### Run Taichi MPM128 Example

Source: https://docs.taichi-lang.org/docs/dev_install

Executes a specific Taichi example script to verify the installation. Ensure you are in the Taichi project directory.

```bash
python3 python/taichi/examples/simulation/mpm128.py
```

--------------------------------

### View All Taichi Examples

Source: https://docs.taichi-lang.org/docs/hello_world

Execute this command to access the complete list of Taichi examples.

```bash
ti example

```

--------------------------------

### Install Test Dependencies

Source: https://docs.taichi-lang.org/docs/write_test

Before running the test launcher, install the necessary dependencies using pip.

```bash
pip install -r requirements_test.txt
```

--------------------------------

### Install ffmpeg on Ubuntu

Source: https://docs.taichi-lang.org/docs/export_results

Use apt-get to install ffmpeg on Ubuntu systems.

```bash
sudo apt-get update  
sudo apt-get install ffmpeg  
```

--------------------------------

### Save Fractal Example

Source: https://docs.taichi-lang.org/docs/hello_world

Run this command to save the fractal example to your current working directory.

```bash
ti example -s fractal

```

--------------------------------

### Install Taichi from Wheel Package

Source: https://docs.taichi-lang.org/docs/faq

Install Taichi and its dependencies using downloaded wheel packages on a local server. Ensure all dependencies are installed before Taichi.

```bash
python -m pip install xxxx.whl
```

--------------------------------

### Install pre-commit

Source: https://docs.taichi-lang.org/docs/contributor_guide

Install the pre-commit tool, which is used to enforce code style checks.

```bash
pip install pre-commit
```

--------------------------------

### Print Fractal Example Source Code

Source: https://docs.taichi-lang.org/docs/hello_world

Use this command to print the source code of the fractal example.

```bash
ti example -p fractal

```

--------------------------------

### Print Fractal Example Source Code (Alternative)

Source: https://docs.taichi-lang.org/docs/hello_world

An alternative command to print the source code of the fractal example.

```bash
ti example -P fractal

```

--------------------------------

### Install ffmpeg on Arch Linux

Source: https://docs.taichi-lang.org/docs/export_results

Use pacman to install ffmpeg on Arch Linux.

```bash
pacman -S ffmpeg  
```

--------------------------------

### Install Taichi Package

Source: https://docs.taichi-lang.org/docs/hello_world

Install the Taichi package using pip. This is a prerequisite for using Taichi.

```bash
pip install taichi
```

--------------------------------

### Install Taichi Nightly

Source: https://docs.taichi-lang.org/docs/tutorial

Install the Taichi nightly build for compiling kernels. Ensure you use a version compatible with your project.

```bash
pip install -i https://pypi.taichi.graphics/simple/ taichi-nightly
```

--------------------------------

### Test ffmpeg Installation on Windows

Source: https://docs.taichi-lang.org/docs/export_results

Run this command in Windows cmd or PowerShell to verify ffmpeg installation.

```bash
ffmpeg -version  
```

--------------------------------

### Check Vulkan SDK Installation on Linux

Source: https://docs.taichi-lang.org/docs/dev_install

After enabling the Vulkan backend, enter the Taichi build shell and run 'vulkaninfo' to confirm the Vulkan SDK is properly installed and configured.

```bash
./build.py --shell
```

```bash
vulkaninfo
```

--------------------------------

### Example: Fetching Color Information

Source: https://docs.taichi-lang.org/docs/ggui

Demonstrates fetching the color buffer as a NumPy array and writing it as a video frame.

```python
window = ti.ui.Window("Test for getting image buffer from ggui", (768, 768), vsync=True)
video_manager = ti.tools.VideoManager("OutputDir")

while window.running:
    # render_scene()
    img = window.get_image_buffer_as_numpy()
    video_manager.write_frame(img)
    window.show()

video_manager.make_video(gif=True, mp4=True)
```

--------------------------------

### Install Taichi from a Mirror Source

Source: https://docs.taichi-lang.org/docs/install

Use this pip command to install Taichi from a mirror source if the default download process is interrupted by HTTPSConnection errors.

```bash
pip install taichi -i https://pypi.douban.com/simple

```

--------------------------------

### Example: Constructing Matrix from Rows

Source: https://docs.taichi-lang.org/api/taichi

Demonstrates how to create a matrix by providing a list of vectors as rows.

```python
>>> @ti.kernel
def test():
    v1 = ti.Vector([1, 2, 3])
    v2 = ti.Vector([4, 5, 6])
    m = ti.Matrix.rows([v1, v2])
    print(m)
>>> test()
[[1, 2, 3], [4, 5, 6]]
```

--------------------------------

### Check Vulkan SDK Installation on Windows

Source: https://docs.taichi-lang.org/docs/dev_install

After enabling the Vulkan backend, enter the Taichi build shell using Python and run 'vulkaninfo' to confirm the Vulkan SDK is properly installed and configured.

```powershell
python ./build.py --shell
```

```powershell
vulkaninfo
```

--------------------------------

### Install Taichi in User Space

Source: https://docs.taichi-lang.org/docs/dev_install

Workaround for 'permission denied' errors during installation. Installs Taichi packages into the user's home directory, avoiding the need for root privileges.

```bash
python3 setup.py develop --user
```

```bash
python3 setup.py install --user
```

--------------------------------

### Test ffmpeg Installation on Linux

Source: https://docs.taichi-lang.org/docs/export_results

Run this command on Linux to check if ffmpeg is installed and accessible.

```bash
ffmpeg -h  
```

--------------------------------

### Install ffmpeg on macOS

Source: https://docs.taichi-lang.org/docs/export_results

Install ffmpeg on macOS using the homebrew package manager.

```bash
brew install ffmpeg  
```

