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Commit 41b732e7 authored by Alexander R. Hankin's avatar Alexander R. Hankin
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Merge branch 'dev' of https://github.cs.tufts.edu/dwerne01/EE194_Manduca_Simulator into dev

parents 616db72d 2617ff41
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README.md
View file @ 41b732e7
......@@ -29,13 +29,15 @@
* [x] Simulation: Population, Manduca, SimpleManduca
* [x] Logged values for plotting: History
* [x] properties
* [ ] saving animations as gifs
* [ ] making animations less ineffecient
* [ ] auto documentation using sphinx
* [x] saving animations as gifs
* [x] saving animations as mp4s!
* [x] making animations less ineffecient
* [x] auto documentation using sphinx
* [x] `make docs`
* [x] `make docs_html`
* [x] `make docs_pdf`
* [ ] Actually document everything..
* [ ] ~~Actually document everything..~~
* [x] Actually document some things!
* [ ] ~~pep8 compliance~~
* [x] Custom Exceptions
* [x] Test code using py.test
......
manduca/Manducas.py
View file @ 41b732e7
......@@ -100,7 +100,7 @@ class Manduca(object):
def legs(self):
"""This function gets the legs for a specified Manduca.
:returns: int -- the legs of the Manduca.
:returns: numpy.array -- the legs of the Manduca.
"""
return self._legs
......@@ -126,7 +126,7 @@ class Manduca(object):
def muscles(self):
"""This function gets the muscles for a specified Manduca.
:returns: int -- the muscles of the Manduca.
:returns: numpy.array -- the muscles of the Manduca.
"""
return self._muscles
......@@ -150,9 +150,9 @@ class Manduca(object):
@property
def time_step(self):
"""This function gets the current time step for a specified Manduca.
"""This function gets the simulation time step for a specified Manduca.
:returns: int -- the current time step for the Manduca.
:returns: float -- the simulation time step for the Manduca.
"""
return self._time_step
......@@ -203,10 +203,10 @@ class Manduca(object):
@staticmethod
def distance_traveled(manduca):
"""This function gets the current time step for a specified Manduca.
:param manduca: The Manduca to evaluated.
:type manduca: Manduca.
:returns: int -- the distance the Manduca has traveled.
:returns: float -- the distance the Manduca has traveled.
"""
positions, velocites, times = manduca.simulate(record_level=0)
......@@ -237,7 +237,9 @@ class Manduca(object):
:returns: numpy array -- the initial position of the Manduca.
"""
return np.arange(self.num_legs)*self.body_properties.L0
pos = np.arange(self.num_legs)*self.body_properties.L0
pos = pos - np.mean(pos)
return pos
def check_consistancy(self):
"""This function checks to make sure the Manduca's body is consistent, i.e., same number of legs and muscles.
......@@ -252,7 +254,7 @@ class Manduca(object):
def change_muscle_value(self, current_value, rng=np.random):
"""This function changes a muscle value for a specified Manduca.
:param current_value: The current muscle value.
:type current_value: float.
:param rng=np.random: The random number generator.
......@@ -263,12 +265,12 @@ class Manduca(object):
return rng.rand()*self.body_properties.muscle_strength
# First randomly choose the number of mutations (1 up to MAX_MUTATIONS)
# - flip a random leg-locked
# - flip a random muscle-on
# - do the secret-sauce mutation if desired.
#- flip a random leg-locked
#- flip a random muscle-on
#- do the secret-sauce mutation if desired.
def mutate (self, rng=np.random, max_mutations = 20):
"""This function mutates a specified Manduca by either flipping a random leg locked or flipping a random muscle on.
:param rng=np.random: The random number generator.
:type rng=np.random: A random number generator.
:param max_mutations = 20: The maximum possible number of mutations that can happen.
......@@ -299,7 +301,7 @@ class Manduca(object):
# This is the final function that you write yourself.
def mate(self, parent2, rng=np.random):
"""This function mates two lucky Manducas. Picks entire rows from one parent or the other to form child.
:param parent2: The other parent involved in the mating.
:type parent2: Manduca.
:param rng=np.random: The random number generator.
......@@ -320,7 +322,7 @@ class Manduca(object):
def __repr__(self):
"""This function prints the Manduca object.
:returns: string -- containing information about the Manduca which includes legs, muscles, and body properties.
"""
......@@ -337,7 +339,7 @@ class Manduca(object):
def __eq__(self, other):
"""This function checks to see if two Manducas are equivalent.
:param other: The other Manduca involved in the comparison.
:type other: Manduca.
:returns: bool -- whether the two Manducas are equivalent.
......@@ -351,13 +353,13 @@ class Manduca(object):
def __ne__(self, other):
"""This function checks to see if two Manducas are different.
