Commit 0f62d443 authored by Chinmay Patwardhan's avatar Chinmay Patwardhan
Browse files

Merge branch '45-fix-stochLevel-config' into 'feature'

Resolve "StochLevel is not set via config file"

Closes #45

See merge request !60
parents 9f42bba7 9aa0aa1a
Pipeline #169532 failed with stages
in 82 minutes and 9 seconds
......@@ -5,8 +5,8 @@ set(SPACE_DIM 2 CACHE STRING "SPACE_DIM")
set(USE_FFTW ON CACHE STRING "USE_FFTW")
set(USE_SPLITTED_COMMS ON CACHE STRING "USE_SPLITTED_COMMS")
set(USE_SPACETIME OFF CACHE STRING "USE_SPACETIME")
#set(COMPILER_OPTIMIZE -O0 CACHE STRING "COMPILER_OPTIMIZE")
set(COMPILER_OPTIMIZE -O3 CACHE STRING "COMPILER_OPTIMIZE")
set(COMPILER_OPTIMIZE -O0 CACHE STRING "COMPILER_OPTIMIZE")
#set(COMPILER_OPTIMIZE -O3 CACHE STRING "COMPILER_OPTIMIZE")
set(NO_DEPRECATED OFF CACHE STRING "NO_DEPRECATED")
set(AFFINE_LINEAR_TRAFO ON CACHE STRING "AFFINE_LINEAR_TRAFO")
set(BUILD_TESTS OFF CACHE STRING "BUILD_TESTS")
......
# ----- Problem Settings -----
#Problem = UniformDistributionBabuskaPDE
Problem = SparseGridBabuskaPDE
Model = LagrangeElliptic
#Mesh = Line;
#Mesh = Triangle
Mesh = UnitSquare
#Mesh = Square-1x1
#Mesh = Square500
#Mesh = Rock
#Estimator = MC
#Estimator = MonteCarlo
#Estimator = MLMC
#Estimator = MultilevelMonteCarlo
Estimator = SC
#Estimator = StochasticCollocation
#Estimator = MLSC
#Estimator = MultilevelStochasticCollocation
degree = 2
#degree = 5
Quantity = L2
#Functional = Energy
#Funcitonal = H1
#Functional = Outflow
#Functional = Goal
# ----- Monte Carlo -----
epsilon = 0.01
Level = 4
Samples = 100
#initLevels = [2,3,4]
MCParallel = false
OnlyFine = true
#----- Sparse Grid ------
stochLevel = 3
# ----- Plotting -----
PDESolverPlotting = 1
# ----- Verbose -----
precision = 3
MCVerbose = 1
MLMCVerbose = 1
MainVerbose = 1
MeshVerbose = 1
ConfigVerbose = 1
LinearVerbose = 0
NewtonVerbose = 0
AssembleVerbose = 0
PDESolverVerbose = 0
GeneratorVerbose = 0
#loadconf = mlmc_transport.conf
loadconf = mlmc_elliptic.conf
\ No newline at end of file
loadconf = mlmc_elliptic.conf
#loadconf = babuska.conf
\ No newline at end of file
......@@ -17,7 +17,7 @@ class MainProgram {
private:
int verbose = 1;
std::string estimatorName = "MultilevelMonteCarlo";
std::string estimatorName;
public:
std::unique_ptr<Estimator> estimator;
......
......@@ -116,6 +116,7 @@ public:
config.get("Samples", _initSamples);
config.get("initLevels", _levelVec);
config.get("initSamples", _samplesVec);
config.get("stochLevel", _stochLevel);
}
EstimatorCreator WithInitLevel(int level) {
......
......@@ -18,6 +18,12 @@ protected:
bool onlyFine;
bool parallel;
int initSamples;
double epsilon;
SampleID fineId;
SampleID coarseId;
......
......@@ -17,6 +17,12 @@ protected:
bool onlyFine;
int stochLevel;
double epsilon;
bool parallel;
SampleID fineId;
SampleID coarseId;
......
