diff --git a/bdikit/functional_api.py b/bdikit/functional_api.py index c5461ac2..e4f2bbf2 100644 --- a/bdikit/functional_api.py +++ b/bdikit/functional_api.py @@ -1,7 +1,9 @@ from enum import Enum from os.path import join, dirname -from typing import Union, Type, List, Optional +from typing import Union, Type, List, Dict, TypedDict, Set, Optional, Tuple, Callable import pandas as pd +import numpy as np +from bdikit.utils import get_gdc_data from bdikit.download import get_cached_model_or_download from bdikit.mapping_algorithms.column_mapping.algorithms import ( BaseColumnMappingAlgorithm, @@ -18,6 +20,23 @@ from bdikit.mapping_algorithms.scope_reducing._algorithms.contrastive_learning.cl_api import ( ContrastiveLearningAPI, ) +from bdikit.mapping_algorithms.value_mapping.algorithms import ( + ValueMatch, + BaseAlgorithm, + TFIDFAlgorithm, + LLMAlgorithm, + EditAlgorithm, + EmbeddingAlgorithm, + AutoFuzzyJoinAlgorithm, + FastTextAlgorithm, +) +from bdikit.mapping_algorithms.value_mapping.value_mappers import ( + ValueMapper, + FunctionValueMapper, + DictionaryMapper, + IdentityValueMapper, +) + GDC_DATA_PATH = join(dirname(__file__), "./resource/gdc_table.csv") @@ -120,16 +139,52 @@ def top_matches( return pd.concat(dfs, ignore_index=True) +class ValueMatchingMethod(Enum): + TFIDF = ("tfidf", TFIDFAlgorithm) + EDIT = ("edit_distance", EditAlgorithm) + EMBEDDINGS = ("embedding", EmbeddingAlgorithm) + AUTOFJ = ("auto_fuzzy_join", AutoFuzzyJoinAlgorithm) + FASTTEXT = ("fasttext", FastTextAlgorithm) + GPT = ("gpt", LLMAlgorithm) + + def __init__(self, method_name: str, method_class: Type[BaseAlgorithm]): + self.method_name = method_name + self.method_class = method_class + + @staticmethod + def get_instance(method_name: str) -> BaseAlgorithm: + methods = { + method.method_name: method.method_class for method in ValueMatchingMethod + } + try: + return methods[method_name]() + except KeyError: + names = ", ".join(list(methods.keys())) + raise ValueError( + f"The {method_name} algorithm is not supported. " + f"Supported algorithms are: {names}" + ) + + def materialize_mapping( - input_dataframe: pd.DataFrame, target: List[dict] + input_table: pd.DataFrame, mapping_spec: List[dict] ) -> pd.DataFrame: + """ + Takes an input DataFrame and a target mapping specification and returns a + new DataFrame created according to the given target mapping specification. + The mapping specification is a list of dictionaries, where each dictionary + defines one column in the output table and how it is created. It includes + the names of the input (source) and output (target) columns and the value + mapper that is used to transform the values of the input column to the + output column. + """ output_dataframe = pd.DataFrame() - for mapping_spec in target: - from_column_name = mapping_spec["from"] - to_column_name = mapping_spec["to"] - value_mapper = mapping_spec["mapper"] + for column_spec in mapping_spec: + from_column_name = column_spec["source"] + to_column_name = column_spec["target"] + value_mapper = column_spec["mapper"] output_dataframe[to_column_name] = map_column_values( - input_dataframe[from_column_name], to_column_name, value_mapper + input_table[from_column_name], to_column_name, value_mapper ) return output_dataframe @@ -140,3 +195,253 @@ def map_column_values( new_column = value_mapper.map(input_column) new_column.name = target return new_column + + +class ValueMatchingResult(TypedDict): + target: str + matches: List[ValueMatch] + coverage: float + unique_values: Set[str] + unmatch_values: Set[str] + + +def match_values( + source: pd.DataFrame, + target: Union[str, pd.DataFrame], + column_mapping: pd.DataFrame, + method: str = ValueMatchingMethod.EDIT.name, +) -> Dict[str, ValueMatchingResult]: + """ + Maps the values of the dataset columns to the target domain using the given method name. + """ + if isinstance(target, str) and target == "gdc": + column_names = column_mapping["target"].unique().tolist() + target_domain = get_gdc_data(column_names) + elif isinstance(target, pd.DataFrame): + target_domain = { + column_name: target[column_name].unique().tolist() + for column_name in target.columns + } + else: + raise ValueError( + "The target must be a DataFrame or a standard vocabulary name." + ) + + column_mapping_dict = column_mapping.set_index("source")["target"].to_dict() + value_matcher = ValueMatchingMethod.get_instance(method) + matches = _match_values(source, target_domain, column_mapping_dict, value_matcher) + return matches + + +def _match_values( + dataset: pd.DataFrame, + target_domain: Dict[str, Optional[List[str]]], + column_mapping: Dict[str, str], + value_matcher: BaseAlgorithm, +) -> Dict[str, ValueMatchingResult]: + + mapping_results: dict[str, ValueMatchingResult] = {} + + for source_column, target_column in column_mapping.items(): + + # 1. Select candidate columns for value mapping + target_domain_list = target_domain[target_column] + if target_domain_list is None or len(target_domain_list) == 0: + continue + + unique_values = dataset[source_column].unique() + if _skip_values(unique_values): + continue + + # 2. Transform the unique values to lowercase + source_values_dict: Dict[str, str] = { + str(x).strip().lower(): str(x).strip() for x in unique_values + } + target_values_dict: Dict[str, str] = {x.lower(): x for x in target_domain_list} + + # 3. Apply the value matcher to create value mapping dictionaries + matches_lowercase = value_matcher.match( + list(source_values_dict.keys()), list(target_values_dict.keys()) + ) + + # 4. Transform the matches to the original case + matches: List[ValueMatch] = [] + for source_value, target_value, similarity in matches_lowercase: + matches.append( + ValueMatch( + current_value=source_values_dict[source_value], + target_value=target_values_dict[target_value], + similarity=similarity, + ) + ) + + # 5. Calculate the coverage and unmatched values + coverage = len(matches) / len(source_values_dict) + source_values = set(source_values_dict.values()) + match_values = set([x[0] for x in matches]) + + mapping_results[source_column] = ValueMatchingResult( + target=target_column, + matches=matches, + coverage=coverage, + unique_values=source_values, + unmatch_values=source_values - match_values, + ) + + return mapping_results + + +def _skip_values(unique_values: np.ndarray, max_length: int = 50): + if isinstance(unique_values[0], float): + return True + elif len(unique_values) > max_length: + return True + else: + return False + + +def preview_value_mappings( + dataset: pd.DataFrame, + column_mapping: Union[Tuple[str, str], pd.DataFrame], + target: Union[str, pd.DataFrame] = "gdc", + method: str = "edit_distance", +) -> List[Dict]: + """ + Print the value mappings in a human-readable format. + """ + if isinstance(column_mapping, pd.DataFrame): + mapping_df = column_mapping + elif isinstance(column_mapping, tuple): + mapping_df = pd.DataFrame( + [ + { + "source": column_mapping[0], + "target": column_mapping[1], + } + ] + ) + else: + raise ValueError( + "The column_mapping must be a DataFrame or a tuple of two strings." + ) + + value_mappings = match_values( + dataset, target=target, column_mapping=mapping_df, method=method + ) + + result = [] + for source_column, matching_result in value_mappings.items(): + # transform matches and unmatched values into DataFrames + matches_df = pd.DataFrame( + data=matching_result["matches"], + columns=["source", "target", "similarity"], + ) + + unmatched_values = matching_result["unmatch_values"] + unmatched_df = pd.DataFrame( + data=list( + zip( + unmatched_values, + [""] * len(unmatched_values), + [""] * len(unmatched_values), + ) + ), + columns=["source", "target", "similarity"], + ) + + result.append( + { + "source": source_column, + "target": matching_result["target"], + "mapping": pd.concat([matches_df, unmatched_df], ignore_index=True), + } + ) + + if isinstance(column_mapping, tuple): + # If only a single mapping is provided (as a tuple), we return the result + # directly as a DataFrame to make it easier to display it in notebooks. + assert len(result) == 1 + return result[0]["mapping"] + else: + return result + + +def update_mappings(value_mappings: Dict, user_mappings: List) -> List: + user_mappings_dict = { + user_mapping["source"] + "__" + user_mapping["target"]: user_mapping + for user_mapping in user_mappings + } + + final_mappings = [] + for source_column, mapping in value_mappings.items(): + # if the mapping is provided by the user, we ignore it here + # since the user mappings take precedence + key = source_column + "__" + mapping["target"] + if key not in user_mappings_dict: + final_mappings.append( + { + "source": source_column, + "target": mapping["target"], + "mapper": create_mapper(mapping), + } + ) + + # include all user mappings + for user_mapping in user_mappings: + mapper_spec = user_mapping.get("mapper", None) + if not isinstance(mapper_spec, ValueMapper): + user_mapping["mapper"] = create_mapper(mapper_spec) + final_mappings.append(user_mapping) + + return final_mappings + + +def create_mapper( + input: Union[None, pd.DataFrame, Dict, Callable[[pd.Series], pd.Series]] +): + """ + Tries to instantiate an appropriate ValueMapper object for the given input argument. + Depending on the input type, it creates one of the following objects: + - If input is a function (or lambda function), it creates a FunctionValueMapper object. + - If input is a dictionary or Pandas DataFrame, it creates a DictionaryMapper object. + - If input is None, it creates an IdentityValueMapper object. + """ + if input is None: + return IdentityValueMapper() + + if isinstance(input, ValueMapper): + return input + + if callable(input): + return FunctionValueMapper(input) + + if ( + isinstance(input, dict) + and "matches" in input + and isinstance(input["matches"], list) + ): + # This is a dictionary returned by match_values function + matches = input["matches"] + mapping_dict = {} + for match in matches: + if isinstance(match, ValueMatch): + mapping_dict[match.current_value] = match.target_value + elif isinstance(match, tuple) and len(match) >= 2: + if isinstance(match[0], str) and isinstance(match[1], str): + mapping_dict[match[0]] = match[1] + else: + raise ValueError( + "Tuple in matches must contain two strings: (current_value, target_value)" + ) + else: + raise ValueError( + "Matches must be a list of ValueMatch objects or tuples" + ) + return DictionaryMapper(mapping_dict) + + if isinstance(input, pd.DataFrame) and all( + k in input.columns for k in ["current_value", "target_value"] + ): + return DictionaryMapper( + input.set_index("current_value")["target_value"].to_dict() + ) diff --git a/bdikit/mapping_algorithms/value_mapping/algorithms.py b/bdikit/mapping_algorithms/value_mapping/algorithms.py index 0e0f26b1..08e5c438 100644 --- a/bdikit/mapping_algorithms/value_mapping/algorithms.py +++ b/bdikit/mapping_algorithms/value_mapping/algorithms.py @@ -3,7 +3,7 @@ from openai import OpenAI from polyfuzz import PolyFuzz from polyfuzz.models import EditDistance, TFIDF, Embeddings -from flair.embeddings import TransformerWordEmbeddings +from flair.embeddings import TransformerWordEmbeddings, WordEmbeddings from autofj import AutoFJ from Levenshtein import ratio import pandas as pd @@ -91,6 +91,17 @@ def __init__(self, model_path: str = "bert-base-multilingual-cased"): super().__init__(PolyFuzz(method)) +class FastTextAlgorithm(PolyFuzzAlgorithm): + """ + Value matching algorithm based on the cosine similarity of FastText embeddings. + """ + + def __init__(self, model_name: str = "en-crawl"): + embeddings = WordEmbeddings(model_name) + method = Embeddings(embeddings, min_similarity=0) + super().__init__(PolyFuzz(method)) + + class LLMAlgorithm(BaseAlgorithm): def __init__(self): self.client = OpenAI() diff --git a/bdikit/mapping_algorithms/value_mapping/value_mappers.py b/bdikit/mapping_algorithms/value_mapping/value_mappers.py index 4c36f4ad..d6ad11d3 100644 --- a/bdikit/mapping_algorithms/value_mapping/value_mappers.py +++ b/bdikit/mapping_algorithms/value_mapping/value_mappers.py @@ -1,4 +1,6 @@ import pandas as pd +from typing import Any, Callable +from collections import defaultdict class ValueMapper: @@ -34,7 +36,7 @@ class FunctionValueMapper(ValueMapper): provided custom function. """ - def __init__(self, function): + def __init__(self, function: Callable[[pd.Series], pd.Series]): self.function = function def map(self, input_column: pd.Series) -> pd.Series: @@ -51,12 +53,12 @@ class DictionaryMapper(ValueMapper): values stored in the provided dictionary. """ - def __init__(self, dictionary: dict): - self.dictionary = dictionary + def __init__(self, dictionary: dict, missing_data_value: Any = None): + self.dictionary = defaultdict(lambda: missing_data_value, dictionary) def map(self, input_column: pd.Series) -> pd.Series: """ Transforms the values in the input_column to the values specified in the dictionary provided using the object constructor. """ - return input_column.map(self.dictionary) + return input_column.map(self.dictionary, na_action="ignore") diff --git a/examples/getting_started.ipynb b/examples/getting_started.ipynb new file mode 100644 index 00000000..f45b5600 --- /dev/null +++ b/examples/getting_started.ipynb @@ -0,0 +1,3111 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "application/javascript": "(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n var py_version = '3.1.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n var is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1;\n var reloading = false;\n var Bokeh = root.Bokeh;\n var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n\n if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n run_callbacks();\n return null;\n }\n if (!reloading) {\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n }\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n window._bokeh_on_load = on_load\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n var skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {'tabulator': 'https://cdn.jsdelivr.net/npm/tabulator-tables@5.5.0/dist/js/tabulator', 'moment': 'https://cdn.jsdelivr.net/npm/luxon/build/global/luxon.min', 'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n require([\"tabulator\"], function(Tabulator) {\n\twindow.Tabulator = Tabulator\n\ton_load()\n })\n require([\"moment\"], function(moment) {\n\twindow.moment = moment\n\ton_load()\n })\n require([\"jspanel\"], function(jsPanel) {\n\twindow.jsPanel = jsPanel\n\ton_load()\n })\n require([\"jspanel-modal\"], function() {\n\ton_load()\n })\n require([\"jspanel-tooltip\"], function() {\n\ton_load()\n })\n require([\"jspanel-hint\"], function() {\n\ton_load()\n })\n require([\"jspanel-layout\"], function() {\n\ton_load()\n })\n require([\"jspanel-contextmenu\"], function() {\n\ton_load()\n })\n require([\"jspanel-dock\"], function() {\n\ton_load()\n })\n require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n })\n require([\"notyf\"], function() {\n\ton_load()\n })\n root._bokeh_is_loading = css_urls.length + 11;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n }\n\n var existing_stylesheets = []\n var links = document.getElementsByTagName('link')\n for (var i = 0; i < links.length; i++) {\n var link = links[i]\n if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n }\n }\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } if (((window['Tabulator'] !== undefined) && (!(window['Tabulator'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/datatabulator/tabulator-tables@5.5.0/dist/js/tabulator.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['moment'] !== undefined) && (!(window['moment'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/datatabulator/luxon/build/global/luxon.min.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } var existing_scripts = []\n var scripts = document.getElementsByTagName('script')\n for (var i = 0; i < scripts.length; i++) {\n var script = scripts[i]\n if (script.src != null) {\n\texisting_scripts.push(script.src)\n }\n }\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (var i = 0; i < js_modules.length; i++) {\n var url = js_modules[i];\n if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (const name in js_exports) {\n var url = js_exports[name];\n if (skip.indexOf(url) >= 0 || root[name] != null) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onerror = on_error;\n element.async = false;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n element.textContent = `\n import ${name} from \"${url}\"\n window.${name} = ${name}\n window._bokeh_on_load()\n `\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n var js_urls = [\"https://cdn.holoviz.org/panel/1.2.3/dist/bundled/datatabulator/tabulator-tables@5.5.0/dist/js/tabulator.js\", \"https://cdn.holoviz.org/panel/1.2.3/dist/bundled/datatabulator/luxon/build/global/luxon.