:param other: The other Manduca involved in the comparison.
:type other: Manduca.
:returns: bool -- whether the two Manducas are different.
"""
return (self.time_step != other.time_step or
not(np.array_equal(self.legs, other.legs)) or
not(np.array_equal(self.muscles, other.muscles) or
......@@ -365,7 +367,7 @@ class Manduca(object):
def __hash__(self):
"""This functions returns a hash of the summary of the Manduca's properties
:param parent2: The other parent involved in the mating.
:type parent2: Manduca.
:returns: Manduca -- the new child Manduca.
......@@ -376,14 +378,14 @@ class Manduca(object):
manduca_str = leg_str + m_str + t_str
return hash(manduca_str)
def simulate(self, record_level=0, sub_intervals = 10):
def simulate(self, record_level=0, sub_intervals = 10, record_legs_and_muscles=False):
"""This functions returns a hash of the summary of the Manduca's properties
:param record_level: Which intervals to record the position/velocity/time
0 -> initial/final only
1 -> once for each interval
2 -> every sub-interval
* -> default to 0
\* -> default to 0
:param sub_intervals: the number of subintervals simulated in the physics for each time interval/
:type sub_intervals: int.
......@@ -403,10 +405,10 @@ class Manduca(object):
Front Leg: fn' = -k(xn-x{n-1}-L0) + c(v{n-1}-vn) + M{n-1}n
:param x: position of legs and velocites of legs
in the form [x0, x1, ..., xn, v0, v1, ..., vn]
in the form [x0, x1, ..., xn, v0, v1, ..., vn]
:param t: is an array of time values over which to integrate
in the form [t0, t1, ..., tN]
in the form [t0, t1, ..., tN]
:return: numpy array -- the derivatives of x
......@@ -466,6 +468,7 @@ class Manduca(object):
# Record the initial position and velocities
recorded_positions, recorded_velocities = [position], [velocities]
recorded_times = [0.0]
recorded_legs, recorded_muscles = [self.legs[0]], [self.muscles[0]]
# For each time-step, advance the simulation
for time, current_legs, current_muscles in zip(times, self.legs, self.muscles):
......@@ -492,21 +495,31 @@ class Manduca(object):
recorded_positions.append(position)
recorded_velocities.append(velocities)
recorded_times.append(end_time)
recorded_legs.append(current_legs)
recorded_muscles.append(current_muscles)
elif record_level == 2:
recorded_positions.extend(new_positions)
recorded_velocities.extend(new_velocities)
recorded_times.extend(new_times)
for _ in range(sub_intervals):
recorded_legs.append(current_legs)
recorded_muscles.append(current_muscles)
# If the record_level is 0, save the final interval as wel
if record_level not in [1,2]:
recorded_positions.append(position)
recorded_velocities.append(velocities)
recorded_times.append(end_time)
recorded_legs.append(current_legs)
recorded_muscles.append(current_muscles)
if record_legs_and_muscles == True:
return recorded_positions, recorded_velocities, recorded_times, recorded_legs,\
recorded_muscles
return recorded_positions, recorded_velocities, recorded_times
def save(self, file_name, compressed=True):
"""This function saves information about a Manduca to a file
:param file_name: The name of the file to be written to.
:type file_name: string.
:param compressed: Whether or not the file should be compressed.
......@@ -524,13 +537,13 @@ class Manduca(object):
@classmethod
def load(cls, file_name, *other_params, **kwargs):
"""This functions loads information about a Manduca from a file
:param cls: The other parent
:type cls: Manduca.
:param file_name: The name of the file to be loaded from
:type file_name: string.
:param *other_params: Additional parameters.
:type *other_params: optional args.
:param \*other_params: Additional properties to load from the file and pass as \*args
:param \**kwargs: kwargs passed to cls.__init__
"""
kwargs_copy = dict(kwargs)
......@@ -538,10 +551,11 @@ class Manduca(object):
results = np.load(file_name)
legs = results['legs']
muscles = results['muscles']
time_step = results['time_step']
time_step = np.asscalar(results['time_step'])
args = []
for param in other_params:
args.append(results[param])
# TODO: This should be removed (body_properties are saved with the manduca now)
if 'body_properties' not in kwargs_copy or kwargs_copy['body_properties'] is None:
kwargs_copy['body_properties'] = ManducaBodyProperties(*results['body_properties'])
new_manduca = cls(legs, muscles, time_step, *args, **kwargs_copy)
......@@ -555,7 +569,7 @@ class Manduca(object):
def clone(self):
"""This functions clones a Manduca
:returns: Manduca -- the Manduca clone.
