or stacking data near nucleotide {nt} or {bp}... skipping')\n",
+ " continue\n",
+ " helixmap[nt] = helixmap[bp] = hid\n",
+ " helixrank[nt] = helixrank[bp] = rank\n",
+ " is_fwd[bp] = 0\n",
+ " rank +=1\n",
+ " processed.add(nt)\n",
+ " processed.add(bp)\n",
+ "\n",
+ " counter = 0\n",
+ " while stacks_above[nt] >= 0:\n",
+ " lastnt = nt\n",
+ " nt = stacks_above[nt]\n",
+ " bp = basepairs[nt]\n",
+ " if nt == nt0 or nt == basepairs[nt0]:\n",
+ " intrahelical.append((lastnt,nt0))\n",
+ " break\n",
+ " \n",
+ " assert( bp >= 0 )\n",
+ " if helixmap[nt] >= 0 or helixmap[bp] >= 0:\n",
+ " logger.warning(f'Ill-formed cyclic helix: problematic basepair or stacking data near nucleotide {nt} or {bp}... skipping')\n",
+ " break\n",
+ " \n",
+ " helixmap[nt] = helixmap[bp] = hid\n",
+ " helixrank[nt] = helixrank[bp] = rank\n",
+ " is_fwd[bp] = 0\n",
+ " processed.add(nt)\n",
+ " processed.add(bp)\n",
+ " rank +=1\n",
+ " hid += 1\n",
+ "\n",
+ " return helixmap, helixrank, is_fwd, intrahelical\n",
+ "\n",
+ "\n",
+ "def set_splines(seg, coordinate, hid, hmap, hrank, fwd, basepair, orientation=None):\n",
+ " maxrank = np.max( hrank[hmap==hid] )\n",
+ " if maxrank == 0:\n",
+ " ids = np.where((hmap == hid))[0]\n",
+ " pos = np.mean( [coordinate[r,:] for r in ids ], axis=0 )\n",
+ " coords = [pos,pos]\n",
+ " contours = [0,1]\n",
+ " if orientation is not None:\n",
+ " ids = np.where((hmap == hid) * fwd)[0]\n",
+ " assert( len(ids) == 1 )\n",
+ " q = quaternion_from_matrix( orientation[ids[0]] )\n",
+ " quats = [q, q]\n",
+ " coords[-1] = pos + orientation[ids[0]].dot(np.array((0,0,1)))\n",
+ "\n",
+ " else:\n",
+ " coords,contours,quats = [[],[],[]]\n",
+ " last_q = None\n",
+ " for rank in range(int(maxrank)+1):\n",
+ " ids = np.where((hmap == hid) * (hrank == rank))[0]\n",
+ " \n",
+ " coords.append(np.mean( [coordinate[r,:] for r in ids ], axis=0 ))\n",
+ " contours.append( float(rank+0.5)/(maxrank+1) )\n",
+ " if orientation is not None:\n",
+ " ids = np.where((hmap == hid) * (hrank == rank) * fwd)[0]\n",
+ " assert(len(ids) == 1)\n",
+ " q = quaternion_from_matrix( orientation[ids[0]] )\n",
+ "\n",
+ " if last_q is not None and last_q.dot(q) < 0:\n",
+ " q = -q\n",
+ "\n",
+ " ## Average quaterion with reverse direction\n",
+ " bp = basepair[ids[0]]\n",
+ " if bp >= 0:\n",
+ " bp_o = orientation[bp].dot(rotationAboutAxis(np.array((1,0,0)),180))\n",
+ " q2 = quaternion_from_matrix( bp_o )\n",
+ " if q.dot(q2) < 0:\n",
+ " q2 = -q2\n",
+ "\n",
+ " ## probably good enough, but slerp is better: q = (q + q2)*0.5\n",
+ " q = quaternion_slerp(q,q2,0.5)\n",
+ "\n",
+ " quats.append(q)\n",
+ " last_q = q\n",
+ "\n",
+ " coords = np.array(coords)\n",
+ " seg.set_splines(contours,coords)\n",
+ " if orientation is not None:\n",
+ " quats = np.array(quats)\n",
+ " seg.set_orientation_splines(contours,quats)\n",
+ "\n",
+ " seg.start_position = coords[0,:]\n",
+ " seg.end_position = coords[-1,:]\n",
+ "\n",
+ "\n",
+ "def model_from_basepair_stack_3prime(coordinate, basepair, stack, three_prime,\n",
+ " sequence=None, orientation=None,\n",
+ " max_basepairs_per_bead = 5,\n",
+ " max_nucleotides_per_bead = 5,\n",
+ " local_twist = False,\n",
+ " dimensions=(5000,5000,5000),\n",
+ " **model_parameters):\n",
+ " \"\"\" \n",
+ " Creates a SegmentModel object from lists of each nucleotide's\n",
+ " basepair, its stack (on 3' side) and its 3'-connected nucleotide\n",