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.1.1.min.js\", \"https://cdn.holoviz.org/panel/1.2.3/dist/panel.min.js\"];\n var js_modules = [];\n var js_exports = {};\n var css_urls = [\"https://cdn.holoviz.org/panel/1.2.3/dist/bundled/datatabulator/tabulator-tables@5.5.0/dist/css/tabulator_simple.min.css\"];\n var inline_js = [ function(Bokeh) {\n inject_raw_css(\".tabulator{position:relative;border:1px solid #999;font-size:14px;text-align:left;overflow:hidden;-webkit-transform:translateZ(0);-moz-transform:translateZ(0);-ms-transform:translateZ(0);-o-transform:translateZ(0);transform:translateZ(0)}.tabulator[tabulator-layout=fitDataFill] .tabulator-tableholder .tabulator-table{min-width:100%}.tabulator[tabulator-layout=fitDataTable]{display:inline-block}.tabulator.tabulator-block-select{user-select:none}.tabulator .tabulator-header{position:relative;box-sizing:border-box;width:100%;border-bottom:1px solid #999;background-color:#fff;color:#555;font-weight:700;white-space:nowrap;overflow:hidden;-moz-user-select:none;-khtml-user-select:none;-webkit-user-select:none;-o-user-select:none}.tabulator .tabulator-header.tabulator-header-hidden{display:none}.tabulator .tabulator-header .tabulator-header-contents{position:relative;overflow:hidden}.tabulator .tabulator-header .tabulator-header-contents .tabulator-headers{display:inline-block}.tabulator .tabulator-header .tabulator-col{display:inline-flex;position:relative;box-sizing:border-box;flex-direction:column;justify-content:flex-start;border-right:1px solid #ddd;background:#fff;text-align:left;vertical-align:bottom;overflow:hidden}.tabulator .tabulator-header .tabulator-col.tabulator-moving{position:absolute;border:1px solid #999;background:#e6e6e6;pointer-events:none}.tabulator .tabulator-header .tabulator-col .tabulator-col-content{box-sizing:border-box;position:relative;padding:4px}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-header-popup-button{padding:0 8px}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-header-popup-button:hover{cursor:pointer;opacity:.6}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-title-holder{position:relative}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-title{box-sizing:border-box;width:100%;white-space:nowrap;overflow:hidden;text-overflow:ellipsis;vertical-align:bottom}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-title.tabulator-col-title-wrap{white-space:normal;text-overflow:clip}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-title .tabulator-title-editor{box-sizing:border-box;width:100%;border:1px solid #999;padding:1px;background:#fff}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-title .tabulator-header-popup-button+.tabulator-title-editor{width:calc(100% - 22px)}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-sorter{display:flex;align-items:center;position:absolute;top:0;bottom:0;right:4px}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-sorter .tabulator-arrow{width:0;height:0;border-left:6px solid transparent;border-right:6px solid transparent;border-bottom:6px solid #bbb}.tabulator .tabulator-header .tabulator-col.tabulator-col-group .tabulator-col-group-cols{position:relative;display:flex;border-top:1px solid #ddd;overflow:hidden;margin-right:-1px}.tabulator .tabulator-header .tabulator-col .tabulator-header-filter{position:relative;box-sizing:border-box;margin-top:2px;width:100%;text-align:center}.tabulator .tabulator-header .tabulator-col .tabulator-header-filter textarea{height:auto!important}.tabulator .tabulator-header .tabulator-col .tabulator-header-filter svg{margin-top:3px}.tabulator .tabulator-header .tabulator-col .tabulator-header-filter input::-ms-clear{width:0;height:0}.tabulator .tabulator-header .tabulator-col.tabulator-sortable .tabulator-col-title{padding-right:25px}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-header .tabulator-col.tabulator-sortable.tabulator-col-sorter-element:hover{cursor:pointer;background-color:#e6e6e6}}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=none] .tabulator-col-content .tabulator-col-sorter{color:#bbb}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=none] .tabulator-col-content .tabulator-col-sorter.tabulator-col-sorter-element .tabulator-arrow:hover{cursor:pointer;border-bottom:6px solid #555}}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=none] .tabulator-col-content .tabulator-col-sorter .tabulator-arrow{border-top:none;border-bottom:6px solid #bbb}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=ascending] .tabulator-col-content .tabulator-col-sorter{color:#666}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=ascending] .tabulator-col-content .tabulator-col-sorter.tabulator-col-sorter-element .tabulator-arrow:hover{cursor:pointer;border-bottom:6px solid #555}}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=ascending] .tabulator-col-content .tabulator-col-sorter .tabulator-arrow{border-top:none;border-bottom:6px solid #666}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=descending] .tabulator-col-content .tabulator-col-sorter{color:#666}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=descending] .tabulator-col-content .tabulator-col-sorter.tabulator-col-sorter-element .tabulator-arrow:hover{cursor:pointer;border-top:6px solid #555}}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=descending] .tabulator-col-content .tabulator-col-sorter .tabulator-arrow{border-bottom:none;border-top:6px solid #666;color:#666}.tabulator .tabulator-header .tabulator-col.tabulator-col-vertical .tabulator-col-content .tabulator-col-title{writing-mode:vertical-rl;text-orientation:mixed;display:flex;align-items:center;justify-content:center}.tabulator .tabulator-header .tabulator-col.tabulator-col-vertical.tabulator-col-vertical-flip .tabulator-col-title{transform:rotate(180deg)}.tabulator .tabulator-header .tabulator-col.tabulator-col-vertical.tabulator-sortable .tabulator-col-title{padding-right:0;padding-top:20px}.tabulator .tabulator-header .tabulator-col.tabulator-col-vertical.tabulator-sortable.tabulator-col-vertical-flip .tabulator-col-title{padding-right:0;padding-bottom:20px}.tabulator .tabulator-header .tabulator-col.tabulator-col-vertical.tabulator-sortable .tabulator-col-sorter{justify-content:center;left:0;right:0;top:4px;bottom:auto}.tabulator .tabulator-header .tabulator-frozen{position:sticky;left:0;z-index:10}.tabulator .tabulator-header .tabulator-frozen.tabulator-frozen-left{border-right:2px solid #ddd}.tabulator .tabulator-header .tabulator-frozen.tabulator-frozen-right{border-left:2px solid #ddd}.tabulator .tabulator-header .tabulator-calcs-holder{box-sizing:border-box;background:#fff!important;border-top:1px solid #ddd;border-bottom:1px solid #ddd}.tabulator .tabulator-header .tabulator-calcs-holder .tabulator-row{background:#fff!important}.tabulator .tabulator-header .tabulator-calcs-holder .tabulator-row .tabulator-col-resize-handle,.tabulator .tabulator-header .tabulator-frozen-rows-holder:empty{display:none}.tabulator .tabulator-tableholder{position:relative;width:100%;white-space:nowrap;overflow:auto;-webkit-overflow-scrolling:touch}.tabulator .tabulator-tableholder:focus{outline:none}.tabulator .tabulator-tableholder .tabulator-placeholder{box-sizing:border-box;display:flex;align-items:center;justify-content:center;width:100%}.tabulator .tabulator-tableholder .tabulator-placeholder[tabulator-render-mode=virtual]{min-height:100%;min-width:100%}.tabulator .tabulator-tableholder .tabulator-placeholder .tabulator-placeholder-contents{display:inline-block;text-align:center;padding:10px;color:#ccc;font-weight:700;font-size:20px;white-space:normal}.tabulator .tabulator-tableholder .tabulator-table{position:relative;display:inline-block;background-color:#fff;white-space:nowrap;overflow:visible;color:#333}.tabulator .tabulator-tableholder .tabulator-table .tabulator-row.tabulator-calcs{font-weight:700;background:#f2f2f2!important}.tabulator .tabulator-tableholder .tabulator-table .tabulator-row.tabulator-calcs.tabulator-calcs-top{border-bottom:2px solid #ddd}.tabulator .tabulator-tableholder .tabulator-table .tabulator-row.tabulator-calcs.tabulator-calcs-bottom{border-top:2px solid #ddd}.tabulator .tabulator-footer{border-top:1px solid #999;background-color:#fff;color:#555;font-weight:700;white-space:nowrap;user-select:none;-moz-user-select:none;-khtml-user-select:none;-webkit-user-select:none;-o-user-select:none}.tabulator .tabulator-footer .tabulator-footer-contents{display:flex;flex-direction:row;align-items:center;justify-content:space-between;padding:5px 10px}.tabulator .tabulator-footer .tabulator-footer-contents:empty{display:none}.tabulator .tabulator-footer .tabulator-calcs-holder{box-sizing:border-box;width:100%;text-align:left;background:#fff!important;border-bottom:1px solid #ddd;border-top:1px solid #ddd;overflow:hidden}.tabulator .tabulator-footer .tabulator-calcs-holder .tabulator-row{display:inline-block;background:#fff!important}.tabulator .tabulator-footer .tabulator-calcs-holder .tabulator-row .tabulator-col-resize-handle{display:none}.tabulator .tabulator-footer .tabulator-calcs-holder:only-child{margin-bottom:-5px;border-bottom:none}.tabulator .tabulator-footer>*+.tabulator-page-counter{margin-left:10px}.tabulator .tabulator-footer .tabulator-page-counter{font-weight:400}.tabulator .tabulator-footer .tabulator-paginator{flex:1;text-align:right;color:#555;font-family:inherit;font-weight:inherit;font-size:inherit}.tabulator .tabulator-footer .tabulator-page-size{display:inline-block;margin:0 5px;padding:2px 5px;border:1px solid #aaa;border-radius:3px}.tabulator .tabulator-footer .tabulator-pages{margin:0 7px}.tabulator .tabulator-footer .tabulator-page{display:inline-block;margin:0 2px;padding:2px 5px;border:1px solid #aaa;border-radius:3px;background:hsla(0,0%,100%,.2)}.tabulator .tabulator-footer .tabulator-page.active{color:#d00}.tabulator .tabulator-footer .tabulator-page:disabled{opacity:.5}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-footer .tabulator-page:not(.disabled):hover{cursor:pointer;background:rgba(0,0,0,.2);color:#fff}}.tabulator .tabulator-col-resize-handle{position:relative;display:inline-block;width:6px;margin-left:-3px;margin-right:-3px;z-index:10;vertical-align:middle}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-col-resize-handle:hover{cursor:ew-resize}}.tabulator .tabulator-col-resize-handle:last-of-type{width:3px;margin-right:0}.tabulator .tabulator-alert{position:absolute;display:flex;align-items:center;top:0;left:0;z-index:100;height:100%;width:100%;background:rgba(0,0,0,.4);text-align:center}.tabulator .tabulator-alert .tabulator-alert-msg{display:inline-block;margin:0 auto;padding:10px 20px;border-radius:10px;background:#fff;font-weight:700;font-size:16px}.tabulator .tabulator-alert .tabulator-alert-msg.tabulator-alert-state-msg{border:4px solid #333;color:#000}.tabulator .tabulator-alert .tabulator-alert-msg.tabulator-alert-state-error{border:4px solid #d00;color:#590000}.tabulator-row{position:relative;box-sizing:border-box;min-height:22px}.tabulator-row,.tabulator-row.tabulator-row-even{background-color:#fff}@media (hover:hover) and (pointer:fine){.tabulator-row.tabulator-selectable:hover{background-color:#bbb;cursor:pointer}}.tabulator-row.tabulator-selected{background-color:#9abcea}@media (hover:hover) and (pointer:fine){.tabulator-row.tabulator-selected:hover{background-color:#769bcc;cursor:pointer}}.tabulator-row.tabulator-row-moving{border:1px solid #000;background:#fff}.tabulator-row.tabulator-moving{position:absolute;border-top:1px solid #ddd;border-bottom:1px solid #ddd;pointer-events:none;z-index:15}.tabulator-row .tabulator-row-resize-handle{position:absolute;right:0;bottom:0;left:0;height:5px}.tabulator-row .tabulator-row-resize-handle.prev{top:0;bottom:auto}@media (hover:hover) and (pointer:fine){.tabulator-row .tabulator-row-resize-handle:hover{cursor:ns-resize}}.tabulator-row .tabulator-responsive-collapse{box-sizing:border-box;padding:5px;border-top:1px solid #ddd;border-bottom:1px solid #ddd}.tabulator-row .tabulator-responsive-collapse:empty{display:none}.tabulator-row .tabulator-responsive-collapse table{font-size:14px}.tabulator-row .tabulator-responsive-collapse table tr td{position:relative}.tabulator-row .tabulator-responsive-collapse table tr td:first-of-type{padding-right:10px}.tabulator-row .tabulator-cell{display:inline-block;position:relative;box-sizing:border-box;padding:4px;border-right:1px solid #ddd;vertical-align:middle;white-space:nowrap;overflow:hidden;text-overflow:ellipsis}.tabulator-row .tabulator-cell.tabulator-frozen{display:inline-block;position:sticky;left:0;background-color:inherit;z-index:10}.tabulator-row .tabulator-cell.tabulator-frozen.tabulator-frozen-left{border-right:2px solid #ddd}.tabulator-row .tabulator-cell.tabulator-frozen.tabulator-frozen-right{border-left:2px solid #ddd}.tabulator-row .tabulator-cell.tabulator-editing{border:1px solid #1d68cd;outline:none;padding:0}.tabulator-row .tabulator-cell.tabulator-editing input,.tabulator-row .tabulator-cell.tabulator-editing select{border:1px;background:transparent;outline:none}.tabulator-row .tabulator-cell.tabulator-validation-fail{border:1px solid #d00}.tabulator-row .tabulator-cell.tabulator-validation-fail input,.tabulator-row .tabulator-cell.tabulator-validation-fail select{border:1px;background:transparent;color:#d00}.tabulator-row .tabulator-cell.tabulator-row-handle{display:inline-flex;align-items:center;justify-content:center;-moz-user-select:none;-khtml-user-select:none;-webkit-user-select:none;-o-user-select:none}.tabulator-row .tabulator-cell.tabulator-row-handle .tabulator-row-handle-box{width:80%}.tabulator-row .tabulator-cell.tabulator-row-handle .tabulator-row-handle-box .tabulator-row-handle-bar{width:100%;height:3px;margin-top:2px;background:#666}.tabulator-row .tabulator-cell .tabulator-data-tree-branch{display:inline-block;vertical-align:middle;height:9px;width:7px;margin-top:-9px;margin-right:5px;border-bottom-left-radius:1px;border-left:2px solid #ddd;border-bottom:2px solid #ddd}.tabulator-row .tabulator-cell .tabulator-data-tree-control{display:inline-flex;justify-content:center;align-items:center;vertical-align:middle;height:11px;width:11px;margin-right:5px;border:1px solid #333;border-radius:2px;background:rgba(0,0,0,.1);overflow:hidden}@media (hover:hover) and (pointer:fine){.tabulator-row .tabulator-cell .tabulator-data-tree-control:hover{cursor:pointer;background:rgba(0,0,0,.2)}}.tabulator-row .tabulator-cell .tabulator-data-tree-control .tabulator-data-tree-control-collapse{display:inline-block;position:relative;height:7px;width:1px;background:transparent}.tabulator-row .tabulator-cell .tabulator-data-tree-control .tabulator-data-tree-control-collapse:after{position:absolute;content:\\\"\\\";left:-3px;top:3px;height:1px;width:7px;background:#333}.tabulator-row .tabulator-cell .tabulator-data-tree-control .tabulator-data-tree-control-expand{display:inline-block;position:relative;height:7px;width:1px;background:#333}.tabulator-row .tabulator-cell .tabulator-data-tree-control .tabulator-data-tree-control-expand:after{position:absolute;content:\\\"\\\";left:-3px;top:3px;height:1px;width:7px;background:#333}.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle{display:inline-flex;align-items:center;justify-content:center;-moz-user-select:none;-khtml-user-select:none;-webkit-user-select:none;-o-user-select:none;height:15px;width:15px;border-radius:20px;background:#666;color:#fff;font-weight:700;font-size:1.1em}@media (hover:hover) and (pointer:fine){.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle:hover{opacity:.7;cursor:pointer}}.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle.open .tabulator-responsive-collapse-toggle-close{display:initial}.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle.open .tabulator-responsive-collapse-toggle-open{display:none}.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle svg{stroke:#fff}.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle .tabulator-responsive-collapse-toggle-close{display:none}.tabulator-row .tabulator-cell .tabulator-traffic-light{display:inline-block;height:14px;width:14px;border-radius:14px}.tabulator-row.tabulator-group{box-sizing:border-box;border-bottom:1px solid #999;border-right:1px solid #ddd;border-top:1px solid #999;padding:5px 5px 5px 10px;background:#ccc;font-weight:700;min-width:100%}@media (hover:hover) and (pointer:fine){.tabulator-row.tabulator-group:hover{cursor:pointer;background-color:rgba(0,0,0,.1)}}.tabulator-row.tabulator-group.tabulator-group-visible .tabulator-arrow{margin-right:10px;border-left:6px solid transparent;border-right:6px solid transparent;border-top:6px solid #666;border-bottom:0}.tabulator-row.tabulator-group.tabulator-group-level-1{padding-left:30px}.tabulator-row.tabulator-group.tabulator-group-level-2{padding-left:50px}.tabulator-row.tabulator-group.tabulator-group-level-3{padding-left:70px}.tabulator-row.tabulator-group.tabulator-group-level-4{padding-left:90px}.tabulator-row.tabulator-group.tabulator-group-level-5{padding-left:110px}.tabulator-row.tabulator-group .tabulator-group-toggle{display:inline-block}.tabulator-row.tabulator-group .tabulator-arrow{display:inline-block;width:0;height:0;margin-right:16px;border-top:6px solid transparent;border-bottom:6px solid transparent;border-right:0;border-left:6px solid #666;vertical-align:middle}.tabulator-row.tabulator-group span{margin-left:10px;color:#d00}.tabulator-popup-container{position:absolute;display:inline-block;box-sizing:border-box;background:#fff;border:1px solid #ddd;box-shadow:0 0 5px 0 rgba(0,0,0,.2);font-size:14px;overflow-y:auto;-webkit-overflow-scrolling:touch;z-index:10000}.tabulator-popup{padding:5px;border-radius:3px}.tabulator-tooltip{max-width:Min(500px,100%);padding:3px 5px;border-radius:2px;box-shadow:none;font-size:12px;pointer-events:none}.tabulator-menu .tabulator-menu-item{position:relative;box-sizing:border-box;padding:5px 10px;user-select:none}.tabulator-menu .tabulator-menu-item.tabulator-menu-item-disabled{opacity:.5}@media (hover:hover) and (pointer:fine){.tabulator-menu .tabulator-menu-item:not(.tabulator-menu-item-disabled):hover{cursor:pointer;background:#fff}}.tabulator-menu .tabulator-menu-item.tabulator-menu-item-submenu{padding-right:25px}.tabulator-menu .tabulator-menu-item.tabulator-menu-item-submenu:after{display:inline-block;position:absolute;top:calc(5px + .4em);right:10px;height:7px;width:7px;content:\\\"\\\";border-color:#ddd;border-style:solid;border-width:1px 1px 0 0;vertical-align:top;transform:rotate(45deg)}.tabulator-menu .tabulator-menu-separator{border-top:1px solid #ddd}.tabulator-edit-list{max-height:200px;font-size:14px;overflow-y:auto;-webkit-overflow-scrolling:touch}.tabulator-edit-list .tabulator-edit-list-item{padding:4px;color:#333;outline:none}.tabulator-edit-list .tabulator-edit-list-item.active{color:#fff;background:#1d68cd}.tabulator-edit-list .tabulator-edit-list-item.active.focused{outline:1px solid hsla(0,0%,100%,.5)}.tabulator-edit-list .tabulator-edit-list-item.focused{outline:1px solid #1d68cd}@media (hover:hover) and (pointer:fine){.tabulator-edit-list .tabulator-edit-list-item:hover{cursor:pointer;color:#fff;background:#1d68cd}}.tabulator-edit-list .tabulator-edit-list-placeholder{padding:4px;color:#333;text-align:center}.tabulator-edit-list .tabulator-edit-list-group{border-bottom:1px solid #ddd;padding:6px 4px 4px;color:#333;font-weight:700}.tabulator-edit-list .tabulator-edit-list-group.tabulator-edit-list-group-level-2,.tabulator-edit-list .tabulator-edit-list-item.tabulator-edit-list-group-level-2{padding-left:12px}.tabulator-edit-list .tabulator-edit-list-group.tabulator-edit-list-group-level-3,.tabulator-edit-list .tabulator-edit-list-item.tabulator-edit-list-group-level-3{padding-left:20px}.tabulator-edit-list .tabulator-edit-list-group.tabulator-edit-list-group-level-4,.tabulator-edit-list .tabulator-edit-list-item.tabulator-edit-list-group-level-4{padding-left:28px}.tabulator-edit-list .tabulator-edit-list-group.tabulator-edit-list-group-level-5,.tabulator-edit-list .tabulator-edit-list-item.tabulator-edit-list-group-level-5{padding-left:36px}.tabulator.tabulator-ltr{direction:ltr}.tabulator.tabulator-rtl{text-align:initial;direction:rtl}.tabulator.tabulator-rtl .tabulator-header .tabulator-col{text-align:initial;border-left:1px solid #ddd;border-right:initial}.tabulator.tabulator-rtl .tabulator-header .tabulator-col.tabulator-col-group .tabulator-col-group-cols{margin-right:0;margin-left:-1px}.tabulator.tabulator-rtl .tabulator-header .tabulator-col.tabulator-sortable .tabulator-col-title{padding-right:0;padding-left:25px}.tabulator.tabulator-rtl .