update

64.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0dab246ac47fdbab7809ae1cdf84f9854f77f7b809ecc249394280bef6f57463
-size 6713611
+oid sha256:d6b832725a9ac119612e7e578c9c32d93c9c90edad65ec1c7a88f0da44f90207
+size 10202443

app.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -27,7 +27,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -139,7 +139,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -209,7 +209,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -220,7 +220,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -304,71 +304,351 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Running on local URL:  http://127.0.0.1:7861\n",
-      "\n",
-      "To create a public link, set `share=True` in `launch()`.\n"
+      "Running on local URL:  http://127.0.0.1:7860\n",
+      "generated images <modelovae.Node object at 0x000001F3A9D89FC0>\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a7c9d42f5242485e92437771b60ab88c",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(-0.003762…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "generated images <modelovae.Node object at 0x000001F3B5E47130>\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0beb7306167340709957143fe3d8412d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(0.4200476…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "generated images <modelovae.Node object at 0x000001F3B5E47820>\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "15699e29642b4c969757709a93569c09",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(-0.002811…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "generated images <modelovae.Node object at 0x000001F3B8AA2F50>\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e8f7321033e74f2cb61d0830f179ce4a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(0.4228083…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "generated images <modelovae.Node object at 0x000001F3B8AF30D0>\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e45f9cfb42a742928111bd96c0bea6c8",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(0.2544228…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "generated images <modelovae.Node object at 0x000001F3B8AA35B0>\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e8b93804c83f437ba86dfb28fc839eda",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(0.2635734…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "generated images <modelovae.Node object at 0x000001F3B8AF09A0>\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7a670daef41b4e1a8aad5cab83ac220c",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(0.5811820…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "generated images <modelovae.Node object at 0x000001F3B8AF07F0>\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "4a0fa599af6846d299e6868130c17a2b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(0.3441835…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "generated images <modelovae.Node object at 0x000001F3B8AA2F50>\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1921954654de45e7835c0ecd7bb0c55a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(0.3771645…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "generated images <modelovae.Node object at 0x000001F3B8A18F10>\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2f112a2375f74531954a5bc3d4de338e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(0.3513652…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "generated images <modelovae.Node object at 0x000001F3B8C315A0>\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "69653cc85476484c9da5003f8dfaf59d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(0.0813838…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "generated images <modelovae.Node object at 0x000001F3B8C566E0>\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a01e1fdbdf824caebcc93977b0c2bb4b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(0.1389834…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "generated images <modelovae.Node object at 0x000001F3B8A70B20>\n"
