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import numpy as np | |
import matplotlib.pyplot as plt | |
import matplotlib.colors as mcolors | |
# here 'gs-style' is the name reference to the custom matplotlib style | |
# typically saved to ~/.matplotlib/stylelib/ | |
plt.style.use('gs-style') | |
# Fixing random state for reproducibility | |
np.random.seed(19680801) |
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# cython: language_level=3 | |
import cython | |
import numpy as np | |
from cython.parallel import prange, parallel | |
from libc.math cimport sqrt | |
from libc.math cimport nearbyint | |
@cython.boundscheck(False) | |
@cython.wraparound(False) |
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// | |
// This is a lattice random walk config generator using pivot algorithm. | |
// can be self-avoid or not self-avoid | |
// lattice_SAW(chain array, number of steps(monomers), step length(bond), self-avoid or no-self-avoid) | |
// | |
// Created by guangshi on 8/25/14. | |
// Copyright (c) 2014 Guang Shi. All rights reserved. | |
// | |
#include <math.h> |
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// dynamically load the script on demand | |
class ScriptLoader { | |
constructor(script) { | |
this.script = script; | |
this.scriptElement = document.createElement('script'); | |
this.head = document.querySelector('head'); | |
} | |
load () { | |
return new Promise((resolve, reject) => { |
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import numpy as np | |
def walk(n): | |
# check if the number of steps is an integer | |
if int(n) != n: | |
print('number of steps should be an integer') | |
return None | |
# the initial position is (0,0) | |
xy_0 = np.array([0.0, 0.0]) | |
# generate displacements of each step |
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import numpy as np | |
x = np.random.rand(1000) | |
y = np.random.rand(1000) |
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def next_batch_nonlinear_map(bs, h, w, anisotropy=True): | |
# ... same code ... | |
y.append(np.dot(item, item)) # only changes here | |
# ... same code ... |
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anisotropy = False | |
learning_rate = 0.005 | |
batch_size = 200 | |
h = 10 | |
w = 10 | |
channels = 1 | |
x = tf.placeholder(tf.float32, [batch_size, h, w, channels]) | |
y = tf.placeholder(tf.float32, [batch_size, h, w, channels]) | |
linear_map = np.random.rand(h,w) |
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import numpy as np | |
import timeit | |
from scipy.spatial.distance import cdist | |
# define a dot product function used for the rotate operation | |
def v_dot(a):return lambda b: np.dot(a,b) | |
class lattice_SAW: | |
def __init__(self,N,l0): | |
self.N = N |
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