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-sorter{left:8px;right:auto}.tabulator.tabulator-rtl .tabulator-row .tabulator-cell{border-right:initial;border-left:1px solid #ddd}.tabulator.tabulator-rtl .tabulator-row .tabulator-cell .tabulator-data-tree-branch{margin-right:0;margin-left:5px;border-bottom-left-radius:0;border-bottom-right-radius:1px;border-left:initial;border-right:2px solid #ddd}.tabulator.tabulator-rtl .tabulator-row .tabulator-cell .tabulator-data-tree-control{margin-right:0;margin-left:5px}.tabulator.tabulator-rtl .tabulator-row .tabulator-cell.tabulator-frozen.tabulator-frozen-left{border-left:2px solid #ddd}.tabulator.tabulator-rtl .tabulator-row .tabulator-cell.tabulator-frozen.tabulator-frozen-right{border-right:2px solid #ddd}.tabulator.tabulator-rtl .tabulator-row .tabulator-col-resize-handle:last-of-type{width:3px;margin-left:0;margin-right:-3px}.tabulator.tabulator-rtl .tabulator-footer .tabulator-calcs-holder{text-align:initial}.tabulator-print-fullscreen{position:absolute;top:0;bottom:0;left:0;right:0;z-index:10000}body.tabulator-print-fullscreen-hide>:not(.tabulator-print-fullscreen){display:none!important}.tabulator-print-table{border-collapse:collapse}.tabulator-print-table .tabulator-data-tree-branch{display:inline-block;vertical-align:middle;height:9px;width:7px;margin-top:-9px;margin-right:5px;border-bottom-left-radius:1px;border-left:2px solid #ddd;border-bottom:2px solid #ddd}.tabulator-print-table .tabulator-print-table-group{box-sizing:border-box;border-bottom:1px solid #999;border-right:1px solid #ddd;border-top:1px solid #999;padding:5px 5px 5px 10px;background:#ccc;font-weight:700;min-width:100%}@media (hover:hover) and (pointer:fine){.tabulator-print-table .tabulator-print-table-group:hover{cursor:pointer;background-color:rgba(0,0,0,.1)}}.tabulator-print-table .tabulator-print-table-group.tabulator-group-visible .tabulator-arrow{margin-right:10px;border-left:6px solid transparent;border-right:6px solid transparent;border-top:6px solid #666;border-bottom:0}.tabulator-print-table .tabulator-print-table-group.tabulator-group-level-1 td{padding-left:30px!important}.tabulator-print-table .tabulator-print-table-group.tabulator-group-level-2 td{padding-left:50px!important}.tabulator-print-table .tabulator-print-table-group.tabulator-group-level-3 td{padding-left:70px!important}.tabulator-print-table .tabulator-print-table-group.tabulator-group-level-4 td{padding-left:90px!important}.tabulator-print-table .tabulator-print-table-group.tabulator-group-level-5 td{padding-left:110px!important}.tabulator-print-table .tabulator-print-table-group .tabulator-group-toggle{display:inline-block}.tabulator-print-table .tabulator-print-table-group .tabulator-arrow{display:inline-block;width:0;height:0;margin-right:16px;border-top:6px solid transparent;border-bottom:6px solid transparent;border-right:0;border-left:6px solid #666;vertical-align:middle}.tabulator-print-table .tabulator-print-table-group span{color:#d00}.tabulator-print-table .tabulator-data-tree-control{display:inline-flex;justify-content:center;align-items:center;vertical-align:middle;height:11px;width:11px;margin-right:5px;border:1px solid #333;border-radius:2px;background:rgba(0,0,0,.1);overflow:hidden}@media (hover:hover) and (pointer:fine){.tabulator-print-table .tabulator-data-tree-control:hover{cursor:pointer;background:rgba(0,0,0,.2)}}.tabulator-print-table .tabulator-data-tree-control .tabulator-data-tree-control-collapse{display:inline-block;position:relative;height:7px;width:1px;background:transparent}.tabulator-print-table .tabulator-data-tree-control .tabulator-data-tree-control-collapse:after{position:absolute;content:\\\"\\\";left:-3px;top:3px;height:1px;width:7px;background:#333}.tabulator-print-table .tabulator-data-tree-control .tabulator-data-tree-control-expand{display:inline-block;position:relative;height:7px;width:1px;background:#333}.tabulator-print-table .tabulator-data-tree-control .tabulator-data-tree-control-expand:after{position:absolute;content:\\\"\\\";left:-3px;top:3px;height:1px;width:7px;background:#333}.tabulator{border:none;background-color:#fff}.tabulator .tabulator-header .tabulator-calcs-holder{background:#f2f2f2!important;border-bottom:1px solid #999}.tabulator .tabulator-header .tabulator-calcs-holder .tabulator-row{background:#f2f2f2!important}.tabulator .tabulator-tableholder .tabulator-placeholder span{color:#000}.tabulator .tabulator-footer .tabulator-calcs-holder{background:#f2f2f2!important;border-bottom:1px solid #fff}.tabulator .tabulator-footer .tabulator-calcs-holder .tabulator-row{background:#f2f2f2!important}.tabulator-row{border-bottom:1px solid #ddd}.tabulator-row .tabulator-cell:last-of-type{border-right:none}.tabulator-row.tabulator-group span{color:#666}.tabulator-print-table .tabulator-print-table-group span{margin-left:10px;color:#666}\\n/*# sourceMappingURL=tabulator_simple.min.css.map */\");\n }, function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n ];\n\n function run_inline_js() {\n if ((root.Bokeh !== undefined) || (force === true)) {\n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n // Cache old bokeh versions\n if (Bokeh != undefined && !reloading) {\n\tvar NewBokeh = root.Bokeh;\n\tif (Bokeh.versions === undefined) {\n\t Bokeh.versions = new Map();\n\t}\n\tif (NewBokeh.version !== Bokeh.version) {\n\t Bokeh.versions.set(NewBokeh.version, NewBokeh)\n\t}\n\troot.Bokeh = Bokeh;\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n }\n root._bokeh_is_initializing = false\n }\n\n function load_or_wait() {\n // Implement a backoff loop that tries to ensure we do not load multiple\n // versions of Bokeh and its dependencies at the same time.\n // In recent versions we use the root._bokeh_is_initializing flag\n // to determine whether there is an ongoing attempt to initialize\n // bokeh, however for backward compatibility we also try to ensure\n // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n // before older versions are fully initialized.\n if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n root._bokeh_is_initializing = false;\n root._bokeh_onload_callbacks = undefined;\n console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n load_or_wait();\n } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n setTimeout(load_or_wait, 100);\n } else {\n Bokeh = root.Bokeh;\n bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n root._bokeh_is_initializing = true\n root._bokeh_onload_callbacks = []\n if (!reloading && (!bokeh_loaded || is_dev)) {\n\troot.Bokeh = undefined;\n }\n load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n });\n }\n }\n // Give older versions of the autoload script a head-start to ensure\n // they initialize before we start loading newer version.\n setTimeout(load_or_wait, 100)\n}(window));", + "application/vnd.holoviews_load.v0+json": "" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n function JupyterCommManager() {\n }\n\n JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n comm_manager.register_target(comm_id, function(comm) {\n comm.on_msg(msg_handler);\n });\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n comm.onMsg = msg_handler;\n });\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n console.log(message)\n var content = {data: message.data, comm_id};\n var buffers = []\n for (var buffer of message.buffers || []) {\n buffers.push(new DataView(buffer))\n }\n var metadata = message.metadata || {};\n var msg = {content, buffers, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n })\n }\n }\n\n JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n if (comm_id in window.PyViz.comms) {\n return window.PyViz.comms[comm_id];\n } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n if (msg_handler) {\n comm.on_msg(msg_handler);\n }\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n comm.open();\n if (msg_handler) {\n comm.onMsg = msg_handler;\n }\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n var comm_promise = google.colab.kernel.comms.open(comm_id)\n comm_promise.then((comm) => {\n window.PyViz.comms[comm_id] = comm;\n if (msg_handler) {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n var content = {data: message.data};\n var metadata = message.metadata || {comm_id};\n var msg = {content, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n }\n }) \n var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n return comm_promise.then((comm) => {\n comm.send(data, metadata, buffers, disposeOnDone);\n });\n };\n var comm = {\n send: sendClosure\n };\n }\n window.PyViz.comms[comm_id] = comm;\n return comm;\n }\n window.PyViz.comm_manager = new JupyterCommManager();\n \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n var div = document.createElement(\"div\");\n var script = document.createElement(\"script\");\n node.appendChild(div);\n node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n var output_area = handle.output_area;\n var output = handle.output;\n if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n return\n }\n var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n if (id !== undefined) {\n var nchildren = toinsert.length;\n var html_node = toinsert[nchildren-1].children[0];\n html_node.innerHTML = output.data[HTML_MIME_TYPE];\n var scripts = [];\n var nodelist = html_node.querySelectorAll(\"script\");\n for (var i in nodelist) {\n if (nodelist.hasOwnProperty(i)) {\n scripts.push(nodelist[i])\n }\n }\n\n scripts.forEach( function (oldScript) {\n var newScript = document.createElement(\"script\");\n var attrs = [];\n var nodemap = oldScript.attributes;\n for (var j in nodemap) {\n if (nodemap.hasOwnProperty(j)) {\n attrs.push(nodemap[j])\n }\n }\n attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n oldScript.parentNode.replaceChild(newScript, oldScript);\n });\n if (JS_MIME_TYPE in output.data) {\n toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n }\n output_area._hv_plot_id = id;\n if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n window.PyViz.plot_index[id] = Bokeh.index[id];\n } else {\n window.PyViz.plot_index[id] = null;\n }\n } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n var bk_div = document.createElement(\"div\");\n bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n var script_attrs = bk_div.children[0].attributes;\n for (var i = 0; i < script_attrs.length; i++) {\n toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n }\n // store reference to server id on output_area\n output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n var id = handle.cell.output_area._hv_plot_id;\n var server_id = handle.cell.output_area._bokeh_server_id;\n if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n if (server_id !== null) {\n comm.send({event_type: 'server_delete', 'id': server_id});\n return;\n } else if (comm !== null) {\n comm.send({event_type: 'delete', 'id': id});\n }\n delete PyViz.plot_index[id];\n if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n var doc = window.Bokeh.index[id].model.document\n doc.clear();\n const i = window.Bokeh.documents.indexOf(doc);\n if (i > -1) {\n window.Bokeh.documents.splice(i, 1);\n }\n }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n delete PyViz.comms[\"hv-extension-comm\"];\n window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n handle_clear_output(event, {cell: {output_area: handle.output_area}})\n handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n function append_mime(data, metadata, element) {\n // create a DOM node to render to\n var toinsert = this.create_output_subarea(\n metadata,\n CLASS_NAME,\n EXEC_MIME_TYPE\n );\n this.keyboard_manager.register_events(toinsert);\n // Render to node\n var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n render(props, toinsert[0]);\n element.append(toinsert);\n return toinsert\n }\n\n events.on('output_added.OutputArea', handle_add_output);\n events.on('output_updated.OutputArea', handle_update_output);\n events.on('clear_output.CodeCell', handle_clear_output);\n events.on('delete.Cell', handle_clear_output);\n events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n safe: true,\n index: 0\n });\n}\n\nif (window.Jupyter !== undefined) {\n try {\n var events = require('base/js/events');\n var OutputArea = require('notebook/js/outputarea').OutputArea;\n if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\n }\n } catch(err) {\n }\n}\n", + "application/vnd.holoviews_load.v0+json": "" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.holoviews_exec.v0+json": "", + "text/html": [ + "
\n", + "
\n", + "
\n", + "" + ] + }, + "metadata": { + "application/vnd.holoviews_exec.v0+json": { + "id": "ef90f212-6a52-4dc3-8d87-f3b72292670f" + } + }, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": "(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n var py_version = '3.1.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n var is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1;\n var reloading = true;\n var Bokeh = root.Bokeh;\n var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n\n if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n run_callbacks();\n return null;\n }\n if (!reloading) {\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n }\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n window._bokeh_on_load = on_load\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n var skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {'tabulator': 'https://cdn.jsdelivr.net/npm/tabulator-tables@5.5.0/dist/js/tabulator', 'moment': 'https://cdn.jsdelivr.net/npm/luxon/build/global/luxon.min', 'mathjax': '//cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS_HTML', 'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'mathjax': {'exports': 'MathJax'}, 'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n require([\"tabulator\"], function(Tabulator) {\n\twindow.Tabulator = Tabulator\n\ton_load()\n })\n require([\"moment\"], function(moment) {\n\twindow.moment = moment\n\ton_load()\n })\n require([\"mathjax\"], function() {\n\ton_load()\n })\n require([\"jspanel\"], function(jsPanel) {\n\twindow.jsPanel = jsPanel\n\ton_load()\n })\n require([\"jspanel-modal\"], function() {\n\ton_load()\n })\n require([\"jspanel-tooltip\"], function() {\n\ton_load()\n })\n require([\"jspanel-hint\"], function() {\n\ton_load()\n })\n require([\"jspanel-layout\"], function() {\n\ton_load()\n })\n require([\"jspanel-contextmenu\"], function() {\n\ton_load()\n })\n require([\"jspanel-dock\"], function() {\n\ton_load()\n })\n require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n })\n require([\"notyf\"], function() {\n\ton_load()\n })\n root._bokeh_is_loading = css_urls.length + 12;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n }\n\n var existing_stylesheets = []\n var links = document.getElementsByTagName('link')\n for (var i = 0; i < links.length; i++) {\n var link = links[i]\n if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n }\n }\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } if (((window['Tabulator'] !== undefined) && (!(window['Tabulator'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/datatabulator/tabulator-tables@5.5.0/dist/js/tabulator.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['moment'] !== undefined) && (!(window['moment'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/datatabulator/luxon/build/global/luxon.min.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['MathJax'] !== undefined) && (!(window['MathJax'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-MML-AM_CHTML'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } var existing_scripts = []\n var scripts = document.getElementsByTagName('script')\n for (var i = 0; i < scripts.length; i++) {\n var script = scripts[i]\n if (script.src != null) {\n\texisting_scripts.push(script.src)\n }\n }\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (var i = 0; i < js_modules.length; i++) {\n var url = js_modules[i];\n if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (const name in js_exports) {\n var url = js_exports[name];\n if (skip.indexOf(url) >= 0 || root[name] != null) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onerror = on_error;\n element.async = false;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n element.textContent = `\n import ${name} from \"${url}\"\n window.${name} = ${name}\n window._bokeh_on_load()\n `\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n var js_urls = [\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-MML-AM_CHTML\", \"https://cdn.holoviz.org/panel/1.2.3/dist/bundled/datatabulator/tabulator-tables@5.5.0/dist/js/tabulator.js\", \"https://cdn.holoviz.org/panel/1.2.3/dist/bundled/datatabulator/luxon/build/global/luxon.min.js\"];\n var js_modules = [];\n var js_exports = {};\n var css_urls = [\"https://cdn.holoviz.org/panel/1.2.3/dist/bundled/datatabulator/tabulator-tables@5.5.0/dist/css/tabulator_simple.min.css\"];\n var inline_js = [ function(Bokeh) {\n inject_raw_css(\".tabulator{position:relative;border:1px solid #999;font-size:14px;text-align:left;overflow:hidden;-webkit-transform:translateZ(0);-moz-transform:translateZ(0);-ms-transform:translateZ(0);-o-transform:translateZ(0);transform:translateZ(0)}.tabulator[tabulator-layout=fitDataFill] .tabulator-tableholder .tabulator-table{min-width:100%}.tabulator[tabulator-layout=fitDataTable]{display:inline-block}.tabulator.tabulator-block-select{user-select:none}.tabulator .tabulator-header{position:relative;box-sizing:border-box;width:100%;border-bottom:1px solid #999;background-color:#fff;color:#555;font-weight:700;white-space:nowrap;overflow:hidden;-moz-user-select:none;-khtml-user-select:none;-webkit-user-select:none;-o-user-select:none}.tabulator .tabulator-header.tabulator-header-hidden{display:none}.tabulator .tabulator-header .tabulator-header-contents{position:relative;overflow:hidden}.tabulator .tabulator-header .tabulator-header-contents .tabulator-headers{display:inline-block}.tabulator .tabulator-header .tabulator-col{display:inline-flex;position:relative;box-sizing:border-box;flex-direction:column;justify-content:flex-start;border-right:1px solid #ddd;background:#fff;text-align:left;vertical-align:bottom;overflow:hidden}.tabulator .tabulator-header .tabulator-col.tabulator-moving{position:absolute;border:1px solid #999;background:#e6e6e6;pointer-events:none}.tabulator .tabulator-header .tabulator-col .tabulator-col-content{box-sizing:border-box;position:relative;padding:4px}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-header-popup-button{padding:0 8px}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-header-popup-button:hover{cursor:pointer;opacity:.6}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-title-holder{position:relative}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-title{box-sizing:border-box;width:100%;white-space:nowrap;overflow:hidden;text-overflow:ellipsis;vertical-align:bottom}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-title.tabulator-col-title-wrap{white-space:normal;text-overflow:clip}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-title .tabulator-title-editor{box-sizing:border-box;width:100%;border:1px solid #999;padding:1px;background:#fff}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-title .tabulator-header-popup-button+.tabulator-title-editor{width:calc(100% - 22px)}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-sorter{display:flex;align-items:center;position:absolute;top:0;bottom:0;right:4px}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-sorter .tabulator-arrow{width:0;height:0;border-left:6px solid transparent;border-right:6px solid transparent;border-bottom:6px solid #bbb}.tabulator .tabulator-header .tabulator-col.tabulator-col-group .tabulator-col-group-cols{position:relative;display:flex;border-top:1px solid #ddd;overflow:hidden;margin-right:-1px}.tabulator .tabulator-header .tabulator-col .tabulator-header-filter{position:relative;box-sizing:border-box;margin-top:2px;width:100%;text-align:center}.tabulator .tabulator-header .tabulator-col .tabulator-header-filter textarea{height:auto!important}.tabulator .tabulator-header .tabulator-col .tabulator-header-filter svg{margin-top:3px}.tabulator .tabulator-header .tabulator-col .tabulator-header-filter input::-ms-clear{width:0;height:0}.tabulator .tabulator-header .tabulator-col.tabulator-sortable .tabulator-col-title{padding-right:25px}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-header .tabulator-col.tabulator-sortable.tabulator-col-sorter-element:hover{cursor:pointer;background-color:#e6e6e6}}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=none] .tabulator-col-content .tabulator-col-sorter{color:#bbb}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=none] .tabulator-col-content .tabulator-col-sorter.tabulator-col-sorter-element .tabulator-arrow:hover{cursor:pointer;border-bottom:6px solid #555}}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=none] .tabulator-col-content .tabulator-col-sorter .tabulator-arrow{border-top:none;border-bottom:6px solid #bbb}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=ascending] .tabulator-col-content .tabulator-col-sorter{color:#666}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=ascending] .tabulator-col-content .tabulator-col-sorter.tabulator-col-sorter-element .tabulator-arrow:hover{cursor:pointer;border-bottom:6px solid #555}}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=ascending] .tabulator-col-content .tabulator-col-sorter .tabulator-arrow{border-top:none;border-bottom:6px solid #666}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=descending] .tabulator-col-content .tabulator-col-sorter{color:#666}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=descending] .tabulator-col-content .tabulator-col-sorter.tabulator-col-sorter-element .tabulator-arrow:hover{cursor:pointer;border-top:6px solid #555}}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=descending] .tabulator-col-content .tabulator-col-sorter .tabulator-arrow{border-bottom:none;border-top:6px solid #666;color:#666}.tabulator .tabulator-header .tabulator-col.tabulator-col-vertical .tabulator-col-content .tabulator-col-title{writing-mode:vertical-rl;text-orientation:mixed;display:flex;align-items:center;justify-content:center}.tabulator .tabulator-header .tabulator-col.tabulator-col-vertical.tabulator-col-vertical-flip .tabulator-col-title{transform:rotate(180deg)}.tabulator .tabulator-header .tabulator-col.tabulator-col-vertical.tabulator-sortable .tabulator-col-title{padding-right:0;padding-top:20px}.tabulator .tabulator-header .tabulator-col.tabulator-col-vertical.tabulator-sortable.tabulator-col-vertical-flip .tabulator-col-title{padding-right:0;padding-bottom:20px}.tabulator .tabulator-header .tabulator-col.tabulator-col-vertical.tabulator-sortable .tabulator-col-sorter{justify-content:center;left:0;right:0;top:4px;bottom:auto}.tabulator .tabulator-header .tabulator-frozen{position:sticky;left:0;z-index:10}.tabulator .tabulator-header .tabulator-frozen.tabulator-frozen-left{border-right:2px solid #ddd}.tabulator .tabulator-header .tabulator-frozen.tabulator-frozen-right{border-left:2px solid #ddd}.tabulator .tabulator-header .tabulator-calcs-holder{box-sizing:border-box;background:#fff!important;border-top:1px solid #ddd;border-bottom:1px solid #ddd}.tabulator .tabulator-header .tabulator-calcs-holder .tabulator-row{background:#fff!important}.tabulator .tabulator-header .tabulator-calcs-holder .tabulator-row .tabulator-col-resize-handle,.tabulator .tabulator-header .tabulator-frozen-rows-holder:empty{display:none}.tabulator .tabulator-tableholder{position:relative;width:100%;white-space:nowrap;overflow:auto;-webkit-overflow-scrolling:touch}.tabulator .tabulator-tableholder:focus{outline:none}.tabulator .tabulator-tableholder .tabulator-placeholder{box-sizing:border-box;display:flex;align-items:center;justify-content:center;width:100%}.tabulator .tabulator-tableholder .tabulator-placeholder[tabulator-render-mode=virtual]{min-height:100%;min-width:100%}.tabulator .tabulator-tableholder .tabulator-placeholder .tabulator-placeholder-contents{display:inline-block;text-align:center;padding:10px;color:#ccc;font-weight:700;font-size:20px;white-space:normal}.tabulator .tabulator-tableholder .tabulator-table{position:relative;display:inline-block;background-color:#fff;white-space:nowrap;overflow:visible;color:#333}.tabulator .tabulator-tableholder .tabulator-table .tabulator-row.tabulator-calcs{font-weight:700;background:#f2f2f2!important}.tabulator .tabulator-tableholder .tabulator-table .tabulator-row.tabulator-calcs.tabulator-calcs-top{border-bottom:2px solid #ddd}.tabulator .tabulator-tableholder .tabulator-table .tabulator-row.tabulator-calcs.tabulator-calcs-bottom{border-top:2px solid #ddd}.tabulator .tabulator-footer{border-top:1px solid #999;background-color:#fff;color:#555;font-weight:700;white-space:nowrap;user-select:none;-moz-user-select:none;-khtml-user-select:none;-webkit-user-select:none;-o-user-select:none}.tabulator .tabulator-footer .tabulator-footer-contents{display:flex;flex-direction:row;align-items:center;justify-content:space-between;padding:5px 10px}.tabulator .tabulator-footer .tabulator-footer-contents:empty{display:none}.tabulator .tabulator-footer .tabulator-calcs-holder{box-sizing:border-box;width:100%;text-align:left;background:#fff!important;border-bottom:1px solid #ddd;border-top:1px solid #ddd;overflow:hidden}.tabulator .tabulator-footer .tabulator-calcs-holder .tabulator-row{display:inline-block;background:#fff!important}.tabulator .tabulator-footer .tabulator-calcs-holder .tabulator-row .tabulator-col-resize-handle{display:none}.tabulator .tabulator-footer .tabulator-calcs-holder:only-child{margin-bottom:-5px;border-bottom:none}.tabulator .tabulator-footer>*+.tabulator-page-counter{margin-left:10px}.tabulator .tabulator-footer .tabulator-page-counter{font-weight:400}.tabulator .tabulator-footer .tabulator-paginator{flex:1;text-align:right;color:#555;font-family:inherit;font-weight:inherit;font-size:inherit}.tabulator .tabulator-footer .tabulator-page-size{display:inline-block;margin:0 5px;padding:2px 5px;border:1px solid #aaa;border-radius:3px}.tabulator .tabulator-footer .tabulator-pages{margin:0 7px}.tabulator .tabulator-footer .tabulator-page{display:inline-block;margin:0 2px;padding:2px 5px;border:1px solid #aaa;border-radius:3px;background:hsla(0,0%,100%,.2)}.tabulator .tabulator-footer .tabulator-page.active{color:#d00}.tabulator .tabulator-footer .tabulator-page:disabled{opacity:.5}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-footer .tabulator-page:not(.disabled):hover{cursor:pointer;background:rgba(0,0,0,.2);color:#fff}}.tabulator .tabulator-col-resize-handle{position:relative;display:inline-block;width:6px;margin-left:-3px;margin-right:-3px;z-index:10;vertical-align:middle}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-col-resize-handle:hover{cursor:ew-resize}}.tabulator .tabulator-col-resize-handle:last-of-type{width:3px;margin-right:0}.tabulator .tabulator-alert{position:absolute;display:flex;align-items:center;top:0;left:0;z-index:100;height:100%;width:100%;background:rgba(0,0,0,.4);text-align:center}.tabulator .tabulator-alert .tabulator-alert-msg{display:inline-block;margin:0 auto;padding:10px 20px;border-radius:10px;background:#fff;font-weight:700;font-size:16px}.tabulator .tabulator-alert .tabulator-alert-msg.tabulator-alert-state-msg{border:4px solid #333;color:#000}.tabulator .tabulator-alert .tabulator-alert-msg.tabulator-alert-state-error{border:4px solid #d00;color:#590000}.tabulator-row{position:relative;box-sizing:border-box;min-height:22px}.tabulator-row,.tabulator-row.tabulator-row-even{background-color:#fff}@media (hover:hover) and (pointer:fine){.tabulator-row.tabulator-selectable:hover{background-color:#bbb;cursor:pointer}}.tabulator-row.tabulator-selected{background-color:#9abcea}@media (hover:hover) and (pointer:fine){.tabulator-row.tabulator-selected:hover{background-color:#769bcc;cursor:pointer}}.tabulator-row.tabulator-row-moving{border:1px solid #000;background:#fff}.tabulator-row.tabulator-moving{position:absolute;border-top:1px solid #ddd;border-bottom:1px solid #ddd;pointer-events:none;z-index:15}.tabulator-row .tabulator-row-resize-handle{position:absolute;right:0;bottom:0;left:0;height:5px}.tabulator-row .tabulator-row-resize-handle.prev{top:0;bottom:auto}@media (hover:hover) and (pointer:fine){.tabulator-row .tabulator-row-resize-handle:hover{cursor:ns-resize}}.tabulator-row .tabulator-responsive-collapse{box-sizing:border-box;padding:5px;border-top:1px solid #ddd;border-bottom:1px solid #ddd}.tabulator-row .tabulator-responsive-collapse:empty{display:none}.tabulator-row .tabulator-responsive-collapse table{font-size:14px}.tabulator-row .tabulator-responsive-collapse table tr td{position:relative}.tabulator-row .tabulator-responsive-collapse table tr td:first-of-type{padding-right:10px}.tabulator-row .tabulator-cell{display:inline-block;position:relative;box-sizing:border-box;padding:4px;border-right:1px solid #ddd;vertical-align:middle;white-space:nowrap;overflow:hidden;text-overflow:ellipsis}.tabulator-row .tabulator-cell.tabulator-frozen{display:inline-block;position:sticky;left:0;background-color:inherit;z-index:10}.tabulator-row .tabulator-cell.tabulator-frozen.tabulator-frozen-left{border-right:2px solid #ddd}.tabulator-row .tabulator-cell.tabulator-frozen.tabulator-frozen-right{border-left:2px solid #ddd}.tabulator-row .tabulator-cell.tabulator-editing{border:1px solid #1d68cd;outline:none;padding:0}.tabulator-row .tabulator-cell.tabulator-editing input,.tabulator-row .tabulator-cell.tabulator-editing select{border:1px;background:transparent;outline:none}.tabulator-row .tabulator-cell.tabulator-validation-fail{border:1px solid #d00}.tabulator-row .tabulator-cell.tabulator-validation-fail input,.tabulator-row .tabulator-cell.tabulator-validation-fail select{border:1px;background:transparent;color:#d00}.tabulator-row .tabulator-cell.tabulator-row-handle{display:inline-flex;align-items:center;justify-content:center;-moz-user-select:none;-khtml-user-select:none;-webkit-user-select:none;-o-user-select:none}.tabulator-row .tabulator-cell.tabulator-row-handle .tabulator-row-handle-box{width:80%}.tabulator-row .tabulator-cell.tabulator-row-handle .tabulator-row-handle-box .tabulator-row-handle-bar{width:100%;height:3px;margin-top:2px;background:#666}.tabulator-row .tabulator-cell .tabulator-data-tree-branch{display:inline-block;vertical-align:middle;height:9px;width:7px;margin-top:-9px;margin-right:5px;border-bottom-left-radius:1px;border-left:2px solid #ddd;border-bottom:2px solid #ddd}.tabulator-row .tabulator-cell .tabulator-data-tree-control{display:inline-flex;justify-content:center;align-items:center;vertical-align:middle;height:11px;width:11px;margin-right:5px;border:1px solid #333;border-radius:2px;background:rgba(0,0,0,.1);overflow:hidden}@media (hover:hover) and (pointer:fine){.tabulator-row .tabulator-cell .tabulator-data-tree-control:hover{cursor:pointer;background:rgba(0,0,0,.2)}}.tabulator-row .tabulator-cell .tabulator-data-tree-control .tabulator-data-tree-control-collapse{display:inline-block;position:relative;height:7px;width:1px;background:transparent}.tabulator-row .tabulator-cell .tabulator-data-tree-control .tabulator-data-tree-control-collapse:after{position:absolute;content:\\\"\\\";left:-3px;top:3px;height:1px;width:7px;background:#333}.tabulator-row .tabulator-cell .tabulator-data-tree-control .tabulator-data-tree-control-expand{display:inline-block;position:relative;height:7px;width:1px;background:#333}.tabulator-row .tabulator-cell .tabulator-data-tree-control .tabulator-data-tree-control-expand:after{position:absolute;content:\\\"\\\";left:-3px;top:3px;height:1px;width:7px;background:#333}.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle{display:inline-flex;align-items:center;justify-content:center;-moz-user-select:none;-khtml-user-select:none;-webkit-user-select:none;-o-user-select:none;height:15px;width:15px;border-radius:20px;background:#666;color:#fff;font-weight:700;font-size:1.1em}@media (hover:hover) and (pointer:fine){.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle:hover{opacity:.7;cursor:pointer}}.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle.open .tabulator-responsive-collapse-toggle-close{display:initial}.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle.open .tabulator-responsive-collapse-toggle-open{display:none}.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle svg{stroke:#fff}.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle .tabulator-responsive-collapse-toggle-close{display:none}.tabulator-row .tabulator-cell .tabulator-traffic-light{display:inline-block;height:14px;width:14px;border-radius:14px}.tabulator-row.tabulator-group{box-sizing:border-box;border-bottom:1px solid #999;border-right:1px solid #ddd;border-top:1px solid #999;padding:5px 5px 5px 10px;background:#ccc;font-weight:700;min-width:100%}@media (hover:hover) and (pointer:fine){.tabulator-row.tabulator-group:hover{cursor:pointer;background-color:rgba(0,0,0,.1)}}.tabulator-row.tabulator-group.tabulator-group-visible .tabulator-arrow{margin-right:10px;border-left:6px solid transparent;border-right:6px solid transparent;border-top:6px solid #666;border-bottom:0}.tabulator-row.tabulator-group.tabulator-group-level-1{padding-left:30px}.tabulator-row.tabulator-group.tabulator-group-level-2{padding-left:50px}.tabulator-row.tabulator-group.tabulator-group-level-3{padding-left:70px}.tabulator-row.tabulator-group.tabulator-group-level-4{padding-left:90px}.tabulator-row.tabulator-group.tabulator-group-level-5{padding-left:110px}.tabulator-row.tabulator-group .tabulator-group-toggle{display:inline-block}.tabulator-row.tabulator-group .tabulator-arrow{display:inline-block;width:0;height:0;margin-right:16px;border-top:6px solid transparent;border-bottom:6px solid transparent;border-right:0;border-left:6px solid #666;vertical-align:middle}.tabulator-row.tabulator-group span{margin-left:10px;color:#d00}.tabulator-popup-container{position:absolute;display:inline-block;box-sizing:border-box;background:#fff;border:1px solid #ddd;box-shadow:0 0 5px 0 rgba(0,0,0,.2);font-size:14px;overflow-y:auto;-webkit-overflow-scrolling:touch;z-index:10000}.tabulator-popup{padding:5px;border-radius:3px}.tabulator-tooltip{max-width:Min(500px,100%);padding:3px 5px;border-radius:2px;box-shadow:none;font-size:12px;pointer-events:none}.tabulator-menu .tabulator-menu-item{position:relative;box-sizing:border-box;padding:5px 10px;user-select:none}.tabulator-menu .tabulator-menu-item.tabulator-menu-item-disabled{opacity:.5}@media (hover:hover) and (pointer:fine){.tabulator-menu .tabulator-menu-item:not(.tabulator-menu-item-disabled):hover{cursor:pointer;background:#fff}}.tabulator-menu .tabulator-menu-item.tabulator-menu-item-submenu{padding-right:25px}.tabulator-menu .tabulator-menu-item.tabulator-menu-item-submenu:after{display:inline-block;position:absolute;top:calc(5px + .4em);right:10px;height:7px;width:7px;content:\\\"\\\";border-color:#ddd;border-style:solid;border-width:1px 1px 0 0;vertical-align:top;transform:rotate(45deg)}.tabulator-menu .tabulator-menu-separator{border-top:1px solid #ddd}.tabulator-edit-list{max-height:200px;font-size:14px;overflow-y:auto;-webkit-overflow-scrolling:touch}.tabulator-edit-list .tabulator-edit-list-item{padding:4px;color:#333;outline:none}.tabulator-edit-list .tabulator-edit-list-item.active{color:#fff;background:#1d68cd}.tabulator-edit-list .tabulator-edit-list-item.active.focused{outline:1px solid hsla(0,0%,100%,.5)}.tabulator-edit-list .tabulator-edit-list-item.focused{outline:1px solid #1d68cd}@media (hover:hover) and (pointer:fine){.tabulator-edit-list .tabulator-edit-list-item:hover{cursor:pointer;color:#fff;background:#1d68cd}}.tabulator-edit-list .tabulator-edit-list-placeholder{padding:4px;color:#333;text-align:center}.tabulator-edit-list .tabulator-edit-list-group{border-bottom:1px solid #ddd;padding:6px 4px 4px;color:#333;font-weight:700}.tabulator-edit-list .tabulator-edit-list-group.tabulator-edit-list-group-level-2,.tabulator-edit-list .tabulator-edit-list-item.tabulator-edit-list-group-level-2{padding-left:12px}.tabulator-edit-list .tabulator-edit-list-group.tabulator-edit-list-group-level-3,.tabulator-edit-list .tabulator-edit-list-item.tabulator-edit-list-group-level-3{padding-left:20px}.tabulator-edit-list .tabulator-edit-list-group.tabulator-edit-list-group-level-4,.tabulator-edit-list .tabulator-edit-list-item.tabulator-edit-list-group-level-4{padding-left:28px}.tabulator-edit-list .tabulator-edit-list-group.tabulator-edit-list-group-level-5,.tabulator-edit-list .tabulator-edit-list-item.tabulator-edit-list-group-level-5{padding-left:36px}.tabulator.tabulator-ltr{direction:ltr}.tabulator.tabulator-rtl{text-align:initial;direction:rtl}.tabulator.tabulator-rtl .tabulator-header .tabulator-col{text-align:initial;border-left:1px solid #ddd;border-right:initial}.tabulator.tabulator-rtl .tabulator-header .tabulator-col.tabulator-col-group .tabulator-col-group-cols{margin-right:0;margin-left:-1px}.tabulator.tabulator-rtl .tabulator-header .tabulator-col.tabulator-sortable .tabulator-col-title{padding-right:0;padding-left:25px}.tabulator.tabulator-rtl .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-sorter{left:8px;right:auto}.tabulator.tabulator-rtl .tabulator-row .tabulator-cell{border-right:initial;border-left:1px solid #ddd}.tabulator.tabulator-rtl .tabulator-row .tabulator-cell .tabulator-data-tree-branch{margin-right:0;margin-left:5px;border-bottom-left-radius:0;border-bottom-right-radius:1px;border-left:initial;border-right:2px solid #ddd}.tabulator.tabulator-rtl .tabulator-row .tabulator-cell .tabulator-data-tree-control{margin-right:0;margin-left:5px}.tabulator.tabulator-rtl .tabulator-row .tabulator-cell.tabulator-frozen.tabulator-frozen-left{border-left:2px solid #ddd}.tabulator.tabulator-rtl .tabulator-row .tabulator-cell.tabulator-frozen.tabulator-frozen-right{border-right:2px solid #ddd}.tabulator.tabulator-rtl .tabulator-row .tabulator-col-resize-handle:last-of-type{width:3px;margin-left:0;margin-right:-3px}.tabulator.tabulator-rtl .tabulator-footer .tabulator-calcs-holder{text-align:initial}.tabulator-print-fullscreen{position:absolute;top:0;bottom:0;left:0;right:0;z-index:10000}body.tabulator-print-fullscreen-hide>:not(.tabulator-print-fullscreen){display:none!important}.tabulator-print-table{border-collapse:collapse}.tabulator-print-table .tabulator-data-tree-branch{display:inline-block;vertical-align:middle;height:9px;width:7px;margin-top:-9px;margin-right:5px;border-bottom-left-radius:1px;border-left:2px solid #ddd;border-bottom:2px solid #ddd}.tabulator-print-table .tabulator-print-table-group{box-sizing:border-box;border-bottom:1px solid #999;border-right:1px solid #ddd;border-top:1px solid #999;padding:5px 5px 5px 10px;background:#ccc;font-weight:700;min-width:100%}@media (hover:hover) and (pointer:fine){.tabulator-print-table .tabulator-print-table-group:hover{cursor:pointer;background-color:rgba(0,0,0,.1)}}.tabulator-print-table .tabulator-print-table-group.tabulator-group-visible .tabulator-arrow{margin-right:10px;border-left:6px solid transparent;border-right:6px solid transparent;border-top:6px solid #666;border-bottom:0}.tabulator-print-table .tabulator-print-table-group.tabulator-group-level-1 td{padding-left:30px!important}.tabulator-print-table .tabulator-print-table-group.tabulator-group-level-2 td{padding-left:50px!important}.tabulator-print-table .tabulator-print-table-group.tabulator-group-level-3 td{padding-left:70px!important}.tabulator-print-table .tabulator-print-table-group.tabulator-group-level-4 td{padding-left:90px!important}.tabulator-print-table .tabulator-print-table-group.tabulator-group-level-5 td{padding-left:110px!important}.tabulator-print-table .tabulator-print-table-group .tabulator-group-toggle{display:inline-block}.tabulator-print-table .tabulator-print-table-group .tabulator-arrow{display:inline-block;width:0;height:0;margin-right:16px;border-top:6px solid transparent;border-bottom:6px solid transparent;border-right:0;border-left:6px solid #666;vertical-align:middle}.tabulator-print-table .tabulator-print-table-group span{color:#d00}.tabulator-print-table .tabulator-data-tree-control{display:inline-flex;justify-content:center;align-items:center;vertical-align:middle;height:11px;width:11px;margin-right:5px;border:1px solid #333;border-radius:2px;background:rgba(0,0,0,.1);overflow:hidden}@media (hover:hover) and (pointer:fine){.tabulator-print-table .tabulator-data-tree-control:hover{cursor:pointer;background:rgba(0,0,0,.2)}}.tabulator-print-table .tabulator-data-tree-control .tabulator-data-tree-control-collapse{display:inline-block;position:relative;height:7px;width:1px;background:transparent}.tabulator-print-table .tabulator-data-tree-control .tabulator-data-tree-control-collapse:after{position:absolute;content:\\\"\\\";left:-3px;top:3px;height:1px;width:7px;background:#333}.tabulator-print-table .tabulator-data-tree-control .tabulator-data-tree-control-expand{display:inline-block;position:relative;height:7px;width:1px;background:#333}.tabulator-print-table .tabulator-data-tree-control .tabulator-data-tree-control-expand:after{position:absolute;content:\\\"\\\";left:-3px;top:3px;height:1px;width:7px;background:#333}.tabulator{border:none;background-color:#fff}.tabulator .tabulator-header .tabulator-calcs-holder{background:#f2f2f2!important;border-bottom:1px solid #999}.tabulator .tabulator-header .tabulator-calcs-holder .tabulator-row{background:#f2f2f2!important}.tabulator .tabulator-tableholder .tabulator-placeholder span{color:#000}.tabulator .tabulator-footer .tabulator-calcs-holder{background:#f2f2f2!important;border-bottom:1px solid #fff}.tabulator .tabulator-footer .tabulator-calcs-holder .tabulator-row{background:#f2f2f2!important}.tabulator-row{border-bottom:1px solid #ddd}.tabulator-row .tabulator-cell:last-of-type{border-right:none}.tabulator-row.tabulator-group span{color:#666}.tabulator-print-table .tabulator-print-table-group span{margin-left:10px;color:#666}\\n/*# sourceMappingURL=tabulator_simple.min.css.map */\");\n }, function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n ];\n\n function run_inline_js() {\n if ((root.Bokeh !