"""
RMSD Analysis
"""
import logging
from collections import deque
from typing import ClassVar
import matplotlib.pyplot as plt
from joblib import delayed
from matplotlib.backends.backend_agg import FigureCanvasAgg
from MDAnalysis.analysis import rms
from mdadash.backend.widgets.base import WidgetBase
logger = logging.getLogger(__name__)
[docs]
class RMSD(WidgetBase):
"""
**RMSD Analysis**
This widget uses `MDAnalysis.analysis.rms.rmsd`_ to calculate `RMSD`_ of a
selection. The reference positions used by this widget are the initial
positions of the selection available for the trajectory from the reference
timestep (:attr:`~mdadash.backend.kernel.core.BufferedTrajectory.reference_ts`).
.. note:: If you use trajectory data from simulations performed under periodic boundary
conditions then you must make your molecules whole before performing RMSD calculations so
that the centers of mass of the mobile and reference structure are properly superimposed.
You can add custom transformations to the universe in the Universe Configuration section
in the Settings page of the dasboard.
.. _MDAnalysis.analysis.rms.rmsd: https://docs.mdanalysis.org/stable/
documentation_pages/analysis/rms.html#MDAnalysis.analysis.rms.rmsd
.. _RMSD: https://userguide.mdanalysis.org/stable/
examples/analysis/alignment_and_rms/rmsd.html
**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``
Selection
MDAnalysis selection phrase
Default: ``protein``
Center
Subtract center of geometry before calculation
Default: ``False``
Superposition:
Perform a rotational and translational superposition with the fast QCP algorithm
Default: ``False``
Custom title
Custom title for the plot
Default: ''
Max values
Max values to show in plot
Default: ``100``
Plot refresh frequency
The frequency with which the plot is refreshed (every n frames).
This only applies when the run frequency is ``every-frame``
Default: ``1``
Reset on connect
Reset the plot on every connect
Default: ``False``
X-axis
X-axis value - `time` or `step`
Default: ``time``
**Output**
Here is an example output plot of this widget:
.. figure:: /_static/images/rmsd_output.jpg
:alt: RMSD output
.. tip::
This widget supports batching and can run in parallel
"""
name = "RMSD"
description = "RMSD of a selection"
_doclink = (
"https://mdadash.readthedocs.io/en/latest/autosummary/"
"mdadash.backend.analyses.rmsd.html"
)
_notes = (
"If simulations are performed under periodic boundary conditions "
"then you must make your molecules whole before performing RMSD "
"calculations so that the centers of mass of the mobile and reference "
"structure are properly superimposed. You can add custom transformations "
"to the universe in the Universe Configuration section in the Settings page.\n\n"
"Note: The reference positions used by this widget are the initial positions "
"of the selection available for the trajectory from the reference "
"timestep (`u.trajectory.reference_ts`)."
)
_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": "selection",
"name": "Selection",
"description": "MDAnalysis selection phrase",
"type": "str",
"validations": ["required"],
},
{
"attribute": "center",
"name": "Center",
"description": "Subtract center of geometry before calculation",
"type": "bool",
},
{
"attribute": "superposition",
"name": "Superposition",
"description": (
"Perform a rotational and translational superposition with the fast QCP algorithm"
),
"type": "bool",
},
{
"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",
"validations": ["min:0"],
},
{
"attribute": "plot_refresh_frequency",
"name": "Plot refresh frequency",
"description": "The frequency with which the plot is refreshed (every n frames)",
"type": "int",
"validations": ["min:1"],
},
{
"attribute": "reset_on_connect",
"name": "Reset on connect",
"description": "Reset the plot on every connect",
"type": "bool",
},
{
"attribute": "x_type",
"name": "X-axis",
"type": "toggle",
"options": [
{"name": "Time", "value": "time"},
{"name": "Step", "value": "step"},
],
},
]
def __init__(self):
super().__init__()
self.selection = "protein"
self.center = False
self.superposition = False
self.ag = None
self.reference_positions = None
self.title = "RMSD"
self.custom_title = None
self.default_maxlen = 100
self.maxlen = self.default_maxlen
self.plot_refresh_count = 1
self.plot_refresh_frequency = 1
self.reset_on_connect = False
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.canvas = FigureCanvasAgg(self.fig)
(self.plot,) = self.ax.plot([], [])
self.ax.set_ylabel("RMSD (Å)")
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.plot_refresh_count = 1
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_selection(self):
"""Update atom groups when selection phrase changes"""
# Use the reference timestep to create the reference positions
_ = self.u.trajectory.reference_ts
self.ag = self.u.select_atoms(self.selection)
self.reference_positions = self.ag.positions.copy()
# reset to current frame
self.reset_frame_latest()
self.title = f"RMSD of '{self.selection}'"
self._set_title()
self._update_plot(self._compute_current_frame())
[docs]
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_selection()
self.plot_refresh_count = 1
if self.reset_on_connect: # pragma: no cover
self._reset_plot_values()
def _compute_current_frame(self):
"""Compute values for current frame"""
rmsd_value = rms.rmsd(
self.ag.positions,
self.reference_positions,
center=self.center,
superposition=self.superposition,
)
return (
self.u.trajectory.ts.data["step"],
self.u.trajectory.ts.data["time"],
rmsd_value,
)
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
if self._run_frequency == "batch" or (
self.plot_refresh_count == 1
or self.plot_refresh_count % self.plot_refresh_frequency == 0
):
self.plot.set_data(self.x_values, self.y_values)
self.ax.relim()
self.ax.autoscale_view()
self.display_canvas(self.canvas)
self.plot_refresh_count += 1
[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)