......@@ -7,7 +7,6 @@
class SparseGridGenerator : public SampleGenerator<RVector> {
protected:
TasGrid::TasmanianSparseGrid grid;
TasGrid::TypeOneDRule rule;
......@@ -23,22 +22,27 @@ protected:
RVector sample{};
std::vector<RVector> samples{};
public:
std::vector<double> weights{};
std::vector<RVector> samples{};
TasGrid::TasmanianSparseGrid grid;
void fillSampleVector() {
std::vector<double> points = grid.getPoints();
for (auto it_start = points.begin(); it_start != points.end(); it_start += dimension)
samples.emplace_back(std::vector<double>(it_start, it_start + dimension));
std::vector<double> points = grid.getPoints();
for (auto it_start = points.begin(); it_start != points.end(); it_start += dimension)
samples.emplace_back(std::vector<double>(it_start, it_start + dimension));
}
void drawSample(const SampleID &id) override {
sample = samples[id.number];
weight = weights[id.number];
sample = samples[id.number];
weight = weights[id.number];
};
public:
// Todo:
// * Use other grid types. (e.g. for normally distributed rv)
......@@ -70,6 +74,16 @@ public:
grid.makeGlobalGrid(dimension, outputs, level, depth, rule);
}
void CreateSequenceGrid(int level, TasGrid::TypeOneDRule rule) {
grid.makeSequenceGrid(dimension, outputs, level, depth, rule);
}
void UpdateGlobalGrid(int level) {
grid.updateGlobalGrid(level,depth);
}
std::vector<RVector> GetSamples() {
return samples;
}
......@@ -78,9 +92,20 @@ public:
return weights;
}
std::vector<double> GetWeightVector() {
return grid.getQuadratureWeights();
}
// Todo implement linear trafo for areas other than [-1, 1]^N
// Todo Use TASMANIAN interface for that
void DomainTransform(std::vector<double> const & a,
std::vector<double> const & b) {
grid.setDomainTransform(a, b);
}
double SampleWeight(const SampleID &id) {
return weights[id.number];
}
......
......@@ -55,6 +55,8 @@ public:
return "Interval";
else if (_problem.find("2D") != string::npos)
return "Square";
else if (_problem == "UniformDistributionBabuskaPDE" || _problem == "SparseGridBabuskaPDE")
return "UnitSquare";
else
return "Interval";
}
......
......@@ -133,7 +133,9 @@ public:
return VectorField(0.0, -1.0);
}
Scalar Load(const Point &x) const override { return 0.0; }
Scalar Load(const Point &x) const override {
return 0.0;
}
Tensor Permeability(const cell &c) const override {
return One;
......@@ -142,6 +144,98 @@ public:
string Name() const override { return "Laplace2D"; }
};
class SparseGridBabuskaPDE : public IStochasticEllipticProblem {
private:
SparseGridGenerator sparseGridGenerator;
double a_min = 0.01;
std::vector<double> a = {0, 0, 0, 0};
std::vector<double> b = {1, 1, 1, 1};
public:
explicit SparseGridBabuskaPDE(const Meshes &meshes)
: IStochasticEllipticProblem(meshes),
sparseGridGenerator(SparseGridGenerator(meshes, 4, 0, 1)) {
int stochLevel;
config.get("stochLevel", stochLevel);
sparseGridGenerator.CreateGlobalGrid(stochLevel);
sparseGridGenerator.DomainTransform(a, b);
sparseGridGenerator.weights = sparseGridGenerator.GetWeightVector();
sparseGridGenerator.fillSampleVector();
}
void DrawSample(const SampleID &id) override {
sparseGridGenerator.DrawSample(id);
}
Scalar Solution(const Point &x) const override {
return -x[1];
}
VectorField Flux(const Point &x) const override {
return VectorField(0.0, -1.0);
}
Scalar Load(const Point &x) const override {
return 0.0;
}
int NumOfSamples() override {
return sparseGridGenerator.GetNumPoints();
}
Tensor Permeability(const cell &c) const override {
return (a_min + exp(
exp(-1.0 / 8.0) * cos(M_PI * c()[1]) * this->sparseGridGenerator.EvalSample()[0]
+ sin(M_PI * c()[1]) * this->sparseGridGenerator.EvalSample()[2]
+ cos(M_PI * c()[0]) * this->sparseGridGenerator.EvalSample()[1]