      ]
     },
     {
      "data": {
-      "text/html": [
-       "<div><iframe src=\"http://127.0.0.1:7861/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
-      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "39ec4db0797340ad8a9ca1e3418a8a68",
+       "version_major": 2,
+       "version_minor": 0
+      },
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(0.0445088…"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "generated images <modelovae.Node object at 0x000001F3B8CE1270>\n"
+     ]
+    },
     {
      "data": {
-      "text/plain": []
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7ace303e1bf347d9be2fb076afdda5eb",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(0.5377806…"
+      ]
      },
-     "execution_count": 12,
      "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "generated images <modelovae.Node object at 0x000001B9ED7F47F0>\n",
-      "//////\n"
+      "generated images <modelovae.Node object at 0x000001F3B8CE1CC0>\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5784de25df5e45cfae4a32ccbcd52ab6",
+       "model_id": "e2719b6258844c46a006bede8f7b79ab",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(0.4668646…"
+       "Renderer(camera=PerspectiveCamera(children=(DirectionalLight(color='white', intensity=0.6, position=(0.4734578…"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "ename": "KeyboardInterrupt",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
+      "Cell \u001b[1;32mIn[17], line 12\u001b[0m\n\u001b[0;32m      9\u001b[0m checkpoint \u001b[39m=\u001b[39m torch\u001b[39m.\u001b[39mload(\u001b[39m\"\u001b[39m\u001b[39m64.pth\u001b[39m\u001b[39m\"\u001b[39m, map_location\u001b[39m=\u001b[39mtorch\u001b[39m.\u001b[39mdevice(\u001b[39m'\u001b[39m\u001b[39mcpu\u001b[39m\u001b[39m'\u001b[39m))\n\u001b[0;32m     10\u001b[0m Grassdecoder\u001b[39m.\u001b[39mload_state_dict(checkpoint[\u001b[39m'\u001b[39m\u001b[39mdecoder_state_dict\u001b[39m\u001b[39m'\u001b[39m])\n\u001b[1;32m---> 12\u001b[0m gr\u001b[39m.\u001b[39;49mInterface( predict, \n\u001b[0;32m     13\u001b[0m     inputs\u001b[39m=\u001b[39;49m\u001b[39mNone\u001b[39;49;00m,\n\u001b[0;32m     14\u001b[0m     outputs\u001b[39m=\u001b[39;49mgr\u001b[39m.\u001b[39;49mPlot()\n\u001b[0;32m     15\u001b[0m )\u001b[39m.\u001b[39;49mlaunch(share \u001b[39m=\u001b[39;49m \u001b[39mTrue\u001b[39;49;00m)\n",
+      "File \u001b[1;32mc:\\Users\\User\\anaconda3\\envs\\py_torch\\lib\\site-packages\\gradio\\blocks.py:2005\u001b[0m, in \u001b[0;36mBlocks.launch\u001b[1;34m(self, inline, inbrowser, share, debug, enable_queue, max_threads, auth, auth_message, prevent_thread_lock, show_error, server_name, server_port, show_tips, height, width, encrypt, favicon_path, ssl_keyfile, ssl_certfile, ssl_keyfile_password, ssl_verify, quiet, show_api, file_directories, allowed_paths, blocked_paths, root_path, _frontend, app_kwargs)\u001b[0m\n\u001b[0;32m   2003\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m   2004\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mshare_url \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m-> 2005\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mshare_url \u001b[39m=\u001b[39m networking\u001b[39m.\u001b[39;49msetup_tunnel(\n\u001b[0;32m   2006\u001b[0m             \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mserver_name, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mserver_port, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mshare_token\n\u001b[0;32m   2007\u001b[0m         )\n\u001b[0;32m   2008\u001b[0m     \u001b[39mprint\u001b[39m(strings\u001b[39m.\u001b[39men[\u001b[39m\"\u001b[39m\u001b[39mSHARE_LINK_DISPLAY\u001b[39m\u001b[39m\"\u001b[39m]\u001b[39m.\u001b[39mformat(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mshare_url))\n\u001b[0;32m   2009\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (quiet):\n",