== undefined) || (force === true)) {\n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n // Cache old bokeh versions\n if (Bokeh != undefined && !reloading) {\n\tvar NewBokeh = root.Bokeh;\n\tif (Bokeh.versions === undefined) {\n\t Bokeh.versions = new Map();\n\t}\n\tif (NewBokeh.version !== Bokeh.version) {\n\t Bokeh.versions.set(NewBokeh.version, NewBokeh)\n\t}\n\troot.Bokeh = Bokeh;\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n }\n root._bokeh_is_initializing = false\n }\n\n function load_or_wait() {\n // Implement a backoff loop that tries to ensure we do not load multiple\n // versions of Bokeh and its dependencies at the same time.\n // In recent versions we use the root._bokeh_is_initializing flag\n // to determine whether there is an ongoing attempt to initialize\n // bokeh, however for backward compatibility we also try to ensure\n // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n // before older versions are fully initialized.\n if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n root._bokeh_is_initializing = false;\n root._bokeh_onload_callbacks = undefined;\n console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n load_or_wait();\n } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n setTimeout(load_or_wait, 100);\n } else {\n Bokeh = root.Bokeh;\n bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n root._bokeh_is_initializing = true\n root._bokeh_onload_callbacks = []\n if (!reloading && (!bokeh_loaded || is_dev)) {\n\troot.Bokeh = undefined;\n }\n load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n });\n }\n }\n // Give older versions of the autoload script a head-start to ensure\n // they initialize before we start loading newer version.\n setTimeout(load_or_wait, 100)\n}(window));", + "application/vnd.holoviews_load.v0+json": "" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n function JupyterCommManager() {\n }\n\n JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n comm_manager.register_target(comm_id, function(comm) {\n comm.on_msg(msg_handler);\n });\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n comm.onMsg = msg_handler;\n });\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n console.log(message)\n var content = {data: message.data, comm_id};\n var buffers = []\n for (var buffer of message.buffers || []) {\n buffers.push(new DataView(buffer))\n }\n var metadata = message.metadata || {};\n var msg = {content, buffers, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n })\n }\n }\n\n JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n if (comm_id in window.PyViz.comms) {\n return window.PyViz.comms[comm_id];\n } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n if (msg_handler) {\n comm.on_msg(msg_handler);\n }\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n comm.open();\n if (msg_handler) {\n comm.onMsg = msg_handler;\n }\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n var comm_promise = google.colab.kernel.comms.open(comm_id)\n comm_promise.then((comm) => {\n window.PyViz.comms[comm_id] = comm;\n if (msg_handler) {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n var content = {data: message.data};\n var metadata = message.metadata || {comm_id};\n var msg = {content, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n }\n }) \n var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n return comm_promise.then((comm) => {\n comm.send(data, metadata, buffers, disposeOnDone);\n });\n };\n var comm = {\n send: sendClosure\n };\n }\n window.PyViz.comms[comm_id] = comm;\n return comm;\n }\n window.PyViz.comm_manager = new JupyterCommManager();\n \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n var div = document.createElement(\"div\");\n var script = document.createElement(\"script\");\n node.appendChild(div);\n node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n var output_area = handle.output_area;\n var output = handle.output;\n if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n return\n }\n var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n if (id !== undefined) {\n var nchildren = toinsert.length;\n var html_node = toinsert[nchildren-1].children[0];\n html_node.innerHTML = output.data[HTML_MIME_TYPE];\n var scripts = [];\n var nodelist = html_node.querySelectorAll(\"script\");\n for (var i in nodelist) {\n if (nodelist.hasOwnProperty(i)) {\n scripts.push(nodelist[i])\n }\n }\n\n scripts.forEach( function (oldScript) {\n var newScript = document.createElement(\"script\");\n var attrs = [];\n var nodemap = oldScript.attributes;\n for (var j in nodemap) {\n if (nodemap.hasOwnProperty(j)) {\n attrs.push(nodemap[j])\n }\n }\n attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n oldScript.parentNode.replaceChild(newScript, oldScript);\n });\n if (JS_MIME_TYPE in output.data) {\n toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n }\n output_area._hv_plot_id = id;\n if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n window.PyViz.plot_index[id] = Bokeh.index[id];\n } else {\n window.PyViz.plot_index[id] = null;\n }\n } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n var bk_div = document.createElement(\"div\");\n bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n var script_attrs = bk_div.children[0].attributes;\n for (var i = 0; i < script_attrs.length; i++) {\n toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n }\n // store reference to server id on output_area\n output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n var id = handle.cell.output_area._hv_plot_id;\n var server_id = handle.cell.output_area._bokeh_server_id;\n if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n if (server_id !== null) {\n comm.send({event_type: 'server_delete', 'id': server_id});\n return;\n } else if (comm !== null) {\n comm.send({event_type: 'delete', 'id': id});\n }\n delete PyViz.plot_index[id];\n if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n var doc = window.Bokeh.index[id].model.document\n doc.clear();\n const i = window.Bokeh.documents.indexOf(doc);\n if (i > -1) {\n window.Bokeh.documents.splice(i, 1);\n }\n }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n delete PyViz.comms[\"hv-extension-comm\"];\n window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n handle_clear_output(event, {cell: {output_area: handle.output_area}})\n handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n function append_mime(data, metadata, element) {\n // create a DOM node to render to\n var toinsert = this.create_output_subarea(\n metadata,\n CLASS_NAME,\n EXEC_MIME_TYPE\n );\n this.keyboard_manager.register_events(toinsert);\n // Render to node\n var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n render(props, toinsert[0]);\n element.append(toinsert);\n return toinsert\n }\n\n events.on('output_added.OutputArea', handle_add_output);\n events.on('output_updated.OutputArea', handle_update_output);\n events.on('clear_output.CodeCell', handle_clear_output);\n events.on('delete.Cell', handle_clear_output);\n events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n safe: true,\n index: 0\n });\n}\n\nif (window.Jupyter !== undefined) {\n try {\n var events = require('base/js/events');\n var OutputArea = require('notebook/js/outputarea').OutputArea;\n if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\n }\n } catch(err) {\n }\n}\n", + "application/vnd.holoviews_load.v0+json": "" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": "(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n var py_version = '3.1.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n var is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1;\n var reloading = true;\n var Bokeh = root.Bokeh;\n var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n\n if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n run_callbacks();\n return null;\n }\n if (!reloading) {\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n }\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n window._bokeh_on_load = on_load\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n var skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {'tabulator': 'https://cdn.jsdelivr.net/npm/tabulator-tables@5.5.0/dist/js/tabulator', 'moment': 'https://cdn.jsdelivr.net/npm/luxon/build/global/luxon.min', 'mathjax': '//cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS_HTML', 'vega-embed': 'https://cdn.jsdelivr.net/npm/vega-embed@6/build/vega-embed.min', 'vega-lite': 'https://cdn.jsdelivr.net/npm/vega-lite@5/build/vega-lite.min', 'vega': 'https://cdn.jsdelivr.net/npm/vega@5/build/vega.min', 'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'mathjax': {'exports': 'MathJax'}, 'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n require([\"tabulator\"], function(Tabulator) {\n\twindow.Tabulator = Tabulator\n\ton_load()\n })\n require([\"moment\"], function(moment) {\n\twindow.moment = moment\n\ton_load()\n })\n require([\"mathjax\"], function() {\n\ton_load()\n })\n require([\"vega-embed\"], function(vegaEmbed) {\n\twindow.vegaEmbed = vegaEmbed\n\ton_load()\n })\n require([\"vega-lite\"], function(vl) {\n\twindow.vl = vl\n\ton_load()\n })\n require([\"vega\"], function(vega) {\n\twindow.vega = vega\n\ton_load()\n })\n require([\"jspanel\"], function(jsPanel) {\n\twindow.jsPanel = jsPanel\n\ton_load()\n })\n require([\"jspanel-modal\"], function() {\n\ton_load()\n })\n require([\"jspanel-tooltip\"], function() {\n\ton_load()\n })\n require([\"jspanel-hint\"], function() {\n\ton_load()\n })\n require([\"jspanel-layout\"], function() {\n\ton_load()\n })\n require([\"jspanel-contextmenu\"], function() {\n\ton_load()\n })\n require([\"jspanel-dock\"], function() {\n\ton_load()\n })\n require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n })\n require([\"notyf\"], function() {\n\ton_load()\n })\n root._bokeh_is_loading = css_urls.length + 15;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n }\n\n var existing_stylesheets = []\n var links = document.getElementsByTagName('link')\n for (var i = 0; i < links.length; i++) {\n var link = links[i]\n if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n }\n }\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } if (((window['Tabulator'] !== undefined) && (!(window['Tabulator'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/datatabulator/tabulator-tables@5.5.0/dist/js/tabulator.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['moment'] !== undefined) && (!(window['moment'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/datatabulator/luxon/build/global/luxon.min.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['MathJax'] !== undefined) && (!(window['MathJax'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-MML-AM_CHTML'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['vega'] !== undefined) && (!(window['vega'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/vegaplot/vega@5'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['vegaLite'] !== undefined) && (!(window['vegaLite'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/vegaplot/vega-lite@5'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['vegaEmbed'] !== undefined) && (!(window['vegaEmbed'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/vegaplot/vega-embed@6'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } var existing_scripts = []\n var scripts = document.getElementsByTagName('script')\n for (var i = 0; i < scripts.length; i++) {\n var script = scripts[i]\n if (script.src != null) {\n\texisting_scripts.push(script.src)\n }\n }\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (var i = 0; i < js_modules.length; i++) {\n var url = js_modules[i];\n if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (const name in js_exports) {\n var url = js_exports[name];\n if (skip.indexOf(url) >= 0 || root[name] != null) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onerror = on_error;\n element.async = false;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n element.textContent = `\n import ${name} from \"${url}\"\n window.${name} = ${name}\n window._bokeh_on_load()\n `\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n var js_urls = [\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-MML-AM_CHTML\", \"https://cdn.holoviz.org/panel/1.2.3/dist/bundled/datatabulator/tabulator-tables@5.5.0/dist/js/tabulator.js\", \"https://cdn.holoviz.org/panel/1.2.3/dist/bundled/datatabulator/luxon/build/global/luxon.min.js\", \"https://cdn.holoviz.org/panel/1.2.3/dist/bundled/vegaplot/vega@5\", \"https://cdn.holoviz.org/panel/1.2.3/dist/bundled/vegaplot/vega-lite@5\", \"https://cdn.holoviz.org/panel/1.2.3/dist/bundled/vegaplot/vega-embed@6\"];\n var js_modules = [];\n var js_exports = {};\n var css_urls = [\"https://cdn.holoviz.org/panel/1.2.3/dist/bundled/datatabulator/tabulator-tables@5.5.0/dist/css/tabulator_simple.min.css\"];\n var inline_js = [ function(Bokeh) {\n inject_raw_css(\".tabulator{position:relative;border:1px solid #999;font-size:14px;text-align:left;overflow:hidden;-webkit-transform:translateZ(0);-moz-transform:translateZ(0);-ms-transform:translateZ(0);-o-transform:translateZ(0);transform:translateZ(0)}.tabulator[tabulator-layout=fitDataFill] .tabulator-tableholder .tabulator-table{min-width:100%}.tabulator[tabulator-layout=fitDataTable]{display:inline-block}.tabulator.tabulator-block-select{user-select:none}.tabulator .tabulator-header{position:relative;box-sizing:border-box;width:100%;border-bottom:1px solid #999;background-color:#fff;color:#555;font-weight:700;white-space:nowrap;overflow:hidden;-moz-user-select:none;-khtml-user-select:none;-webkit-user-select:none;-o-user-select:none}.tabulator .tabulator-header.tabulator-header-hidden{display:none}.tabulator .tabulator-header .tabulator-header-contents{position:relative;overflow:hidden}.tabulator .tabulator-header .tabulator-header-contents .tabulator-headers{display:inline-block}.tabulator .tabulator-header .tabulator-col{display:inline-flex;position:relative;box-sizing:border-box;flex-direction:column;justify-content:flex-start;border-right:1px solid #ddd;background:#fff;text-align:left;vertical-align:bottom;overflow:hidden}.tabulator .tabulator-header .tabulator-col.tabulator-moving{position:absolute;border:1px solid #999;background:#e6e6e6;pointer-events:none}.tabulator .tabulator-header .tabulator-col .tabulator-col-content{box-sizing:border-box;position:relative;padding:4px}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-header-popup-button{padding:0 8px}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-header-popup-button:hover{cursor:pointer;opacity:.6}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-title-holder{position:relative}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-title{box-sizing:border-box;width:100%;white-space:nowrap;overflow:hidden;text-overflow:ellipsis;vertical-align:bottom}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-title.tabulator-col-title-wrap{white-space:normal;text-overflow:clip}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-title .tabulator-title-editor{box-sizing:border-box;width:100%;border:1px solid #999;padding:1px;background:#fff}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-title .tabulator-header-popup-button+.tabulator-title-editor{width:calc(100% - 22px)}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-sorter{display:flex;align-items:center;position:absolute;top:0;bottom:0;right:4px}.tabulator .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-sorter .tabulator-arrow{width:0;height:0;border-left:6px solid transparent;border-right:6px solid transparent;border-bottom:6px solid #bbb}.tabulator .tabulator-header .tabulator-col.tabulator-col-group .tabulator-col-group-cols{position:relative;display:flex;border-top:1px solid #ddd;overflow:hidden;margin-right:-1px}.tabulator .tabulator-header .tabulator-col .tabulator-header-filter{position:relative;box-sizing:border-box;margin-top:2px;width:100%;text-align:center}.tabulator .tabulator-header .tabulator-col .tabulator-header-filter textarea{height:auto!important}.tabulator .tabulator-header .tabulator-col .tabulator-header-filter svg{margin-top:3px}.tabulator .tabulator-header .tabulator-col .tabulator-header-filter input::-ms-clear{width:0;height:0}.tabulator .tabulator-header .tabulator-col.tabulator-sortable .tabulator-col-title{padding-right:25px}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-header .tabulator-col.tabulator-sortable.tabulator-col-sorter-element:hover{cursor:pointer;background-color:#e6e6e6}}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=none] .tabulator-col-content .tabulator-col-sorter{color:#bbb}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=none] .tabulator-col-content .tabulator-col-sorter.tabulator-col-sorter-element .tabulator-arrow:hover{cursor:pointer;border-bottom:6px solid #555}}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=none] .tabulator-col-content .tabulator-col-sorter .tabulator-arrow{border-top:none;border-bottom:6px solid #bbb}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=ascending] .tabulator-col-content .tabulator-col-sorter{color:#666}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=ascending] .tabulator-col-content .tabulator-col-sorter.tabulator-col-sorter-element .tabulator-arrow:hover{cursor:pointer;border-bottom:6px solid #555}}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=ascending] .tabulator-col-content .tabulator-col-sorter .tabulator-arrow{border-top:none;border-bottom:6px solid #666}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=descending] .tabulator-col-content .tabulator-col-sorter{color:#666}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=descending] .tabulator-col-content .tabulator-col-sorter.tabulator-col-sorter-element .tabulator-arrow:hover{cursor:pointer;border-top:6px solid #555}}.tabulator .tabulator-header .tabulator-col.tabulator-sortable[aria-sort=descending] .tabulator-col-content .tabulator-col-sorter .tabulator-arrow{border-bottom:none;border-top:6px solid #666;color:#666}.tabulator .tabulator-header .tabulator-col.tabulator-col-vertical .tabulator-col-content .tabulator-col-title{writing-mode:vertical-rl;text-orientation:mixed;display:flex;align-items:center;justify-content:center}.tabulator .tabulator-header .tabulator-col.tabulator-col-vertical.tabulator-col-vertical-flip .tabulator-col-title{transform:rotate(180deg)}.tabulator .tabulator-header .tabulator-col.tabulator-col-vertical.tabulator-sortable .tabulator-col-title{padding-right:0;padding-top:20px}.tabulator .tabulator-header .tabulator-col.tabulator-col-vertical.tabulator-sortable.tabulator-col-vertical-flip .tabulator-col-title{padding-right:0;padding-bottom:20px}.tabulator .tabulator-header .tabulator-col.tabulator-col-vertical.tabulator-sortable .tabulator-col-sorter{justify-content:center;left:0;right:0;top:4px;bottom:auto}.tabulator .tabulator-header .tabulator-frozen{position:sticky;left:0;z-index:10}.tabulator .tabulator-header .tabulator-frozen.tabulator-frozen-left{border-right:2px solid #ddd}.tabulator .tabulator-header .tabulator-frozen.tabulator-frozen-right{border-left:2px solid #ddd}.tabulator .tabulator-header .tabulator-calcs-holder{box-sizing:border-box;background:#fff!important;border-top:1px solid #ddd;border-bottom:1px solid #ddd}.tabulator .tabulator-header .tabulator-calcs-holder .tabulator-row{background:#fff!important}.tabulator .tabulator-header .tabulator-calcs-holder .tabulator-row .tabulator-col-resize-handle,.tabulator .tabulator-header .tabulator-frozen-rows-holder:empty{display:none}.tabulator .tabulator-tableholder{position:relative;width:100%;white-space:nowrap;overflow:auto;-webkit-overflow-scrolling:touch}.tabulator .tabulator-tableholder:focus{outline:none}.tabulator .tabulator-tableholder .tabulator-placeholder{box-sizing:border-box;display:flex;align-items:center;justify-content:center;width:100%}.tabulator .tabulator-tableholder .tabulator-placeholder[tabulator-render-mode=virtual]{min-height:100%;min-width:100%}.tabulator .tabulator-tableholder .tabulator-placeholder .tabulator-placeholder-contents{display:inline-block;text-align:center;padding:10px;color:#ccc;font-weight:700;font-size:20px;white-space:normal}.tabulator .tabulator-tableholder .tabulator-table{position:relative;display:inline-block;background-color:#fff;white-space:nowrap;overflow:visible;color:#333}.tabulator .tabulator-tableholder .tabulator-table .tabulator-row.tabulator-calcs{font-weight:700;background:#f2f2f2!important}.tabulator .tabulator-tableholder .tabulator-table .tabulator-row.tabulator-calcs.tabulator-calcs-top{border-bottom:2px solid #ddd}.tabulator .tabulator-tableholder .tabulator-table .tabulator-row.tabulator-calcs.tabulator-calcs-bottom{border-top:2px solid #ddd}.tabulator .tabulator-footer{border-top:1px solid #999;background-color:#fff;color:#555;font-weight:700;white-space:nowrap;user-select:none;-moz-user-select:none;-khtml-user-select:none;-webkit-user-select:none;-o-user-select:none}.tabulator .tabulator-footer .tabulator-footer-contents{display:flex;flex-direction:row;align-items:center;justify-content:space-between;padding:5px 10px}.tabulator .tabulator-footer .tabulator-footer-contents:empty{display:none}.tabulator .tabulator-footer .tabulator-calcs-holder{box-sizing:border-box;width:100%;text-align:left;background:#fff!important;border-bottom:1px solid #ddd;border-top:1px solid #ddd;overflow:hidden}.tabulator .tabulator-footer .tabulator-calcs-holder .tabulator-row{display:inline-block;background:#fff!important}.tabulator .tabulator-footer .tabulator-calcs-holder .tabulator-row .tabulator-col-resize-handle{display:none}.tabulator .tabulator-footer .tabulator-calcs-holder:only-child{margin-bottom:-5px;border-bottom:none}.tabulator .tabulator-footer>*+.tabulator-page-counter{margin-left:10px}.tabulator .tabulator-footer .tabulator-page-counter{font-weight:400}.tabulator .tabulator-footer .tabulator-paginator{flex:1;text-align:right;color:#555;font-family:inherit;font-weight:inherit;font-size:inherit}.tabulator .tabulator-footer .tabulator-page-size{display:inline-block;margin:0 5px;padding:2px 5px;border:1px solid #aaa;border-radius:3px}.tabulator .tabulator-footer .tabulator-pages{margin:0 7px}.tabulator .tabulator-footer .tabulator-page{display:inline-block;margin:0 2px;padding:2px 5px;border:1px solid #aaa;border-radius:3px;background:hsla(0,0%,100%,.2)}.tabulator .tabulator-footer .tabulator-page.active{color:#d00}.tabulator .tabulator-footer .tabulator-page:disabled{opacity:.5}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-footer .tabulator-page:not(.disabled):hover{cursor:pointer;background:rgba(0,0,0,.2);color:#fff}}.tabulator .tabulator-col-resize-handle{position:relative;display:inline-block;width:6px;margin-left:-3px;margin-right:-3px;z-index:10;vertical-align:middle}@media (hover:hover) and (pointer:fine){.tabulator .tabulator-col-resize-handle:hover{cursor:ew-resize}}.tabulator .tabulator-col-resize-handle:last-of-type{width:3px;margin-right:0}.tabulator .tabulator-alert{position:absolute;display:flex;align-items:center;top:0;left:0;z-index:100;height:100%;width:100%;background:rgba(0,0,0,.4);text-align:center}.tabulator .tabulator-alert .tabulator-alert-msg{display:inline-block;margin:0 auto;padding:10px 20px;border-radius:10px;background:#fff;font-weight:700;font-size:16px}.tabulator .tabulator-alert .tabulator-alert-msg.tabulator-alert-state-msg{border:4px solid #333;color:#000}.tabulator .tabulator-alert .tabulator-alert-msg.tabulator-alert-state-error{border:4px solid #d00;color:#590000}.tabulator-row{position:relative;box-sizing:border-box;min-height:22px}.tabulator-row,.tabulator-row.tabulator-row-even{background-color:#fff}@media (hover:hover) and (pointer:fine){.tabulator-row.tabulator-selectable:hover{background-color:#bbb;cursor:pointer}}.tabulator-row.tabulator-selected{background-color:#9abcea}@media (hover:hover) and (pointer:fine){.tabulator-row.tabulator-selected:hover{background-color:#769bcc;cursor:pointer}}.tabulator-row.tabulator-row-moving{border:1px solid #000;background:#fff}.tabulator-row.tabulator-moving{position:absolute;border-top:1px solid #ddd;border-bottom:1px solid #ddd;pointer-events:none;z-index:15}.tabulator-row .tabulator-row-resize-handle{position:absolute;right:0;bottom:0;left:0;height:5px}.tabulator-row .tabulator-row-resize-handle.prev{top:0;bottom:auto}@media (hover:hover) and (pointer:fine){.tabulator-row .tabulator-row-resize-handle:hover{cursor:ns-resize}}.tabulator-row .tabulator-responsive-collapse{box-sizing:border-box;padding:5px;border-top:1px solid #ddd;border-bottom:1px solid #ddd}.tabulator-row .tabulator-responsive-collapse:empty{display:none}.tabulator-row .tabulator-responsive-collapse table{font-size:14px}.tabulator-row .tabulator-responsive-collapse table tr td{position:relative}.tabulator-row .tabulator-responsive-collapse table tr td:first-of-type{padding-right:10px}.tabulator-row .tabulator-cell{display:inline-block;position:relative;box-sizing:border-box;padding:4px;border-right:1px solid #ddd;vertical-align:middle;white-space:nowrap;overflow:hidden;text-overflow:ellipsis}.tabulator-row .tabulator-cell.tabulator-frozen{display:inline-block;position:sticky;left:0;background-color:inherit;z-index:10}.tabulator-row .tabulator-cell.tabulator-frozen.tabulator-frozen-left{border-right:2px solid #ddd}.tabulator-row .tabulator-cell.tabulator-frozen.tabulator-frozen-right{border-left:2px solid #ddd}.tabulator-row .tabulator-cell.tabulator-editing{border:1px solid #1d68cd;outline:none;padding:0}.tabulator-row .tabulator-cell.tabulator-editing input,.tabulator-row .tabulator-cell.tabulator-editing select{border:1px;background:transparent;outline:none}.tabulator-row .tabulator-cell.tabulator-validation-fail{border:1px solid #d00}.tabulator-row .tabulator-cell.tabulator-validation-fail input,.tabulator-row .tabulator-cell.tabulator-validation-fail select{border:1px;background:transparent;color:#d00}.tabulator-row .tabulator-cell.tabulator-row-handle{display:inline-flex;align-items:center;justify-content:center;-moz-user-select:none;-khtml-user-select:none;-webkit-user-select:none;-o-user-select:none}.tabulator-row .tabulator-cell.tabulator-row-handle .tabulator-row-handle-box{width:80%}.tabulator-row .tabulator-cell.tabulator-row-handle .tabulator-row-handle-box .tabulator-row-handle-bar{width:100%;height:3px;margin-top:2px;background:#666}.tabulator-row .tabulator-cell .tabulator-data-tree-branch{display:inline-block;vertical-align:middle;height:9px;width:7px;margin-top:-9px;margin-right:5px;border-bottom-left-radius:1px;border-left:2px solid #ddd;border-bottom:2px solid #ddd}.tabulator-row .tabulator-cell .tabulator-data-tree-control{display:inline-flex;justify-content:center;align-items:center;vertical-align:middle;height:11px;width:11px;margin-right:5px;border:1px solid #333;border-radius:2px;background:rgba(0,0,0,.1);overflow:hidden}@media (hover:hover) and (pointer:fine){.tabulator-row .tabulator-cell .tabulator-data-tree-control:hover{cursor:pointer;background:rgba(0,0,0,.2)}}.tabulator-row .tabulator-cell .tabulator-data-tree-control .tabulator-data-tree-control-collapse{display:inline-block;position:relative;height:7px;width:1px;background:transparent}.tabulator-row .tabulator-cell .tabulator-data-tree-control .tabulator-data-tree-control-collapse:after{position:absolute;content:\\\"\\\";left:-3px;top:3px;height:1px;width:7px;background:#333}.tabulator-row .tabulator-cell .tabulator-data-tree-control .tabulator-data-tree-control-expand{display:inline-block;position:relative;height:7px;width:1px;background:#333}.tabulator-row .tabulator-cell .tabulator-data-tree-control .tabulator-data-tree-control-expand:after{position:absolute;content:\\\"\\\";left:-3px;top:3px;height:1px;width:7px;background:#333}.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle{display:inline-flex;align-items:center;justify-content:center;-moz-user-select:none;-khtml-user-select:none;-webkit-user-select:none;-o-user-select:none;height:15px;width:15px;border-radius:20px;background:#666;color:#fff;font-weight:700;font-size:1.1em}@media (hover:hover) and (pointer:fine){.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle:hover{opacity:.7;cursor:pointer}}.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle.open .tabulator-responsive-collapse-toggle-close{display:initial}.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle.open .tabulator-responsive-collapse-toggle-open{display:none}.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle svg{stroke:#fff}.tabulator-row .tabulator-cell .tabulator-responsive-collapse-toggle .tabulator-responsive-collapse-toggle-close{display:none}.tabulator-row .tabulator-cell .tabulator-traffic-light{display:inline-block;height:14px;width:14px;border-radius:14px}.tabulator-row.tabulator-group{box-sizing:border-box;border-bottom:1px solid #999;border-right:1px solid #ddd;border-top:1px solid #999;padding:5px 5px 5px 10px;background:#ccc;font-weight:700;min-width:100%}@media (hover:hover) and (pointer:fine){.tabulator-row.tabulator-group:hover{cursor:pointer;background-color:rgba(0,0,0,.1)}}.tabulator-row.tabulator-group.tabulator-group-visible .tabulator-arrow{margin-right:10px;border-left:6px solid transparent;border-right:6px solid transparent;border-top:6px solid #666;border-bottom:0}.tabulator-row.tabulator-group.tabulator-group-level-1{padding-left:30px}.tabulator-row.tabulator-group.tabulator-group-level-2{padding-left:50px}.tabulator-row.tabulator-group.tabulator-group-level-3{padding-left:70px}.tabulator-row.tabulator-group.tabulator-group-level-4{padding-left:90px}.tabulator-row.tabulator-group.tabulator-group-level-5{padding-left:110px}.tabulator-row.tabulator-group .tabulator-group-toggle{display:inline-block}.tabulator-row.tabulator-group .tabulator-arrow{display:inline-block;width:0;height:0;margin-right:16px;border-top:6px solid transparent;border-bottom:6px solid transparent;border-right:0;border-left:6px solid #666;vertical-align:middle}.tabulator-row.tabulator-group span{margin-left:10px;color:#d00}.tabulator-popup-container{position:absolute;display:inline-block;box-sizing:border-box;background:#fff;border:1px solid #ddd;box-shadow:0 0 5px 0 rgba(0,0,0,.2);font-size:14px;overflow-y:auto;-webkit-overflow-scrolling:touch;z-index:10000}.tabulator-popup{padding:5px;border-radius:3px}.tabulator-tooltip{max-width:Min(500px,100%);padding:3px 5px;border-radius:2px;box-shadow:none;font-size:12px;pointer-events:none}.tabulator-menu .tabulator-menu-item{position:relative;box-sizing:border-box;padding:5px 10px;user-select:none}.tabulator-menu .tabulator-menu-item.tabulator-menu-item-disabled{opacity:.5}@media (hover:hover) and (pointer:fine){.tabulator-menu .tabulator-menu-item:not(.tabulator-menu-item-disabled):hover{cursor:pointer;background:#fff}}.tabulator-menu .tabulator-menu-item.tabulator-menu-item-submenu{padding-right:25px}.tabulator-menu .tabulator-menu-item.tabulator-menu-item-submenu:after{display:inline-block;position:absolute;top:calc(5px + .4em);right:10px;height:7px;width:7px;content:\\\"\\\";border-color:#ddd;border-style:solid;border-width:1px 1px 0 0;vertical-align:top;transform:rotate(45deg)}.tabulator-menu .tabulator-menu-separator{border-top:1px solid #ddd}.tabulator-edit-list{max-height:200px;font-size:14px;overflow-y:auto;-webkit-overflow-scrolling:touch}.tabulator-edit-list .tabulator-edit-list-item{padding:4px;color:#333;outline:none}.tabulator-edit-list .tabulator-edit-list-item.active{color:#fff;background:#1d68cd}.tabulator-edit-list .tabulator-edit-list-item.active.focused{outline:1px solid hsla(0,0%,100%,.5)}.tabulator-edit-list .tabulator-edit-list-item.focused{outline:1px solid #1d68cd}@media (hover:hover) and (pointer:fine){.tabulator-edit-list .tabulator-edit-list-item:hover{cursor:pointer;color:#fff;background:#1d68cd}}.tabulator-edit-list .tabulator-edit-list-placeholder{padding:4px;color:#333;text-align:center}.tabulator-edit-list .tabulator-edit-list-group{border-bottom:1px solid #ddd;padding:6px 4px 4px;color:#333;font-weight:700}.tabulator-edit-list .tabulator-edit-list-group.tabulator-edit-list-group-level-2,.tabulator-edit-list .tabulator-edit-list-item.tabulator-edit-list-group-level-2{padding-left:12px}.tabulator-edit-list .tabulator-edit-list-group.tabulator-edit-list-group-level-3,.tabulator-edit-list .tabulator-edit-list-item.tabulator-edit-list-group-level-3{padding-left:20px}.tabulator-edit-list .tabulator-edit-list-group.tabulator-edit-list-group-level-4,.tabulator-edit-list .tabulator-edit-list-item.tabulator-edit-list-group-level-4{padding-left:28px}.tabulator-edit-list .tabulator-edit-list-group.tabulator-edit-list-group-level-5,.tabulator-edit-list .tabulator-edit-list-item.tabulator-edit-list-group-level-5{padding-left:36px}.tabulator.tabulator-ltr{direction:ltr}.tabulator.tabulator-rtl{text-align:initial;direction:rtl}.tabulator.tabulator-rtl .tabulator-header .tabulator-col{text-align:initial;border-left:1px solid #ddd;border-right:initial}.tabulator.tabulator-rtl .tabulator-header .tabulator-col.tabulator-col-group .tabulator-col-group-cols{margin-right:0;margin-left:-1px}.tabulator.tabulator-rtl .tabulator-header .tabulator-col.tabulator-sortable .tabulator-col-title{padding-right:0;padding-left:25px}.tabulator.tabulator-rtl .tabulator-header .tabulator-col .tabulator-col-content .tabulator-col-sorter{left:8px;right:auto}.tabulator.tabulator-rtl .tabulator-row .tabulator-cell{border-right:initial;border-left:1px solid #ddd}.tabulator.tabulator-rtl .tabulator-row .tabulator-cell .tabulator-data-tree-branch{margin-right:0;margin-left:5px;border-bottom-left-radius:0;border-bottom-right-radius:1px;border-left:initial;border-right:2px solid #ddd}.tabulator.tabulator-rtl .tabulator-row .tabulator-cell .tabulator-data-tree-control{margin-right:0;margin-left:5px}.tabulator.tabulator-rtl .tabulator-row .tabulator-cell.tabulator-frozen.tabulator-frozen-left{border-left:2px solid #ddd}.tabulator.tabulator-rtl .tabulator-row .tabulator-cell.tabulator-frozen.tabulator-frozen-right{border-right:2px solid #ddd}.tabulator.tabulator-rtl .tabulator-row .tabulator-col-resize-handle:last-of-type{width:3px;margin-left:0;margin-right:-3px}.tabulator.tabulator-rtl .tabulator-footer .tabulator-calcs-holder{text-align:initial}.tabulator-print-fullscreen{position:absolute;top:0;bottom:0;left:0;right:0;z-index:10000}body.tabulator-print-fullscreen-hide>:not(.tabulator-print-fullscreen){display:none!important}.tabulator-print-table{border-collapse:collapse}.tabulator-print-table .tabulator-data-tree-branch{display:inline-block;vertical-align:middle;height:9px;width:7px;margin-top:-9px;margin-right:5px;border-bottom-left-radius:1px;border-left:2px solid #ddd;border-bottom:2px solid #ddd}.tabulator-print-table .tabulator-print-table-group{box-sizing:border-box;border-bottom:1px solid #999;border-right:1px solid #ddd;border-top:1px solid #999;padding:5px 5px 5px 10px;background:#ccc;font-weight:700;min-width:100%}@media (hover:hover) and (pointer:fine){.tabulator-print-table .tabulator-print-table-group:hover{cursor:pointer;background-color:rgba(0,0,0,.1)}}.tabulator-print-table .tabulator-print-table-group.tabulator-group-visible .tabulator-arrow{margin-right:10px;border-left:6px solid transparent;border-right:6px solid transparent;border-top:6px solid #666;border-bottom:0}.tabulator-print-table .tabulator-print-table-group.tabulator-group-level-1 td{padding-left:30px!important}.tabulator-print-table .tabulator-print-table-group.tabulator-group-level-2 td{padding-left:50px!important}.tabulator-print-table .tabulator-print-table-group.tabulator-group-level-3 td{padding-left:70px!important}.tabulator-print-table .tabulator-print-table-group.tabulator-group-level-4 td{padding-left:90px!important}.tabulator-print-table .tabulator-print-table-group.tabulator-group-level-5 td{padding-left:110px!important}.tabulator-print-table .tabulator-print-table-group .tabulator-group-toggle{display:inline-block}.tabulator-print-table .tabulator-print-table-group .tabulator-arrow{display:inline-block;width:0;height:0;margin-right:16px;border-top:6px solid transparent;border-bottom:6px solid transparent;border-right:0;border-left:6px solid #666;vertical-align:middle}.tabulator-print-table .tabulator-print-table-group span{color:#d00}.tabulator-print-table .tabulator-data-tree-control{display:inline-flex;justify-content:center;align-items:center;vertical-align:middle;height:11px;width:11px;margin-right:5px;border:1px solid #333;border-radius:2px;background:rgba(0,0,0,.1);overflow:hidden}@media (hover:hover) and (pointer:fine){.tabulator-print-table .tabulator-data-tree-control:hover{cursor:pointer;background:rgba(0,0,0,.2)}}.tabulator-print-table .tabulator-data-tree-control .tabulator-data-tree-control-collapse{display:inline-block;position:relative;height:7px;width:1px;background:transparent}.tabulator-print-table .tabulator-data-tree-control .tabulator-data-tree-control-collapse:after{position:absolute;content:\\\"\\\";left:-3px;top:3px;height:1px;width:7px;background:#333}.tabulator-print-table .tabulator-data-tree-control .tabulator-data-tree-control-expand{display:inline-block;position:relative;height:7px;width:1px;background:#333}.tabulator-print-table .tabulator-data-tree-control .tabulator-data-tree-control-expand:after{position:absolute;content:\\\"\\\";left:-3px;top:3px;height:1px;width:7px;background:#333}.tabulator{border:none;background-color:#fff}.tabulator .tabulator-header .tabulator-calcs-holder{background:#f2f2f2!important;border-bottom:1px solid #999}.tabulator .tabulator-header .tabulator-calcs-holder .tabulator-row{background:#f2f2f2!important}.tabulator .tabulator-tableholder .tabulator-placeholder span{color:#000}.tabulator .tabulator-footer .tabulator-calcs-holder{background:#f2f2f2!important;border-bottom:1px solid #fff}.tabulator .tabulator-footer .tabulator-calcs-holder .tabulator-row{background:#f2f2f2!important}.tabulator-row{border-bottom:1px solid #ddd}.tabulator-row .tabulator-cell:last-of-type{border-right:none}.tabulator-row.tabulator-group span{color:#666}.tabulator-print-table .tabulator-print-table-group span{margin-left:10px;color:#666}\\n/*# sourceMappingURL=tabulator_simple.min.css.map */\");\n }, function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n ];\n\n function run_inline_js() {\n if ((root.Bokeh !