How to use default_node method in lisa

Best Python code snippet using lisa_python

appendix2.py

Source:appendix2.py

1# -*- coding: utf-8 -*-2import urllib3import urllib24from urllib2 import URLError, HTTPError5import json 6import pdb7import os8import sys9from bs4 import BeautifulSoup10import re11p = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))12sys.path.insert(0, p)13sys.path.insert(0,p+"/sources")14os.environ['DJANGO_SETTINGS_MODULE'] = "sefaria.settings"15from local_settings import *16sys.path.append(p+"/data_utilities")17from data_utilities.dibur_hamatchil_matcher import *18from functions import *19sys.path.insert(0, SEFARIA_PROJECT_PATH)20from sefaria.model import *21from sefaria.model.schema import AddressTalmud22root = SchemaNode()23root.add_title("Sefer Mitzvot Gadol", "en", primary=True)24root.add_title("SeMaG", "en")25root.add_title(u"×¡×¤×¨ ××¦×××ª ××××", "he", primary=True)26root.add_title(u'×¡×"×', 'he')27root.key = "smg"28vol1 = SchemaNode()29vol1.key = 'vol1'30vol1.add_title("Volume One", "en", primary=True)31vol1.add_title(u"×××§ ××××××", "he", primary=True)32intro = JaggedArrayNode()33intro.key = "intropt1"34intro.addressTypes = ["Integer"]35intro.sectionNames = ["Paragraph"]36intro.depth = 137intro.add_title("Introduction", "en", primary=True)38intro.add_title(u"××§×××ª ×××××¨", "he", primary=True)39vol1.append(intro)40remazim = JaggedArrayNode()41remazim.key = "remazimpt1"42remazim.addressTypes = ["Integer"]43remazim.sectionNames = ["Paragraph"]44remazim.depth = 145remazim.add_title("Remazim", "en", primary=True)46remazim.add_title(u"×¨××××", "he", primary=True)47vol1.append(remazim)48default_node = JaggedArrayNode()49default_node.depth = 250default_node.sectionNames = ["Negative Mitzvah", "Paragraph"]51default_node.addressTypes = ["Integer", "Integer"]52default_node.default = True53default_node.key = "default"54vol1.append(default_node)55vol2 = SchemaNode()56vol2.key = 'vol2'57vol2.add_title("Volume Two", "en", primary=True)58vol2.add_title(u"×××§ ××¢×©××", "he", primary=True)59intro = JaggedArrayNode()60intro.key = "intropt2"61intro.addressTypes = ["Integer"]62intro.sectionNames = ["Paragraph"]63intro.depth = 164intro.add_title("Introduction", "en", primary=True)65intro.add_title(u"××§×××ª ×××××¨", "he", primary=True)66vol2.append(intro)67remazim = JaggedArrayNode()68remazim.key = "remazimpt2"69remazim.addressTypes = ["Integer"]70remazim.sectionNames = ["Paragraph"]71remazim.depth = 172remazim.add_title("Remazim", "en", primary=True)73remazim.add_title(u"×¨××××", "he", primary=True)74vol2.append(remazim)75default_node = JaggedArrayNode()76default_node.depth = 277default_node.sectionNames = ["Positive Mitzvah", "Paragraph"]78default_node.addressTypes = ["Integer", "Integer"]79default_node.default = True80default_node.key = "default"81vol2.append(default_node)82heb_nodes = [u"×××××ª ×¢××¨××××", u"×××××ª ××××××ª", u"×××××ª ×ª×©×¢× ×××", u"×××××ª ×××××", u"×××××ª ×× ×××"]83eng_nodes = ["Laws of Eruvin", "Laws of Mourning", "Laws of Tisha B'Av", "Laws of Megillah", "Laws of Chanukah"]84for count, heb_node in enumerate(heb_nodes):85    node = JaggedArrayNode()86    node.depth = 187    node.sectionNames = ["Paragraph"]88    node.addressTypes = ["Integer"]89    node.key = eng_nodes[count]90    node.add_title(heb_node, "he", primary=True)91    node.add_title(eng_nodes[count], "en", primary=True)92    vol2.append(node)93def addMitzvah(mitzvah, text):94    if not isGematria(mitzvah):95        print 'not gematria!'96        pdb.set_trace()97    current_mitzvah = getGematria(mitzvah)98    if current_mitzvah in text:99        print "double mitzvah"100        pdb.set_trace()101    return current_mitzvah102smag = open("appendix.txt",'r')103tag = re.compile('@\d+')104text = {}105prev_line=""106msg=""107root.append(vol1)108root.append(vol2)109root.validate()110index = {111    "title": "Sefer Mitzvot Gadol",112    "categories": ["Halakhah"],113    "schema": root.serialize()114    }...