+      "File \u001b[1;32mc:\\Users\\User\\anaconda3\\envs\\py_torch\\lib\\site-packages\\gradio\\networking.py:228\u001b[0m, in \u001b[0;36msetup_tunnel\u001b[1;34m(local_host, local_port, share_token)\u001b[0m\n\u001b[0;32m    224\u001b[0m     remote_host, remote_port \u001b[39m=\u001b[39m payload[\u001b[39m\"\u001b[39m\u001b[39mhost\u001b[39m\u001b[39m\"\u001b[39m], \u001b[39mint\u001b[39m(payload[\u001b[39m\"\u001b[39m\u001b[39mport\u001b[39m\u001b[39m\"\u001b[39m])\n\u001b[0;32m    225\u001b[0m     tunnel \u001b[39m=\u001b[39m Tunnel(\n\u001b[0;32m    226\u001b[0m         remote_host, remote_port, local_host, local_port, share_token\n\u001b[0;32m    227\u001b[0m     )\n\u001b[1;32m--> 228\u001b[0m     address \u001b[39m=\u001b[39m tunnel\u001b[39m.\u001b[39;49mstart_tunnel()\n\u001b[0;32m    229\u001b[0m     \u001b[39mreturn\u001b[39;00m address\n\u001b[0;32m    230\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mException\u001b[39;00m \u001b[39mas\u001b[39;00m e:\n",
+      "File \u001b[1;32mc:\\Users\\User\\anaconda3\\envs\\py_torch\\lib\\site-packages\\gradio\\tunneling.py:59\u001b[0m, in \u001b[0;36mTunnel.start_tunnel\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m     57\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mstart_tunnel\u001b[39m(\u001b[39mself\u001b[39m) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m \u001b[39mstr\u001b[39m:\n\u001b[0;32m     58\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdownload_binary()\n\u001b[1;32m---> 59\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39murl \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_start_tunnel(BINARY_PATH)\n\u001b[0;32m     60\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39murl\n",
+      "File \u001b[1;32mc:\\Users\\User\\anaconda3\\envs\\py_torch\\lib\\site-packages\\gradio\\tunneling.py:95\u001b[0m, in \u001b[0;36mTunnel._start_tunnel\u001b[1;34m(self, binary)\u001b[0m\n\u001b[0;32m     93\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mproc\u001b[39m.\u001b[39mstdout \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m     94\u001b[0m     \u001b[39mcontinue\u001b[39;00m\n\u001b[1;32m---> 95\u001b[0m line \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mproc\u001b[39m.\u001b[39;49mstdout\u001b[39m.\u001b[39;49mreadline()\n\u001b[0;32m     96\u001b[0m line \u001b[39m=\u001b[39m line\u001b[39m.\u001b[39mdecode(\u001b[39m\"\u001b[39m\u001b[39mutf-8\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m     97\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39m\"\u001b[39m\u001b[39mstart proxy success\u001b[39m\u001b[39m\"\u001b[39m \u001b[39min\u001b[39;00m line:\n",
+      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
+     ]
     }
    ],
    "source": [
     "a = [1.,1.,1.]\n",
     "mult = torch.Tensor(a)\n",
-    "latent_size = 128\n",
+    "latent_size = 32\n",
     "Grassdecoder = GRASSDecoder(latent_size=latent_size, hidden_size=256, mult = mult)\n",
     "Grassdecoder = Grassdecoder\n",
     "\n",
     "Grassdecoder.eval()\n",
     "\n",
-    "checkpoint = torch.load(\"128.pth\", map_location=torch.device('cpu'))\n",
+    "checkpoint = torch.load(\"64.pth\", map_location=torch.device('cpu'))\n",
     "Grassdecoder.load_state_dict(checkpoint['decoder_state_dict'])\n",
     "\n",
     "gr.Interface( predict, \n",

