libasd

A C++11 header-only library to read an .asd file generated by high-speed AFM, depending only on the C++ standard library.

libasd provides a binding for Python3 depending on pybind11.

Table of Contents

• libasd
• Python usage
  • Building Python Library
  • Example Code
  • With Numpy
  • Miscellaneous
• C++ usage
• FAQ
  • Read file header only, not whole data
  • Without iostreams
  • How does it contain data
  • Hook Container and Allocator
• Licensing terms and Citation

Usage in Python3

Installation via pip

If you are ...

• on Windows (x86_64), macOS (x86_64), or Linux (x86_64) and
• using Python 3.6, 3.7, 3.8, 3.9, 3.10, or 3.11,

you can install it via pip.

console $ pip install libasd

The complete list of supported environment can be found here

Otherwise, you need to build it by yourself (see the following section).

Building by yourself

It depends on pybind11. The build script uses CMake. Please make sure that you have installed cmake.

console $ git clone --recursive https://github.com/ToruNiina/libasd.git $ pip install --user ./libasd

Example Code

After installation, you can use the library in the following way.

```python import libasd import numpy as np import matplotlib.pyplot as plt

data = libasd.read_asd("example.asd")

print("version = {}" .format(data.header.fileversion)) print("image size = {}x{}" .format(data.header.xpixel, data.header.y_pixel)) print("there are {} frames.".format(len(data.frames)))

plt.imshow(data.frames[0].image(), cmap="afmhot") plt.show() ```

Unlike C++ version, Python version requires neither a version information nor a channel information. By reading the file, it extracts the information at a runtime, dynamically. C++ version requires both of them in order to determine types at a compile time, statically.

If the file contains several channels, then the data will have data.channels that is a list of frames.

```python print("version = {}".format(data.header.fileversion)) print("number of channels = {}".format(len(data.channels))) print("type of channel1 = {}".format(data.header.datatype1ch)) print("type of channel2 = {}".format(data.header.datatype_2ch)) print("number of frames: 1ch = {}, 2ch = {}".format(len(data.channels[0]), len(data.channels[1])))

It plots 10-th frame in the first(0-th) channel.

plt.imshow(data.channels[0][10].image(), cmap="afmhot") plt.show() ```

For more details, run help(data) on the python interpreter.

With NumPy

Because libasd aims the interoperability with NumPy, frame.image() function returns numpy.ndarray.

python img = data.frames[0].image() # img is numpy.ndarray

libasd.Frame also has data object as a member that contains the same information as the return value of image. It uses Buffer protocol relying on pybind11 that enables users to cast a libasd.Frame object to NumPy Array without copying all the elements in the frame (don't forget to set copy = False).

```python import libasd import numpy as np

read the data

data = libasd.read_asd("example.asd")

cast frame data into numpy Array

frame_0 = np.array(data.frames[0].data, copy = False) ```

To manipulate the frame datas, it is recommended to cast the data to the NumPy Arrays.

Miscellaneous

Python binding provides a method to read a header information only.

```python import libasd

header = libasd.read_header("example.asd")

print("version = {}" .format(header.fileversion)) print("image size = {}x{}".format(header.xpixel, header.y_pixel)) ```

And it also supports reading raw data. read_asd returns frame data after converting the raw data to the height information, but read_raw_data returns frames without any conversion.

```python import libasd

rawdata = libasd.readrawdata("example.asd") rawframe0 = np.array(rawdata.frames[0].data, copy = False) plt.imshow(rawframe0) plt.show() ```

Usage in C++

libasd is a header-only library, so you don't need to build anything if you use it in your C++ code.

The only thing you have to do is adding path/to/libasd to your include path when you compile your code.

sh $ g++ -I/path/to/libasd -std=c++11 your_code.cpp

Then you can read the data in the way described below.

```cpp

include

include

include

int main() { std::ifstream ifs("example.asd"); const auto data = asd::read_asd(ifs);

std::cout << "x_pixel = " << data.header.x_pixel << '\n';
std::cout << "y_pixel = " << data.header.y_pixel << '\n';

for(auto const& frame : data.frames)
{
    for(auto const& line : frame)
    {
        for(auto const& pixel : line)
        {
            std::cout << pixel << ','; // height [nm] for topography, ...
        }
        std::cout << '\n';
    }
    std::cout << "\n\n";
}
std::cout << std::flush;
return 0;

} ```

Here you can access each frame, line, and pixel intuitively by using range-based for loops.