+ "\n",
+ " The first argument should be an N-by-3 numpy array containing the\n",
+ " coordinate of each nucleotide, where N is the number of\n",
+ " nucleotides. The following three arguments should be integer lists\n",
+ " where the i-th element corresponds to the i-th nucleotide; the\n",
+ " list element should the integer index of the corresponding\n",
+ " basepaired / stacked / phosphodiester-bonded nucleotide. If there\n",
+ " is no such nucleotide, the value should be -1.\n",
+ "\n",
+ " Args:\n",
+ " basepair: List of each nucleotide's basepair's index\n",
+ " stack: List containing index of the nucleotide stacked on the 3' of each nucleotide\n",
+ " three_prime: List of each nucleotide's the 3' end of each nucleotide\n",
+ "\n",
+ " Returns:\n",
+ " SegmentModel\n",
+ " \"\"\"\n",
+ "\n",
+ " \"\"\" Validate Input \"\"\"\n",
+ " inputs = (basepair,three_prime)\n",
+ " try:\n",
+ " basepair,three_prime = [np.array(a,dtype=int) for a in inputs]\n",
+ " except:\n",
+ " raise TypeError(\"One or more of the input lists could not be converted into a numpy array\")\n",
+ " inputs = (basepair,three_prime)\n",
+ " coordinate = np.array(coordinate)\n",
+ "\n",
+ " if np.any( [len(a.shape) > 1 for a in inputs] ):\n",
+ " raise ValueError(\"One or more of the input lists has the wrong dimensionality\")\n",
+ "\n",
+ " if len(coordinate.shape) != 2:\n",
+ " raise ValueError(\"Coordinate array has the wrong dimensionality\")\n",
+ "\n",
+ " inputs = (coordinate,basepair,three_prime)\n",
+ " if not np.all(np.diff([len(a) for a in inputs]) == 0):\n",
+ " raise ValueError(\"Inputs are not the same length\")\n",
+ " \n",
+ " num_nt = len(basepair)\n",
+ " if sequence is not None and len(sequence) != num_nt:\n",
+ " raise ValueError(\"The 'sequence' parameter is the wrong length {} != {}\".format(len(sequence),num_nt))\n",
+ "\n",
+ " if orientation is not None:\n",
+ " orientation = np.array(orientation)\n",
+ " if len(orientation.shape) != 3:\n",
+ " raise ValueError(\"The 'orientation' array has the wrong dimensionality (should be Nx3x3)\")\n",
+ " if orientation.shape != (num_nt,3,3):\n",
+ " raise ValueError(\"The 'orientation' array is not properly formatted\")\n",
+ "\n",
+ " if stack is None:\n",
+ " if orientation is not None:\n",
+ " stack = find_stacks(coordinate, orientation)\n",
+ " else:\n",
+ " ## Guess stacking based on 3' connectivity\n",
+ " stack = np.array(three_prime,dtype=int) # Assume nts on 3' ends are stacked\n",
+ " _stack_below = _three_prime_list_to_five_prime(stack)\n",
+ " _has_bp = (basepair >= 0)\n",
+ " _nostack = np.where( (stack == -1)*_has_bp )[0]\n",
+ " _has_stack_below = _stack_below[basepair[_nostack]] >= 0\n",
+ " _nostack2 = _nostack[_has_stack_below]\n",
+ " stack[_nostack2] = basepair[_stack_below[basepair[_nostack2]]]\n",
+ "\n",
+ " else:\n",
+ " try:\n",
+ " stack = np.array(stack,dtype=int)\n",
+ " except:\n",
+ " raise TypeError(\"The 'stack' array could not be converted into a numpy integer array\")\n",
+ "\n",
+ " if len(stack.shape) != 1:\n",
+ " raise ValueError(\"The 'stack' array has the wrong dimensionality\")\n",
+ "\n",
+ " if len(stack) != num_nt:\n",
+ " raise ValueError(\"The length of the 'stack' array does not match other inputs\")\n",
+ "\n",
+ " bps = basepair # alias\n",
+ "\n",
+ " \"\"\" Fix stacks: require that the stack of a bp of a base's stack is its bp \"\"\"\n",