app.py

@@ -12,7 +12,6 @@ from torch.utils.data import Dataset, DataLoader
 import os
 from resamplear import *
 import open3d as o3d
-from meshSubplot import sTree, plotTree
 
 from vedo import *
 def count_fn(f):
@@ -306,7 +305,7 @@ def predict():
 
 a = [1.,1.,1.]
 mult = torch.Tensor(a)
-latent_size = 32
+latent_size = 64
 Grassdecoder = GRASSDecoder(latent_size=latent_size, hidden_size=256, mult = mult)
 Grassdecoder = Grassdecoder
 

meshSubplot.py

@@ -1,111 +0,0 @@
-import uuid
-from ipywidgets import Output, HBox
-import meshplot as mp
-rendertype = 'JUPYTER'
-import numpy as np
-import networkx as nx
-
-class Subplot():
-    def __init__(self, data, view, s):
-        if data == None:
-            self.rows = []
-            self.hboxes = []
-        else:
-            self.rows = data.rows
-        if s[0] != 1 or s[1] != 1:
-            if data == None: # Intialize subplot array
-                cnt = 0
-                for r in range(s[0]):
-                    row = []
-                    for c in range(s[1]):
-                        row.append(Output())
-                        cnt += 1
-                    self.rows.append(row)
-
-                for r in self.rows:
-                    hbox = HBox(r)
-                    if rendertype == "JUPYTER":
-                        display(hbox)
-                    self.hboxes.append(hbox)
-        
-            out = self.rows[int(s[2]/s[1])][s[2]%s[1]]
-            if rendertype == "JUPYTER":
-                with out:
-                    display(view._renderer)
-            self.rows[int(s[2]/s[1])][s[2]%s[1]] = view
-
-    def save(self, filename=""):
-        if filename == "":
-            uid = str(uuid.uuid4()) + ".html"
-        else:
-            filename = filename.replace(".html", "")
-            uid = filename + '.html'
-
-        s = ""
-        imports = True
-        for r in self.rows:
-            for v in r:
-                s1 = v.to_html(imports=imports, html_frame=False)
-                s = s + s1
-                imports = False
-
-        s = "<html>\n<body>\n" + s + "\n</body>\n</html>"
-        with open(uid, "w") as f:
-            f.write(s)
-        print("Plot saved to file %s."%uid)
-
-    def to_html(self, imports=True, html_frame=True):
-        s = ""
-        for r in self.rows:
-            for v in r:
-                s1 = v.to_html(imports=imports, html_frame=html_frame)
-                s = s + s1
-                imports = False
-
-        return s
-
-def subplot(f, c = 'red', uv=None, n=None, shading={}, s=[1, 1, 0], data=None, **kwargs):
-    
-    shading={'point_size':0.05, "point_color": c, "line_color": c, "width":400, "height":400}
-    view = mp.Viewer(settings = {"width": 500, "height": 500, "antialias": True, "scale": 1.5, "background": "#ffffff",
-                "fov": 30})
-
-    #obj = view.add_points(np.array([ f.nodes[v]['posicion'] for v in f.nodes]), shading=shading)
-    obj = view.add_points( np.array([f.nodes[v]['posicion'] for v in f.nodes if f.nodes[v]['root'] == True]), shading={'point_size':.02, 'point_color':'red'})
-    if len(np.array([ f.nodes[v]['posicion'] for v in f.nodes if f.nodes[v]['root'] == False])) != 0:
-        obj = view.add_points( np.array([f.nodes[v]['posicion'] for v in f.nodes if f.nodes[v]['root'] == False]), shading={'point_size':.02, 'point_color':'black'})
-    for arista in f.edges:
-        obj = view.add_lines( f.nodes[arista[0]]['posicion'], f.nodes[arista[1]]['posicion'], shading  = shading)
-   
-    subplot = Subplot(data, view, s)
-    return subplot
-
-def plotTree( root, dec ):
-    graph = nx.Graph()
-    root.toGraph( graph, 0, dec, 0)
-    edges=nx.get_edge_attributes(graph,'procesada')
-
-    p = mp.plot( np.array([ graph.nodes[v]['posicion'] for v in graph.nodes if graph.nodes[v]['root'] == True]), shading={'point_size':0.05, 'point_color':'red'}, return_plot=True)
-    if len(np.array([ graph.nodes[v]['posicion'] for v in graph.nodes if graph.nodes[v]['root'] == False])) != 0:
-        p.add_points( np.array([graph.nodes[v]['posicion'] for v in graph.nodes if graph.nodes[v]['root'] == False]), shading={'point_size':.05, 'point_color':'black'})
-    for arista in graph.edges:
-        p.add_lines( graph.nodes[arista[0]]['posicion'], graph.nodes[arista[1]]['posicion'])
-
-    return 
-
-
-def sTree( root, dec, s, c, d=None):
-    "plot trees next to each other"
-    graph = nx.Graph()
-    root.toGraph( graph, 0, dec, 0)
-  
-    if d:
-        subplot(graph, c=c, s=s, data = d)
-    else:
-        
-        d = subplot(graph, c=c, s=s)
-
-    return d
-
-
-

