# Path: pyfor/rasterizer.py
# class Grid:
# class ImportedGrid(Grid):
# class Raster:
#     def __init__(self, cloud, cell_size):
#     def _update(self):
#     def raster(self, func, dim, **kwargs):
#     def empty_cells(self):
#     def interpolate(self, func, dim, interp_method="nearest"):
#     def metrics(self, func_dict, as_raster=False):
#     def standard_metrics(self, heightbreak=0):
#     def __init__(self, path, cloud):
#     def _update(self):
#     def __init__(self, array, grid):
#     def from_rasterio(cls):
#     def force_extent(self, bbox):
#     def plot(self, cmap="viridis", block=False, return_plot=False):
#     def pit_filter(self, kernel_size):
#     def write(self, path):
#         X, Y = np.mgrid[1 : self.n + 1, 1 : self.m + 1]
# 
# Path: pyfor/clip.py
# def square_clip(points, bounds):
# def ray_trace(x, y, poly):
#     def ray(x, y):
# def poly_clip(points, poly):


import laspy
import plyfile
import os
import numpy as np
import pandas as pd
import matplotlib.cm as cm
import pathlib
import warnings
        import pyqtgraph as pg
        import pyqtgraph.opengl as gl
from pyfor import rasterizer
from pyfor import clip
        from os.path import getsize
        from pyqtgraph.Qt import QtCore, QtGui
        from pyfor.ground_filter import Zhang2003
        from pyfor.metrics import standard_metrics_cloud
        from scipy.spatial import ConvexHull
        from shapely.geometry import Polygon

            if self.extension.lower() == ".las" or self.extension.lower() == ".laz":
                summary["LAS Specification"] = self.data.header.version

        if self.crs is not None:
            summary["CRS"] = self.crs

        string_list = [key + ": " + str(val) + "\n" for key, val in summary.items()]
        return "".join(str(x) for x in string_list)

    def grid(self, cell_size):
        """
        Generates a :class:`.Grid` object for the parent object given a cell size. \
        See the documentation for :class:`.Grid` for more information.

        :param cell_size: The resolution of the plot in the same units as the input file.
        :return: A :class:`.Grid` object.
        """
        return rasterizer.Grid(self, cell_size)

    def plot(self, cell_size=1, cmap="viridis", return_plot=False, block=False):
        """
        Plots a basic canopy height model of the Cloud object. This is mainly a convenience function for \
        :class:`.Raster.plot`. More robust methods exist for dealing with canopy height models. Please see the \
        `user manual <https://github.com/brycefrank/pyfor_manual/blob/master/notebooks/3-CanopyHeightModel.ipynb>`_.

        :param clip_size: The resolution of the plot in the same units as the input file.
        :param return_plot: If true, returns a matplotlib plt object.
        :return: If return_plot == True, returns matplotlib plt object. Not yet implemented.
        """

# Path: pyfor/rasterizer.py
# class Grid:
# class ImportedGrid(Grid):
# class Raster:
#     def __init__(self, cloud, cell_size):
#     def _update(self):
#     def raster(self, func, dim, **kwargs):
#     def empty_cells(self):
#     def interpolate(self, func, dim, interp_method="nearest"):
#     def metrics(self, func_dict, as_raster=False):
#     def standard_metrics(self, heightbreak=0):
#     def __init__(self, path, cloud):
#     def _update(self):
#     def __init__(self, array, grid):
#     def from_rasterio(cls):
#     def force_extent(self, bbox):
#     def plot(self, cmap="viridis", block=False, return_plot=False):
#     def pit_filter(self, kernel_size):
#     def write(self, path):
#         X, Y = np.mgrid[1 : self.n + 1, 1 : self.m + 1]
# 
# Path: pyfor/clip.py
# def square_clip(points, bounds):
# def ray_trace(x, y, poly):
#     def ray(x, y):
# def poly_clip(points, poly):


# Path: pyfor/cloud.py
import laspy
import plyfile
import os
import numpy as np
import pandas as pd
import matplotlib.cm as cm
import pathlib
import warnings
        import pyqtgraph as pg
        import pyqtgraph.opengl as gl
from pyfor import rasterizer
from pyfor import clip
        from os.path import getsize
        from pyqtgraph.Qt import QtCore, QtGui
        from pyfor.ground_filter import Zhang2003
        from pyfor.metrics import standard_metrics_cloud
        from scipy.spatial import ConvexHull
        from shapely.geometry import Polygon


            if self.extension.lower() == ".las" or self.extension.lower() == ".laz":
                summary["LAS Specification"] = self.data.header.version

        if self.crs is not None:
            summary["CRS"] = self.crs

        string_list = [key + ": " + str(val) + "\n" for key, val in summary.items()]
        return "".join(str(x) for x in string_list)

    def grid(self, cell_size):
        """
        Generates a :class:`.Grid` object for the parent object given a cell size. \
        See the documentation for :class:`.Grid` for more information.

        :param cell_size: The resolution of the plot in the same units as the input file.
        :return: A :class:`.Grid` object.
        """
        return rasterizer.Grid(self, cell_size)

    def plot(self, cell_size=1, cmap="viridis", return_plot=False, block=False):
        """
        Plots a basic canopy height model of the Cloud object. This is mainly a convenience function for \
        :class:`.Raster.plot`. More robust methods exist for dealing with canopy height models. Please see the \
        `user manual <https://github.com/brycefrank/pyfor_manual/blob/master/notebooks/3-CanopyHeightModel.ipynb>`_.

        :param clip_size: The resolution of the plot in the same units as the input file.
        :param return_plot: If true, returns a matplotlib plt object.
        :return: If return_plot == True, returns matplotlib plt object. Not yet implemented.
        """

        rasterizer.Grid(self, cell_size).raster("max", "z").plot(