+ sin(M_PI * c()[0]) * this->sparseGridGenerator.EvalSample()[3])) * One;
}
string Name() const override { return "SparseGridBabuskaPDE"; }
};
class UniformDistributionBabuskaPDE : public IStochasticEllipticProblem {
private:
UniformDistributionRVector rVectorGenerator;
double a_min = 1 / 100;
public:
explicit UniformDistributionBabuskaPDE(const Meshes &meshes)
: IStochasticEllipticProblem(meshes),
rVectorGenerator(UniformDistributionRVector(meshes, 4, 0.0, 1.0)) {}
void DrawSample(const SampleID &id) override {
rVectorGenerator.DrawSample(id);
}
Scalar Solution(const Point &x) const override {
return -x[1];
}
VectorField Flux(const Point &x) const override {
return VectorField(0.0, -1.0);
}
Scalar Load(const Point &x) const override {
return 0.0;
}
Tensor Permeability(const cell &c) const override {
return (a_min
+ exp(exp(-1.0 / 8.0) * (cos(M_PI * c()[1]) * this->rVectorGenerator.EvalSample()[0]
+ sin(M_PI * c()[1]) * this->rVectorGenerator.EvalSample()[2]
+ cos(M_PI * c()[0]) * this->rVectorGenerator.EvalSample()[1]
+ sin(M_PI * c()[0]) * this->rVectorGenerator.EvalSample()[3]))) * One;
}
string Name() const override { return "UniformDistributionBabuskaPDE"; }
};
IStochasticEllipticProblem *
CreateStochasticEllipticProblem(const string &problemName, const Meshes &meshes) {
if (problemName == "StochasticLaplace1D")
......@@ -154,7 +248,9 @@ CreateStochasticEllipticProblem(const string &problemName, const Meshes &meshes)
return new Laplace2D(meshes);
if (problemName == "StochasticLaplace2DTest")
return new StochasticLaplace2DTest(meshes);
if (problemName == "SparseGridTestPDE")
return new SparseGridTestPDE(meshes);
if (problemName == "SparseGridBabuskaPDE")
return new SparseGridBabuskaPDE(meshes);
if (problemName == "UniformDistributionBabuskaPDE")
return new UniformDistributionBabuskaPDE(meshes);
Exit(problemName + " not found")
}
\ No newline at end of file
......@@ -23,39 +23,6 @@ public:
}
};
class SparseGridTestPDE : public IStochasticEllipticProblem {
UniformDistributionRVector rVectorGenerator;
private:
double a_min = 1/100 ;
public:
explicit SparseGridTestPDE(const Meshes &meshes) : IStochasticEllipticProblem(meshes),
rVectorGenerator(UniformDistributionRVector(meshes, 4, 0.0, 1.0)) {}
void DrawSample(const SampleID &id) override {
rVectorGenerator.DrawSample(id);
}
//Sets dirichlet boundary condition
Scalar Solution(const Point &x) const override{
return 0.0;
}
//sets neumann boundary conditions
VectorField Flux(const Point &x) const override {
return VectorField(1.0,0.0);
}
Scalar Load(const Point &x) const override {
return 0.0;
}
Tensor Permeability(const cell &c) const override {
return a_min + exp((cos(M_PI * c()[1]) * this -> rVectorGenerator.EvalSample()[0] + sin(M_PI * c()[1]) * this -> rVectorGenerator.EvalSample()[2]) * exp(-1/8)
+ (cos(M_PI * c()[0]) * this -> rVectorGenerator.EvalSample()[1] + sin(M_PI * c()[0]) * this -> rVectorGenerator.EvalSample()[4])* exp(-1/8));;
}
string Name() const override { return "SparseGridTestPDE";}
};
IStochasticEllipticProblem *
CreateStochasticEllipticProblem(const string &problemName, const Meshes &meshes);
......
......@@ -29,6 +29,7 @@ const ConfigMap DefaultEllipticConfigMap = {
{"sigma", "1.0"},
{"lambda", "[0.15, 0.15]"},
{"smoothing", "1.8"},
{"Estimator", "MLMC"},
// ----- Plotting -----
{"PDESolverPlotting", "1"},
......
......@@ -267,7 +267,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.5"
"version": "3.8.5"
}
},
"nbformat": 4,
......
......@@ -474,7 +474,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.5"
"version": "3.7.3"
}
},
"nbformat": 4,
......
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This diff is collapsed.
