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config_version: 3

datasources:
  my_gcs_datasource:
    class_name: Datasource
    module_name: "great_expectations.datasource"
    execution_engine:
        class_name: PandasExecutionEngine
    data_connectors:
        default_runtime_data_connector_name:

julian-west

"""Great Expectations Checkpoint"""
import logging
import os
from typing import Any, Dict

from great_expectations.checkpoint import SimpleCheckpoint
from great_expectations.checkpoint.types.checkpoint_result import CheckpointResult
from great_expectations.core.batch import RuntimeBatchRequest
from great_expectations.data_context import BaseDataContext
from great_expectations.data_context.types.base import DataContextConfig

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repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
  rev: v3.2.0
  hooks:
    - id: trailing-whitespace
    - id: mixed-line-ending
    - id: check-added-large-files
      args: ['--maxkb=1000']
    - id: end-of-file-fixer
    - id: requirements-txt-fixer

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# ---------------------------------------
# Plot graph
# ---------------------------------------

# edges
tracer = go.Scatter(x=Xedges, y=Yedges,
                    mode='lines',
                    line= dict(color='#DCDCDC', width=1),
                    hoverinfo='none',
                    showlegend=False)

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# ---------------------------------------
# Get statistics for tooltip
# ---------------------------------------

# make list of node labels.
node_label = list(mst.nodes())
# calculate annualised returns, annualised volatility and round to 2dp
annual_vol, annual_ret, annual_vol_2dp, annual_ret_2dp = calculate_stats()
# get top and bottom 3 correlations for each node
top_3_corrs, bottom_3_corrs = get_top_and_bottom_three()

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def get_coordinates(G=mst):
    """Returns the positions of nodes and edges in a format for Plotly to draw the network"""
    # get list of node positions
    pos = nx.fruchterman_reingold_layout(mst)

    Xnodes = [pos[n][0] for n in mst.nodes()]
    Ynodes = [pos[n][1] for n in mst.nodes()]

    Xedges = []
    Yedges = []

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def convert_rankings_to_string(ranking):
    """
    Concatenates list of node and correlation into a single string which is the 
    preferred format for the plotly tooltip.

    Inserts html "<br>" inbetween each item in order to add a new line in the tooltip
    """
    s = ''
    for r in ranking:
        s += r + "<br>"

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#create minimum spanning tree layout from Gx (after small correlations have been removed)
mst = nx.minimum_spanning_tree(Gx)

edge_colours = []

#assign edge colours
for key, value in nx.get_edge_attributes(mst, 'correlation').items():
    edge_colours.append(assign_colour(value))

    

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# draw improved graph
nx.draw(Gx, pos=nx.fruchterman_reingold_layout(Gx), with_labels=True,
        node_size=node_size, node_color="#e1575c", edge_color=edge_colours,
       width = edge_width)
plt.title("Asset price correlations - Fruchterman-Reingold layout",fontdict=font_dict)
plt.show()

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# draw improved graph
sns.set(rc={'figure.figsize': (9, 9)})
font_dict = {'fontsize': 18}

nx.draw(Gx, pos=nx.circular_layout(Gx), with_labels=True,
        node_size=node_size, node_color="#e1575c", edge_color=edge_colours,
        width=edge_width)
plt.title("Asset price correlations", fontdict=font_dict)
plt.show()