+ " _has_bp = (bps >= 0)\n",
+ " _has_stack = (stack >= 0)\n",
+ " _stack_has_basepair = (bps[stack] >= 0) * _has_stack\n",
+ " stack = np.where( (stack[bps[stack]] == bps) * _has_bp * _has_stack * _has_bp,\n",
+ " stack, -np.ones(len(stack),dtype=int) )\n",
+ "\n",
+ " five_prime = _three_prime_list_to_five_prime(three_prime)\n",
+ "\n",
+ " \"\"\" Build map of dsDNA helices and strands \"\"\"\n",
+ " hmap,hrank,fwd,intrahelical = basepairs_and_stacks_to_helixmap(bps,stack)\n",
+ " double_stranded_helices = np.unique(hmap[hmap >= 0]) \n",
+ " strands, strand_is_circular = _primes_list_to_strands(three_prime, five_prime)\n",
+ "\n",
+ " \"\"\" Add ssDNA to hmap \"\"\"\n",
+ " if len(double_stranded_helices) > 0:\n",
+ " hid = double_stranded_helices[-1]+1\n",
+ " else:\n",
+ " hid = 0\n",
+ " ss_residues = hmap < 0\n",
+ " #\n",
+ " if np.any(bps[ss_residues] != -1):\n",
+ " logger.warning(f'{np.sum(bps[ss_residues] != -1)} ssDNA nucleotides appear to have basepairs... ignoring')\n",
+ " \n",
+ " for s,c in zip(strands, strand_is_circular):\n",
+ " strand_segment_ends = [i for i in np.where( np.diff(hmap[s]) != 0 )[0]] + [len(s)-1]\n",
+ " seg_start = 0\n",
+ " for i in strand_segment_ends:\n",
+ " if hmap[s[i]] < 0:\n",
+ " ## Found single-stranded segment\n",
+ " ids = s[seg_start:i+1]\n",
+ " assert( np.all(hmap[ids] == -1) )\n",
+ " hmap[ids] = hid\n",
+ " hrank[ids] = np.arange(i+1-seg_start)\n",
+ " hid+=1\n",
+ " seg_start = i+1\n",
+ "\n",
+ " if len(double_stranded_helices) > 0:\n",
+ " single_stranded_helices = np.arange(double_stranded_helices[-1]+1,hid)\n",
+ " else:\n",
+ " single_stranded_helices = np.arange(hid)\n",
+ "\n",
+ " ## Create double-stranded segments\n",
+ " doubleSegments = []\n",
+ " for hid in double_stranded_helices:\n",
+ " seg = DoubleStrandedSegment(name=str(hid),\n",
+ " num_bp = np.sum(hmap==hid)//2)\n",
+ " set_splines(seg, coordinate, hid, hmap, hrank, fwd, basepair, orientation)\n",
+ "\n",
+ " assert(hid == len(doubleSegments))\n",
+ " doubleSegments.append(seg)\n",
+ "\n",
+ " ## Create single-stranded segments\n",
+ " singleSegments = []\n",
+ " for hid in single_stranded_helices:\n",
+ " seg = SingleStrandedSegment(name=str(hid),\n",
+ " num_nt = np.sum(hmap==hid))\n",
+ " set_splines(seg, coordinate, hid, hmap, hrank, fwd, basepair, orientation)\n",
+ "\n",
+ " assert(hid == len(doubleSegments) + len(singleSegments))\n",
+ " singleSegments.append(seg)\n",
+ "\n",
+ " ## Find crossovers and 5prime/3prime ends\n",
+ " crossovers,prime5,prime3 = [[],[],[]]\n",
+ " for s,c in zip(strands,strand_is_circular):\n",
+ " tmp = np.where(np.diff(hmap[s]) != 0)[0]\n",
+ " for i in tmp:\n",
+ " crossovers.append( (s[i],s[i+1]) )\n",
+ " if c:\n",
+ " if hmap[s[-1]] != hmap[s[0]]:\n",
+ " crossovers.append( (s[-1],s[0]) )\n",
+ " else:\n",
+ " prime5.append(s[0])\n",
+ " prime3.append(s[-1])\n",
+ "\n",
+ " ## Add connections\n",
+ " allSegments = doubleSegments+singleSegments\n",
+ "\n",
+ " for r1,r2 in crossovers:\n",
+ " seg1,seg2 = [allSegments[hmap[i]] for i in (r1,r2)]\n",
+ " nt1,nt2 = [hrank[i] for i in (r1,r2)]\n",
+ " f1,f2 = [fwd[i] for i in (r1,r2)]\n",
+ "\n",
+ " ## Handle connections at the ends\n",
+ " is_terminal1 = (nt1,f1) in ((0,0),(seg1.num_nt-1,1))\n",
+ " is_terminal2 = (nt2,f2) in ((0,1),(seg2.num_nt-1,0))\n",
+ "\n",
