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# -*- coding: utf-8 -*-
"""
Created on Wed Jan 15 10:17:16 2020

@author: Mike
"""

from reikna.core import Annotation, Type, Transformation, Parameter
from reikna.cluda import dtypes, any_api
from pyopencl import cltypes

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import numpy
import pyopencl as cl
import pyopencl.array as array

src = """
__kernel void test(__global int *a)
{
    int gid = get_global_id(0);
    a[gid] = gid;
}

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import time
import numpy as np
from scipy.interpolate import griddata

def func(x, y):
    return x*(1-x)*np.cos(4*np.pi*x) * np.sin(4*np.pi*y**2)**2

grid_x, grid_y = np.mgrid[0:1:200j, 0:1:200j]

points = np.random.rand(410500, 2)

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import numpy
import pyopencl as cl
import pyopencl.array as array

ctx = cl.create_some_context()
queue = cl.CommandQueue(ctx)

program = cl.Program(ctx, """
#define BLOCK_LEN 256

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import time
import numpy

from reikna.cluda import cuda_api
from reikna.fft import FFT, FFTShift

import reikna.cluda.dtypes as dtypes
from reikna.core import Transformation, Parameter, Annotation, Type

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#!/usr/bin/env python
# -*- coding: utf-8 -*-

import numpy as np
import pyopencl as cl
from mako.template import Template

a_np = np.random.rand(50000).astype(np.float32)
b_np = np.random.rand(50000).astype(np.float32)

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import numpy

from reikna.cluda import ocl_api
from reikna.core import Annotation, Type, Parameter
from reikna.algorithms import PureParallel
import reikna.cluda.functions as functions


api = ocl_api()
thr = api.Thread.create()

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bogdan@Aldan ~/w/r/h/test> py.test
======================================= test session starts ========================================
platform darwin -- Python 3.4.2 -- py-1.4.25 -- pytest-2.6.3
plugins: cov
collected 847 items 

test_Parser.py .
test_blocks.py ...............
test_call.py ...................................................
test_cast.py ....................................................................................

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# Exercise 1 from http://webapp.dam.brown.edu/wiki/SciComp/CudaExercises

# Transposition of a matrix
# by Hendrik Riedmann <riedmann@dam.brown.edu>

from __future__ import division, print_function

import pycuda.driver as cuda
import pycuda.gpuarray as gpuarray
import pycuda.autoinit

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import numpy as np
import pyopencl as cl
import pyopencl.array as array

ctx = cl.create_some_context()
queue = cl.CommandQueue(ctx)

a = np.random.rand(128).astype(np.float32)
a_gpu = array.to_device(queue, a)
dest_gpu = array.empty_like(a_gpu)