nuevostrees/ArteryObjAN1-0_tree.dat

@@ -0,0 +1 @@
+#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;64_[18.4358, -44.29, -72.1166, 0.14045223501625542];63_[17.9591, -44.4522, -71.6953, 0.403573266044137];62_[17.1169, -45.2517, -71.3105, 0.8029114735081432];61_[16.3855, -45.3593, -70.8019, 1.0187573276734132];60_[15.809, -45.3361, -70.3118, 1.0796678574234027];59_[15.2539, -45.2645, -69.8457, 1.1186587190032882];58_[14.7137, -45.2195, -69.2712, 1.178612602062069];57_[14.1889, -45.032, -68.5225, 1.256801171856488];56_[13.7702, -44.9884, -67.7696, 1.2860268725742952];55_[13.4166, -45.0094, -66.8967, 1.3276042657955311];54_[13.1157, -45.0318, -66.0227, 1.3531062106588545];53_[12.9326, -45.1113, -65.2933, 1.3625480499351235];52_[12.8581, -45.1902, -64.7051, 1.315014140354939];51_[12.797, -45.3, -64.0935, 1.2792292325291321];50_[12.7547, -45.4448, -63.2618, 1.298599894327267];49_[12.8355, -45.525, -62.4382, 1.3088316214465625];48_[12.9574, -45.5145, -61.7159, 1.2980517927275128];47_[13.1082, -45.5022, -61.0202, 1.2882097327424118];46_[13.3011, -45.5242, -60.2936, 1.3025941008010864];45_[13.4852, -45.5404, -59.6609, 1.3063079339302943];44_[13.6766, -45.5475, -59.0595, 1.3003554052994089];43_[13.8649, -45.5193, -58.5107, 1.2837322881440623];42_[14.0486, -45.4518, -57.9303, 1.2499262816216308];41_[14.209, -45.3847, -57.3913, 1.2227846761568837];40_[14.3632, -45.3128, -56.7425, 1.1993538076671975];#;#;#;#;#;#;#;#;#;#;#;#;0_[13.5786, -51.5181, -49.7241, 1.3800136573420192];1_[14.0803, -49.9515, -50.1683, 1.242986510775065];2_[14.163, -49.2643, -50.5715, 1.203160429549945];3_[14.2522, -48.7474, -50.9454, 1.1771591758030262];4_[14.3465, -48.1901, -51.3516, 1.155078195654739];5_[14.464, -47.6848, -51.8335, 1.120665293332171];6_[14.5301, -47.1985, -52.3879, 1.0846350215276885];7_[14.5892, -46.774, -52.9033, 1.0656488699877038];8_[14.6433, -46.408, -53.3952, 1.061596539122783];9_[14.6859, -46.112, -53.8552, 1.0530857965317164];10_[14.6826, -45.8357, -54.3367, 1.0764728974449453];11_[14.6605, -45.0716, -55.5973, 1.3210565807509667];#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;12_[15.3504, -39.3078, -60.8679, 0.5174749763616134];13_[15.2636, -39.3216, -60.4038, 0.4460627741690528];14_[15.2531, -39.3313, -60.1263, 0.44187572365516525];15_[15.2607, -39.369, -59.813, 0.4332178683266909];16_[15.2729, -39.4313, -59.4835, 0.417646993714681];17_[15.2838, -39.5519, -59.2268, 0.45827872879241227];18_[15.3279, -39.6724, -58.9834, 0.4834146269181603];19_[15.3978, -39.7911, -58.7452, 0.4792100897220925];20_[15.4732, -39.9179, -58.4865, 0.4948604346989655];21_[15.5286, -40.0226, -58.2625, 0.5125249390450025];22_[15.5562, -40.1525, -58.0043, 0.5015276165545921];23_[15.5975, -40.2901, -57.761, 0.5027064944406794];24_[15.6486, -40.4329, -57.5167, 0.5051134320862425];25_[15.6766, -40.6155, -57.2739, 0.5307891242722393];26_[15.7131, -40.7927, -57.0714, 0.5584149133222199];27_[15.7453, -40.9725, -56.8397, 0.5947434625707492];28_[15.7422, -41.2093, -56.5928, 0.6062132958791181];29_[15.7446, -41.4696, -56.3619, 0.6182867568305569];30_[15.7334, -41.7223, -56.1538, 0.6411799606915449];31_[15.6883, -42.0525, -55.9308, 0.6388974893210343];32_[15.5908, -42.4454, -55.7448, 0.6284244881197587];33_[15.4662, -42.7968, -55.6302, 0.6484866030093436];34_[15.3266, -43.1132, -55.5824, 0.6836578226228262];35_[15.2172, -43.3799, -55.5669, 0.7088888545285122];36_[15.128, -43.5787, -55.5608, 0.7549826966395634];37_[15.0763, -43.6933, -55.5604, 0.7834196693190479]

