Added diverged symbols view
This commit is contained in:
Jamie Cash
@@ -161,6 +161,34 @@ class Correlation:
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return filtered_data
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@property
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def diverged_symbols(self):
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"""
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:return: dataframe containing all diverged, diverging or converging symbols and count of number of
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divergences for those symbols.
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"""
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filtered_data = None
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if self.coefficient_data is not None:
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# Only rows where we have a divergence
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filtered_data = self.coefficient_data \
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.loc[(self.coefficient_data['Status'] == STATUS_DIVERGED) |
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(self.coefficient_data['Status'] == STATUS_DIVERGING) |
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(self.coefficient_data['Status'] == STATUS_CONVERGING)]
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# We only need the symbols
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all_symbols = pd.DataFrame(columns=['Symbol', 'Count'],
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data={'Symbol': filtered_data['Symbol 1'].append(filtered_data['Symbol 2']),
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'Count': 1})
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# Group and count. Reset index so that we have named SYMBOL column.
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filtered_data = all_symbols.groupby(by='Symbol').count().reset_index()
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# Sort
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filtered_data = filtered_data.sort_values('Count', ascending=False)
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return filtered_data
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def load(self, filename):
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"""
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Loads calculated coefficients, price data used to calculate them and tick data used during monitoring.
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@@ -76,6 +76,8 @@ class CorrelationMDIFrame(wx.MDIParentFrame):
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menu_view = wx.Menu()
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self.Bind(wx.EVT_MENU, self.__on_view_status, menu_view.Append(wx.ID_ANY, "Status",
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"View status of correlations."))
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self.Bind(wx.EVT_MENU, self.__on_view_diverged, menu_view.Append(wx.ID_ANY, "Diverged Symbols",
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"View diverged symbols."))
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self.menubar.Append(menu_view, "&View")
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# Set menu bar
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@@ -260,6 +262,20 @@ class CorrelationMDIFrame(wx.MDIParentFrame):
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else:
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opened_instance.Raise()
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def __on_view_diverged(self, evt):
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from mt5_correlation.gui.mdi_child_diverged_symbols import MDIChildDivergedSymbols
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# Only open if not already open. If already open then raise to top.
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opened_instance = None
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for child in self.GetChildren():
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if isinstance(child, MDIChildDivergedSymbols):
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opened_instance = child
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if opened_instance is None:
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MDIChildDivergedSymbols(parent=self).Show(True)
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else:
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opened_instance.Raise()
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def __refresh(self):
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"""
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Refresh all open child frames
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@@ -0,0 +1,138 @@
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import logging
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import pandas as pd
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import wx
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import wx.grid
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import mt5_correlation.gui.mdi as mdi
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# Columns for diverged symbols table
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COLUMN_INDEX = 0
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COLUMN_SYMBOL = 1
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COLUMN_NUM_DIVERGENCES = 2
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class MDIChildDivergedSymbols(mdi.CorrelationMDIChild):
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"""
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Shows the status of all correlations that are within the monitoring threshold
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"""
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# The table and grid containing the symbols that form part of the diverged correlations. Defined at instance level
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# to enable refresh.
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__table = None
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__grid = None
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# Number of rows. Required for and updated by refresh method
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__rows = 0
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__log = None # The logger
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def __init__(self, parent):
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# Super
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wx.MDIChildFrame.__init__(self, parent=parent, id=wx.ID_ANY, title="Diverged Symbols",
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size=wx.Size(width=240, height=-1), style=wx.DEFAULT_FRAME_STYLE)
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# Create logger
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self.__log = logging.getLogger(__name__)
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# Panel and sizer for table
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panel = wx.Panel(self, wx.ID_ANY)
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sizer = wx.BoxSizer(wx.VERTICAL)
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panel.SetSizer(sizer)
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# Create the grid. This is a data table using pandas dataframe for underlying data. Add the
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# grid to the sizer.
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self.__table = _DataTable(columns=self.GetMDIParent().cor.diverged_symbols.columns)
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self.__grid = wx.grid.Grid(panel, wx.ID_ANY)
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self.__grid.SetTable(self.__table, takeOwnership=True)
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self.__grid.EnableEditing(False)
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self.__grid.EnableDragRowSize(False)
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self.__grid.EnableDragColSize(True)
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self.__grid.EnableDragGridSize(True)
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self.__grid.SetSelectionMode(wx.grid.Grid.SelectRows)
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self.__grid.SetRowLabelSize(0)
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self.__grid.SetColSize(COLUMN_INDEX, 0) # Index. Hide
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self.__grid.SetColSize(COLUMN_SYMBOL, 100) # Symbol
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self.__grid.SetColSize(COLUMN_NUM_DIVERGENCES, 100) # Num divergences
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self.__grid.SetMinSize((220, 100))
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sizer.Add(self.__grid, 1, wx.ALL | wx.EXPAND)
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# Refresh to populate
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self.refresh()
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def refresh(self):
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"""
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Refreshes grid. Notifies if rows have been added or deleted.
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:return:
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"""
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self.__log.debug(f"Refreshing grid.")
