

import colorsys
import io

import cva
import matplotlib as mpl
import matplotlib.colors as mplc
import matplotlib.figure as mplfigure
import numpy as np
import torch
from matplotlib.backends.backend_agg import FigureCanvasAgg

from utils import img_tensorize


lowerCAmelCase__							=			1000






class     __magic_name__     :


 def __init__(    self		:			Optional[Any]      ,    lowerCAmelCase__		:			int      ,    lowerCAmelCase__		:			str=1.2      ,    lowerCAmelCase__		:			int="g"      ,    lowerCAmelCase__		:			Optional[int]=0.5      ,    lowerCAmelCase__		:			str="-"      ,    lowerCAmelCase__		:			List[str]="test_out.jpg"      ,    lowerCAmelCase__		:			str=True      ,    lowerCAmelCase__		:			Union[str, Any]=False      ,    lowerCAmelCase__		:			Dict=None      ,    lowerCAmelCase__		:			int=None      ,    lowerCAmelCase__		:			str=0.7      ,    )     ->   List[str]:
   if isinstance(lowerCAmelCase__      ,    torch.Tensor     ):
     UpperCAmelCase          =	img.numpy().astype("np.uint8"     )
   if isinstance(lowerCAmelCase__      ,    lowerCAmelCase__     ):
     UpperCAmelCase          =	img_tensorize(lowerCAmelCase__     )
   assert isinstance(lowerCAmelCase__      ,    np.ndarray     )

   UpperCAmelCase   ,						UpperCAmelCase          =	img.shape[1], img.shape[0]
   UpperCAmelCase          =	mplfigure.Figure(frameon=lowerCAmelCase__     )
   UpperCAmelCase          =	fig.get_dpi()
   UpperCAmelCase          =	(width * scale + 1e-2) / dpi
   UpperCAmelCase          =	(height * scale + 1e-2) / dpi
   fig.set_size_inches(lowerCAmelCase__      ,    lowerCAmelCase__     )
   UpperCAmelCase          =	fig.add_axes([0.0, 0.0, 1.0, 1.0]     )
   ax.axis("off"     )
   ax.set_xlim(0.0      ,    lowerCAmelCase__     )
   ax.set_ylim(lowerCAmelCase__     )

   UpperCAmelCase          =	saveas
   UpperCAmelCase          =	rgb
   UpperCAmelCase          =	pynb
   UpperCAmelCase          =	img
   UpperCAmelCase          =	edgecolor
   UpperCAmelCase          =	0.5
   UpperCAmelCase          =	linestyle
   UpperCAmelCase          =	int(np.sqrt(min(lowerCAmelCase__      ,    lowerCAmelCase__     )     ) * scale // 3     )
   UpperCAmelCase          =	width
   UpperCAmelCase          =	height
   UpperCAmelCase          =	scale
   UpperCAmelCase          =	fig
   UpperCAmelCase          =	ax
   UpperCAmelCase          =	pad
   UpperCAmelCase          =	idaobj
   UpperCAmelCase          =	idaattr
   UpperCAmelCase          =	FigureCanvasAgg(lowerCAmelCase__     )


 def _UpperCamelCase						(    self		:			List[Any]      ,    lowerCAmelCase__		:			Tuple      ,    lowerCAmelCase__		:			List[Any]=None     )     ->   Tuple:
   if color is None:
     UpperCAmelCase          =	self.edgecolor
   ((UpperCAmelCase)   ,						(UpperCAmelCase)   ,						(UpperCAmelCase)   ,						(UpperCAmelCase))          =	box
   UpperCAmelCase          =	xa - xa
   UpperCAmelCase          =	ya - ya
   self.ax.add_patch(
       mpl.patches.Rectangle(
           (xa, ya)      ,    lowerCAmelCase__      ,    lowerCAmelCase__      ,    fill=lowerCAmelCase__      ,    edgecolor=lowerCAmelCase__      ,    linewidth=self.font_size // 3      ,    alpha=self.alpha      ,    linestyle=self.linestyle      ,    )     )