For the N-channel data, you need one more loop.

```cpp

include

include

include

int main() { std::ifstream ifs("example.asd"); const auto data = asd::read_asd>(ifs);

std::cout << "x_pixel = " << data.header.x_pixel << '\n';
std::cout << "y_pixel = " << data.header.y_pixel << '\n';

for(auto const& frames : data.channels)
{
    for(auto const& frame : frames)
    {
        for(auto const& line : frame)
        {
            for(auto const& pixel : line)
            {
                std::cout << pixel << ','; // height [nm] for topography, ...
            }
            std::cout << '\n';
        }
        std::cout << "\n\n";
    }
}
std::cout << std::flush;
return 0;

} ```

You can set file version and channel as a template parameter.

cpp const auto data = asd::read_asd<double, asd::ch<2>, asd::ver<0>>(ifs);

By default, these are set as channel 1, version 1 respectively.

You can access to each pixel in each line by index.

cpp const std::size_t x_pixel = data.header.x_pixel; const std::size_t y_pixel = data.header.y_pixel; for(const auto& frame : data.frames) { for(std::size_t y=0; y<y_pixel; ++y) { for(std::size_t x=0; x<x_pixel; ++x) { std::cout << frame[y][x]; // note: not [x][y]. } std::cout << '\n'; } std::cout << "\n\n"; }

Be careful with the order of index. Frame[y] returns a Line at y. So first you must specify y value of the pixel.

FAQ

I need only file-header information. Frame data are not needed.

libasd provides asd::read_header function (libasd.read_header in python). It reads only file-header information.

```cpp

include

include

include

int main() { std::ifstream ifs("example.asd"); const auto data = asd::readheader(ifs); // If you want to set file version information, // data = libasd.readheaderasd::ver<2>("example.asd"); // file version is set as asd::ver<1> by default. return 0; } ```

```python import libasd

data = libasd.read_header("example.asd");

If you want to set file version information,

data = libasd.read_header("example.asd", version = 2);

```

It does not need the channel information because header format does not depend on the number of channels.

I don't want to use streams. What can I do?

You can pass a char const* to read_asd function in exactly the same way as iostreams.

How does it contain frame data?

It contains pixels in one frame data by one, contiguous container.

You might think that libasd contains a frame as an array of arrays because you can access to the pixel by using this form frame[y][x]. So you might be afraid of the performance loss that is owing to a cache-miss while you access to each line. But it is NOT true.

To make the usage easier, libasd provides a proxy class to access each lines. It wraps frame class and enable you to access a particular line by using container-like interface.

You can use raw std::vector<pixel_type>::(const_)iterator in the following way if you want.

cpp const auto frame = data.frames.front(); for(auto iter = frame.raw_begin(), iend = frame.raw_end(); iter != iend; ++iter) { std::cerr << *iter << ' '; // you can traverse all the pixel in one frame! }

Can I use my awesome container with libasd?

If you implemented or found a container or an allocator that has a great feature, you may want to use it with libasd instead of std::vector<T, std::allocator<T>>.

In libasd, you can specify the container used to store pixel data by passing the special struct as a template parameter. NOTE: The container should be randomly accessible(by using operator[]). But ContiguousContainer concept is not required (e.g. std::deque can be used as a backend container).

For example, asd::container::vec that is used by default is defined as follows.

```cpp namespace asd { namespace container {

struct vec { template struct rebind { typedef std::vector> other; }; };

template struct containertraits> { using ptraccessibility = std::truetype; using valuetype = T; };

} // container } // asd ```

libasd uses vec class to define container in the same way as STL does to define allocators.

cpp typedef typename vec::template rebind<int>::other int_array;

The struct container_traits provides a tag to dispatch utility functions. If the container has an interface to access the pointer that points the first element as a traditional C-array, ptr_accessibility is set as std::true_type, otherwise, std::false_type.

Additionally, to deal with different interfaces of containers, libasd has some helper functions. If it is needed (the container has a different interface from standard containers), you should overload these functions.

Fortunately, if your awesome container has member functions that are named in the same way as STL containers (e.g. data(), size(), resize() and clear()), libasd automatically finds and uses them.

```cpp // example: add overload for std::vector.

namespace asd { namespace container {

template inline T const* getptr(const std::vector& v) noexcept { return v.data(); } template inline std::sizet size(const std::vector& v) noexcept { return v.size(); } template inline void resize(std::vector& v, const std::size_t N) { return v.resize(N); } template inline void clear(std::vector& v) { return v.clear(); }

} // container } // asd ```

After implementing these structs and functions, you can use your awesome container/allocator class with libasd by passing your dispatcher to read_asd function.

By default, asd::container::vec and asd::container::deq are defined in libasd/container_dispatcher.hpp. They correspond to std::vector and std::deque, respectively.

Additionally, you can find asd::container::boost_vec, asd::container::boost_static_vec, asd::container::boost_small_vec and asd::container::boost_deq in the file libasd/boost/container_dispatcher.hpp. It is not included by default, but you can manually include this file. Then you can use containers provided by the Boost.Container library if you already installed it.

Licensing terms

Author - Toru Niina

cite as

Toru Niina. (2018, March 28). ToruNiina/libasd v1.0.0 (Version v1.0.0). Zenodo. http://doi.org/10.5281/zenodo.1209119

This product is licensed under the terms of the MIT License.

• Copyright (c) 2017 Toru Niina

All rights reserved.