repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/preconditioners/nystrom.py | #This implementation is based on the article:
#
# @article{Quinonero-Candela:2005:UVS:1046920.1194909,
# author = {Qui\~{n}onero-Candela, Joaquin and Rasmussen, Carl Edward},
# title = {A Unifying View of Sparse Approximate Gaussian Process Regression},
# journal = {J. Mach. Learn. Res.},
# issue_date = {12/1/2005}... | 3,672 | 26.616541 | 86 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/preconditioners/pitc.py | #This implementation is based on the article:
#
# @article{Quinonero-Candela:2005:UVS:1046920.1194909,
# author = {Qui\~{n}onero-Candela, Joaquin and Rasmussen, Carl Edward},
# title = {A Unifying View of Sparse Approximate Gaussian Process Regression},
# journal = {J. Mach. Learn. Res.},
# issue_date = {12/1/2005}... | 4,201 | 28.591549 | 98 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/preconditioners/preconditioner.py | """
Superclass for classes of Preconditioners.
"""
class Preconditioner(object):
def __init__(self, name = ""):
self.name = name
| 143 | 15 | 42 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/preconditioners/fitc.py | #This implementation is based on the article:
#
# @article{Quinonero-Candela:2005:UVS:1046920.1194909,
# author = {Qui\~{n}onero-Candela, Joaquin and Rasmussen, Carl Edward},
# title = {A Unifying View of Sparse Approximate Gaussian Process Regression},
# journal = {J. Mach. Learn. Res.},
# issue_date = {12/1/2005}... | 3,171 | 26.344828 | 90 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/preconditioners/spectral.py | #This implementation of spectral GP approximation is based on the article:
#
# @article{lazaro2010sparse,
# title={Sparse spectrum Gaussian process regression},
# author={L{\'a}zaro-Gredilla, Miguel and Qui{\~n}onero-Candela, Joaquin and Rasmussen, Carl Edward and Figueiras-Vidal, An{\'\i}bal R},
# journal={The J... | 2,446 | 28.481928 | 138 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/preconditioners/__init__.py | from preconditioner import Preconditioner
from blockJacobi import BlockJacobi
from nystrom import Nystrom
from svd import SVD
from kiss import Kiss
from pitc import PITC
from fitc import FITC
from spectral import Spectral | 221 | 26.75 | 41 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/preconditioners/blockJacobi.py | import numpy as np
from scipy.linalg import block_diag
from preconditioner import Preconditioner
import time
"""
Block Jacobi Preconditioner
"""
class BlockJacobi(Preconditioner):
"""
Construct preconditioner
X - Training data
kern - Class of kernel function
M - Number of points ber bl... | 1,826 | 28.467742 | 87 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/kernels/rbf.py | import numpy as np
from scipy.spatial.distance import cdist
from kernel import Kernel
"""
Implementation of isotropic RBF/SE kernel
"""
class RBF(Kernel):
def __init__(self, lengthscale=1, variance=1, noise=1):
super(RBF, self).__init__("RBF")
self.lengthscale = lengthscale
self.variance ... | 898 | 33.576923 | 123 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/kernels/matern32.py | import numpy as np
from scipy.spatial.distance import cdist
from kernel import Kernel
"""
Implementation of isotropic Matern-3/2 kernel
"""
class Matern32(Kernel):
def __init__(self, lengthscale=1, variance=1, noise=1):
super(Matern32, self).__init__("Matern 3/2")
self.lengthscale = lengthscale
... | 745 | 31.434783 | 106 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/kernels/__init__.py | from kernel import Kernel
from rbf import RBF
from matern32 import Matern32 | 75 | 24.333333 | 29 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/kernels/kernel.py | """
Superclass for classes of Kernel functions.