nuevostrees/ArteryObjAN1-11_tree.dat

@@ -0,0 +1 @@
+#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;59_[17.408846, -43.047993, -21.384293, 0.5203586296605394];58_[17.64306, -43.37741, -21.355518, 0.5251156675478624];57_[17.851841, -43.672535, -21.350382, 0.5503146051746227];56_[18.112484, -44.01957, -21.297783, 0.5856978607025812];55_[18.304565, -44.317417, -21.22882, 0.6042614358983214];54_[18.517483, -44.604805, -21.159409, 0.6308531999827302];53_[18.918982, -45.114784, -21.0982, 0.7303732735174482];52_[19.338268, -45.64431, -20.967096, 0.85814118058838];51_[19.539131, -45.956276, -20.759523, 0.8555726942673486];50_[19.795923, -46.303493, -20.543453, 0.8497687158167809];49_[20.076767, -46.724243, -20.385927, 0.8607316277638337];48_[20.423218, -47.16801, -20.28508, 0.8907819385631582];47_[20.743519, -47.558903, -20.262493, 0.8936788988184949];46_[21.069622, -47.910965, -20.283005, 0.8934315901827654];45_[21.412281, -48.26757, -20.30388, 0.8825793361278201];44_[21.817987, -48.77926, -20.378408, 0.8845932526550415];43_[22.125633, -49.13445, -20.647516, 0.8700839954451356];42_[22.404924, -49.606323, -20.946714, 0.8662729259545044];41_[22.642023, -50.038666, -21.31455, 0.8457290375203732];40_[22.831697, -50.462856, -21.732967, 0.8105080881683254];39_[22.962801, -50.829582, -22.17698, 0.7856107166532511];38_[23.036161, -51.166214, -22.564146, 0.7806119294563753];37_[23.036776, -51.575016, -22.924294, 0.7527905391715242];36_[22.943663, -51.97864, -23.29539, 0.753834754464688];35_[22.826574, -52.3516, -23.54022, 0.7408618083359093];34_[22.69135, -52.658215, -23.75543, 0.7265218894341579];33_[22.547844, -52.958664, -23.978727, 0.7273849214631647];32_[22.347042, -53.34037, -24.215357, 0.7503687441615178];31_[22.128975, -53.6632, -24.36372, 0.7450538458725552];30_[21.922277, -53.943024, -24.455168, 0.7388486540022395];#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;0_[12.440931, -63.221115, -24.508806, 0.7968910780869148];1_[13.014572, -62.69765, -24.738977, 0.7680696015207862];2_[13.653531, -62.27783, -24.763042, 0.736635802151607];3_[13.988204, -61.949554, -24.891594, 0.7285343306038191];4_[14.238006, -61.69715, -24.97357, 0.7446161077039783];5_[14.514402, -61.41231, -25.050596, 0.7580093037394248];6_[14.793104, -61.146297, -25.120539, 0.7706375395485513];7_[15.13749, -60.830242, -25.133812, 0.7716745941655831];8_[15.452703, -60.50044, -25.189047, 0.750380024796662];9_[15.853822, -60.120663, -25.260378, 0.7133067721905683];10_[16.208954, -59.75527, -25.333538, 0.6984696601507978];11_[16.548092, -59.3984, -25.40265, 0.6846971426303157];12_[16.840425, -59.138393, -25.46966, 0.7021030377213092];13_[17.128323, -58.883667, -25.505411, 0.7081743684919454];14_[17.405348, -58.62361, -25.530397, 0.7123703588945288];15_[17.693558, -58.397682, -25.556232, 0.7097361239098717];16_[17.986979, -58.16308, -25.565716, 0.7028312846771281];17_[18.311884, -57.879105, -25.553783, 0.6919960892368269];18_[18.592943, -57.604572, -25.532885, 0.6854730316080048];19_[18.881912, -57.309093, -25.482346, 0.6783280666845813];20_[19.16941, -57.023094, -25.440063, 0.6693605231997098];21_[19.5036, -56.70772, -25.390318, 0.6711482296220536];22_[19.859776, -56.380535, -25.287493, 0.673489841380318];23_[20.133188, -56.097652, -25.14902, 0.6807019224080906];24_[20.439766, -55.71128, -25.056572, 0.6802130619031441];25_[20.721985, -55.385006, -24.959757, 0.6815577610042173];26_[20.986904, -55.097893, -24.837059, 0.6944069302118568];27_[21.205956, -54.862637, -24.728191, 0.7244298107746436];28_[21.483206, -54.538868, -24.631865, 0.7414084281252717];29_[21.735943, -54.20471, -24.541605, 0.7385774955087492]