== undefined) || (force === true)) {\n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n // Cache old bokeh versions\n if (Bokeh != undefined && !reloading) {\n\tvar NewBokeh = root.Bokeh;\n\tif (Bokeh.versions === undefined) {\n\t Bokeh.versions = new Map();\n\t}\n\tif (NewBokeh.version !== Bokeh.version) {\n\t Bokeh.versions.set(NewBokeh.version, NewBokeh)\n\t}\n\troot.Bokeh = Bokeh;\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n }\n root._bokeh_is_initializing = false\n }\n\n function load_or_wait() {\n // Implement a backoff loop that tries to ensure we do not load multiple\n // versions of Bokeh and its dependencies at the same time.\n // In recent versions we use the root._bokeh_is_initializing flag\n // to determine whether there is an ongoing attempt to initialize\n // bokeh, however for backward compatibility we also try to ensure\n // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n // before older versions are fully initialized.\n if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n root._bokeh_is_initializing = false;\n root._bokeh_onload_callbacks = undefined;\n console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n load_or_wait();\n } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n setTimeout(load_or_wait, 100);\n } else {\n Bokeh = root.Bokeh;\n bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n root._bokeh_is_initializing = true\n root._bokeh_onload_callbacks = []\n if (!reloading && (!bokeh_loaded || is_dev)) {\n\troot.Bokeh = undefined;\n }\n load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n });\n }\n }\n // Give older versions of the autoload script a head-start to ensure\n // they initialize before we start loading newer version.\n setTimeout(load_or_wait, 100)\n}(window));", + "application/vnd.holoviews_load.v0+json": "" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n function JupyterCommManager() {\n }\n\n JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n comm_manager.register_target(comm_id, function(comm) {\n comm.on_msg(msg_handler);\n });\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n comm.onMsg = msg_handler;\n });\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n console.log(message)\n var content = {data: message.data, comm_id};\n var buffers = []\n for (var buffer of message.buffers || []) {\n buffers.push(new DataView(buffer))\n }\n var metadata = message.metadata || {};\n var msg = {content, buffers, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n })\n }\n }\n\n JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n if (comm_id in window.PyViz.comms) {\n return window.PyViz.comms[comm_id];\n } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n if (msg_handler) {\n comm.on_msg(msg_handler);\n }\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n comm.open();\n if (msg_handler) {\n comm.onMsg = msg_handler;\n }\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n var comm_promise = google.colab.kernel.comms.open(comm_id)\n comm_promise.then((comm) => {\n window.PyViz.comms[comm_id] = comm;\n if (msg_handler) {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n var content = {data: message.data};\n var metadata = message.metadata || {comm_id};\n var msg = {content, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n }\n }) \n var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n return comm_promise.then((comm) => {\n comm.send(data, metadata, buffers, disposeOnDone);\n });\n };\n var comm = {\n send: sendClosure\n };\n }\n window.PyViz.comms[comm_id] = comm;\n return comm;\n }\n window.PyViz.comm_manager = new JupyterCommManager();\n \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n var div = document.createElement(\"div\");\n var script = document.createElement(\"script\");\n node.appendChild(div);\n node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n var output_area = handle.output_area;\n var output = handle.output;\n if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n return\n }\n var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n if (id !== undefined) {\n var nchildren = toinsert.length;\n var html_node = toinsert[nchildren-1].children[0];\n html_node.innerHTML = output.data[HTML_MIME_TYPE];\n var scripts = [];\n var nodelist = html_node.querySelectorAll(\"script\");\n for (var i in nodelist) {\n if (nodelist.hasOwnProperty(i)) {\n scripts.push(nodelist[i])\n }\n }\n\n scripts.forEach( function (oldScript) {\n var newScript = document.createElement(\"script\");\n var attrs = [];\n var nodemap = oldScript.attributes;\n for (var j in nodemap) {\n if (nodemap.hasOwnProperty(j)) {\n attrs.push(nodemap[j])\n }\n }\n attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n oldScript.parentNode.replaceChild(newScript, oldScript);\n });\n if (JS_MIME_TYPE in output.data) {\n toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n }\n output_area._hv_plot_id = id;\n if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n window.PyViz.plot_index[id] = Bokeh.index[id];\n } else {\n window.PyViz.plot_index[id] = null;\n }\n } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n var bk_div = document.createElement(\"div\");\n bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n var script_attrs = bk_div.children[0].attributes;\n for (var i = 0; i < script_attrs.length; i++) {\n toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n }\n // store reference to server id on output_area\n output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n var id = handle.cell.output_area._hv_plot_id;\n var server_id = handle.cell.output_area._bokeh_server_id;\n if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n if (server_id !== null) {\n comm.send({event_type: 'server_delete', 'id': server_id});\n return;\n } else if (comm !== null) {\n comm.send({event_type: 'delete', 'id': id});\n }\n delete PyViz.plot_index[id];\n if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n var doc = window.Bokeh.index[id].model.document\n doc.clear();\n const i = window.Bokeh.documents.indexOf(doc);\n if (i > -1) {\n window.Bokeh.documents.splice(i, 1);\n }\n }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n delete PyViz.comms[\"hv-extension-comm\"];\n window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n handle_clear_output(event, {cell: {output_area: handle.output_area}})\n handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n function append_mime(data, metadata, element) {\n // create a DOM node to render to\n var toinsert = this.create_output_subarea(\n metadata,\n CLASS_NAME,\n EXEC_MIME_TYPE\n );\n this.keyboard_manager.register_events(toinsert);\n // Render to node\n var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n render(props, toinsert[0]);\n element.append(toinsert);\n return toinsert\n }\n\n events.on('output_added.OutputArea', handle_add_output);\n events.on('output_updated.OutputArea', handle_update_output);\n events.on('clear_output.CodeCell', handle_clear_output);\n events.on('delete.Cell', handle_clear_output);\n events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n safe: true,\n index: 0\n });\n}\n\nif (window.Jupyter !== undefined) {\n try {\n var events = require('base/js/events');\n var OutputArea = require('notebook/js/outputarea').OutputArea;\n if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\n }\n } catch(err) {\n }\n}\n", + "application/vnd.holoviews_load.v0+json": "" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import bdikit as bdi\n", + "import pandas as pd\n", + "from bdikit.utils import get_gdc_data\n", + "from pprint import pprint\n", + "\n", + "import flair, torch\n", + "flair.device = torch.device('cpu') " + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
CountryHistologic_Grade_FIGOHistologic_typePath_Stage_Primary_Tumor-pTPath_Stage_Reg_Lymph_Nodes-pNClin_Stage_Dist_Mets-cMPath_Stage_Dist_Mets-pMtumor_Stage-PathologicalFIGO_stageBMIAgeRaceEthnicityGenderTumor_SiteTumor_FocalityTumor_Size_cm
0United StatesFIGO grade 1EndometrioidpT1a (FIGO IA)pN0cM0Staging IncompleteStage IIA38.8864.0WhiteNot-Hispanic or LatinoFemaleAnterior endometriumUnifocal2.9
1United StatesFIGO grade 1EndometrioidpT1a (FIGO IA)pNXcM0Staging IncompleteStage IVIA39.7658.0WhiteNot-Hispanic or LatinoFemalePosterior endometriumUnifocal3.5
2United StatesFIGO grade 2EndometrioidpT1a (FIGO IA)pN0cM0Staging IncompleteStage IIA51.1950.0WhiteNot-Hispanic or LatinoFemaleOther, specifyUnifocal4.5
3NaNNaNCarcinosarcomaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
4United StatesFIGO grade 2EndometrioidpT1a (FIGO IA)pNXcM0No pathologic evidence of distant metastasisStage IIA32.6975.0WhiteNot-Hispanic or LatinoFemaleOther, specifyUnifocal3.5
\n", + "
" + ], + "text/plain": [ + " Country Histologic_Grade_FIGO Histologic_type \\\n", + "0 United States FIGO grade 1 Endometrioid \n", + "1 United States FIGO grade 1 Endometrioid \n", + "2 United States FIGO grade 2 Endometrioid \n", + "3 NaN NaN Carcinosarcoma \n", + "4 United States FIGO grade 2 Endometrioid \n", + "\n", + " Path_Stage_Primary_Tumor-pT Path_Stage_Reg_Lymph_Nodes-pN \\\n", + "0 pT1a (FIGO IA) pN0 \n", + "1 pT1a (FIGO IA) pNX \n", + "2 pT1a (FIGO IA) pN0 \n", + "3 NaN NaN \n", + "4 pT1a (FIGO IA) pNX \n", + "\n", + " Clin_Stage_Dist_Mets-cM Path_Stage_Dist_Mets-pM \\\n", + "0 cM0 Staging Incomplete \n", + "1 cM0 Staging Incomplete \n", + "2 cM0 Staging Incomplete \n", + "3 NaN NaN \n", + "4 cM0 No pathologic evidence of distant metastasis \n", + "\n", + " tumor_Stage-Pathological FIGO_stage BMI Age Race \\\n", + "0 Stage I IA 38.88 64.0 White \n", + "1 Stage IV IA 39.76 58.0 White \n", + "2 Stage I IA 51.19 50.0 White \n", + "3 NaN NaN NaN NaN NaN \n", + "4 Stage I IA 32.69 75.0 White \n", + "\n", + " Ethnicity Gender Tumor_Site Tumor_Focality \\\n", + "0 Not-Hispanic or Latino Female Anterior endometrium Unifocal \n", + "1 Not-Hispanic or Latino Female Posterior endometrium Unifocal \n", + "2 Not-Hispanic or Latino Female Other, specify Unifocal \n", + "3 NaN NaN NaN NaN \n", + "4 Not-Hispanic or Latino Female Other, specify Unifocal \n", + "\n", + " Tumor_Size_cm \n", + "0 2.9 \n", + "1 3.5 \n", + "2 4.5 \n", + "3 NaN \n", + "4 3.5 " + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset = pd.read_csv('./datasets/dou.csv')\n", + "dataset.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Some weights of RobertaModel were not initialized from the model checkpoint at roberta-base and are newly initialized: ['roberta.pooler.dense.bias', 'roberta.pooler.dense.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + " 0%| | 0/17 [00:00\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcetarget
0Countrycountry_of_birth
1Histologic_Grade_FIGOhistologic_progression_type
2Histologic_typedysplasia_type
3Path_Stage_Primary_Tumor-pTuicc_clinical_m
4Path_Stage_Reg_Lymph_Nodes-pNfigo_stage
5Clin_Stage_Dist_Mets-cMinrg_stage
6Path_Stage_Dist_Mets-pMlast_known_disease_status
7tumor_Stage-Pathologicaltumor_grade_category
8FIGO_stagefigo_stage
9BMIhpv_positive_type
10Ageweight
11Racerace
12Ethnicityethnicity
13Gendergender
14Tumor_Sitetumor_shape
15Tumor_Focalitytumor_focality
16Tumor_Size_cmtumor_depth
\n", + "" + ], + "text/plain": [ + " source target\n", + "0 Country country_of_birth\n", + "1 Histologic_Grade_FIGO histologic_progression_type\n", + "2 Histologic_type dysplasia_type\n", + "3 Path_Stage_Primary_Tumor-pT uicc_clinical_m\n", + "4 Path_Stage_Reg_Lymph_Nodes-pN figo_stage\n", + "5 Clin_Stage_Dist_Mets-cM inrg_stage\n", + "6 Path_Stage_Dist_Mets-pM last_known_disease_status\n", + "7 tumor_Stage-Pathological tumor_grade_category\n", + "8 FIGO_stage figo_stage\n", + "9 BMI hpv_positive_type\n", + "10 Age weight\n", + "11 Race race\n", + "12 Ethnicity ethnicity\n", + "13 Gender gender\n", + "14 Tumor_Site tumor_shape\n", + "15 Tumor_Focality tumor_focality\n", + "16 Tumor_Size_cm tumor_depth" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "column_mappings = bdi.match_columns(dataset, target='gdc', method='two_phase')\n", + "column_mappings" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Some weights of RobertaModel were not initialized from the model checkpoint at roberta-base and are newly initialized: ['roberta.pooler.dense.bias', 'roberta.pooler.dense.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "100%|██████████| 1/1 [00:00<00:00, 13.80it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Table features extracted from 1 columns\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 734/734 [00:48<00:00, 15.14it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Table features extracted from 734 columns\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcematchessimilarity
0BMInecrosis_percent0.7141
1BMIrecist_targeted_regions_sum0.7075
2BMIpercent_stromal_cells0.6953
3BMIspindle_cell_percent0.686
4BMIpercent_neutrophil_infiltration0.6063
5BMIfragment_standard_deviation_length0.593
6BMIlongest_dimension0.5782
7BMIintermediate_dimension0.5464
8BMIaverage_base_quality0.5251
9BMIbmi0.5218
\n", + "
" + ], + "text/plain": [ + " source matches similarity\n", + "0 BMI necrosis_percent 0.7141\n", + "1 BMI recist_targeted_regions_sum 0.7075\n", + "2 BMI percent_stromal_cells 0.6953\n", + "3 BMI spindle_cell_percent 0.686\n", + "4 BMI percent_neutrophil_infiltration 0.6063\n", + "5 BMI fragment_standard_deviation_length 0.593\n", + "6 BMI longest_dimension 0.5782\n", + "7 BMI intermediate_dimension 0.5464\n", + "8 BMI average_base_quality 0.5251\n", + "9 BMI bmi 0.5218" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bdi.top_matches(dataset, columns=['BMI'], target='gdc')" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Some weights of RobertaModel were not initialized from the model checkpoint at roberta-base and are newly initialized: ['roberta.pooler.dense.bias', 'roberta.pooler.dense.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "100%|██████████| 1/1 [00:00<00:00, 13.58it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Table features extracted from 1 columns\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 734/734 [00:45<00:00, 15.98it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Table features extracted from 734 columns\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcematchessimilarity
0Ageepithelioid_cell_percent0.6855
1Agefev1_fvc_post_bronch_percent0.6439
2Agefev1_fvc_pre_bronch_percent0.642
3Agepercent_tumor_invasion0.6393
4Agepercent_necrosis0.5937
5Agepercent_tumor_nuclei0.5624
6Agepercent_inflam_infiltration0.5255
7Ageicd_10_code0.5052
8Ageage_at_last_exposure0.4992
9Agepercent_normal_cells0.4867
\n", + "
" + ], + "text/plain": [ + " source matches similarity\n", + "0 Age epithelioid_cell_percent 0.6855\n", + "1 Age fev1_fvc_post_bronch_percent 0.6439\n", + "2 Age fev1_fvc_pre_bronch_percent 0.642\n", + "3 Age percent_tumor_invasion 0.6393\n", + "4 Age percent_necrosis 0.5937\n", + "5 Age percent_tumor_nuclei 0.5624\n", + "6 Age percent_inflam_infiltration 0.5255\n", + "7 Age icd_10_code 0.5052\n", + "8 Age age_at_last_exposure 0.4992\n", + "9 Age percent_normal_cells 0.4867" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bdi.top_matches(dataset, columns=['Age'], target='gdc')" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Some weights of RobertaModel were not initialized from the model checkpoint at roberta-base and are newly initialized: ['roberta.pooler.dense.bias', 'roberta.pooler.dense.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "100%|██████████| 1/1 [00:00<00:00, 13.62it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Table features extracted from 1 columns\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 734/734 [00:45<00:00, 16.17it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Table features extracted from 734 columns\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcematchessimilarity
0Tumor_Size_cmshortest_dimension0.7114
1Tumor_Size_cmsize_extraocular_nodule0.6994
2Tumor_Size_cmtumor_depth_measurement0.6734
3Tumor_Size_cmtumor_width_measurement0.6553
4Tumor_Size_cmanalyte_quantity0.634
5Tumor_Size_cmtumor_thickness0.6234
6Tumor_Size_cmaverage_insert_size0.6005
7Tumor_Size_cmmitotic_total_area0.5605
8Tumor_Size_cmrin0.5513
9Tumor_Size_cmimaging_suv0.5378
\n", + "
" + ], + "text/plain": [ + " source matches similarity\n", + "0 Tumor_Size_cm shortest_dimension 0.7114\n", + "1 Tumor_Size_cm size_extraocular_nodule 0.6994\n", + "2 Tumor_Size_cm tumor_depth_measurement 0.6734\n", + "3 Tumor_Size_cm tumor_width_measurement 0.6553\n", + "4 Tumor_Size_cm analyte_quantity 0.634\n", + "5 Tumor_Size_cm tumor_thickness 0.6234\n", + "6 Tumor_Size_cm average_insert_size 0.6005\n", + "7 Tumor_Size_cm mitotic_total_area 0.5605\n", + "8 Tumor_Size_cm rin 0.5513\n", + "9 Tumor_Size_cm imaging_suv 0.5378" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bdi.top_matches(dataset, columns=['Tumor_Size_cm'], target='gdc')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Some weights of RobertaModel were not initialized from the model checkpoint at roberta-base and are newly initialized: ['roberta.pooler.dense.bias', 'roberta.pooler.dense.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "100%|██████████| 1/1 [00:00<00:00, 21.02it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Table features extracted from 1 columns\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 734/734 [00:43<00:00, 16.84it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Table features extracted from 734 columns\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcematchessimilarity
0Tumor_Focalitytumor_focality0.6059
1Tumor_Focalitytumor_depth_descriptor0.5419
2Tumor_Focalitytumor_shape0.4857
3Tumor_Focalityspectrophotometer_method0.4609
4Tumor_Focalitywilms_tumor_histologic_subtype0.4346
5Tumor_Focalitybiospecimen_type0.4199
6Tumor_Focalitywgs_coverage0.4196
7Tumor_Focalityvascular_invasion_type0.4117
8Tumor_Focalityslides0.4094
9Tumor_Focalitytumor_depth_measurement0.3923
\n", + "
" + ], + "text/plain": [ + " source matches similarity\n", + "0 Tumor_Focality tumor_focality 0.6059\n", + "1 Tumor_Focality tumor_depth_descriptor 0.5419\n", + "2 Tumor_Focality tumor_shape 0.4857\n", + "3 Tumor_Focality spectrophotometer_method 0.4609\n", + "4 Tumor_Focality wilms_tumor_histologic_subtype 0.4346\n", + "5 Tumor_Focality biospecimen_type 0.4199\n", + "6 Tumor_Focality wgs_coverage 0.4196\n", + "7 Tumor_Focality vascular_invasion_type 0.4117\n", + "8 Tumor_Focality slides 0.4094\n", + "9 Tumor_Focality tumor_depth_measurement 0.3923" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bdi.top_matches(dataset, columns=['Tumor_Focality'], target='gdc')" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Some weights of RobertaModel were not initialized from the model checkpoint at roberta-base and are newly initialized: ['roberta.pooler.dense.bias', 'roberta.pooler.dense.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "100%|██████████| 1/1 [00:00<00:00, 18.49it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Table features extracted from 1 columns\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 734/734 [00:49<00:00, 14.83it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Table features extracted from 734 columns\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcematchessimilarity
0Histologic_Grade_FIGOtumor_grade0.6154
1Histologic_Grade_FIGOwho_nte_grade0.581
2Histologic_Grade_FIGOinpc_grade0.5651
3Histologic_Grade_FIGOwho_cns_grade0.5456
4Histologic_Grade_FIGOhistologic_progression_type0.5343
5Histologic_Grade_FIGOigcccg_stage0.5319