"""
......@@ -563,20 +577,44 @@ class Manduca(object):
time_step=self.time_step,
body_properties=self.body_properties)
@staticmethod
def random_individual(num_legs, time_segments, time_step, **kwargs):
"""This functions returns a hash of the summary of the Manduca's properties
:param num_legs: The number of the legs the Manduca has.
:type num_legs: int.
:param time_step: .
:type time_step: int.
:param time_step: the time of one interval.
:type time_step: int.
:param \**kwargs: keyword args passed to super.
:returns: Manduca -- the new random Manduca.
"""
body_properties = kwargs.pop('body_properties', None)
if body_properties == None:
body_properties = Manduca.default_body_properties
kwargs['body_properties'] = body_properties
muscle_strength = body_properties.muscle_strength
rng = kwargs.pop('rng', np.random)
legs = rng.choice([0, 1], size=(time_segments, num_legs))
muscles = rng.uniform(size=(time_segments, num_legs-1))*muscle_strength
return Manduca(legs, muscles, time_step, **kwargs)
class SimpleManduca(Manduca):
"""A Manduca that has legs and muscles that are either ON/OFF"""
def __init__(self, legs, muscles, time_step, **kwargs):
"""This function is the constructor for the Simple Manduca class
:param legs: 2D array representing Manduca's legs.
:type legs: int.
:param muscles: 2D array representing Manduca's muscles.
:type muscles: int.
:param time_step: the time of one interval.
:type time_step: int.
:param **kwargs: keyword args passed to super.
:type **kwargs: keyword args.
:param \**kwargs: keyword args passed to super.
"""
super(SimpleManduca, self).__init__(legs, muscles, time_step, **kwargs)
......@@ -589,16 +627,15 @@ class SimpleManduca(Manduca):
@staticmethod
def random_individual(num_legs, time_segments, time_step, **kwargs):
"""This functions returns a hash of the summary of the Manduca's properties
:param num_legs: The number of the legs the Manduca has.
:type num_legs: int.
:param time_step: .
:type time_step: int.
:param time_step: the time of one interval.
:type time_step: int.
:param **kwargs: keyword args passed to super.
:type **kwargs: keyword args.
:param \**kwargs: keyword args passed to super.
:returns: Manduca -- the new random Manduca.
"""
......@@ -615,7 +652,7 @@ class SimpleManduca(Manduca):
def change_muscle_value(self, current_value, rng=np.random):
"""This functions determines a new muscle value based on the previous
:param current_value: the current muscle value.
:type current_value: float.
:param rng=np.random: A random number generator
......
manduca/Visualization.py 0 → 100644
View file @ 41b732e7
"""
Makes animations of manducas moving
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import matplotlib.patches as patches
import os
def animate(*manducas, **kwargs):
anim = _get_animation(*manducas, **kwargs)
plt.show()
plt.close()
def animate_as_gif(file_name, *manducas, **kwargs):
anim = _get_animation(*manducas, **kwargs)
_save_as_gif(file_name, anim)
plt.close()
def animate_as_mp4(file_name, *manducas, **kwargs):
anim = _get_animation(*manducas, **kwargs)
_save_as_gif(file_name, anim)
plt.close()
def _get_animation(*manducas, **kwargs):
""" Produces an animation of all \*manducas racing
NOTE: Requires all manducas to have same time_step and num_time_steps!
"""
show_winners = kwargs.pop('show_winners', False)
show_fitnesses = kwargs.pop('show_fitnesses', False)
manducas_with_labels = []
for idx,val in enumerate(manducas):
if isinstance(val, tuple):
manducas_with_labels.append(val)
else:
manducas_with_labels.append((val, str(idx)))
if show_fitnesses or show_winners:
fitnesses = [man.fitness for man, _ in manducas_with_labels]
if show_winners:
max_f = max(fitnesses)
winners = np.array(fitnesses) == max_f
else:
winners = None
if not show_fitnesses:
fitnesses = None
for idx in range(len(manducas_with_labels)):
manduca, label = manducas_with_labels[idx]
if fitnesses is not None:
new_label = "{}[fitness={}]".format(label, fitnesses[idx])
else:
new_label = str(label)
if winners is not None:
if winners[idx]:
new_label = "{}[WINNER]".format(new_label)
manducas_with_labels[idx] = (manduca, new_label)