+ " print(seg1,seg2, r1, r2, is_terminal1, is_terminal2)\n",
+ " if is_terminal1 or is_terminal2:\n",
+ " \"\"\" Ensure that we don't have three-way dsDNA junctions \"\"\"\n",
+ " if is_terminal1 and (bps[r1] >= 0) and (five_prime[bps[r1]] >= 0) and (three_prime[r1] >= 0):\n",
+ " if (bps[five_prime[bps[r1]]] >= 0) and (bps[three_prime[r1]] >= 0):\n",
+ " # is_terminal1 = (three_prime[r1] == bps[five_prime[bps[r1]]])\n",
+ " is_terminal1 = hmap[five_prime[bps[r1]]] == hmap[three_prime[r1]]\n",
+ " if is_terminal2 and (bps[r2] >= 0) and (three_prime[bps[r2]] >= 0) and (five_prime[r2] >= 0):\n",
+ " if (bps[three_prime[bps[r2]]] >= 0) and (bps[five_prime[r2]] >= 0):\n",
+ " # is_terminal2 = (five_prime[r2] == bps[three_prime[bps[r2]]])\n",
+ " is_terminal2 = hmap[three_prime[bps[r2]]] == hmap[five_prime[r2]]\n",
+ " \n",
+ " \"\"\" Place connection \"\"\"\n",
+ " if is_terminal1 and is_terminal2:\n",
+ " end1 = seg1.end3 if f1 else seg1.start3\n",
+ " end2 = seg2.start5 if f2 else seg2.end5\n",
+ " seg1._connect_ends( end1, end2, type_='intrahelical')\n",
+ " else:\n",
+ " seg1.add_crossover(nt1,seg2,nt2,[f1,f2],type_=\"terminal_crossover\")\n",
+ " else:\n",
+ " seg1.add_crossover(nt1,seg2,nt2,[f1,f2])\n",
+ "\n",
+ " ## Add 5prime/3prime ends\n",
+ " for r in prime5:\n",
+ " seg = allSegments[hmap[r]]\n",
+ " seg.add_5prime(hrank[r],fwd[r])\n",
+ " for r in prime3:\n",
+ " seg = allSegments[hmap[r]]\n",
+ " seg.add_3prime(hrank[r],fwd[r])\n",
+ "\n",
+ " ## Add intrahelical connections to circular helical sections\n",
+ " for nt0,nt1 in intrahelical:\n",
+ " seg = allSegments[hmap[nt0]]\n",
+ " assert( seg is allSegments[hmap[nt1]] )\n",
+ " if three_prime[nt0] >= 0:\n",
+ " if hmap[nt0] == hmap[three_prime[nt0]]:\n",
+ " seg.connect_end3(seg.start5)\n",
+ "\n",
+ " bp0,bp1 = [bps[nt] for nt in (nt0,nt1)]\n",
+ " if three_prime[bp1] >= 0:\n",
+ " if hmap[bp1] == hmap[three_prime[bp1]]:\n",
+ " seg.connect_start3(seg.end5)\n",
+ "\n",
+ " ## Assign sequence\n",
+ " if sequence is not None:\n",
+ " for hid in range(len(allSegments)):\n",
+ " resids = np.where( (hmap==hid)*(fwd==1) )[0]\n",
+ " s = allSegments[hid]\n",
+ " s.sequence = [sequence[r] for r in sorted(resids,key=lambda x: hrank[x])]\n",
+ "\n",
+ "\n",
+ " ## Build model\n",
+ " model = SegmentModel( allSegments,\n",
+ " max_basepairs_per_bead = max_basepairs_per_bead,\n",
+ " max_nucleotides_per_bead = max_nucleotides_per_bead,\n",
+ " local_twist = local_twist,\n",
+ " dimensions = dimensions,\n",
+ " **model_parameters )\n",
+ "\n",
+ "\n",
+ " model._reader_list_coordinates = coordinate\n",
+ " model._reader_list_basepair = basepair\n",
+ " model._reader_list_stack = stack\n",
+ " model._reader_list_three_prime = three_prime\n",
+ " model._reader_list_five_prime = five_prime\n",
+ " model._reader_list_sequence = sequence\n",
+ " model._reader_list_orientation = orientation\n",
+ " model._reader_list_hmap = hmap\n",
+ " model._reader_list_fwd = fwd\n",
+ " model._reader_list_hrank = hrank\n",
+ "\n",
+ " if sequence is None:\n",
+ " for s in model.segments:\n",
+ " s.randomize_unset_sequence()\n",
+ "\n",
+ " return model\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "ba82a4ed",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<DoubleStrandedSegment'> 1[1]> <DoubleStrandedSegment'> 0[1]> 5 3 True True\n",
+ "<SingleStrandedSegment'> 2[2]> <DoubleStrandedSegment'> 0[1]> 1 2 True True\n",
