Source code for mdadash.backend.analyses.contacts
"""
Contacts within a cutoff
"""
import logging
from collections import deque
from typing import ClassVar
import matplotlib.pyplot as plt
from IPython.display import display
from joblib import delayed
from MDAnalysis.lib.distances import capped_distance
from mdadash.backend.widgets.base import WidgetBase
logger = logging.getLogger(__name__)
[docs]
class Contacts(WidgetBase):
r"""
**Contacts within a cutoff**
This widget uses `MDAnalysis.lib.distances.capped_distance`_ to caclulate
`number of contacts within a cutoff`_ between two contacting groups.
.. _number of contacts within a cutoff: https://userguide.mdanalysis.org/
stable/examples/analysis/distances_and_contacts/contacts_within_cutoff.html
.. _MDAnalysis.lib.distances.capped_distance: https://docs.mdanalysis.org/stable/
documentation_pages/lib/distances.html#MDAnalysis.lib.distances.capped_distance
**Inputs**
Run frequency
.. compound::
The frequency with which the widget is run - `every-frame` or `batch`
Default: ``every-frame``
Run mode
The mode in which the widget is run - `serial` or `parallel`
Default: ``serial``
Contacting Group 1
MDAnalysis selection phrase of first group
Default: ``(resname ASP GLU) and (name OE* OD*)``
Contacting Group 2
MDAnalysis selection phrase of second group
Default: ``(resname ARG LYS) and (name NH* NZ)``
Radius
Radius within which contacts exist
Default: ``4.5``
Custom title
Custom title for the plot
Default: ''
Max values
Max values to show in plot
Default: ``100``
X-axis
X-axis value - `time` or `step`
Default: ``time``
**Output**
Here is an example output plot of this widget:
.. figure:: /_static/images/contacts_output.jpg
:alt: Contacts output
.. tip::
This widget supports batching and can run in parallel
"""
name = "Contacts"
description = "Contacts within a cutoff"
_doclink = (
"https://mdadash.readthedocs.io/en/latest/autosummary/"
"mdadash.backend.analyses.contacts.html"
)
_inputs: ClassVar = [
{
"attribute": "_run_frequency",
"name": "Run frequency",
"description": "The frequency with which the widget is run",
"type": "select",
"items": [
"every-frame",
"batch",
],
},
{
"attribute": "_run_mode",
"name": "Run mode",
"description": "The mode in which the widget is run",
"type": "select",
"items": [
"serial",
"parallel",
],
},
{
"attribute": "selection1",
"name": "Contacting Group 1",
"description": "MDAnalysis selection phrase of first group",
"type": "str",
"validations": ["required"],
},
{
"attribute": "selection2",
"name": "Contacting Group 2",
"description": "MDAnalysis selection phrase of second group",
"type": "str",
"validations": ["required"],
},
{
"attribute": "radius",
"name": "Radius",
"description": "Radius within which contacts exist",
"type": "float",
},
{
"attribute": "custom_title",
"name": "Custom title",
"description": "Custom title for the plot",
"type": "str",
},
{
"attribute": "maxlen",
"name": "Max values",
"description": "Max values to show in plot",
"type": "int",
},
{
"attribute": "x_type",
"name": "X-axis",
"type": "toggle",
"options": [
{"name": "Time", "value": "time"},
{"name": "Step", "value": "step"},
],
},
]
def __init__(self):
super().__init__()
self.selection1 = "(resname ASP GLU) and (name OE* OD*)"
self.selection2 = "(resname ARG LYS) and (name NH* NZ)"
self.radius = 4.5
self.ag1 = None
self.ag2 = None
self.title = "Contacts within cutoff"
self.custom_title = None
self.default_maxlen = 100
self.maxlen = self.default_maxlen
self.x_type = "time"
self.x_values = None
self._setup_plot()
self._reset_plot_values()
def _setup_plot(self):
"""Setup matplotlib plot"""
self.fig, self.ax = plt.subplots()
(self.plot,) = self.ax.plot([], [])
self.ax.set_ylabel("Number of contacts")
self.ax.grid(True)
self._set_title()
def _reset_plot_values(self):
"""Reset plot values"""
self.steps = deque(maxlen=self.maxlen)
self.times = deque(maxlen=self.maxlen)
self.y_values = deque(maxlen=self.maxlen)
self._set_x_values()
def _set_title(self):
"""Set plot title"""
self.ax.set_title(
self.custom_title.replace("\\n", "\n") if self.custom_title else self.title
)
def _set_x_values(self):
"""Set the values for the x-axis"""
if self.x_type == "step":
x_label = "Step"
self.x_values = self.steps
else:
x_label = "Time (ps)"
self.x_values = self.times
self.ax.set_xlabel(x_label)
def _update_selections(self):
"""Update atom groups when selection phrases change"""
self.ag1 = self.u.select_atoms(self.selection1)
self.ag2 = self.u.select_atoms(self.selection2)
self.title = f"Contacts between\n'{self.selection1}' and '{self.selection2}'"
self._set_title()
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def on_post_create(self):
""":meth:`~mdadash.backend.widgets.base.WidgetBase.on_post_create` handler"""
self._set_title()
self._reset_plot_values()
[docs]
def on_post_connect(self):
""":meth:`~mdadash.backend.widgets.base.WidgetBase.on_post_connect` handler"""
self._update_selections()
[docs]
def on_input_change(self, attribute, _old_value, new_value):
""":meth:`~mdadash.backend.widgets.base.WidgetBase.on_input_change` handler"""
if attribute == "maxlen":
if new_value < 0:
self.maxlen = self.default_maxlen
self._reset_plot_values()
elif attribute == "x_type":
self._set_x_values()
elif attribute == "custom_title":
self._set_title()
elif attribute in ("selection1", "selection2", "radius"):
self._reset_plot_values()
self._update_selections()
def _compute_current_frame(self):
"""Compute values for current frame"""
pairs = capped_distance(
self.ag1.positions,
self.ag2.positions,
max_cutoff=self.radius,
box=self.u.dimensions,
return_distances=False,
)
return (
self.u.trajectory.ts.data["step"],
self.u.trajectory.ts.data["time"],
len(pairs),
)
def _compute_batch(self):
"""Compute values for current batch"""
values = []
for i in range(self.u.trajectory.buffer_size):
_ = self.u.trajectory[i]
values.append(self._compute_current_frame())
return values
def _update_plot(self, values):
"""Append values and update plot"""
if isinstance(values, tuple):
values = [values]
# update plot points
for value in values:
(steps, times, v) = value
self.steps.append(steps)
self.times.append(times)
self.y_values.append(v)
# update plot
self.plot.set_data(self.x_values, self.y_values)
self.ax.relim()
self.ax.autoscale_view()
self.fig.canvas.draw()
display(self.fig)
[docs]
def run_every_frame(self):
""":meth:`~mdadash.backend.widgets.base.WidgetBase.run_every_frame` handler"""
self._update_plot(self._compute_current_frame())
[docs]
def run_batch(self):
""":meth:`~mdadash.backend.widgets.base.WidgetBase.run_batch` handler"""
self._update_plot(self._compute_batch())
[docs]
def get_parallel_job(self):
""":meth:`~mdadash.backend.widgets.base.WidgetBase.get_parallel_job` handler"""
if self._run_frequency == "batch":
return delayed(self._compute_batch)()
return delayed(self._compute_current_frame)()
[docs]
def apply_parallel_results(self, values):
""":meth:`~mdadash.backend.widgets.base.WidgetBase.apply_parallel_results` handler"""
self._update_plot(values)