--------------------------------

### Install CUDA on Arch Linux

Source: https://docs.taichi-lang.org/docs/dev_install

Install the CUDA toolkit on Arch Linux using the pacman package manager.

```bash
pacman -S cuda
```

--------------------------------

### Install wget using Homebrew

Source: https://docs.taichi-lang.org/docs/dev_install

Installs the 'wget' utility on macOS using the Homebrew package manager. This is a workaround for macOS systems that do not come with 'wget' pre-installed.

```bash
brew install wget
```

--------------------------------

### Check CUDA Installation

Source: https://docs.taichi-lang.org/docs/dev_install

Verify that the CUDA toolkit is correctly installed and accessible on your system by running the nvidia-smi command.

```bash
nvidia-smi
```

--------------------------------

### Install pre-commit hooks

Source: https://docs.taichi-lang.org/docs/contributor_guide

Install pre-commit as a git hook to automatically run checks before each commit.

```bash
pre-commit install
```

--------------------------------

### Install ffmpeg on CentOS and RHEL

Source: https://docs.taichi-lang.org/docs/export_results

Use yum to install ffmpeg on CentOS and RHEL systems.

```bash
sudo yum install ffmpeg ffmpeg-devel  
```

--------------------------------

### Python Logging Examples

Source: https://docs.taichi-lang.org/docs/developer_utilities

Demonstrates how to write logs at different levels in Python using the ti.* interface. Ensure ti is imported.

```python
import taichi as ti
ti.trace("Hello world!")
ti.debug("Hello world!")
ti.info("Hello world!")
ti.warn("Hello world!")
ti.error("Hello world!")
```

--------------------------------

### User Input Processing Example (mpm128)

Source: https://docs.taichi-lang.org/docs/ggui

An example demonstrating keyboard and mouse event processing for user input, including movement controls and mouse button actions.

```python
gravity = ti.Vector.field(2, ti.f32, shape=())
attractor_strength = ti.field(ti.f32, shape=())

while window.running:
    # keyboard event processing
    if window.get_event(ti.ui.PRESS):
        if window.event.key == 'r': reset()
        elif window.event.key in [ti.ui.ESCAPE]: break
    if window.event is not None: gravity[None] = [0, 0]  # if had any event
    if window.is_pressed(ti.ui.LEFT, 'a'): gravity[None][0] = -1
    if window.is_pressed(ti.ui.RIGHT, 'd'): gravity[None][0] = 1
    if window.is_pressed(ti.ui.UP, 'w'): gravity[None][1] = 1
    if window.is_pressed(ti.ui.DOWN, 's'): gravity[None][1] = -1

    # mouse event processing
    mouse = window.get_cursor_pos()
    # ...
    if window.is_pressed(ti.ui.LMB):
        attractor_strength[None] = 1
    if window.is_pressed(ti.ui.RMB):
        attractor_strength[None] = -1

    window.show()
```

--------------------------------

### Taichi List Generation Example

Source: https://docs.taichi-lang.org/docs/internal

Demonstrates how Taichi generates lists for sparse data structures. This example initializes fields and defines a kernel that triggers list generation for different SNode types.

```python
import taichi as ti

ti.init(print_ir=True)

x = ti.field(ti.i32)

S0 = ti.root
S1 = S0.dense(ti.i, 4)
S2 = S1.bitmasked(ti.i, 4)
S2.place(x)

@ti.kernel
def func():
    for i in x:
        print(i)

func()
```

--------------------------------

### Example: Creating a VectorNdarray

Source: https://docs.taichi-lang.org/api/taichi

Shows the instantiation of a VectorNdarray with specified vector size, data type, and shape.

```python
>>> a = ti.VectorNdarray(3, ti.f32, (3, 3))
```

--------------------------------

### Taichi Sine Function Example

Source: https://docs.taichi-lang.org/api/taichi

Demonstrates calculating the sine of elements in a Taichi matrix.

```python
>>> from math import pi 
>>> x = ti.Matrix([-pi/2., 0, pi/2.]) 
>>> ti.sin(x)  
[-1., 0., 1.]  
```

--------------------------------

### Camera Setup and Control

Source: https://docs.taichi-lang.org/api/taichi/ui

Demonstrates how to initialize a camera, set its position, lookat, and up vectors, and attach it to a window for user input tracking. This is useful for interactive 3D scenes.

```python
>>> scene = ti.ui.Scene()  # assume you have a scene
>>> 
>>> camera = ti.ui.Camera()
>>> camera.position(1, 1, 1)  # set camera position
>>> camera.lookat(0, 0, 0)  # set camera lookat
>>> camera.up(0, 1, 0)  # set camera up vector
>>> scene.set_camera(camera)
>>> 
>>> # you can also control camera movement in a window
>>> window = ti.ui.Window("GGUI Camera", res=(640, 480), vsync=True)
>>> camera.track_user_inputs(window, movement_speed=0.03, hold_key=ti.ui.RMB)
```

--------------------------------

### Uninstall Taichi Pip Build

Source: https://docs.taichi-lang.org/docs/dev_install

Uninstalls Taichi when it was installed using 'pip'. This is part of the process to get a fresh Taichi build.

```bash
pip uninstall taichi
```