nuevostrees/ArteryObjAN1-12_tree.dat

@@ -0,0 +1 @@
+#;#;#;#;#;#;#;#;#;#;#;#;#;#;25_[9.97178, -81.7223, -28.8028, 2.5229322359932054];24_[10.8062, -81.6117, -30.9931, 1.9529558097990039];23_[11.2442, -81.0632, -31.3842, 1.8820801044280082];22_[11.5618, -80.2239, -31.7192, 1.844168886262388];21_[11.7589, -79.1235, -31.7512, 1.8934404233287745];20_[11.8629, -77.8718, -31.4977, 2.014595165199141];19_[12.0583, -76.7125, -31.2827, 2.0852408548593937];18_[12.5086, -75.2239, -31.2196, 2.138398489462607];17_[13.3132, -74.0139, -31.4181, 2.1274076120686147];16_[14.1099, -72.7872, -31.8877, 2.1484429545268946];15_[14.7363, -71.7512, -32.6929, 2.153906485647311];14_[15.1197, -71.4623, -33.535, 2.065839820941147];13_[15.3164, -71.3786, -34.2359, 1.9759274089907142];#;#;#;#;#;#;#;#;#;#;#;#;#;0_[17.1501, -72.011, -47.8547, 1.8989815261396552];1_[15.8616, -72.6106, -46.6053, 1.8397382655653185];2_[15.2757, -72.8396, -45.7381, 1.867745422883582];3_[14.8626, -72.8795, -44.6033, 1.873175733934367];4_[14.7169, -73.1806, -43.1301, 1.8714757894424148];5_[14.7373, -73.0487, -41.5932, 1.81544268772423];6_[14.9186, -72.936, -40.4737, 1.7999103150775697];7_[15.1547, -72.6212, -39.3198, 1.7919087978580446];8_[15.2521, -72.4371, -38.2619, 1.813269729505654];9_[15.3694, -72.0262, -37.2664, 1.8069395860876356];10_[15.4361, -71.7385, -36.4772, 1.8051567508564799];11_[15.5409, -71.5155, -35.6813, 1.8214260532736186];12_[15.4285, -71.3982, -34.8832, 1.8821728714783135]

nuevostrees/ArteryObjAN1-15_tree.dat

@@ -0,0 +1 @@
+#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;40_[-8.62122, -39.3818, -72.1034, 0.05748303894122518];39_[-8.29661, -39.8988, -71.9209, 0.37021296100204537];38_[-8.08708, -40.2494, -71.6355, 0.5363217650259714];37_[-7.91979, -41.1918, -71.2568, 0.8505569537492481];36_[-7.81514, -41.7735, -70.6367, 0.9652163506593121];35_[-7.77147, -42.3392, -70.0536, 1.089259601461783];34_[-7.54018, -42.9503, -69.5173, 1.13527241825701];33_[-7.23391, -43.4637, -68.9873, 1.1580100544883754];32_[-6.87366, -43.8797, -68.5345, 1.1677522877477529];31_[-6.38237, -44.2515, -68.1089, 1.2123495474240369];30_[-5.86354, -44.5459, -67.8754, 1.194821271550589];29_[-5.33054, -44.8498, -67.6662, 1.182706294729575];28_[-4.85379, -45.1066, -67.4669, 1.1520232501991685];27_[-4.33031, -45.3594, -67.2509, 1.1463161674445446];26_[-3.80383, -45.6166, -67.0635, 1.1460839268316407];25_[-3.25193, -45.8264, -66.8523, 1.1457436768649703];24_[-2.58078, -46.1057, -66.6338, 1.166135917221331];23_[-1.99585, -46.2566, -66.4356, 1.1655875869918313];22_[-1.45462, -46.4491, -66.23, 1.1522822750950938];21_[-0.900659, -46.588, -66.0292, 1.146191277416196];#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;0_[9.15811, -51.3426, -61.4497, 1.1171930305442603];1_[8.64654, -50.9663, -61.9747, 1.1116431389521217];2_[8.19122, -50.6306, -62.3463, 1.0954866513566976];3_[7.7812, -50.3636, -62.6852, 1.09412659766696];4_[7.32013, -50.0106, -62.9759, 1.0702547114339225];5_[6.93401, -49.727, -63.2066, 1.0745003237459436];6_[6.53848, -49.4394, -63.4242, 1.0789232559550777];7_[6.1646, -49.1846, -63.5994, 1.095986362346742];8_[5.78336, -48.9439, -63.7385, 1.1129992236069146];9_[5.37316, -48.6969, -63.8502, 1.1385659578045317];10_[4.94579, -48.4387, -63.9876, 1.1499333223426758];11_[4.4961, -48.1904, -64.1544, 1.1579047271311493];12_[3.95236, -47.9086, -64.3373, 1.1646870906047289];13_[3.42331, -47.6884, -64.4967, 1.1694988787391858];14_[2.95388, -47.5183, -64.6617, 1.168065425346949];15_[2.39158, -47.3108, -64.8564, 1.1595413757685713];16_[1.82927, -47.1431, -65.0408, 1.158025999679285];17_[1.21709, -47.046, -65.285, 1.1525294744681];18_[0.629382, -46.9535, -65.5015, 1.155002332662437];19_[0.0674255, -46.8128, -65.7168, 1.1505494424942244];20_[-0.390698, -46.7069, -65.8503, 1.1528394758217573]