# Make sure the manducas are compatible!
time_steps = list(set([manduca.time_step for manduca, _ in manducas_with_labels]))
assert len(time_steps) == 1, \
"All manducas must have same time_step to be animated together"
num_time_steps = list(set([manduca.num_time_steps for manduca, _ in manducas_with_labels]))
assert len(time_steps) == 1, \
"All manducas must have same number of time steps to be animated together"
dx = time_steps[0]
positions, legs, muscles = [], [], []
# Read the file(s) and build points[n_frames][15 items][n_worms]
for manduca, labels in manducas_with_labels:
sim_kwargs = {key: kwargs[key] for key in ['sub_intervals'] if key in kwargs}
x, v, t, l, m = manduca.simulate(record_level=2, record_legs_and_muscles=True, **sim_kwargs)
positions.append(x)
legs.append(l)
muscle_strength = manduca.body_properties.muscle_strength
muscles.append([force/muscle_strength for force in m])
labels = [label for manduca, label in manducas_with_labels]
return _animate(labels, positions, legs, muscles, dx, fitnesses=fitnesses, winners=winners, **kwargs)
#TODO: Also do still-frames
def get_stills(manduca, sub_intervals=None):
pass
def _save_as_gif(output_file, animation, dpi=80, **kwargs):
animation.save(output_file, dpi=dpi, writer='imagemagick', **kwargs)
def _save_as_mp4(output_file, animation, dpi=80, **kwargs):
animation.save(output_file, dpi=dpi, writer='mencoder', **kwargs)
def _animate(labels, positions, legs, muscles, dx, **kwargs):
leg_width = kwargs.pop('leg_width', 30)
show_result_percent = kwargs.pop('show_result_percent', 0.90)
fitnesses = kwargs.pop('fitnesses', None)
winners = kwargs.pop('winners', None)
# The per-frame animation function.
# Inputs: 'points' is a full array with[n_timepoints][data][n_worms] (where
# n_timepoints is the number of frames to be displayed).
# Remember that our display axes are:
# * x ranges over the min/max x values from the simulation.
# * y ranges from 0 to n_worms; i.e., each worm is allocated a vertical
# space of 1.
def per_frame (frame_number):
test_patches = []
for manduca_number in range(len(positions)):
mx = positions[manduca_number][frame_number]
ml = legs[manduca_number][frame_number]
mm = muscles[manduca_number][frame_number]
lrs = all_leg_rects[manduca_number]
brs = all_body_rects[manduca_number]
mrs = all_muscle_rects[manduca_number]
for rect, leg, pos in zip(lrs, ml, mx):
x, w = pos, leg_width
if leg == 0:
y = manduca_number + 0.2
else:
y = manduca_number + 0.1
h = 0.75 - (y - manduca_number)
rect.set_bounds(x,y,w,h)
for br, mr, musc, pos, next_pos in zip(brs, mrs, mm, mx, mx[1:]):
br.set_x(pos+leg_width)
br.set_width(next_pos-pos-leg_width)
mr.set_x(pos+leg_width)
mr.set_width(next_pos-pos-leg_width)
mr.set_alpha(musc)
return all_patches
xmin = min([min(min(val) for val in l) for l in positions])
xmax = max([max(max(val) for val in l) for l in positions])
xmax += leg_width
subplot_kwargs = kwargs.pop('subplot_kwargs',{})
fig,axes = plt.subplots(**subplot_kwargs)
axes.axis ([xmin,xmax,0,len(positions) + 0.1])
axes.set_autoscale_on(False)
axes.get_yaxis().set_visible(False)
for i,label in enumerate(labels):
axes.text (xmin, i+0.95,label, va='top')
axes.plot([xmin,xmax],[i+0.1]*2, 'brown')
all_patches = []
all_leg_rects, all_body_rects, all_muscle_rects = [], [], []
for idx, (x, l, m) in enumerate(zip(positions, legs, muscles)):
x0, l0, m0 = x[0], l[0], m[0]
leg_rects = [patches.Rectangle ((0,0),0,0, facecolor='r') for _ in l0]
body_rects = [patches.Rectangle ((0,idx+0.25),0,0.5, facecolor='g') for _ in m0]
muscle_rects = [patches.Rectangle ((0,idx+0.375),0,0.25, facecolor='k') for _ in m0]
all_leg_rects.append(leg_rects)
all_body_rects.append(body_rects)
all_muscle_rects.append(muscle_rects)
all_patches.extend(leg_rects+body_rects+muscle_rects)
[axes.add_patch(p) for p in all_patches]
msec_per_frame = dx * 1
num_frames = len(positions[0])
ani = animation.FuncAnimation(fig, per_frame, frames=num_frames,
interval=msec_per_frame,
blit=True,
repeat=False)
return ani
manduca/__init__.py
View file @ 41b732e7
from .Manducas import Manduca, SimpleManduca, ManducaDeformityError, ManducaBodyProperties
from .Population import EvolutionParameters, EvolutionSimulator, GenerationInfo
from .Visualization import animate, animate_as_gif, animate_as_mp4
setup.py
View file @ 41b732e7
from setuptools import setup
setup(name='manduca',
version='0.0.2',
version='0.0.3',
description='A package for simulating manduca sexta',
author='David Werner',
author_email='david.werner@tufts.edu',
......
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