+ "<DoubleStrandedSegment'> 0[1]> <DoubleStrandedSegment'> 1[1]> 2 4 True True\n",
+ "<DoubleStrandedSegment'> 1[1]> <SingleStrandedSegment'> 3[1]> 4 6 True True\n",
+ "<SingleStrandedSegment'> 3[1]> <SingleStrandedSegment'> 2[2]> 6 0 True True\n"
+ ]
+ }
+ ],
+ "source": [
+ "coordinate = [(0,0,3.4*i) for i in range(7)]\n",
+ "three_prime = [ 1, 2, 4,-1, 6, 3, 0]\n",
+ "basepair = [-1,-1, 3, 2, 5, 4,-1]\n",
+ "stack = [-1,-1, -1,-1,-1, -1,-1]\n",
+ "for i in [3,5]:\n",
+ " coordinate[i] = (1,0,3.4*i)\n",
+ "\n",
+ "model = model_from_basepair_stack_3prime(coordinate, basepair, stack, three_prime,\n",
+ " max_basepairs_per_bead=1,\n",
+ " max_nucleotides_per_bead=1,\n",
+ " local_twist=False)\n",
+ "model.writePsf(\"list.psf\")\n",
+ "model.writePdb(\"list.pdb\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "79e8a471",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[[<SegmentParticle DNA on <DoubleStrandedSegment'> 0[1]>[1.00]>], [<SegmentParticle DNA on <DoubleStrandedSegment'> 1[1]>[0.00]>, <SegmentParticle DNA on <DoubleStrandedSegment'> 1[1]>[1.00]>], [<SegmentParticle NAS on <SingleStrandedSegment'> 2[2]>[0.00]>, <SegmentParticle NAS on <SingleStrandedSegment'> 2[2]>[0.50]>, <SegmentParticle NAS on <SingleStrandedSegment'> 2[2]>[1.00]>], [<SegmentParticle NAS on <SingleStrandedSegment'> 3[1]>[0.50]>]]\n",
+ "[[<Connection <Location 1.end3[0,on_fwd_strand]>--intrahelical--<Location 0.end5[0,on_fwd_strand]>]>, <Connection <Location 2.end3[1,on_fwd_strand]>--sscrossover--<Location 0.end5[0,on_rev_strand]>]>, <Connection <Location 0.end3[0,on_rev_strand]>--intrahelical--<Location 1.end5[0,on_rev_strand]>]>], [<Connection <Location 1.end3[0,on_fwd_strand]>--intrahelical--<Location 0.end5[0,on_fwd_strand]>]>, <Connection <Location 0.end3[0,on_rev_strand]>--intrahelical--<Location 1.end5[0,on_rev_strand]>]>, <Connection <Location 1.end3[0,on_rev_strand]>--intrahelical--<Location 3.end5[0,on_fwd_strand]>]>], [<Connection <Location 2.end3[1,on_fwd_strand]>--sscrossover--<Location 0.end5[0,on_rev_strand]>]>, <Connection <Location 3.end3[0,on_fwd_strand]>--intrahelical--<Location 2.end5[0,on_fwd_strand]>]>], [<Connection <Location 1.end3[0,on_rev_strand]>--intrahelical--<Location 3.end5[0,on_fwd_strand]>]>, <Connection <Location 3.end3[0,on_fwd_strand]>--intrahelical--<Location 2.end5[0,on_fwd_strand]>]>]]\n"
+ ]
+ }
+ ],
+ "source": [
+ "print([i.children for i in model.children])\n",
+ "print([i.connections for i in model.children])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "71b7ffdc",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "s=model.children[0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "f7c95c63",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'0'"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "s.segname"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "e905bb35",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[(0, 0, 0.0),\n",
+ " (0, 0, 3.4),\n",
+ " (0, 0, 6.8),\n",
+ " (1, 0, 10.2),\n",
+ " (0, 0, 13.6),\n",
+ " (1, 0, 17.0),\n",
+ " (0, 0, 20.4)]"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "coordinate"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "8964b3a5",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.8.18"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
--
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