 def _UpperCamelCase						(    self		:			int      ,    lowerCAmelCase__		:			Optional[Any]      ,    lowerCAmelCase__		:			str=None      ,    lowerCAmelCase__		:			Any=None      ,    lowerCAmelCase__		:			Union[str, Any]=None      ,    lowerCAmelCase__		:			Dict=None     )     ->   Optional[Any]:
   if len(boxes.shape     ) > 2:
     UpperCAmelCase          =	boxes[0]
   if len(obj_ids.shape     ) > 1:
     UpperCAmelCase          =	obj_ids[0]
   if len(obj_scores.shape     ) > 1:
     UpperCAmelCase          =	obj_scores[0]
   if len(attr_ids.shape     ) > 1:
     UpperCAmelCase          =	attr_ids[0]
   if len(attr_scores.shape     ) > 1:
     UpperCAmelCase          =	attr_scores[0]
   if isinstance(lowerCAmelCase__      ,    torch.Tensor     ):
     UpperCAmelCase          =	boxes.numpy()
   if isinstance(lowerCAmelCase__      ,    lowerCAmelCase__     ):
     UpperCAmelCase          =	np.array(lowerCAmelCase__     )
   assert isinstance(lowerCAmelCase__      ,    np.ndarray     )
   UpperCAmelCase          =	np.prod(boxes[:, 2:] - boxes[:, :2]      ,    axis=1     )
   UpperCAmelCase          =	np.argsort(-areas     ).tolist()
   UpperCAmelCase          =	boxes[sorted_idxs] if boxes is not None else None
   UpperCAmelCase          =	obj_ids[sorted_idxs] if obj_ids is not None else None
   UpperCAmelCase          =	obj_scores[sorted_idxs] if obj_scores is not None else None
   UpperCAmelCase          =	attr_ids[sorted_idxs] if attr_ids is not None else None
   UpperCAmelCase          =	attr_scores[sorted_idxs] if attr_scores is not None else None

   UpperCAmelCase          =	[self._random_color(maximum=1     ) for _ in range(len(lowerCAmelCase__     )     )]
   UpperCAmelCase          =	[assigned_colors[idx] for idx in sorted_idxs]
   if obj_ids is not None:
     UpperCAmelCase          =	self._create_text_labels_attr(lowerCAmelCase__      ,    lowerCAmelCase__      ,    lowerCAmelCase__      ,    lowerCAmelCase__     )
     for i in range(len(lowerCAmelCase__     )     ):
       UpperCAmelCase          =	assigned_colors[i]
       self.add_box(boxes[i]      ,    lowerCAmelCase__     )
       self.draw_labels(labels[i]      ,    boxes[i]      ,    lowerCAmelCase__     )


 def _UpperCamelCase						(    self		:			List[str]      ,    lowerCAmelCase__		:			Optional[Any]      ,    lowerCAmelCase__		:			str      ,    lowerCAmelCase__		:			Any     )     ->   int:
   UpperCAmelCase   ,						UpperCAmelCase   ,						UpperCAmelCase   ,						UpperCAmelCase          =	box
   UpperCAmelCase          =	(xa, ya)
   UpperCAmelCase          =	(ya - ya) * (xa - xa)
   UpperCAmelCase          =	_SMALL_OBJ * self.scale
   if instance_area < small or ya - ya < 4_0 * self.scale:
     if ya >= self.height - 5:
       UpperCAmelCase          =	(xa, ya)
     else:
       UpperCAmelCase          =	(xa, ya)

   UpperCAmelCase          =	(ya - ya) / np.sqrt(self.height * self.width     )
   UpperCAmelCase          =	self._change_color_brightness(lowerCAmelCase__      ,    brightness_factor=0.7     )
   UpperCAmelCase          =	np.clip((height_ratio - 0.02) / 0.08 + 1      ,    1.2      ,    2     )
   font_size *= 0.75 * self.font_size

   self.draw_text(
       text=lowerCAmelCase__      ,    position=lowerCAmelCase__      ,    color=lowerCAmelCase__      ,    )


