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Merge pull request #8 from hyanwong/ARG
Add the 2 "What is an ARG" workbooks
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‎content/WhatIsAnARG_module.py‎

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import collections
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import itertools
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import sys
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import numpy as np
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from IPython.display import HTML
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def remove_edges(ts, edge_id_remove_list):
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edges_to_remove_by_child = collections.defaultdict(list)
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edge_id_remove_list = set(edge_id_remove_list)
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for m in ts.mutations():
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if m.edge in edge_id_remove_list:
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# If we remove this edge, we will remove the associated mutation
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# as the child node won't have ancestral material in this region.
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# So we force the user to explicitly (re)move the mutations beforehand
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raise ValueError("Cannot remove edges that have associated mutations")
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for remove_edge in edge_id_remove_list:
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e = ts.edge(remove_edge)
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edges_to_remove_by_child[e.child].append(e)
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# sort left-to-right for each child
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for k, v in edges_to_remove_by_child.items():
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edges_to_remove_by_child[k] = sorted(v, key=lambda e: e.left)
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# check no overlaps
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for e1, e2 in zip(edges_to_remove_by_child[k], edges_to_remove_by_child[k][1:]):
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assert e1.right <= e2.left
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# Sanity check: this means the topmost node will deal with modified edges left at the end
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assert ts.edge(-1).parent not in edges_to_remove_by_child
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new_edges = collections.defaultdict(list)
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tables = ts.dump_tables()
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tables.edges.clear()
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samples = set(ts.samples())
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# Edges are sorted by parent time, youngest first, so we can iterate over
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# nodes-as-parents visiting children before parents by using itertools.groupby
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for parent_id, ts_edges in itertools.groupby(ts.edges(), lambda e: e.parent):
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# Iterate through the ts edges *plus* the polytomy edges we created in previous steps.
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# This allows us to re-edit polytomy edges when the edges_to_remove are stacked
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edges = list(ts_edges)
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if parent_id in new_edges:
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edges += new_edges.pop(parent_id)
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if parent_id in edges_to_remove_by_child:
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for e in edges:
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assert parent_id == e.parent
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l = -1
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if e.id in edge_id_remove_list:
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continue
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# NB: we go left to right along the target edges, reducing edge e as required
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for target_edge in edges_to_remove_by_child[parent_id]:
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# As we go along the target_edges, gradually split e into chunks.
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# If edge e is in the target_edge region, change the edge parent
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assert target_edge.left > l
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l = target_edge.left
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if e.left >= target_edge.right:
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# This target edge is entirely to the LHS of edge e, with no overlap
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continue
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elif e.right <= target_edge.left:
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# This target edge is entirely to the RHS of edge e with no overlap.
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# Since target edges are sorted by left coord, all other target edges
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# are to RHS too, and we are finished dealing with edge e
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tables.edges.append(e)
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e = None
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break
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else:
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# Edge e must overlap with current target edge somehow
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if e.left < target_edge.left:
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# Edge had region to LHS of target
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# Add the left hand section (change the edge right coord)
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tables.edges.add_row(left=e.left, right=target_edge.left, parent=e.parent, child=e.child)
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e = e.replace(left=target_edge.left)
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if e.right > target_edge.right:
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# Edge continues after RHS of target
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assert e.left < target_edge.right
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new_edges[target_edge.parent].append(
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e.replace(right=target_edge.right, parent=target_edge.parent)
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)
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e = e.replace(left=target_edge.right)
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else:
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# No more of edge e to RHS
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assert e.left < e.right
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new_edges[target_edge.parent].append(e.replace(parent=target_edge.parent))
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e = None
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break
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if e is not None:
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# Need to add any remaining regions of edge back in
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tables.edges.append(e)
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else:
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# NB: sanity check at top means that the oldest node will have no edges above,
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# so the last iteration should hit this branch
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for e in edges:
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if e.id not in edge_id_remove_list:
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tables.edges.append(e)
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assert len(new_edges) == 0
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tables.sort()
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return tables.tree_sequence()
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def unsupported_edges(ts, per_interval=False):
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"""
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Return the internal edges that are unsupported by a mutation.
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If ``per_interval`` is True, each interval needs to be supported,
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otherwise, a mutation on an edge (even if there are multiple intervals
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per edge) will result in all intervals on that edge being treated
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as supported.
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"""
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edges_to_remove = np.ones(ts.num_edges, dtype="bool")
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edges_to_remove[[m.edge for m in ts.mutations()]] = False
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# We don't remove edges above samples
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edges_to_remove[np.isin(ts.edges_child, ts.samples())] = False
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if per_interval:
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return np.where(edges_to_remove)[0]
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else:
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keep = (edges_to_remove == False)
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for p, c in zip(ts.edges_parent[keep], ts.edges_child[keep]):
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edges_to_remove[np.logical_and(ts.edges_parent == p, ts.edges_child == c)] = False
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return np.where(edges_to_remove)[0]
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class Workbook:
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@staticmethod
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def setup():
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display(HTML(
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"<style type='text/css'>" +
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".exercise {background-color: yellow; color: black; font-family: 'serif'; font-size: 1.2em}" +
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".exercise code {font-size: 0.7em}" +
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"</style>" +
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"<h4>✅ Your notebook is ready to go!</h4>" +
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("This notebook is not running in JupyterLite: you may need to install tskit, tszip, etc."
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if sys.platform != 'emscripten' else '''
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To clear the notebook and reset,
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select "Clear Browser Data" from the JupyterLite help menu.
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''')
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))
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def node_coalescence_status(arg):
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"""
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Uses the num_children_array attribute to find nodes that represent local coalescence.
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See https://tskit.dev/tskit/docs/latest/python-api.html#tskit.Tree.num_children_array
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Returns an array of length num_nodes containing 0 if a node never has any coalescent
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segments, 1 if some segments of the node are coalescent and some unary, and 2 if
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all node segments represent a local coalescence point.
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"""
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has_unary = np.zeros(arg.num_nodes, dtype=int)
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has_coal = np.zeros(arg.num_nodes, dtype=int)
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tree = arg.first()
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nca = tree.num_children_array
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for edge_diffs in arg.edge_diffs():
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for e in edge_diffs.edges_out:
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if nca[e.parent] == 0:
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has_unary[e.parent] = 1
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elif nca[e.parent] > 1:
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has_coal[e.parent] = 1
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for e in edge_diffs.edges_in:
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if nca[e.parent] == 0:
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has_unary[e.parent] = 1
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elif nca[e.parent] > 1:
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has_coal[e.parent] = 1
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tree.next()
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return np.where(has_coal, np.where(has_unary, 1, 2), 0)
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def remove_unsupported_edges(ts, per_interval=True):
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"""
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Remove edges from the tree sequence that are unsupported by mutations.
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If ``per_interval`` is True, each interval needs to be supported,
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otherwise, a mutation on an edge (even if there are multiple intervals
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per edge) will result in all intervals on that edge being treated
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as supported.
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"""
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edges_to_remove = unsupported_edges(ts, per_interval=per_interval)
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tables = remove_edges(ts, edges_to_remove).dump_tables()
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tables.edges.squash()
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return tables.tree_sequence()
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class Workbook1(Workbook):
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url = "json/WhatIsAnARG/Workbook1/" # could also put a full URL here, but a local one will work offline too
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class Workbook2(Workbook):
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url = "json/WhatIsAnARG/Workbook2/" # could also put a full URL here, but a local one will work offline too

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