6Histologic_Grade_FIGOtumor_grade_category0.5209
7Histologic_Grade_FIGOenneking_msts_grade0.4896
8Histologic_Grade_FIGOeducation_level0.4864
9Histologic_Grade_FIGOextrathyroid_extension0.4736
\n", + "
" + ], + "text/plain": [ + " source matches similarity\n", + "0 Histologic_Grade_FIGO tumor_grade 0.6154\n", + "1 Histologic_Grade_FIGO who_nte_grade 0.581\n", + "2 Histologic_Grade_FIGO inpc_grade 0.5651\n", + "3 Histologic_Grade_FIGO who_cns_grade 0.5456\n", + "4 Histologic_Grade_FIGO histologic_progression_type 0.5343\n", + "5 Histologic_Grade_FIGO igcccg_stage 0.5319\n", + "6 Histologic_Grade_FIGO tumor_grade_category 0.5209\n", + "7 Histologic_Grade_FIGO enneking_msts_grade 0.4896\n", + "8 Histologic_Grade_FIGO education_level 0.4864\n", + "9 Histologic_Grade_FIGO extrathyroid_extension 0.4736" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bdi.top_matches(dataset, columns=['Histologic_Grade_FIGO'], target='gdc')" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Some weights of RobertaModel were not initialized from the model checkpoint at roberta-base and are newly initialized: ['roberta.pooler.dense.bias', 'roberta.pooler.dense.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "100%|██████████| 1/1 [00:00<00:00, 13.74it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Table features extracted from 1 columns\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 734/734 [00:54<00:00, 13.56it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Table features extracted from 734 columns\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcematchessimilarity
0Path_Stage_Primary_Tumor-pTuicc_clinical_stage0.7404
1Path_Stage_Primary_Tumor-pTajcc_clinical_stage0.6784
2Path_Stage_Primary_Tumor-pTuicc_pathologic_stage0.6754
3Path_Stage_Primary_Tumor-pTfigo_stage0.673
4Path_Stage_Primary_Tumor-pTajcc_pathologic_stage0.6702
5Path_Stage_Primary_Tumor-pTinss_stage0.6422
6Path_Stage_Primary_Tumor-pTensat_pathologic_stage0.598
7Path_Stage_Primary_Tumor-pTmasaoka_stage0.5898
8Path_Stage_Primary_Tumor-pTiss_stage0.5569
9Path_Stage_Primary_Tumor-pTann_arbor_clinical_stage0.5407
\n", + "
" + ], + "text/plain": [ + " source matches similarity\n", + "0 Path_Stage_Primary_Tumor-pT uicc_clinical_stage 0.7404\n", + "1 Path_Stage_Primary_Tumor-pT ajcc_clinical_stage 0.6784\n", + "2 Path_Stage_Primary_Tumor-pT uicc_pathologic_stage 0.6754\n", + "3 Path_Stage_Primary_Tumor-pT figo_stage 0.673\n", + "4 Path_Stage_Primary_Tumor-pT ajcc_pathologic_stage 0.6702\n", + "5 Path_Stage_Primary_Tumor-pT inss_stage 0.6422\n", + "6 Path_Stage_Primary_Tumor-pT ensat_pathologic_stage 0.598\n", + "7 Path_Stage_Primary_Tumor-pT masaoka_stage 0.5898\n", + "8 Path_Stage_Primary_Tumor-pT iss_stage 0.5569\n", + "9 Path_Stage_Primary_Tumor-pT ann_arbor_clinical_stage 0.5407" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bdi.top_matches(dataset, columns=['Path_Stage_Primary_Tumor-pT'], target='gdc')" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'tumor_grade': ['G1',\n", + " 'G2',\n", + " 'G3',\n", + " 'G4',\n", + " 'GB',\n", + " 'GX',\n", + " 'High Grade',\n", + " 'Intermediate Grade',\n", + " 'Low Grade',\n", + " 'Unknown',\n", + " 'Not Reported'],\n", + " 'who_nte_grade': ['G1', 'G2', 'G3', 'GX', 'Unknown', 'Not Reported']}\n" + ] + } + ], + "source": [ + "pprint(\n", + " get_gdc_data(\n", + " [\n", + " \"tumor_grade\",\n", + " \"who_nte_grade\",\n", + " ]\n", + " )\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Some weights of RobertaModel were not initialized from the model checkpoint at roberta-base and are newly initialized: ['roberta.pooler.dense.bias', 'roberta.pooler.dense.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n", + "100%|██████████| 1/1 [00:00<00:00, 18.26it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Table features extracted from 1 columns\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 734/734 [00:53<00:00, 13.68it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Table features extracted from 734 columns\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcematchessimilarity
0Ethnicityethnicity0.8297
1Ethnicityrace0.6577
2Ethnicityvariant_origin0.5169
3Ethnicitydemographics0.4102
4Ethnicitycountry_of_residence_at_enrollment0.3763
5Ethnicitycountry_of_birth0.3586
6Ethnicityeye_color0.3333
7Ethnicitymeasurement_type0.3144
8Ethnicityexposure_source0.314
9Ethnicityalcohol_type0.3134
\n", + "
" + ], + "text/plain": [ + " source matches similarity\n", + "0 Ethnicity ethnicity 0.8297\n", + "1 Ethnicity race 0.6577\n", + "2 Ethnicity variant_origin 0.5169\n", + "3 Ethnicity demographics 0.4102\n", + "4 Ethnicity country_of_residence_at_enrollment 0.3763\n", + "5 Ethnicity country_of_birth 0.3586\n", + "6 Ethnicity eye_color 0.3333\n", + "7 Ethnicity measurement_type 0.3144\n", + "8 Ethnicity exposure_source 0.314\n", + "9 Ethnicity alcohol_type 0.3134" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bdi.top_matches(dataset, columns=['Ethnicity'], target='gdc')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcetargetsimilarity
0Hispanic or Latinohispanic or latino1.0
1Not-Hispanic or Latinonot hispanic or latino0.936364
2nan
3Not reported
\n", + "
" + ], + "text/plain": [ + " source target similarity\n", + "0 Hispanic or Latino hispanic or latino 1.0\n", + "1 Not-Hispanic or Latino not hispanic or latino 0.936364\n", + "2 nan \n", + "3 Not reported " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bdi.preview_value_mappings(\n", + " dataset,\n", + " column_mapping=(\"Ethnicity\", \"ethnicity\"),\n", + " target=\"gdc\",\n", + " method=\"edit_distance\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcetargetsimilarity
0Whitewhite1.0
1Asianasian1.0
2Not Reportednot reported1.0
3Black or African Americanblack or african american1.0
4nan
\n", + "
" + ], + "text/plain": [ + " source target similarity\n", + "0 White white 1.0\n", + "1 Asian asian 1.0\n", + "2 Not Reported not reported 1.0\n", + "3 Black or African American black or african american 1.0\n", + "4 nan " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bdi.preview_value_mappings(\n", + " dataset,\n", + " column_mapping=(\"Race\", \"race\"),\n", + " target=\"gdc\",\n", + " method=\"edit_distance\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcetargetsimilarity
0UnifocalUnifocal1.0
1MultifocalMultifocal1.0
2nan
\n", + "
" + ], + "text/plain": [ + " source target similarity\n", + "0 Unifocal Unifocal 1.0\n", + "1 Multifocal Multifocal 1.0\n", + "2 nan " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bdi.preview_value_mappings(\n", + " dataset,\n", + " column_mapping=(\"Tumor_Focality\", \"tumor_focality\"),\n", + " target=\"gdc\",\n", + " method=\"edit_distance\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "column_mappings = pd.DataFrame(\n", + " [\n", + " {\n", + " \"source\": \"Ethnicity\",\n", + " \"target\": \"ethnicity\",\n", + " },\n", + " {\n", + " \"source\": \"Gender\",\n", + " \"target\": \"gender\",\n", + " },\n", + " {\n", + " \"source\": \"Race\",\n", + " \"target\": \"race\",\n", + " },\n", + " {\n", + " \"source\": \"Country\",\n", + " \"target\": \"country_of_birth\",\n", + " },\n", + " {\n", + " \"source\": \"Tumor_Focality\",\n", + " \"target\": \"tumor_focality\",\n", + " },\n", + " {\n", + " \"source\": \"FIGO_stage\",\n", + " \"target\": \"figo_stage\",\n", + " },\n", + " {\n", + " \"source\": \"Histologic_Grade_FIGO\",\n", + " \"target\": \"tumor_grade\",\n", + " },\n", + " {\n", + " \"source\": \"BMI\",\n", + " \"target\": \"bmi\",\n", + " }\n", + " ]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Ethnicity => ethnicity\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcetargetsimilarity
0Hispanic or Latinohispanic or latino1.0
1Not-Hispanic or Latinonot hispanic or latino0.936364
2nan
3Not reported
\n", + "
" + ], + "text/plain": [ + " source target similarity\n", + "0 Hispanic or Latino hispanic or latino 1.0\n", + "1 Not-Hispanic or Latino not hispanic or latino 0.936364\n", + "2 nan \n", + "3 Not reported " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Gender => gender\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcetargetsimilarity
0Femalefemale1.0
1nan
\n", + "
" + ], + "text/plain": [ + " source target similarity\n", + "0 Female female 1.0\n", + "1 nan " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Race => race\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcetargetsimilarity
0Whitewhite1.0
1Asianasian1.0
2Not Reportednot reported1.0
3Black or African Americanblack or african american1.0
4nan
\n", + "
" + ], + "text/plain": [ + " source target similarity\n", + "0 White white 1.0\n", + "1 Asian asian 1.0\n", + "2 Not Reported not reported 1.0\n", + "3 Black or African American black or african american 1.0\n", + "4 nan " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Country => country_of_birth\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcetargetsimilarity
0United StatesUnited States1.0
1UkraineUkraine1.0
2PolandPoland1.0
3nan
4Other_specify
\n", + "
" + ], + "text/plain": [ + " source target similarity\n", + "0 United States United States 1.0\n", + "1 Ukraine Ukraine 1.0\n", + "2 Poland Poland 1.0\n", + "3 nan \n", + "4 Other_specify " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Tumor_Focality => tumor_focality\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcetargetsimilarity
0UnifocalUnifocal1.0
1MultifocalMultifocal1.0
2nan
\n", + "
" + ], + "text/plain": [ + " source target similarity\n", + "0 Unifocal Unifocal 1.0\n", + "1 Multifocal Multifocal 1.0\n", + "2 nan " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "FIGO_stage => figo_stage\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcetargetsimilarity
0IIIC2Stage IIIC21.0
1IIIC1Stage IIIC11.0
2IB
3nan
4IVB
5IIIB
6IA
7II
8IIIA
\n", + "
" + ], + "text/plain": [ + " source target similarity\n", + "0 IIIC2 Stage IIIC2 1.0\n", + "1 IIIC1 Stage IIIC1 1.0\n", + "2 IB \n", + "3 nan \n", + "4 IVB \n", + "5 IIIB \n", + "6 IA \n", + "7 II \n", + "8 IIIA " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Histologic_Grade_FIGO => tumor_grade\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
sourcetargetsimilarity
0FIGO grade 1High Grade1.0
1FIGO grade 2High Grade1.0
2FIGO grade 3High Grade1.0
3nan
\n", + "
" + ], + "text/plain": [ + " source target similarity\n", + "0 FIGO grade 1 High Grade 1.0\n", + "1 FIGO grade 2 High Grade 1.0\n", + "2 FIGO grade 3 High Grade 1.0\n", + "3 nan " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "mappings = bdi.preview_value_mappings(\n", + " dataset,\n", + " column_mapping=column_mappings,\n", + " target=\"gdc\",\n", + " method=\"edit_distance\",\n", + ")\n", + "\n", + "for mapping in mappings:\n", + " print(f\"{mapping['source']} => {mapping['target']}\")\n", + " display(mapping[\"mapping\"])\n", + " print(\"\")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "value_mappings = bdi.match_values(\n", + " dataset, target=\"gdc\", column_mapping=column_mappings, method=\"edit_distance\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "from bdikit import update_mappings\n", + "import re\n", + "\n", + "\n", + "def map_hist_grade_figo(value_str):\n", + " if isinstance(value_str, str):\n", + " return re.sub(r\"FIGO grade (\\d+)\", r\"G\\1\", value_str)\n", + " else:\n", + " return \"Unknown\"\n", + "\n", + "\n", + "user_mappings = [\n", + " {\n", + " \"source\": \"BMI\",\n", + " \"target\": \"bmi\",\n", + " },\n", + " {\n", + " \"source\": \"Age\",\n", + " \"target\": \"days_to_birth\",\n", + " \"mapper\": lambda age: -age * 365,\n", + " },\n", + " {\n", + " \"source\": \"Histologic_Grade_FIGO\",\n", + " \"target\": \"tumor_grade\",\n", + " \"mapper\": map_hist_grade_figo,\n", + " },\n", + " {\n", + " \"source\": \"FIGO_stage\",\n", + " \"target\": \"figo_stage\",\n", + " \"mapper\": lambda x: f\"Stage {x}\" if isinstance(x, str) else \"Unknown\",\n", + " },\n", + "]\n", + "\n", + "harmonization_spec = update_mappings(value_mappings, user_mappings)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
ethnicitygenderracecountry_of_birthtumor_focalitybmidays_to_birthtumor_gradefigo_stage
0not hispanic or latinofemalewhiteUnited StatesUnifocal38.88-23360.0G1Stage IA
1not hispanic or latinofemalewhiteUnited StatesUnifocal39.76-21170.0G1Stage IA
2not hispanic or latinofemalewhiteUnited StatesUnifocal51.19-18250.0G2Stage IA
3NaNNaNNaNNaNNaNNaNNaNUnknownUnknown
4not hispanic or latinofemalewhiteUnited StatesUnifocal32.69-27375.0G2Stage IA
..............................
99NaNfemaleNaNUkraineUnifocal29.40-27375.0G3Stage IA
100NaNfemaleNaNUkraineUnifocal35.42-27010.0G2Stage II
101not hispanic or latinofemaleblack or african americanUnited StatesUnifocal24.32-31025.0UnknownStage II
102NaNfemaleNaNUkraineUnifocal34.06-25550.0UnknownStage IA
103NaNNaNNaNUkraineNaNNaNNaNUnknownUnknown
\n", + "

104 rows × 9 columns

\n", + "
" + ], + "text/plain": [ + " ethnicity gender race \\\n", + "0 not hispanic or latino female white \n", + "1 not hispanic or latino female white \n", + "2 not hispanic or latino female white \n", + "3 NaN NaN NaN \n", + "4 not hispanic or latino female white \n", + ".. ... ... ... \n", + "99 NaN female NaN \n", + "100 NaN female NaN \n", + "101 not hispanic or latino female black or african american \n", + "102 NaN female NaN \n", + "103 NaN NaN NaN \n", + "\n", + " country_of_birth tumor_focality bmi days_to_birth tumor_grade \\\n", + "0 United States Unifocal 38.88 -23360.0 G1 \n", + "1 United States Unifocal 39.76 -21170.0 G1 \n", + "2 United States Unifocal 51.19 -18250.0 G2 \n", + "3 NaN NaN NaN NaN Unknown \n", + "4 United States Unifocal 32.69 -27375.0 G2 \n", + ".. ... ... ... ... ... \n", + "99 Ukraine Unifocal 29.40 -27375.0 G3 \n", + "100 Ukraine Unifocal 35.42 -27010.0 G2 \n", + "101 United States Unifocal 24.32 -31025.0 Unknown \n", + "102 Ukraine Unifocal 34.06 -25550.0 Unknown \n", + "103 Ukraine NaN NaN NaN Unknown \n", + "\n", + " figo_stage \n", + "0 Stage IA \n", + "1 Stage IA \n", + "2 Stage IA \n", + "3 Unknown \n", + "4 Stage IA \n", + ".. ... \n", + "99 Stage IA \n", + "100 Stage II \n", + "101 Stage II \n", + "102 Stage IA \n", + "103 Unknown \n", + "\n", + "[104 rows x 9 columns]" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "harmonized_dataset = bdi.materialize_mapping(dataset, harmonization_spec)\n", + "harmonized_dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
EthnicityGenderRaceCountryTumor_FocalityBMIAgeHistologic_Grade_FIGOFIGO_stage
0Not-Hispanic or LatinoFemaleWhiteUnited StatesUnifocal38.8864.0FIGO grade 1IA
1Not-Hispanic or LatinoFemaleWhiteUnited StatesUnifocal39.7658.0FIGO grade 1IA
2Not-Hispanic or LatinoFemaleWhiteUnited StatesUnifocal51.1950.0FIGO grade 2IA
3NaNNaNNaNNaNNaNNaNNaNNaNNaN
4Not-Hispanic or LatinoFemaleWhiteUnited StatesUnifocal32.6975.0FIGO grade 2IA
..............................
99NaNFemaleNaNUkraineUnifocal29.4075.0FIGO grade 3IA
100NaNFemaleNaNUkraineUnifocal35.4274.0FIGO grade 2II
101Not-Hispanic or LatinoFemaleBlack or African AmericanUnited StatesUnifocal24.3285.0NaNII
102NaNFemaleNaNUkraineUnifocal34.0670.0NaNIA
103NaNNaNNaNUkraineNaNNaNNaNNaNNaN
\n", + "

104 rows × 9 columns

\n", + "
" + ], + "text/plain": [ + " Ethnicity Gender Race Country \\\n", + "0 Not-Hispanic or Latino Female White United States \n", + "1 Not-Hispanic or Latino Female White United States \n", + "2 Not-Hispanic or Latino Female White United States \n", + "3 NaN NaN NaN NaN \n", + "4 Not-Hispanic or Latino Female White United States \n", + ".. ... ... ... ... \n", + "99 NaN Female NaN Ukraine \n", + "100 NaN Female NaN Ukraine \n", + "101 Not-Hispanic or Latino Female Black or African American United States \n", + "102 NaN Female NaN Ukraine \n", + "103 NaN NaN NaN Ukraine \n", + "\n", + " Tumor_Focality BMI Age Histologic_Grade_FIGO FIGO_stage \n", + "0 Unifocal 38.88 64.0 FIGO grade 1 IA \n", + "1 Unifocal 39.76 58.0 FIGO grade 1 IA \n", + "2 Unifocal 51.19 50.0 FIGO grade 2 IA \n", + "3 NaN NaN NaN NaN NaN \n", + "4 Unifocal 32.69 75.0 FIGO grade 2 IA \n", + ".. ... ... ... ... ... \n", + "99 Unifocal 29.40 75.0 FIGO grade 3 IA \n", + "100 Unifocal 35.42 74.0 FIGO grade 2 II \n", + "101 Unifocal 24.32 85.0 NaN II \n", + "102 Unifocal 34.06 70.0 NaN IA \n", + "103 NaN NaN NaN NaN NaN \n", + "\n", + "[104 rows x 9 columns]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "original_columns = map(lambda m: m[\"source\"], harmonization_spec)\n", + "dataset[original_columns]" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/tests/test_api.py b/tests/test_api.py index 39248a1c..1d21ae74 100644 --- a/tests/test_api.py +++ b/tests/test_api.py @@ -146,7 +146,7 @@ def test_map_column_values(): ) # then - upper_cased_values = ["A", "B", "C", "D", "E"] + upper_cased_values = pd.Series(["A", "B", "C", "D", "E"]) assert mapped_column.name == target_column_name assert mapped_column.eq(upper_cased_values).all() @@ -159,19 +159,19 @@ def test_map_dataframe_column_values(): value_mapping_spec = [ { - "from": "column_str_1", - "to": "string column 1", + "source": "column_str_1", + "target": "string column 1", "mapper": IdentityValueMapper(), }, { - "from": "column_str_2", - "to": "string column 2", + "source": "column_str_2", + "target": "string column 2", "mapper": FunctionValueMapper(function=lambda x: x.upper()), }, ] # when - df_mapped = bdi.materialize_mapping(df_base, target=value_mapping_spec) + df_mapped = bdi.materialize_mapping(df_base, mapping_spec=value_mapping_spec) # then assert len(df_mapped.columns) == 2 @@ -181,3 +181,67 @@ def test_map_dataframe_column_values(): assert "string column 2" in df_mapped.columns assert df_mapped["string column 2"].eq(["A", "B", "C", "D", "E"]).all() + + +def test_value_mapping_dataframe(): + # given + df_source = pd.DataFrame( + {"src_column": ["Red Apple", "Banana", "Oorange", "Strawberry"]} + ) + df_target = pd.DataFrame( + {"tgt_column": ["apple", "banana", "orange", "kiwi", "grapes"]} + ) + + df_matches = pd.DataFrame({"source": ["src_column"], "target": ["tgt_column"]}) + + # when + value_mappings = bdi.match_values(df_source, df_target, df_matches, method="tfidf") + + # then + assert value_mappings is not None + assert "src_column" in value_mappings + assert value_mappings["src_column"]["matches"] is not None + assert value_mappings["src_column"]["target"] == "tgt_column" + + src_column_mapping = value_mappings["src_column"] + assert len(src_column_mapping["matches"]) == 3 + assert len(src_column_mapping["matches"]) == 3 + + +def test_end_to_end_api_integration(): + # given + df_source = pd.DataFrame( + {"src_column": ["Red Apple", "Banana", "Oorange", "Strawberry"]} + ) + df_target = pd.DataFrame( + {"tgt_column": ["apple", "banana", "orange", "kiwi", "grapes"]} + ) + + # when + column_mappings = bdi.match_columns(df_source, df_target, method="coma") + # then + assert column_mappings is not None + assert column_mappings.empty == False + assert "source" in column_mappings.columns + assert "target" in column_mappings.columns + + # when + value_mappings = bdi.match_values( + df_source, df_target, column_mappings, method="tfidf" + ) + + assert value_mappings is not None + assert "src_column" in value_mappings + assert value_mappings["src_column"]["matches"] is not None + assert value_mappings["src_column"]["target"] == "tgt_column" + + src_column_mapping = value_mappings["src_column"] + assert len(src_column_mapping["matches"]) == 3 + assert len(src_column_mapping["matches"]) == 3 + + # when + harmonization_spec = bdi.update_mappings(value_mappings, []) + df_mapped = bdi.materialize_mapping(df_source, harmonization_spec) + + assert "tgt_column" in df_mapped.columns + assert df_mapped["tgt_column"].tolist() == ["apple", "banana", "orange", None]