 def _UpperCamelCase						(    self		:			List[Any]      ,    lowerCAmelCase__		:			int      ,    lowerCAmelCase__		:			Dict      ,    lowerCAmelCase__		:			Union[str, Any]="g"      ,    lowerCAmelCase__		:			str="left"      ,    )     ->   Dict:
   UpperCAmelCase          =	0
   UpperCAmelCase          =	self.font_size
   UpperCAmelCase          =	np.maximum(list(mplc.to_rgb(lowerCAmelCase__     )     )      ,    0.2     )
   UpperCAmelCase          =	max(0.8      ,    np.max(lowerCAmelCase__     )     )
   UpperCAmelCase          =	{
       "facecolor": "black",
       "alpha": self.alpha,
       "pad": self.pad,
       "edgecolor": "none",
   }
   UpperCAmelCase   ,						UpperCAmelCase          =	position
   self.ax.text(
       lowerCAmelCase__      ,    lowerCAmelCase__      ,    lowerCAmelCase__      ,    size=font_size * self.scale      ,    family="sans-serif"      ,    bbox=lowerCAmelCase__      ,    verticalalignment="top"      ,    horizontalalignment=lowerCAmelCase__      ,    color=lowerCAmelCase__      ,    zorder=1_0      ,    rotation=lowerCAmelCase__      ,    )


 def _UpperCamelCase						(    self		:			List[Any]      ,    lowerCAmelCase__		:			Dict=None     )     ->   Any:
   if saveas is None:
     UpperCAmelCase          =	self.saveas
   if saveas.lower().endswith(".jpg"     ) or saveas.lower().endswith(".png"     ):
     cva.imwrite(
         lowerCAmelCase__      ,    self._get_buffer()[:, :, ::-1]      ,    )
   else:
     self.fig.savefig(lowerCAmelCase__     )


 def _UpperCamelCase						(    self		:			Tuple      ,    lowerCAmelCase__		:			List[Any]      ,    lowerCAmelCase__		:			Tuple      ,    lowerCAmelCase__		:			int      ,    lowerCAmelCase__		:			Union[str, Any]     )     ->   Tuple:
   UpperCAmelCase          =	[self.idaobj[i] for i in classes]
   UpperCAmelCase          =	[self.idaattr[i] for i in attr_classes]
   UpperCAmelCase          =	[
       f"{label} {score:.2f} {attr} {attr_score:.2f}"
       for label, score, attr, attr_score in zip(lowerCAmelCase__      ,    lowerCAmelCase__      ,    lowerCAmelCase__      ,    lowerCAmelCase__     )
   ]
   return labels


 def _UpperCamelCase						(    self		:			Tuple      ,    lowerCAmelCase__		:			Union[str, Any]      ,    lowerCAmelCase__		:			Optional[int]     )     ->   Optional[Any]:
   UpperCAmelCase          =	[self.idaobj[i] for i in classes]
   if scores is not None:
     if labels is None:
       UpperCAmelCase          =	["{:.0f}%".format(s * 1_0_0     ) for s in scores]
     else:
       UpperCAmelCase          =	["{} {:.0f}%".format(lowerCAmelCase__      ,    s * 1_0_0     ) for li, s in zip(lowerCAmelCase__      ,    lowerCAmelCase__     )]
   return labels


 def _UpperCamelCase						(    self		:			Dict      ,    lowerCAmelCase__		:			Union[str, Any]=2_5_5     )     ->   Optional[Any]:
   UpperCAmelCase          =	np.random.randint(0      ,    len(_COLORS     )     )
   UpperCAmelCase          =	_COLORS[idx] * maximum
   if not self.rgb:
     UpperCAmelCase          =	ret[::-1]
   return ret


 def _UpperCamelCase						(    self		:			Tuple     )     ->   Dict:
   if not self.pynb:
     UpperCAmelCase   ,						UpperCAmelCase          =	self.canvas.print_to_buffer()
     if (width, height) != (self.width, self.height):
       UpperCAmelCase          =	cva.resize(self.img      ,    (width, height)     )
     else:
       UpperCAmelCase          =	self.img
   else:
     UpperCAmelCase          =	io.BytesIO()  # works for cairo backend
     self.canvas.print_rgba(lowerCAmelCase__     )
     UpperCAmelCase   ,						UpperCAmelCase          =	self.width, self.height
     UpperCAmelCase          =	buf.getvalue()
     UpperCAmelCase          =	self.img

