# ========================== # # Let's start to use Lightmetrica by rendering a blank image. # We first import the ``lightmetrica`` module, where we use ``lm`` as an alias of ``lightmetrica`` for simplicity. # # .. note:: # Although we recommend to use Python API to organize the experiments, similar APIs can be accessible from C++. See `example directory`_ for the detail. # # .. _example directory: https://github.com/hi2p-perim/lightmetrica-v3/tree/master/example # # .. note:: # ``lmenv`` is a simple module to configure Lightmetrica envrionment from a specified file. Here we load ``.lmenv``. You want to create your own ``.lmenv`` file if you want to execute examples or tests by yourself. For detail, please refer to :ref:`executing_functional_tests`. # - import lmenv lmenv.load('.lmenv') import lightmetrica as lm # + {"nbsphinx": "hidden"} if not lm.Release: lm.debug.attach_to_debugger() # + {"raw_mimetype": "text/restructuredtext", "active": ""} # Lightmetrica offers an extension for the Jupyter notebook to support logging or interactive progress reporting inside the notebook. The extension can be loaded by a line magic command as below. # - # %load_ext lightmetrica_jupyter # + {"raw_mimetype": "text/restructuredtext", "active": ""} # After importing the module, you can initialize the framwork by calling :cpp:func:`lm::init` function. You can pass various arguments to configure the framework to the function, but here we keep it empty so that everything is configured to be default.
# display_name: Python 3 # language: python # name: python3 # --- # + {"raw_mimetype": "text/restructuredtext", "active": ""} # .. _example_raycast: # # Raycasting a scene with OBJ models # ======================================= # # This example demonstrates how to render a scene with OBJ models using raycasting. # - import lmenv env = lmenv.load('.lmenv') import os import numpy as np import imageio # %matplotlib inline import matplotlib.pyplot as plt import lightmetrica as lm # %load_ext lightmetrica_jupyter # + {"nbsphinx": "hidden"} if not lm.Release: lm.debug.attach_to_debugger() # - lm.init()