--------------------------------

### Setup ti.tools.PLYWriter

Source: https://docs.taichi-lang.org/docs/export_results

Initialize PLYWriter with the number of vertices and optionally the number of faces and face type. num_vertices must be a positive integer.

```python
# num_vertices must be a positive int  
# num_faces is optional, default to 0  
# face_type can be either "tri" or "quad", default to "tri"  
  
# in our previous example, a writer with 1000 vertices and 0 triangle faces is created  
num_vertices = 1000  
writer = ti.tools.PLYWriter(num_vertices=num_vertices)  
  
# in the below example, a writer with 20 vertices and 5 quadrangle faces is created  
writer2 = ti.tools.PLYWriter(num_vertices=20, num_faces=5, face_type="quad")  
```

--------------------------------

### Define Sparse Data Structure

Source: https://docs.taichi-lang.org/docs/sparse

Defines a sparse data structure using Taichi's root, pointer, and bitmasked SNodes. This setup is used for subsequent sparsity manipulation examples.

```python
x = ti.field(dtype=ti.i32)  
block1 = ti.root.pointer(ti.ij, (3, 3))  
block2 = block1.pointer(ti.ij, (2, 2))  
pixel = block2.bitmasked(ti.ij, (2, 2))  
pixel.place(x)  
```

--------------------------------

### Initialize Taichi with CPU Backend

Source: https://docs.taichi-lang.org/docs/accelerate_python

Import Taichi and initialize it to use the CPU backend for accelerated computation. This is the first step to leverage Taichi's performance.

```python
import taichi as ti  
ti.init(arch=ti.cpu)  

```

--------------------------------

### CMakeLists.txt for Taichi C-API Project

Source: https://docs.taichi-lang.org/docs/tutorial

Configure CMake to find the Taichi installation and link the Taichi runtime library to the executable.

```cmake
cmake_minimum_required(VERSION 3.17)
 
 set(TAICHI_AOT_APP_NAME TaichiAot)
 project(${TAICHI_AOT_APP_NAME} LANGUAGES C CXX)
 set(CMAKE_CXX_STANDARD 17)
 set(CMAKE_CXX_STANDARD_REQUIRED ON)
 
 # Declare executable target.
 add_executable(${TAICHI_AOT_APP_NAME} app.cpp)
 target_include_directories(${TAICHI_AOT_APP_NAME} PUBLIC ${TAICHI_C_API_INSTALL_DIR}/include)
 
 # Find and link Taichi runtime library.
 set(CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake)
 find_package(Taichi REQUIRED)
 target_link_libraries(${TAICHI_AOT_APP_NAME} Taichi::Runtime)
```

--------------------------------

### Create and Fill Sparse Matrix Builder

Source: https://docs.taichi-lang.org/docs/sparse_matrix

Demonstrates the three steps to use sparse matrices: creating a builder, filling it with data using a kernel, and building the sparse matrix. Supports += and -= operators for filling.

```python
import taichi as ti
arch = ti.cpu # or ti.cuda
ti.init(arch=arch)

n = 4
# step 1: create sparse matrix builder
K = ti.linalg.SparseMatrixBuilder(n, n, max_num_triplets=100)

@ti.kernel
def fill(A: ti.types.sparse_matrix_builder()):
    for i in range(n):
        A[i, i] += 1  # Only += and -= operators are supported for now.

# step 2: fill the builder with data. 
fill(K)

print(">>>> K.print_triplets()")
K.print_triplets()
# outputs:
# >>>> K.print_triplets()
# n=4, m=4, num_triplets=4 (max=100)(0, 0) val=1.0(1, 1) val=1.0(2, 2) val=1.0(3, 3) val=1.0

# step 3: create a sparse matrix from the builder. 
A = K.build()
print(">>>> A = K.build()")
print(A)
# outputs:
# >>>> A = K.build()
# [1, 0, 0, 0]
# [0, 1, 0, 0]
# [0, 0, 1, 0]
# [0, 0, 0, 1]
```

--------------------------------

### Taichi Field Layout Example

Source: https://docs.taichi-lang.org/api/taichi

Demonstrates how to define and place a Taichi field using nested layout functions.

```python
>>> x = ti.field(ti.f32) 
>>> ti.root.pointer(ti.ij, 4).dense(ti.ij, 8).place(x)  
```

--------------------------------

### Gui.begin

Source: https://docs.taichi-lang.org/api/taichi/ui

Creates a subwindow that holds imgui widgets.

```APIDOC
## Gui.begin

### Description
Creates a subwindow that holds imgui widgets. All widget function calls (e.g. text, button) after the begin and before the next end will describe the widgets within this subwindow.

### Parameters
* **name** (str): The name of the subwindow.
* **x** (float): The x-coordinate (between 0 and 1) of the top-left corner of the subwindow, relative to the full window.
* **y** (float): The y-coordinate (between 0 and 1) of the top-left corner of the subwindow, relative to the full window.
* **width** (float): The width of the subwindow relative to the full window.
* **height** (float): The height of the subwindow relative to the full window.
```

--------------------------------

### Taichi Static Compile-Time Loop Unrolling Example

Source: https://docs.taichi-lang.org/api/taichi

Demonstrates using taichi.static with a range to achieve compile-time loop unrolling.

```python
>>> @ti.kernel 
>>> def run(): 
>>>     for i in ti.static(range(3)): 
>>>         print(i) 
>>> 
>>> # The above will be unrolled to: 
>>> @ti.kernel 
>>> def run(): 
>>>     print(0) 
>>>     print(1) 
>>>     print(2) 