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# Update data
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self.__table.data = self.GetMDIParent().cor.diverged_symbols.copy()
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# Start refresh
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self.__grid.BeginBatch()
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# Check if num rows in dataframe has changed, and send appropriate APPEND or DELETE messages
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cur_rows = len(self.GetMDIParent().cor.diverged_symbols.index)
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if cur_rows < self.__rows:
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# Data has been deleted. Send message
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msg = wx.grid.GridTableMessage(self.__table, wx.grid.GRIDTABLE_NOTIFY_ROWS_DELETED,
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self.__rows - cur_rows, self.__rows - cur_rows)
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self.__grid.ProcessTableMessage(msg)
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elif cur_rows > self.__rows:
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# Data has been added. Send message
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msg = wx.grid.GridTableMessage(self.__table, wx.grid.GRIDTABLE_NOTIFY_ROWS_APPENDED,
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cur_rows - self.__rows) # how many
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self.__grid.ProcessTableMessage(msg)
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self.__grid.EndBatch()
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# Send updated message
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msg = wx.grid.GridTableMessage(self.__table, wx.grid.GRIDTABLE_REQUEST_VIEW_GET_VALUES)
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self.__grid.ProcessTableMessage(msg)
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# Update row count
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self.__rows = cur_rows
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class _DataTable(wx.grid.GridTableBase):
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"""
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A data table that holds data in a pandas dataframe.
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"""
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data = None # The data for this table. A Pandas DataFrame
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def __init__(self, columns):
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wx.grid.GridTableBase.__init__(self)
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self.headerRows = 1
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self.data = pd.DataFrame(columns=columns)
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def GetNumberRows(self):
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return len(self.data)
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def GetNumberCols(self):
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return len(self.data.columns) + 1
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def GetValue(self, row, col):
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if row < self.RowsCount and col < self.ColsCount:
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return self.data.index[row] if col == 0 else self.data.iloc[row, col - 1]
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else:
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raise Exception(f"Trying to access row {row} and col {col} which does not exist.")
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def SetValue(self, row, col, value):
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self.data.iloc[row, col - 1] = value
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def GetColLabelValue(self, col):
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if col == 0:
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if self.data.index.name is None:
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return 'Index'
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else:
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return self.data.index.name
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return str(self.data.columns[col - 1])
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def GetTypeName(self, row, col):
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return wx.grid.GRID_VALUE_STRING
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def GetAttr(self, row, col, prop):
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attr = wx.grid.GridCellAttr()
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return attr
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@@ -1,5 +1,5 @@
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import unittest
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from unittest.mock import patch
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from unittest.mock import patch, PropertyMock
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import time
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import mt5_correlation.correlation as correlation
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import pandas as pd
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@@ -121,7 +121,7 @@ class TestCorrelation(unittest.TestCase):
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self.assertEqual(cor.coefficient_data.iloc[1, 2], 1, "The correlation for SYMBOL1:SYMBOL5 should be 1.")
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self.assertEqual(cor.coefficient_data.iloc[2, 2], 1, "The correlation for SYMBOL4:SYMBOL5 should be 1.")
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# Get the price data used to calculate the coefficients fro symbol 1. It should match mock_base_prices.
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# Get the price data used to calculate the coefficients for symbol 1. It should match mock_base_prices.
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price_data = cor.get_price_data('SYMBOL1')
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self.assertTrue(price_data.equals(self.mock_base_prices), "Price data returned post calculation should match "
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"mock price data.")
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@@ -325,6 +325,38 @@ class TestCorrelation(unittest.TestCase):
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# Cleanup. delete the file
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os.remove("unittest.cpd")
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@patch('mt5_correlation.correlation.Correlation.coefficient_data', new_callable=PropertyMock)
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def test_diverged_symbols(self, mock):
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"""
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Test that diverged_symbols property correctly groups symbols and counts.
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:param mock:
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:return:
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"""
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# Correlation class
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cor = correlation.Correlation()
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# Mock the correlation data. Symbol 1 has diverged 3 times; symbols 2 has diverged twice; symbol 3 has
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# diverged once; symbols 4 has diverged twice and symbol 5 has not diverged at all. Use all diverged status'
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# (diverged, diverging & converging). Also add a row for a non diverged pair.
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mock.return_value = pd.DataFrame(columns=['Symbol 1', 'Symbol 2', 'Status'], data=[
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['SYMBOL1', 'SYMBOL2', correlation.STATUS_DIVERGED],
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['SYMBOL1', 'SYMBOL3', correlation.STATUS_DIVERGING],
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['SYMBOL1', 'SYMBOL4', correlation.STATUS_CONVERGING],
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['SYMBOL2', 'SYMBOL4', correlation.STATUS_DIVERGED],
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['SYMBOL2', 'SYMBOL3', correlation.STATUS_CORRELATED]])
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# Get the diverged_symbols data and check the counts
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diverged_symbols = cor.diverged_symbols
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self.assertEqual(diverged_symbols.loc[(diverged_symbols['Symbol'] == 'SYMBOL1')]['Count'].iloc[0], 3,
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"Symbol 1 has diverged three times.")
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self.assertEqual(diverged_symbols.loc[(diverged_symbols['Symbol'] == 'SYMBOL2')]['Count'].iloc[0], 2,
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"Symbol 2 has diverged twice.")
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self.assertEqual(diverged_symbols.loc[(diverged_symbols['Symbol'] == 'SYMBOL3')]['Count'].iloc[0], 1,
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"Symbol 3 has diverged once.")
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self.assertEqual(diverged_symbols.loc[(diverged_symbols['Symbol'] == 'SYMBOL4')]['Count'].iloc[0], 2,
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"Symbol 4 has diverged twice.")
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self.assertFalse('SYMBOL5' in diverged_symbols['Symbol'])
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if __name__ == '__main__':
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unittest.main()
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