   UpperCAmelCase          =	np.frombuffer(lowerCAmelCase__      ,    dtype="uint8"     )
   UpperCAmelCase          =	buffer.reshape(lowerCAmelCase__      ,    lowerCAmelCase__      ,    4     )
   UpperCAmelCase   ,						UpperCAmelCase          =	np.split(lowerCAmelCase__      ,    [3]      ,    axis=2     )

   try:
     import numexpr as ne  # fuse them with numexpr

     UpperCAmelCase          =	ne.evaluate("img * (1 - alpha / 255.0) + rgb * (alpha / 255.0)"     )
   except ImportError:
     UpperCAmelCase          =	alpha.astype("float32"     ) / 255.0
     UpperCAmelCase          =	img * (1 - alpha) + rgb * alpha

   return visualized_image.astype("uint8"     )


 def _UpperCamelCase						(    self		:			List[str]      ,    lowerCAmelCase__		:			Tuple      ,    lowerCAmelCase__		:			Any     )     ->   str:
   assert brightness_factor >= -1.0 and brightness_factor <= 1.0
   UpperCAmelCase          =	mplc.to_rgb(lowerCAmelCase__     )
   UpperCAmelCase          =	colorsys.rgb_to_hls(*mplc.to_rgb(lowerCAmelCase__     )     )
   UpperCAmelCase          =	polygon_color[1] + (brightness_factor * polygon_color[1])
   UpperCAmelCase          =	0.0 if modified_lightness < 0.0 else modified_lightness
   UpperCAmelCase          =	1.0 if modified_lightness > 1.0 else modified_lightness
   UpperCAmelCase          =	colorsys.hls_to_rgb(polygon_color[0]      ,    lowerCAmelCase__      ,    polygon_color[2]     )
   return modified_color

lowerCAmelCase__							=			(
    np.array(
        [
            0.0_0_0,
            0.4_4_7,
            0.7_4_1,
            0.8_5_0,
            0.3_2_5,
            0.0_9_8,
            0.9_2_9,
            0.6_9_4,
            0.1_2_5,
            0.4_9_4,
            0.1_8_4,
            0.5_5_6,
            0.4_6_6,
            0.6_7_4,
            0.1_8_8,
            0.3_0_1,
            0.7_4_5,
            0.9_3_3,
            0.6_3_5,
            0.0_7_8,
            0.1_8_4,
            0.3_0_0,
            0.3_0_0,
            0.3_0_0,
            0.6_0_0,
            0.6_0_0,
            0.6_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.5_0_0,
            0.0_0_0,
            0.7_4_9,
            0.7_4_9,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.6_6_7,
            0.0_0_0,
            1.0_0_0,
            0.3_3_3,
            0.3_3_3,
            0.0_0_0,
            0.3_3_3,
            0.6_6_7,
            0.0_0_0,
            0.3_3_3,
            1.0_0_0,
            0.0_0_0,
            0.6_6_7,
            0.3_3_3,
            0.0_0_0,
            0.6_6_7,
            0.6_6_7,
            0.0_0_0,
            0.6_6_7,
            1.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.3_3_3,
            0.0_0_0,
            1.0_0_0,
            0.6_6_7,
            0.0_0_0,
            1.0_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.3_3_3,
            0.5_0_0,
            0.0_0_0,
            0.6_6_7,
            0.5_0_0,
            0.0_0_0,
            1.0_0_0,
            0.5_0_0,
            0.3_3_3,
            0.0_0_0,
            0.5_0_0,
            0.3_3_3,
            0.3_3_3,
            0.5_0_0,
            0.3_3_3,
            0.6_6_7,
            0.5_0_0,
            0.3_3_3,
            1.0_0_0,
            0.5_0_0,
            0.6_6_7,
            0.0_0_0,
            0.5_0_0,
            0.6_6_7,
            0.3_3_3,
            0.5_0_0,
            0.6_6_7,
            0.6_6_7,
            0.5_0_0,
            0.6_6_7,
            1.0_0_0,
            0.5_0_0,
            1.0_0_0,
            0.0_0_0,
            0.5_0_0,
            1.0_0_0,
            0.3_3_3,
            0.5_0_0,
            1.0_0_0,
            0.6_6_7,
            0.5_0_0,
            1.0_0_0,
            1.0_0_0,
            0.5_0_0,
            0.0_0_0,
            0.3_3_3,
            1.0_0_0,
            0.0_0_0,
            0.6_6_7,
            1.0_0_0,
            0.0_0_0,
            1.0_0_0,
            1.0_0_0,
            0.3_3_3,
            0.0_0_0,
            1.0_0_0,
            0.3_3_3,
            0.3_3_3,
            1.0_0_0,
            0.3_3_3,
            0.6_6_7,
            1.0_0_0,
            0.3_3_3,
            1.0_0_0,
            1.0_0_0,
            0.6_6_7,
            0.0_0_0,
            1.0_0_0,
            0.6_6_7,
            0.3_3_3,
            1.0_0_0,
            0.6_6_7,
            0.6_6_7,
            1.0_0_0,
            0.6_6_7,
            1.0_0_0,
            1.0_0_0,
            1.0_0_0,
            0.0_0_0,
            1.0_0_0,
            1.0_0_0,
            0.3_3_3,
            1.0_0_0,
            1.0_0_0,
            0.6_6_7,
            1.0_0_0,
            0.3_3_3,
            0.0_0_0,
            0.0_0_0,
            0.5_0_0,
            0.0_0_0,
            0.0_0_0,
            0.6_6_7,
            0.0_0_0,
            0.0_0_0,
            0.8_3_3,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.1_6_7,
            0.0_0_0,
            0.0_0_0,
            0.3_3_3,
            0.0_0_0,
            0.0_0_0,
            0.5_0_0,
            0.0_0_0,
            0.0_0_0,
            0.6_6_7,
            0.0_0_0,
            0.0_0_0,
            0.8_3_3,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.1_6_7,
            0.0_0_0,
            0.0_0_0,
            0.3_3_3,
            0.0_0_0,
            0.0_0_0,
            0.5_0_0,
            0.0_0_0,
            0.0_0_0,
            0.6_6_7,
            0.0_0_0,
            0.0_0_0,
            0.8_3_3,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.1_4_3,
            0.1_4_3,
            0.1_4_3,
            0.8_5_7,
            0.8_5_7,
            0.8_5_7,
            1.0_0_0,
            1.0_0_0,
            1.0_0_0,
        ]
    )
    .astype(np.floataa)
    .reshape(-1, 3)
)