```

--------------------------------

### Initialize Structs with Positional and Keyword Arguments

Source: https://docs.taichi-lang.org/docs/type

Demonstrates various ways to initialize struct instances, including positional arguments, keyword arguments, and default zero initialization.

```python
@ti.dataclass  
class Ray:  
    ro: vec3  
    rd: vec3  
    t: float  
  
# The definition above is equivalent to  
#Ray = ti.types.struct(ro=vec3, rd=vec3, t=float)  
# Use positional arguments to set struct members in order  
ray = Ray(vec3(0), vec3(1, 0, 0), 1.0)  
# ro is set to vec3(0) and t will be set to 0  
ray = Ray(vec3(0), rd=vec3(1, 0, 0))  
# both ro and rd are set to vec3(0)  
ray = Ray(t=1.0)  
# ro is set to vec3(1), rd=vec3(0) and t=0.0  
ray = Ray(1)  
# All members are set to 0  
ray = Ray()  
```

--------------------------------

### GGUI GUI Components Example

Source: https://docs.taichi-lang.org/docs/ggui

Demonstrates the usage of GGUI components like text, buttons, sliders, and color edits, following Dear ImGui APIs.

```python
window = ti.ui.Window("Test for GUI", res=(512, 512))
gui = window.get_gui()
value = 0
color = (1.0, 1.0, 1.0)
with gui.sub_window("Sub Window", x=10, y=10, width=300, height=100):
    gui.text("text")
    is_clicked = gui.button("name")
    value = gui.slider_float("name1", value, minimum=0, maximum=100)
    color = gui.color_edit_3("name2", color)
```

--------------------------------

### C++ Logging Examples

Source: https://docs.taichi-lang.org/docs/developer_utilities

Shows how to write logs at different levels in C++ using the TI_* interface. Ensure necessary Taichi headers are included.

```cpp
#include <taichi/platform/logging.h>
TI_TRACE("Hello world!");
TI_DEBUG("Hello world!");
TI_INFO("Hello world!");
TI_WARN("Hello world!");
TI_ERROR("Hello world!");
```

--------------------------------

### Open Taichi Gallery

Source: https://docs.taichi-lang.org/docs/hello_world

Run this command to open the Taichi gallery and view featured demos.

```bash
ti gallery  

```

--------------------------------

### Prepare and Launch Kernel with Positional Arguments

Source: https://docs.taichi-lang.org/docs/taichi_core

Prepares a TiNdArray and several TiArgument objects for launching a kernel. Ensure types, sizes, and order match the source code.

```c++
TiNdArray ndarray{};  
ndarray.memory = get_some_memory();  
ndarray.shape.dim_count = 1;  
ndarray.shape.dims[0] = 16;  
ndarray.elem_shape.dim_count = 2;  
ndarray.elem_shape.dims[0] = 4;  
ndarray.elem_shape.dims[1] = 4;  
ndarray.elem_type = TI_DATA_TYPE_F32;  
  
std::array<TiArgument, 3> args{};  
  
TiArgument& arg0 = args[0];  
arg0.type = TI_ARGUMENT_TYPE_I32;  
arg0.value.i32 = 123;  
  
TiArgument& arg1 = args[1];  
arg1.type = TI_ARGUMENT_TYPE_F32;  
arg1.value.f32 = 123.0f;  
  
TiArgument& arg2 = args[2];  
arg2.type = TI_ARGUMENT_TYPE_NDARRAY;  
arg2.value.ndarray = ndarray;  
  
ti_launch_kernel(runtime, kernel, args.size(), args.data());  
```

--------------------------------

### Create a GGUI Window

Source: https://docs.taichi-lang.org/docs/ggui

Initializes a new GGUI window with a specified title, resolution, FPS limit, and position. The window serves as the base for rendering UI elements.

```python
window = ti.ui.Window(name='Window Title', res = (640, 360), fps_limit=200, pos = (150, 150))
```

--------------------------------

### Show all test options

Source: https://docs.taichi-lang.org/docs/contributor_guide

Display all available command-line options for the test runner script.

```bash
python tests/run_tests.py -h
```

--------------------------------

### Start Recording Taichi Kernel Information

Source: https://docs.taichi-lang.org/api/taichi/aot

Starts recording kernel information to a yml file. This function should be paired with `stop_recording()` and is useful for debugging and analysis.

```python
ti.aot.start_recording('record.yml')
ti.init(arch=ti.cc)
loss = ti.field(float, (), needs_grad=True)
x = ti.field(float, 233, needs_grad=True)

@ti.kernel
def compute_loss():
    for i in x:
        loss[None] += x[i]**2

@ti.kernel
def do_some_works():
    for i in x:
        x[i] -= x.grad[i]

with ti.ad.Tape(loss):
    compute_loss()
do_some_works()
```

--------------------------------

### Instantiate and Build a Taichi Mesh Model

Source: https://docs.taichi-lang.org/api/taichi

Demonstrates how to instantiate a mesh builder, define vertex attributes, and build a Taichi mesh model.

```python
mesh_builder = ti.Mesh.tri()
mesh_builder.verts.place({
    'x' : ti.f32,
    'y' : ti.f32
})
model = mesh_builder.build(meta)
```

--------------------------------

### Taichi IR Output Example

Source: https://docs.taichi-lang.org/docs/internal

This is an example of the Intermediate Representation (IR) generated by Taichi for a simple kernel. It showcases the static-single assignment and hierarchical nature of the IR.

```text
kernel {
  $0 = offloaded range_for(0, 10) grid_dim=0 block_dim=32
  body {
    <i32> $1 = loop $0 index 0
    <i32> $2 = const [4]
    <i32> $3 = cmp_lt $1 $2
    <i32> $4 = const [1]
    <i32> $5 = bit_and $3 $4
    $6 : if $5 {
      print $1, "\n"
    }
  }
}
```