"""
class Kernel(object):
def __init__(self, name = ""):
self.name = name
"""
Computation of Kernel matrix for the given inputs - Noise excluded
"""
def K(self, X1, X2):
raise NotImplementedError
"""
Computation of scalar Kernel matrix - for grid inputs
""... | 399 | 19 | 67 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/__init__.py | import warnings
warnings.filterwarnings("ignore", category=DeprecationWarning)
import methods
import preconditioners
import kernels
def load(file_path):
"""
Load a previously pickled model, using `m.pickle('path/to/file.pickle)'
:param file_name: path/to/file.pickle
"""
import cPickle as pickle
... | 530 | 21.125 | 75 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/methods/cg.py | import numpy as np
"""
Solve linear system using conjugate gradient
Params:
K - Covariance Matrix
Y - Target labels
init - Initial solution
thershold - Termintion criteria
"""
class Cg(object):
def __init__(self, K, Y, init=None, threshold=1e-9):
N = np.shape(K)[0]
if init is None:
init = np.zeros((N,1))... | 772 | 17.853659 | 63 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/methods/laplaceCg.py | import numpy as np
from scipy.stats import norm
from cg import Cg
import random
"""
Laplace approximation using conjugate gradient
Params:
K - Covariance Matrix
Y - Target labels
init - Initial solution
threshold - Termintion criteria for algorithm
"""
class LaplaceCg(object):
def __init__(self, K, ... | 1,118 | 20.519231 | 68 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/methods/regularPcg.py | import numpy as np
"""
Solve linear system using regular preconditioned conjugate gradient
Params:
K - Covariance Matrix
Y - Target labels
P - Preconditioner Matrix (can be set to none)
init - Initial solution
threshold - Termintion criteria for outer loop
preconInv - Inversion of preconditione... | 1,109 | 20.764706 | 72 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/methods/flexPcg.py | import numpy as np
from cg import Cg
"""
Solve linear system using flexible conjugate gradient (without truncation)
Params:
K - Covariance Matrix
Y - Target labels
P - Preconditioner Matrix (can be set to none)
init - Initial solution
threshold - Termintion criteria for outer loop
innerThreshol... | 1,709 | 27.983051 | 95 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/methods/kronCgDirect.py | import numpy as np
from ..util.kronHelper import KronHelper
from scipy import sparse
import time
"""
Solve linear system using conjugate gradient (intended for SKI inference)
Params:
K - Covariance Matrix
Ws - Sparse representation of weight matrix W
WTs - Sparse representation of transposed wieght matrix ... | 1,384 | 29.108696 | 140 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/methods/kronTruncFlexPcg.py | import numpy as np
from cg import Cg
from scipy import sparse
from kronCgDirect import KronCgDirect
"""
Solve linear system using truncated flexible conjugate gradient (intended for SKI inference)
Params:
K - Covariance Matrix
Y - Target labels
P - Preconditioning matrix
W - Weight matrix W
Ku - A... | 2,176 | 28.418919 | 98 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/methods/truncFlexPcg.py | import numpy as np
from cg import Cg
"""
Solve linear system using flexible conjugate gradient (with truncation)
Params:
K - Covariance Matrix
Y - Target labels
P - Preconditioner Matrix (can be set to none)
init - Initial solution
thershold - Termintion criteria for outer loop
innerThreshold -... | 1,869 | 27.333333 | 95 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/methods/__init__.py | from cg import Cg
from regularPcg import RegularPcg
from flexPcg import FlexiblePcg
from truncFlexPcg import TruncatedFlexiblePcg
from kronCgDirect import KronCgDirect
from kronTruncFlexPcg import KronTruncatedFlexiblePcg
from laplaceCg import LaplaceCg
from laplacePcg import LaplacePcg | 287 | 35 | 53 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/methods/laplacePcg.py | import numpy as np
from scipy.stats import norm
from regularPcg import RegularPcg
import random
"""
Laplace approximation using preconditioned conjugate gradient
Params:
K - Covariance Matrix
Y - Target labels
P - Preconditioner Matrix (can be set to none)
init - Initial solution
threshold - Termin... | 1,278 | 23.132075 | 105 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/util/inducingPointsHelper.py | #This implementation is based on the article:
# @inproceedings{snelson2005sparse,
# title={Sparse Gaussian processes using pseudo-inputs},
# author={Snelson, Edward and Ghahramani, Zoubin},
# booktitle={Advances in neural information processing systems},
# pages={1257--1264},
# year={2005}
# }
from __future... | 5,072 | 30.70625 | 190 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/util/kronHelper.py | #This implementation is based on the article:
#
# @article{gilboa2015scaling,
# title={Scaling multidimensional inference for structured Gaussian processes},
# author={Gilboa, Elad and Saat{\c{c}}i, Yunus and Cunningham, John P},
# journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on},
# vol... | 1,634 | 24.546875 | 81 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/util/__init__.py | from kronHelper import KronHelper
from inducingPointsHelper import InducingPointsHelper
from ssgp import SsgpHelper | 115 | 37.666667 | 53 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/util/ssgp.py | #This implementation of spectral GP approximation is based on the article:
#
# @article{lazaro2010sparse,
# title={Sparse spectrum Gaussian process regression},
# author={L{\'a}zaro-Gredilla, Miguel and Qui{\~n}onero-Candela, Joaquin and Rasmussen, Carl Edward and Figueiras-Vidal, An{\'\i}bal R},
# journal={The J... | 1,999 | 30.25 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/preconditioners/svd.py | import numpy as np
import time
from sklearn.utils.extmath import randomized_svd
from preconditioner import Preconditioner
"""
Randomized Singular Value Decomposition (SVD) Preconditioner
"""
class SVD(Preconditioner):
"""
Construct preconditioning matrix
X - Training data
kern - Class of kernel function
M - ... | 2,924 | 27.676471 | 101 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/preconditioners/kiss.py | #This implementation of Structured Kernel Interpolation is based on the article:
#
# @inproceedings{DBLP:conf/icml/WilsonN15,
# author = {Andrew Gordon Wilson and
# Hannes Nickisch},
# title = {Kernel Interpolation for Scalable Structured Gaussian Processes {(KISS-GP)}},
# booktitle = {Proce... | 4,131 | 30.784615 | 113 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/preconditioners/nystrom.py | #This implementation is based on the article:
#
# @article{Quinonero-Candela:2005:UVS:1046920.1194909,
# author = {Qui\~{n}onero-Candela, Joaquin and Rasmussen, Carl Edward},
# title = {A Unifying View of Sparse Approximate Gaussian Process Regression},
# journal = {J. Mach. Learn. Res.},
# issue_date = {12/1/2005}... | 3,672 | 26.616541 | 86 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/preconditioners/pitc.py | #This implementation is based on the article:
#
# @article{Quinonero-Candela:2005:UVS:1046920.1194909,
# author = {Qui\~{n}onero-Candela, Joaquin and Rasmussen, Carl Edward},
# title = {A Unifying View of Sparse Approximate Gaussian Process Regression},
# journal = {J. Mach. Learn. Res.},
# issue_date = {12/1/2005}... | 4,201 | 28.591549 | 98 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/preconditioners/preconditioner.py | """
Superclass for classes of Preconditioners.
"""
class Preconditioner(object):
def __init__(self, name = ""):
self.name = name
| 143 | 15 | 42 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/preconditioners/fitc.py | #This implementation is based on the article:
#
# @article{Quinonero-Candela:2005:UVS:1046920.1194909,
# author = {Qui\~{n}onero-Candela, Joaquin and Rasmussen, Carl Edward},
# title = {A Unifying View of Sparse Approximate Gaussian Process Regression},
# journal = {J. Mach. Learn. Res.},
# issue_date = {12/1/2005}... | 3,171 | 26.344828 | 90 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/preconditioners/spectral.py | #This implementation of spectral GP approximation is based on the article:
#
# @article{lazaro2010sparse,
# title={Sparse spectrum Gaussian process regression},
# author={L{\'a}zaro-Gredilla, Miguel and Qui{\~n}onero-Candela, Joaquin and Rasmussen, Carl Edward and Figueiras-Vidal, An{\'\i}bal R},
# journal={The J... | 2,446 | 28.481928 | 138 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/preconditioners/__init__.py | from preconditioner import Preconditioner
from blockJacobi import BlockJacobi
from nystrom import Nystrom
from svd import SVD
from kiss import Kiss
from pitc import PITC
from fitc import FITC
from spectral import Spectral | 221 | 26.75 | 41 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/preconditioners/blockJacobi.py | import numpy as np
from scipy.linalg import block_diag
from preconditioner import Preconditioner
import time
"""
Block Jacobi Preconditioner
"""
class BlockJacobi(Preconditioner):
"""
Construct preconditioner
X - Training data
kern - Class of kernel function
M - Number of points ber bl... | 1,826 | 28.467742 | 87 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/preconditioners/ilu.py | import numpy as np
from preconditioner import Preconditioner
import time
class ILU(Preconditioner):
def __init__(self, X, kern):
super(ILU, self).__init__("ILU")
start = time.time()
K = kern.K(X,X)
N = np.shape(K)[0]
A = np.copy(K)
for k in xrange(N):
A[k][k] = np.sqrt(K[... | 732 | 20.558824 | 44 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/kernels/rbf.py | import numpy as np
from scipy.spatial.distance import cdist
from kernel import Kernel
"""
Implementation of isotropic RBF/SE kernel
"""
class RBF(Kernel):
def __init__(self, lengthscale=1, variance=1, noise=1):
super(RBF, self).__init__("RBF")
self.lengthscale = lengthscale
self.variance ... | 898 | 33.576923 | 123 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/kernels/matern32.py | import numpy as np
from scipy.spatial.distance import cdist
from kernel import Kernel
"""
Implementation of isotropic Matern-3/2 kernel
"""
class Matern32(Kernel):
def __init__(self, lengthscale=1, variance=1, noise=1):
super(Matern32, self).__init__("Matern 3/2")
self.lengthscale = lengthscale
... | 745 | 31.434783 | 106 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/kernels/__init__.py | from kernel import Kernel
from rbf import RBF
from matern32 import Matern32 | 75 | 24.333333 | 29 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/build/lib/PcgComp/kernels/kernel.py | """
Superclass for classes of Kernel functions.
"""
class Kernel(object):
def __init__(self, name = ""):
self.name = name
"""
Computation of Kernel matrix for the given inputs - Noise excluded
"""
def K(self, X1, X2):
raise NotImplementedError
"""
Computation of scalar Kernel matrix - for grid inputs