nuevostrees/ArteryObjAN1-16_tree.dat

@@ -0,0 +1 @@
+#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;#;88_[-3.8818474, -62.36828, -29.58682, 0.1838778653749099];87_[-3.4834578, -62.476013, -29.57358, 0.35712298989523966];86_[-3.2201054, -62.576283, -29.457872, 0.3847878470309573];85_[-2.987393, -62.628567, -29.292885, 0.4186208583661626];84_[-2.7752826, -62.696922, -29.172356, 0.4198347579166753];83_[-2.502199, -62.76016, -28.99289, 0.41948136881266007];82_[-2.2407587, -62.7787, -28.809956, 0.4284093694401138];81_[-2.019985, -62.81731, -28.645163, 0.43658801071402936];80_[-1.7918751, -62.842175, -28.467808, 0.4399645468946349];79_[-1.5896012, -62.87635, -28.307756, 0.44428792308804016];78_[-1.3922774, -62.91347, -28.119707, 0.4378061243008222];77_[-1.1830904, -62.923004, -27.860249, 0.456100227814256];76_[-0.90002, -62.981243, -27.578215, 0.5017335367865524];75_[-0.68995017, -62.962467, -27.290699, 0.5163932116482326];74_[-0.51145434, -62.974453, -27.006573, 0.5561536294830343];73_[-0.31960133, -63.03423, -26.68946, 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nuevostrees/ArteryObjAN1-17_tree.dat

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nuevostrees/ArteryObjAN1-19_tree.dat

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nuevostrees/ArteryObjAN1-2_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN1-4_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN1-5_tree.dat

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nuevostrees/ArteryObjAN1-6_tree.dat

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nuevostrees/ArteryObjAN1-7_tree.dat

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nuevostrees/ArteryObjAN11-0_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN11-11_tree.dat

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nuevostrees/ArteryObjAN11-16_tree.dat

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nuevostrees/ArteryObjAN11-17_tree.dat

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nuevostrees/ArteryObjAN11-1_tree.dat

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nuevostrees/ArteryObjAN11-2_tree.dat

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nuevostrees/ArteryObjAN11-3_tree.dat

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nuevostrees/ArteryObjAN11-4_tree.dat

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nuevostrees/ArteryObjAN11-6_tree.dat

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nuevostrees/ArteryObjAN11-8_tree.dat

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nuevostrees/ArteryObjAN116-0_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN116-11_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN116-12_tree.dat

@@ -0,0 +1 @@
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0.7906881463733733];32_[37.6534, -34.2616, 25.8567, 0.7969752428118557];33_[38.0435, -34.2131, 25.838, 0.8106772209855708];34_[38.4518, -34.1285, 25.7669, 0.7908096262317645];35_[38.8828, -34.0566, 25.6897, 0.7721624560472966];36_[39.3387, -34.011, 25.6014, 0.7559981594754236];37_[39.7003, -33.9605, 25.5298, 0.7628705509416732];38_[40.0825, -33.9388, 25.4266, 0.7874339991780335]

nuevostrees/ArteryObjAN116-16_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN116-17_tree.dat

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nuevostrees/ArteryObjAN116-1_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN116-2_tree.dat

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nuevostrees/ArteryObjAN116-3_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN116-4_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN116-6_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN116-7_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN116-8_tree.dat

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nuevostrees/ArteryObjAN117-0_tree.dat

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nuevostrees/ArteryObjAN117-10_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN117-12_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN117-14_tree.dat

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nuevostrees/ArteryObjAN117-15_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN117-16_tree.dat

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nuevostrees/ArteryObjAN117-18_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN117-19_tree.dat

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nuevostrees/ArteryObjAN117-2_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN117-5_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN117-6_tree.dat

@@ -0,0 +1 @@
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nuevostrees/ArteryObjAN117-8_tree.dat

@@ -0,0 +1 @@
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