--------------------------------

### Example of ti.static_assert in a Function

Source: https://docs.taichi-lang.org/docs/debugging

This example demonstrates using `ti.static_assert` within a Taichi function to ensure that the shapes of source and destination fields match before copying elements.

```python
@ti.func
def copy(dst: ti.template(), src: ti.template()):
    ti.static_assert(dst.shape == src.shape, "copy() needs src and dst fields to be same shape")
    for I in ti.grouped(src):
        dst[I] = src[I]
```

--------------------------------

### Launching a Kernel

Source: https://docs.taichi-lang.org/docs/taichi_core

Shows how to launch a Taichi kernel with positional arguments. Ensure argument types, sizes, and order match the Python source.

```APIDOC
## Launching a Kernel

### Description
You can launch a kernel with positional arguments. Please ensure the types, the sizes and the order matches the source code in Python.

### Code Example
```c++
TiNdArray ndarray{};  
ndarray.memory = get_some_memory();  
ndarray.shape.dim_count = 1;  
ndarray.shape.dims[0] = 16;  
ndarray.elem_shape.dim_count = 2;  
ndarray.elem_shape.dims[0] = 4;  
ndarray.elem_shape.dims[1] = 4;  
ndarray.elem_type = TI_DATA_TYPE_F32;  
  
std::array<TiArgument, 3> args{};  

TiArgument& arg0 = args[0];  
arg0.type = TI_ARGUMENT_TYPE_I32;  
arg0.value.i32 = 123;  
  
TiArgument& arg1 = args[1];  
arg1.type = TI_ARGUMENT_TYPE_F32;  
arg1.value.f32 = 123.0f;  
  
TiArgument& arg2 = args[2];  
arg2.type = TI_ARGUMENT_TYPE_NDARRAY;  
arg2.value.ndarray = ndarray;  
  
ti_launch_kernel(runtime, kernel, args.size(), args.data());  
```
```

--------------------------------

### Launching a Compute Graph

Source: https://docs.taichi-lang.org/docs/taichi_core

Explains how to launch a compute graph, emphasizing the need for matching argument names with the Python source.

```APIDOC
## Launching a Compute Graph

### Description
You can launch a compute graph in a similar way. But additionally please ensure the argument names matches those in the Python source.

### Code Example
```c++
std::array<TiNamedArgument, 3> named_args{};  
TiNamedArgument& named_arg0 = named_args[0];  
named_arg0.name = "foo";  
named_arg0.argument = args[0];  
TiNamedArgument& named_arg1 = named_args[1];  
named_arg1.name = "bar";  
named_arg1.argument = args[1];  
TiNamedArgument& named_arg2 = named_args[2];  
named_arg2.name = "baz";  
named_arg2.argument = args[2];  
  
ti_launch_compute_graph(runtime, compute_graph, named_args.size(), named_args.data());  
```
```

--------------------------------

### Taichi OpenGL Stack Trace Example

Source: https://docs.taichi-lang.org/docs/install

Example of a stack trace indicating a segmentation fault related to OpenGL initialization, often due to an old OpenGL API version.

```text
[Taichi] mode=release
[E 05/12/20 18.25:00.129] Received signal 11 (Segmentation Fault)
***********************************
* Taichi Compiler Stack Traceback *
***********************************

... (many lines, omitted)

/lib/python3.8/site-packages/taichi/core/../lib/taichi_python.so: _glfwPlatformCreateWindow
/lib/python3.8/site-packages/taichi/core/../lib/taichi_python.so: glfwCreateWindow
/lib/python3.8/site-packages/taichi/core/../lib/taichi_python.so: taichi::lang::opengl::initialize_opengl(bool)

... (many lines, omitted)

```

--------------------------------

### Example: Fetching Depth Data

Source: https://docs.taichi-lang.org/docs/ggui

An example of fetching depth data into a Taichi ndarray or field. The shape must match the window's shape and the data type must be ti.f32.

```python
window_shape = (720, 1080)
window = ti.ui.Window("Test for copy depth data", window_shape)
canvas = window.get_canvas()
scene = ti.ui.Scene()
camera = ti.ui.Camera()

# Get the shape of the window
w, h = window.get_window_shape()
# The field/ndarray stores the depth information, and must be of the ti.f32 data type and have a 2d shape.
# or, in other words, the shape must equal the window's shape
scene_depth = ti.ndarray(ti.f32, shape = (w, h))
# scene_depth = ti.field(ti.f32, shape = (w, h))

while window.running:
    # render()
    canvas.scene(scene)
    window.get_depth_buffer(scene_depth)
    window.show()
```

--------------------------------

### Create and Use a Sub-window in Taichi UI

Source: https://docs.taichi-lang.org/api/taichi/ui

Demonstrates how to create a sub-window using a context manager and add text within it. Ensure 'gui', 'name', 'x', 'y', 'width', and 'height' are properly defined before use.

```python
with gui.sub_window(name, x, y, width, height) as g:
    g.text("Hello, World!")
```

--------------------------------

### Initialize Taichi and Simulation Parameters

Source: https://docs.taichi-lang.org/docs/cloth_simulation

Initializes Taichi with the Vulkan backend and sets up simulation parameters like grid size, time step, gravity, and spring constants. This code defines the foundational elements for the cloth simulation.

```python
import taichi as ti
tiw.init(arch=ti.vulkan)  # Alternatively, ti.init(arch=ti.cpu)

n = 128
quad_size = 1.0 / n
dt = 4e-2 / n
substeps = int(1 / 60 // dt)

gravity = ti.Vector([0, -9.8, 0])
spring_Y = 3e4
dashpot_damping = 1e4
drag_damping = 1

ball_radius = 0.3
ball_center = ti.Vector.field(3, dtype=float, shape=(1, ))
ball_center[0] = [0, 0, 0]

x = ti.Vector.field(3, dtype=float, shape=(n, n))
v = ti.Vector.field(3, dtype=float, shape=(n, n))

num_triangles = (n - 1) * (n - 1) * 2
indices = ti.field(int, shape=num_triangles * 3)
vertices = ti.Vector.field(3, dtype=float, shape=n * n)
colors = ti.Vector.field(3, dtype=float, shape=n * n)

bending_springs = False
```

