Installation:

Default installation directory is /usr/local. To specifya different directory, add -DCMAKE_INSTALL_PREFIX=/path/to/install/dir to cmake invocation in step 4.

1. get cmake at www.cmake.org
2. create a build directory, say $HOME/build
3. cd $HOME/build
4. cmake /path/to/cnpy
5. make
6. make install

Description:

There are two functions for writing data: npy_save, npz_save.

template<typename T> void npy_save(std::string fname, const T* data, const unsigned int* shape, const unsigned int ndims, std::string mode = "w") {
template<typename T> void npz_save(std::string zipname, std::string fname, const T* data, const unsigned int* shape, const unsigned int ndims, std::string mode = "w")

There are 3 functions for reading. npy_load will load a .npy file. npz_load(fname) will load a .npz and return a dictionary of NpyArray structues. npz_load(fname,varname) will load and return the NpyArray for data varname from the specified .npz file.
Note that NpyArray allocates char* data using new[] and *will not* delete the data upon the NpyArray destruction. You are responsible for delete the data yourself.

std::map<std::string,cnpy::NpyArray> cnpy::npz_load(std::string fname)
cnpy::NpyArray cnpy::npz_load(std::string fname, std::string varname) 
cnpy::NpyArray cnpy::npy_load(std::string fname)

The data structure for loaded data is below. Data is loaded into a a raw byte array. The array shape and word size are read from the npy header. You are responsible for casting/copying the data to its intended data type.

struct NpyArray {
    char* data;
    std::vector<unsigned int> shape;
    unsigned int word_size;
};


Usage examples:

//Write a npy file 
int nx = 10, ny = 20;
complex<double>* my_arr = new complex<double>[nx*ny];
const unsigned int shape[] = {ny,nx}; //cnpy assumes "row-major" data, so list the most quickly varying index last!
cnpy::npy_save("my_arr.npy",my_arr,shape,2,"w"); //"w" will overwrite an existing my_arr.npy file

//Append to a npy file
//If the shape of my_arr.npy is currently (n0,n1) and my_append has shape (ny,nx)
//then after appending, my_arry.npy will have shape (n0+ny,nx)
int nx = 10, ny = 20;
float* my_append = new float[nx*ny];
const unsigned int shape[] = {ny,nx};
cnpy::npy_save("my_arr.npy",my_append,shape,2,"a"); 

//Write an npz file with mixed data
int x = 1;
const unsigned int y_shape[] = {1};
cnpy::npz_save("params.npz","x",&EQUIL,shape,1,"w"); //"w" overwrites any existing file

double y = 2;
const unsigned int y_shape[] = {1};
cnpy::npz_save("params.npz","y",&EQUIL,shape,1,"a"); //"a" appends to existing file

int nx = 10, ny = 20;
float* my_arr = new float[nx*ny];
const unsigned int z_shape[] = {ny,nx}; 
cnpy::npz_save("params.npz","my_arr",my_arr,shape,2,"a");

//Load an npy file
NpyArray my_arr = npy_load("my_arr.npy");
float* data = reinterpret_cast<float*>(my_arr.data);
assert(my_arr.word_size == sizeof(float)) 
delete[] data; //you are always responsible for deleting the allocated data