import matplotlib.pyplot as plt
import numpy as np
def   _lowerCAmelCase(						__A ,							__A ,							__A      ):
  UpperCAmelCase          =	len(__A      )  # Number of training samples
  UpperCAmelCase          =	np.eye(__A      )  # Initialize weights as identity matrix
  for j in range(__A      ):
    UpperCAmelCase          =	point - x_train[j]
    UpperCAmelCase          =	np.exp(diff @ diff.T / (-2.0 * tau**2)      )

  return weights
def   _lowerCAmelCase(						__A ,							__A ,							__A ,							__A      ):
  UpperCAmelCase          =	weight_matrix(__A ,							__A ,							__A      )
  UpperCAmelCase          =	np.linalg.inv(x_train.T @ weight_mat @ x_train      ) @ (
      x_train.T @ weight_mat @ y_train.T
  )

  return weight
def   _lowerCAmelCase(						__A ,							__A ,							__A      ):
  UpperCAmelCase          =	np.zeros(len(__A      )      )  # Initialize array of predictions
  for i, item in enumerate(__A      ):
    UpperCAmelCase          =	item @ local_weight(__A ,							__A ,							__A ,							__A      )

  return y_pred
def   _lowerCAmelCase(						__A ,							__A ,							__A      ):
  import seaborn as sns

  UpperCAmelCase          =	sns.load_dataset(__A      )
  UpperCAmelCase          =	np.array(data[x_name]      )
  UpperCAmelCase          =	np.array(data[y_name]      )

  UpperCAmelCase          =	np.ones(len(__A      )      )

  # pairing elements of one and x_data
  UpperCAmelCase          =	np.column_stack((one, x_data)      )

  return x_train, x_data, y_data
def   _lowerCAmelCase(						__A ,							__A ,							__A ,							__A ,							__A ,							__A ,							):
  UpperCAmelCase          =	np.sort(__A ,							axis=0      )
  plt.scatter(__A ,							__A ,							color="blue"      )
  plt.plot(
      x_train_sorted[:, 1] ,							preds[x_train[:, 1].argsort(0      )] ,							color="yellow" ,							linewidth=5 ,							)
  plt.title("Local Weighted Regression"      )
  plt.xlabel(__A      )
  plt.ylabel(__A      )
  plt.show()


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      # Demo with a dataset from the seaborn module
      lowerCAmelCase__,			lowerCAmelCase__,			lowerCAmelCase__							=			load_data("tips", "total_bill", "tip")
      lowerCAmelCase__							=			local_weight_regression(training_data_x, tip, 5)
      plot_preds(training_data_x, predictions, total_bill, tip, "total_bill", "tip")