--------------------------------

### ScalarNdarray.get_type

Source: https://docs.taichi-lang.org/api/taichi

Gets the data type of the ScalarNdarray.

```APIDOC
## get_type(_self_)

### Description
Gets the data type of the ScalarNdarray.

### Returns
The data type of the ScalarNdarray.
```

--------------------------------

### Get Matrix Shape

Source: https://docs.taichi-lang.org/api/taichi

Retrieves the shape of the matrix.

```python
get_shape(_self_)
```

--------------------------------

### Create a GUI Window

Source: https://docs.taichi-lang.org/docs/gui_system

Creates a GUI window with a specified title and resolution. This is the first step to using the GUI system.

```python
gui = ti.GUI('Hello World!', (640, 360))
```

--------------------------------

### ScalarField.parent

Source: https://docs.taichi-lang.org/api/taichi

Gets an ancestor of the representative SNode in the SNode tree.

```APIDOC
## parent(_self_ , _n =1_)

### Description
Gets an ancestor of the representative SNode in the SNode tree.

### Parameters
* **n** (_int_) – the number of levels going up from the representative SNode.

### Returns
The n-th parent of the representative SNode.

### Return type
SNode
```

--------------------------------

### Build LLVM from Source on Linux/macOS

Source: https://docs.taichi-lang.org/docs/dev_install

Steps to download, configure, and build LLVM 15.0.0 from source. This is an alternative to using pre-built binaries. Ensure you have the necessary build tools installed.

```bash
wget https://github.com/llvm/llvm-project/archive/refs/tags/llvmorg-15.0.5.tar.gz

tar zxvf llvmorg-15.0.5.tar.gz

cd llvm-project-llvmorg-15.0.5/llvm

mkdir build

cd build

cmake .. -DLLVM_ENABLE_RTTI:BOOL=ON -DBUILD_SHARED_LIBS:BOOL=OFF -DCMAKE_BUILD_TYPE=Release -DLLVM_TARGETS_TO_BUILD="X86;NVPTX" -DLLVM_ENABLE_ASSERTIONS=ON -DLLVM_ENABLE_TERMINFO=OFF

# If you are building on Apple M1, use -DLLVM_TARGETS_TO_BUILD="AArch64".

# If you are building on NVIDIA Jetson TX2, use -DLLVM_TARGETS_TO_BUILD="ARM;NVPTX"

# If you are building for a PyPI release, add -DLLVM_ENABLE_Z3_SOLVER=OFF to reduce the library dependency.

make -j 8

sudo make install

# Check your LLVM installation

llvm-config --version  # You should get 15.0.5
```

--------------------------------

### parent

Source: https://docs.taichi-lang.org/api/taichi

Gets an ancestor of the current SNode in the SNode tree.

```APIDOC
## parent(_self_ , _n =1_)

### Description
Gets an ancestor of self in the SNode tree.

### Parameters
* **n** (_int_) – the number of levels going up from self.

### Returns
The n-th parent of self.

### Return type
Union[None, _Root, SNode]
```

--------------------------------

### Off-screen Rendering Setup

Source: https://docs.taichi-lang.org/docs/ggui

Enable off-screen rendering by setting `show_window=False` during window initialization. This allows saving frames without displaying the window.

```python
window = ti.ui.Window('Window Title', (640, 360), show_window = False)
```

--------------------------------

### MeshInstance.get_relation_size

Source: https://docs.taichi-lang.org/api/taichi

Gets the size of the relation for a given mesh element.

```APIDOC
## Method: MeshInstance.get_relation_size

### Parameters
* **from_index** - The index of the starting element.
* **to_element_type** - The type of the target element.
```

--------------------------------

### MeshInstance.get_relation_access

Source: https://docs.taichi-lang.org/api/taichi

Gets the relation access for a given mesh element.

```APIDOC
## Method: MeshInstance.get_relation_access

### Parameters
* **from_index** - The index of the starting element.
* **to_element_type** - The type of the target element.
* **neighbor_idx_ptr** - Pointer to the neighbor index.
```

--------------------------------

### List Built Wheel Files

Source: https://docs.taichi-lang.org/docs/dev_install

Lists the generated wheel files in the dist directory after building.

```bash
ls dist/*.whl
```

--------------------------------

### Get Data Type

Source: https://docs.taichi-lang.org/api/taichi

Retrieves the data type of the elements in the ndarray.

```python
get_type()
```

--------------------------------

### taichi.init()

Source: https://docs.taichi-lang.org/api/taichi

Initializes the Taichi runtime and sets the backend for the program. It accepts various parameters to configure the runtime, including the architecture, default floating-point and integral types, and other compilation-related keyword arguments.

```APIDOC
## taichi.init(_arch =None_, _default_fp =None_, _default_ip =None_, __test_mode =False_, _enable_fallback =True_, _require_version =None_, _** kwargs_)

### Description
Initializes the Taichi runtime.
This should always be the entry point of your Taichi program. Most importantly, it sets the backend used throughout the program.

### Parameters:
* **arch** – Backend to use. This is usually `cpu` or `gpu`.
* **default_fp** (_Optional_ _[__type_ _]_) – Default floating-point type.
* **default_ip** (_Optional_ _[__type_ _]_) – Default integral type.
* **require_version** (_Optional_ _[__string_ _]_) – A version string.
* ****kwargs** – 
Taichi provides highly customizable compilation through `kwargs`, which allows for fine grained control of Taichi compiler behavior. Below we list some of the most frequently used ones. For a complete list, please check out https://github.com/taichi-dev/taichi/blob/master/taichi/program/compile_config.h.
    * `cpu_max_num_threads` (int): Sets the number of threads used by the CPU thread pool.
    * `debug` (bool): Enables the debug mode, under which Taichi does a few more things like boundary checks.
    * `print_ir` (bool): Prints the CHI IR of the Taichi kernels.
*`offline_cache` (bool): Enables offline cache of the compiled kernels. Default to True. When this is enabled Taichi will cache compiled kernel on your local disk to accelerate future calls. *`random_seed` (int): Sets the seed of the random generator. The default is 0.
```