......@@ -2,17 +2,16 @@
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "0683418b",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'/home/chinsp/CLionProjects/mlmc/notebooks'"
"'/home/chinsp/mluq/build/TASMANIAN/Python'"
]
},
"execution_count": 1,
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
......@@ -26,27 +25,37 @@
},
{
"cell_type": "code",
"execution_count": 2,
"id": "9fe07bcd",
"execution_count": 9,
"metadata": {},
"outputs": [],
"outputs": [
{
"ename": "FileNotFoundError",
"evalue": "[Errno 2] No such file or directory: '../build/TASMANIAN/Python'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-9-192464e0df79>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mchdir\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'../build/TASMANIAN/Python'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '../build/TASMANIAN/Python'"
]
}
],
"source": [
"os.chdir('../build/TASMANIAN/Python')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "4f4a480b",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'/home/chinsp/CLionProjects/mlmc/build/TASMANIAN/Python'"
"'/home/chinsp/mluq/build/TASMANIAN/Python'"
]
},
"execution_count": 3,
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
......@@ -57,10 +66,26 @@
},
{
"cell_type": "code",
"execution_count": 4,
"id": "f130bc08",
"execution_count": 11,
"metadata": {},
"outputs": [],
"outputs": [
{
"ename": "OSError",
"evalue": "/home/chinsp/mlmc/build/TASMANIAN/Python/../DREAM/libtasmaniandream.so: cannot open shared object file: No such file or directory",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mOSError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-11-379d5cfd7bb8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mTasmanian\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/home/chinsp/mluq/build/TASMANIAN/Python/Tasmanian.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 41\u001b[0m \u001b[0mSparseGrid\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTasmanianSparseGrid\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 42\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 43\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mTasmanianDREAM\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mDREAM\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 44\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 45\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mTasmanianAddons\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/home/chinsp/mluq/build/TASMANIAN/Python/TasmanianDREAM.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 29\u001b[0m \u001b[0;31m##############################################################################################################################################################################\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 30\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 31\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mTasmanianDreamLikely\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 32\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mTasmanianDreamSampler\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 33\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mTasmanianDreamState\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mDreamState\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mState\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/home/chinsp/mluq/build/TASMANIAN/Python/TasmanianDreamLikely.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 36\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mTasmanianConfig\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mTasmanianInputError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mInputError\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 37\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 38\u001b[0;31m \u001b[0mpLibDTSG\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcdll\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLoadLibrary\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m__path_libdream__\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 39\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 40\u001b[0m \u001b[0mpLibDTSG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtsgGetNumOutputsLikelihood\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrestype\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mc_int\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/snap/jupyter/6/lib/python3.7/ctypes/__init__.py\u001b[0m in \u001b[0;36mLoadLibrary\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 432\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 433\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mLoadLibrary\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 434\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dlltype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 435\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 436\u001b[0m \u001b[0mcdll\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mLibraryLoader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mCDLL\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/snap/jupyter/6/lib/python3.7/ctypes/__init__.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, name, mode, handle, use_errno, use_last_error)\u001b[0m\n\u001b[1;32m 354\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 355\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mhandle\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 356\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_handle\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_dlopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 357\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 358\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_handle\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mhandle\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mOSError\u001b[0m: /home/chinsp/mlmc/build/TASMANIAN/Python/../DREAM/libtasmaniandream.so: cannot open shared object file: No such file or directory"
]
}
],
"source": [
"import Tasmanian\n",
"import numpy as np\n",
......@@ -69,7 +94,6 @@
},
{
"cell_type": "markdown",
"id": "d7ad54ea",
"metadata": {},
"source": [
"# Sparse Grids\n",
......@@ -89,7 +113,6 @@
{
"cell_type": "code",
"execution_count": 13,
"id": "c69ac2e5",
"metadata": {},
"outputs": [
{
......@@ -157,7 +180,6 @@
{
"cell_type": "code",
"execution_count": null,
"id": "de05f425",
"metadata": {},
"outputs": [],
"source": [
......@@ -167,7 +189,6 @@
{
"cell_type": "code",
"execution_count": 6,
"id": "7dc50120",
"metadata": {},
"outputs": [
{
......@@ -200,7 +221,6 @@
{
"cell_type": "code",
"execution_count": 7,
"id": "7974743f",
"metadata": {},
"outputs": [
{
......@@ -240,7 +260,6 @@
{
"cell_type": "code",
"execution_count": 8,
"id": "68d2afa1",
"metadata": {},
"outputs": [
{
......@@ -350,7 +369,6 @@
{
"cell_type": "code",
"execution_count": 9,
"id": "b4a3b8d0",
"metadata": {},
"outputs": [
{
......@@ -414,7 +432,6 @@
{
"cell_type": "code",
"execution_count": 10,
"id": "ee3b6e86",
"metadata": {},
"outputs": [],
"source": [
......@@ -428,7 +445,6 @@
{
"cell_type": "code",
"execution_count": 11,
"id": "38350dee",
"metadata": {},
"outputs": [
{
......@@ -500,7 +516,6 @@
},
{
"cell_type": "markdown",
"id": "b9437334",
"metadata": {},
"source": [
"## References\n",
......@@ -511,7 +526,6 @@
{
"cell_type": "code",
"execution_count": null,
"id": "a659ad1f",
"metadata": {},
"outputs": [],
"source": []
......@@ -533,7 +547,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.5"
"version": "3.7.3"
}
},
"nbformat": 4,
......
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