""... | 399 | 19 | 67 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/Comparison Results/PowerPlant/plot.py | import sys
import numpy as np
import random as ran
import matplotlib as m
import matplotlib
# import PcgComp
import random as ran
import time
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
def show_values(pc, fmt="%s", **kw):
from itertools import izip
pc.update_scalarmapp... | 4,739 | 34.111111 | 176 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/Comparison Results/Concrete/plot.py | import sys
import numpy as np
import random as ran
import matplotlib as m
import matplotlib
# import PcgComp
import random as ran
import time
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
def show_values(pc, fmt="%s", **kw):
from itertools import izip
pc.update_scalarmapp... | 3,951 | 30.870968 | 176 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/Comparison Results/Protein/plot2.py | import sys
import numpy as np
import random as ran
import matplotlib as m
import matplotlib
import PcgComp
import random as ran
import time
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
def show_values(pc, fmt="%.2f", **kw):
from itertools import izip
pc.update_scalarmapp... | 3,136 | 32.37234 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/Comparison Results/Protein/plot.py | import sys
import numpy as np
import random as ran
import matplotlib as m
import matplotlib
# import PcgComp
import random as ran
import time
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
def show_values(pc, fmt="%s", **kw):
from itertools import izip
pc.update_scalarmapp... | 4,695 | 34.044776 | 176 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - N^(3:2)/ProtResultsGps/averageFicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,405 | 31.697674 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - N^(3:2)/ProtResultsGps/averagePicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,405 | 31.697674 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - N^(3:2)/ProtResultsGps/plots.py | import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'Con... | 1,503 | 33.181818 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - N^(3:2)/ProtResultsGps/averageVarNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,405 | 31.697674 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - N^(3:2)/ConcResultsGps/averageFicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,461 | 33 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - N^(3:2)/ConcResultsGps/averagePicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,461 | 33 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - N^(3:2)/ConcResultsGps/plots.py | import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'Con... | 1,506 | 33.25 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - N^(3:2)/ConcResultsGps/averageVarNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,461 | 33 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - N^(3:2)/PowResultsGps/averageFicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,446 | 32.651163 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - N^(3:2)/PowResultsGps/averagePicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,446 | 32.651163 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - N^(3:2)/PowResultsGps/plots.py | import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'Con... | 1,514 | 33.431818 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - N^(3:2)/PowResultsGps/averageVarNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,446 | 32.651163 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - SqrtN/ProtResultsGps/averageFicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,405 | 31.697674 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - SqrtN/ProtResultsGps/averagePicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,405 | 31.697674 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - SqrtN/ProtResultsGps/plots.py | import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'Con... | 1,493 | 33.744186 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - SqrtN/ProtResultsGps/averageVarNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,405 | 31.697674 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - SqrtN/ConcResultsGps/averageFicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,461 | 33 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - SqrtN/ConcResultsGps/averagePicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,461 | 33 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - SqrtN/ConcResultsGps/plots.py | import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'Con... | 1,496 | 33.813953 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - SqrtN/ConcResultsGps/averageVarNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,461 | 33 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - SqrtN/PowResultsGps/averageFicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,446 | 32.651163 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - SqrtN/PowResultsGps/averagePicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,446 | 32.651163 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - SqrtN/PowResultsGps/plots.py | import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'Con... | 1,504 | 34 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF_OLD/RBF - SqrtN/PowResultsGps/averageVarNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,446 | 32.651163 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD_OLD/ConcResultsGps/averageFicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,461 | 33 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD_OLD/ConcResultsGps/averagePicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,461 | 33 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD_OLD/ConcResultsGps/plots.py | import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'Con... | 1,506 | 33.25 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD_OLD/ConcResultsGps/averageVarNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,461 | 33 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD_OLD/PowResultsGps/averageFicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,446 | 32.651163 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD_OLD/PowResultsGps/averagePicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,446 | 32.651163 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD_OLD/PowResultsGps/plots.py | import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'Con... | 1,514 | 33.431818 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD_OLD/PowResultsGps/averageVarNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,446 | 32.651163 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD/ARD_RESULTS_POWER/averageFicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,445 | 32.627907 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD/ARD_RESULTS_POWER/averagePicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,445 | 32.627907 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD/ARD_RESULTS_POWER/plots.py | import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'Con... | 1,514 | 33.431818 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD/ARD_RESULTS_POWER/averageVarNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,445 | 32.627907 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD/ARD_RESULTS_CONC/averageFicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,460 | 32.976744 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD/ARD_RESULTS_CONC/averagePicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,460 | 32.976744 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD/ARD_RESULTS_CONC/plots.py | import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'Con... | 1,506 | 33.25 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD/ARD_RESULTS_CONC/averageVarNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,460 | 32.976744 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD/ARD_RESULTS_PROTEIN/averageFicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,407 | 31.744186 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD/ARD_RESULTS_PROTEIN/averagePicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,407 | 31.744186 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD/ARD_RESULTS_PROTEIN/plots.py | import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'Con... | 1,503 | 33.181818 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/ARD/ARD_RESULTS_PROTEIN/averageVarNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,407 | 31.744186 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/CLASS/CL_RESULTS_CREDIT/averageFicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,480 | 33.44186 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/CLASS/CL_RESULTS_CREDIT/averagePicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,480 | 33.44186 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/CLASS/CL_RESULTS_CREDIT/plots.py | import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'Con... | 1,500 | 33.113636 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/CLASS/CL_RESULTS_CREDIT/averageVarNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,480 | 33.44186 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/CLASS/CL_RESULTS_SPAM/averageFicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,494 | 33.767442 | 175 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/CLASS/CL_RESULTS_SPAM/averagePicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,494 | 33.767442 | 175 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/CLASS/CL_RESULTS_SPAM/plots.py | import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'Con... | 1,498 | 33.068182 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/CLASS/CL_RESULTS_SPAM/averageVarNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,495 | 33.790698 | 176 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF/RBF_RESULTS_CONCRETE/averageFicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,460 | 32.976744 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF/RBF_RESULTS_CONCRETE/averagePicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,460 | 32.976744 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF/RBF_RESULTS_CONCRETE/plots.py | import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'Con... | 1,506 | 33.25 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF/RBF_RESULTS_CONCRETE/averageVarNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,460 | 32.976744 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/GpStuff Comparison/RBF/RBF_RESULTS_POWER/averageFicNML.py | import numpy as np
# names = ['Concrete - Block Precon','Concrete - Pitc Precon', 'Concrete - Fitc Precon','Concrete - Nyst Precon', 'Concrete - Spec Precon', 'Concrete - Randomized SVD']
# files = ['ConcBlock.txt','ConcPitc.txt', 'ConcFitc.txt','ConcNyst.txt','ConcSpec.txt','ConcSvd.txt']
# names = ['Protein - Block ... | 1,445 | 32.627907 | 168 | py |
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