--------------------------------

### MeshInstance.get_position_as_numpy

Source: https://docs.taichi-lang.org/api/taichi

Gets the vertex position of the current mesh as a numpy array.

```APIDOC
## Method: MeshInstance.get_position_as_numpy

### Description
Get the vertex position of current mesh to numpy array.

### Returns
* **3d numpy array** - [x, y, z] with float-format.
```

--------------------------------

### Example Output and Performance

Source: https://docs.taichi-lang.org/docs/accelerate_python

Shows a sample output of the LCS length calculation and its execution time. Highlights the significant performance improvement achieved with Taichi (around 0.9s) compared to a pure Python/NumPy approach (476s).

```text
2721

real        0m1.409s
user        0m1.112s
sys        0m0.549s

```

--------------------------------

### Taichi Field Index Mapping Example

Source: https://docs.taichi-lang.org/docs/internal

Demonstrates the virtual-to-physical index mapping for dense and custom-laid-out fields in Taichi. Use this to verify memory layout assumptions.

```python
a = ti.field(ti.f32, shape=(128, 32, 8))
  
b = ti.field(ti.f32)
 ti.root.dense(ti.j, 32).dense(ti.i, 16).place(b)
  
ti.lang.impl.get_runtime().materialize() # This is an internal api for dev, we don't make sure it is stable for user.  
  
mapping_a = a.snode().physical_index_position()
  
assert mapping_a == {0: 0, 1: 1, 2: 2}
  
mapping_b = b.snode().physical_index_position()
  
assert mapping_b == {0: 1, 1: 0}
# Note that b is column-major:  
# the virtual first index exposed to the user comes second in memory layout.
```

--------------------------------

### Set Taichi Logging Level

Source: https://docs.taichi-lang.org/api/taichi

Example of setting the Taichi logging level to 'debug'.

```python
>>> set_logging_level('debug')  
```

--------------------------------

### Drawing 3D Lines and Particles

Source: https://docs.taichi-lang.org/docs/ggui

This snippet demonstrates initializing Taichi, setting up a window, scene, and camera, and then drawing 3D particles and lines. It includes camera controls and lighting setup.

```python
import taichi as ti

ti.init(arch=ti.cuda)

N = 10

particles_pos = ti.Vector.field(3, dtype=ti.f32, shape = N)
points_pos = ti.Vector.field(3, dtype=ti.f32, shape = N)

@ti.kernel
def init_points_pos(points : ti.template()):
    for i in range(points.shape[0]):
        points[i] = [i for j in ti.static(range(3))]

init_points_pos(particles_pos)
init_points_pos(points_pos)

window = ti.ui.Window("Test for Drawing 3d-lines", (768, 768))
cavas = window.get_canvas()
scene = ti.ui.Scene()
camera = ti.ui.Camera()
camera.position(5, 2, 2)

while window.running:
    camera.track_user_inputs(window, movement_speed=0.03, hold_key=ti.ui.RMB)
    scene.set_camera(camera)
    scene.ambient_light((0.8, 0.8, 0.8))
    scene.point_light(pos=(0.5, 1.5, 1.5), color=(1, 1, 1))

    scene.particles(particles_pos, color = (0.68, 0.26, 0.19), radius = 0.1)
    # Draw 3d-lines in the scene
    scene.lines(points_pos, color = (0.28, 0.68, 0.99), width = 5.0)
    canvas.scene(scene)
    window.show()
```

--------------------------------

### Vector Absolute Value Example

Source: https://docs.taichi-lang.org/api/taichi

Calculates the element-wise absolute value of a Taichi vector.

```python
x = ti.Vector([-1.0, 0.0, 1.0])
y = ti.abs(x)
print(y)
```

--------------------------------

### Taichi Runtime Error Example

Source: https://docs.taichi-lang.org/api/taichi

Demonstrates TaichiRuntimeError, thrown when the compiled program cannot be executed.

```python
raise ti.TaichiRuntimeError('Runtime error occurred!')
```

--------------------------------

### Initialize Taichi Backend

Source: https://docs.taichi-lang.org/docs/hello_world

Initialize the Taichi environment, specifying the compute backend (e.g., GPU or CPU).

```python
ti.init(arch=ti.gpu)
```

--------------------------------

### Taichi Compilation Error Example

Source: https://docs.taichi-lang.org/api/taichi

Illustrates TaichiCompilationError, the base class for all compilation exceptions.

```python
raise ti.TaichiCompilationError('Compilation failed!')
```

--------------------------------

### Create a 3D Scene

Source: https://docs.taichi-lang.org/docs/ggui

Initializes an empty 3D scene object. This scene will be populated with geometries, lights, and a camera.

```python
scene = ti.ui.Scene()
```