test_helpers.py

Source:test_helpers.py

...55        # but the default can be changed when the node is added back56        helpers.save_node(node1)57        default_node = helpers.get_node()58        self.assertEqual(default_node.name, "node2")59        helpers.set_default_node("node1")60        default_node = helpers.get_node()61        self.assertEqual(default_node.name, "node1")62        # all nodes can be retrieved63        nodes = helpers.get_nodes()64        self.assertEqual(len(nodes), 2)65        self.assertTrue(nodes[0].name in ["node1", "node2"])66        self.assertTrue(nodes[1].name in ["node1", "node2"])67    def test_lists_all_nodes(self):68        pass69    def test_delete_node(self):70        # nodes can be deleted by object or name71        node1 = TcpNode("node1", "https://localhost:8088",72                        "node1_key")73        node2 = TcpNode("node2", "https://localhost:8089",...

samplers.py

Source:samplers.py

1import tensorflow as tf2from tf_euler.python import euler_ops345vanilla_sample_fanout = euler_ops.sample_fanout678def sample_sim_cor_fanout(nodes, edge_types, counts, default_node=-1):9  neighbors_list = [tf.reshape(nodes, [-1])]10  for hop_edge_types, count in zip(edge_types, counts):11    sim_edge_type = cor_edge_type = None12    if len(hop_edge_types) == 2:13      sim_edge_type, cor_edge_type = hop_edge_types14    elif len(hop_edge_types) == 1:15      sim_edge_type = cor_edge_type = hop_edge_types[0]16    sim_neighbors, _, _ = euler_ops.sample_neighbor(17      neighbors_list[-1], [sim_edge_type], count, default_node=default_node)18    cor_neighbors, _, _ = euler_ops.sample_neighbor(19      neighbors_list[-1], [cor_edge_type], count, default_node=default_node)20    sim_neighbors = tf.reshape(sim_neighbors, [-1])21    cor_neighbors = tf.reshape(cor_neighbors, [-1])22    neighbors = tf.concat([sim_neighbors, cor_neighbors], axis=-1)23    neighbors_list.append(neighbors)24  return [neighbors_list]252627def sample_patterned_metapaths(nodes, patterns, count_per_path, default_node=-1):28  all_neighbors = []29  for meta_pattern in patterns:30    pattern_neighbors = nodes31    last_neighbors = tf.reshape(nodes, [-1])32    counts = [int(count_per_path // len(meta_pattern))] + [1] * (len(meta_pattern) - 1)33    for hop_edge_types, count in zip(meta_pattern, counts):34      neighbors, _, _ = euler_ops.sample_neighbor(35          last_neighbors, [hop_edge_types], count, default_node=default_node)36      last_neighbors = tf.reshape(neighbors, [-1])37      neighbors = tf.reshape(neighbors, [-1, counts[0]])38      pattern_neighbors = tf.concat([pattern_neighbors, neighbors], axis=-1)39    all_neighbors.append(pattern_neighbors)40  all_nodes = [nodes] * len(patterns)41  return all_nodes, all_neighbors
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