--------------------------------

### Elif Clause Example

Source: https://docs.taichi-lang.org/docs/language_reference

Illustrates the use of elif clauses for multiple conditional branches.

```taichi
if cond_a:
    body_a
elif cond_b:
    body_b
elif cond_c:
    body_c
else:
    body_d

```

--------------------------------

### Get Matrix Dimensions

Source: https://docs.taichi-lang.org/api/taichi

Retrieves the number of rows (n) and columns (m) of a Taichi Matrix.

```python
M = ti.Matrix([[0, 1], [2, 3], [4, 5]], ti.i32)
M.n  # number of rows
M.m  # number of cols
```

--------------------------------

### Example: Filling VectorNdarray from NumPy

Source: https://docs.taichi-lang.org/api/taichi

Demonstrates copying data from a NumPy array into a Taichi VectorNdarray.

```python
>>> import numpy as np
>>> a = ti.VectorNdarray(3, ti.f32, (2, 2), 0)
>>> b = np.ones((2, 2, 3), dtype=np.float32)
>>> a.from_numpy(b)
```

--------------------------------

### Initialize Mass Points for Cloth

Source: https://docs.taichi-lang.org/docs/cloth_simulation

Sets up the initial positions and velocities for the mass points of a cloth simulation. Includes random offsets for variation.

```python
import taichi as ti

@ti.kernel
def initialize_mass_points():
    # A random offset to apply to each mass point
    random_offset = ti.Vector([ti.random() - 0.5, ti.random() - 0.5]) * 0.1

    # Field x stores the mass points' positions
    for i, j in x:
        # The piece of cloth is 0.6 (y-axis) above the original point
        #
        # By taking away 0.5 from each mass point's [x,z] coordinate value
        # you move the cloth right above the original point
        x[i, j] = [
            i * quad_size - 0.5 + random_offset[0], 0.6,
            j * quad_size - 0.5 + random_offset[1]
        ]
        # The initial velocity of each mass point is set to 0
        v[i, j] = [0, 0, 0]
```

--------------------------------

### Using KernelProfiler for Device Kernel Analysis

Source: https://docs.taichi-lang.org/docs/profiler

This example shows how to use KernelProfiler to analyze Taichi kernels. Enable it with kernel_profiler=True in ti.init(). Use print_kernel_profiler_info('trace') for detailed kernel launches or print_kernel_profiler_info() for default 'count' mode. Remember to call ti.sync() before profiling on GPU. Use clear_kernel_profiler_info() to reset records.

```python
import taichi as ti

ti.init(ti.cpu, kernel_profiler=True)
x = ti.field(ti.f32, shape=1024*1024)

@ti.kernel
def fill():
    for i in x:
        x[i] = i

for i in range(8):
    fill()
ti.profiler.print_kernel_profiler_info('trace')
ti.profiler.clear_kernel_profiler_info()  # Clears all records

for i in range(100):
    fill()
ti.profiler.print_kernel_profiler_info()  # The default mode: 'count'
```

--------------------------------

### Taichi Type Error Example

Source: https://docs.taichi-lang.org/api/taichi

Demonstrates TaichiTypeError, thrown when a type mismatch is found during compilation.

```python
raise ti.TaichiTypeError('Type mismatch!')
```

--------------------------------

### Download Taichi Wheel Package

Source: https://docs.taichi-lang.org/docs/faq

Use this command to download the Taichi wheel package and its dependencies for offline installation. Ensure the operating system matches the target server.

```bash
pip download taichi
```

--------------------------------

### Initialize Taichi with Default CPU Backend

Source: https://docs.taichi-lang.org/docs/global_settings

If no `arch` argument or `TI_ARCH` environment variable is set, Taichi defaults to the CPU backend.

```python
ti.init()
```

--------------------------------

### Taichi Syntax Error Example

Source: https://docs.taichi-lang.org/api/taichi

Shows TaichiSyntaxError, thrown when a syntax error is found during compilation.

```python
raise ti.TaichiSyntaxError('Syntax error!')
```

--------------------------------

### Taichi Name Error Example

Source: https://docs.taichi-lang.org/api/taichi

Shows TaichiNameError, which is thrown when an undefined name is found during compilation.

```python
raise ti.TaichiNameError('Name not found!')
```

--------------------------------

### Initialize Taichi with GPU Backend

Source: https://docs.taichi-lang.org/docs/accelerate_python

Initialize Taichi to use the GPU backend. This allows Taichi to offload computations to the GPU for potentially greater acceleration.

```python
ti.init(arch=ti.gpu)  

```

--------------------------------

### Taichi Assertion Error Example

Source: https://docs.taichi-lang.org/api/taichi

Demonstrates the usage of TaichiAssertionError, which is thrown when an assertion fails at runtime.

```python
raise ti.TaichiAssertionError('Assertion failed!')
```

--------------------------------

### ndrange for loop example

Source: https://docs.taichi-lang.org/docs/language_reference

Iterates over multidimensional ranges. The loop variables are assigned integers for each dimension.

```python
for i in ti.ndrange(10):
    # i is a scalar
    for j in ti.ndrange(10):
        # j is a scalar
        for k in ti.ndrange(10, 20):
            # k is a scalar
            for l, m in ti.ndrange(10, (10, 20)):
                # l is a scalar, m is a scalar
                pass

```

--------------------------------

### Initialize Taichi Runtime and Load Module

Source: https://docs.taichi-lang.org/docs/tutorial

Create a Taichi runtime with a specified target architecture and load a compiled AOT module.

```cpp
ti::Runtime runtime(TI_ARCH_VULKAN);
 ti::AotModule aot_module = runtime.load_aot_module("module.tcm");
 ti::Kernel kernel_paint = aot_module.get_kernel("paint");
```