Fix typo in core math module filename and update all references.

Changes:
- Renamed market_trade/core/CoreTraidMath.py → CoreTradeMath.py
- Updated 28 import references across 14 files:
  - All Ind_*.py indicator modules
  - indicators.py, indicators_v2.py
  - signals.py, signals_v2.py
  - CoreDraw.py
- Updated documentation references in CLAUDE.md

This eliminates the "Traid" typo and aligns with proper English spelling.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

@@ -0,0 +26,4 @@
+            'actionOptions':{}
+        }
+        self.base_df=base_df.reset_index(drop=True)
+        self.params=params if params is not None else default_params

@@ -83,3 +83,3 @@
             'actionOptions':{'MeanType':'EMA','span':10}
         }        
-        ans=np.asarray(CoreTraidMath.CoreMath(ser,op).ans)
+        ans=np.asarray(CoreTradeMath.CoreMath(ser,op).ans)

@@ -63,3 +63,3 @@
         
         for i in range(self.options['window'],len(self.base_df)-self.options['shift']+1):
-            ans['MaxExt'].append(CoreTraidMath.CoreMath(self.base_df[i-self.options['window']:i],opMax).ans)
+            ans['MaxExt'].append(CoreTradeMath.CoreMath(self.base_df[i-self.options['window']:i],opMax).ans)

@@ -54,3 +54,3 @@
                 }
             x=self.base_df['date'].to_list()
-        y= CoreTraidMath.CoreMath(self.base_df,op).ans
+        y= CoreTradeMath.CoreMath(self.base_df,op).ans

@@ -28,0 +34,4 @@
+                        'params': {'MeanType': 'SMA', 'window': 30, 'valueType': 'close', 'kDev': 2.5}
+                    }
+                }
+            }

@@ -95,0 +61,4 @@
+        Returns:
+            Risk-adjusted decision dictionary.
+        """
+        probability_decision = self.TV.get_decision_by_signals(self.get_signals_answer(signals_ans))

@@ -95,0 +78,4 @@
+        Returns:
+            Dictionary of signal results.
+        """
+        return self.SA.get_answer(signals_data_dict)

@@ -95,0 +89,4 @@
+
+        Returns:
+            Direction: 'down' if value decreases, 'up' if increases, 'none' if same.
+        """

@@ -127,0 +126,4 @@
+                target = self.SA.signals[i].params['target']
+                for j in retro_template_dict[i]['indicatorData'].keys():
+                    req_sig[i]['indicatorData'][j] = data[k:k+window]
+

@@ -145,0 +147,4 @@
+                signal_decisions=dict_signals['signalsAns'][i],
+                trande=dict_signals['rightAns'][i]
+            )
+        self.TV.generate_matrix_probability()

@@ -16,1 +34,4 @@
+        Returns:
+            Calculated indicator values or "ERROR" if not implemented.
+        """
         return "ERROR"

@@ -75,1 +38,3 @@
-                'window':self.options['window']
+
+
+class IndicatorsAggregator:

@@ -88,0 +61,4 @@
+            ind_dict: Dictionary mapping indicator names to configurations.
+                Defaults to empty dict if not provided.
+        """
+        self.ind_dict = ind_dict if ind_dict is not None else {}

@@ -88,0 +86,4 @@
+        ans = {}
+        for i in data_dict.keys():
+            ans[i] = self.ind_instances[i].get_answer(data_dict[i])
+        return ans

@@ -88,0 +89,4 @@
+        return ans
+
+
+class ind_BB(CoreIndicator):

@@ -88,0 +113,4 @@
+            data_type='ohlc',
+            predict_type='trend',
+            name=name
+        )

@@ -88,0 +155,4 @@
+        ans['pSTD'] = ans['BB'] + ans['STD'] * self.options['kDev']
+        ans['mSTD'] = ans['BB'] - ans['STD'] * self.options['kDev']
+        ans['x'] = np.array(data['date'][self.options['window']-1:].to_list())
+        self.ans = ans

@@ -12,0 +31,4 @@
+            Dictionary with 'decision' ('buy', 'sell', 'none') and additional fields:
+                - For 'buy': includes 'amount' field
+                - For 'sell': includes 'deals' list of position UUIDs to close
+        """

@@ -27,0 +49,4 @@
+                    ans['deals'] = []
+                    row = deals.iloc[i]
+                    # Check if position is profitable after commission
+                    if row.startPrice < price * pow(1 + self.commission, 2):

@@ -57,0 +36,4 @@
+        Returns:
+            IndicatorsAggregator instance.
+        """
+        return IndicatorsAggregator(req['indicators'])

@@ -57,0 +68,4 @@
+    Generates trading signals based on Bollinger Bands indicator:
+    - 'up' when price is below lower band
+    - 'down' when price is above upper band
+    - 'none' when price is within bands

@@ -103,2 +153,2 @@
-        for i in siganlsDict.keys():
-            ans[i]=siganlsDict[i]['className'](name = i, req = siganlsDict[i])
+        for i in signals_dict.keys():
+            ans[i] = signals_dict[i]['className'](name=i, req=signals_dict[i])

@@ -22,0 +17,4 @@
+    # Function to create DataFrame with specified columns and indices. Indices are unique combinations.
+    def create_df_by_names(self, names_index, column_names, default_value=0.0):
+        df = pd.DataFrame(dict.fromkeys(column_names, [default_value]*pow(3, len(names_index))),
+                          index=pd.MultiIndex.from_product([self.trade_values_list]*len(names_index), names=names_index)

@@ -55,0 +50,4 @@
+            self.matrix_probability.iloc[i]['down'] = self.matrix_amounts.iloc[i]['down'] / row_sum
+
+    # Get decision from probability matrix based on signal values
+    def get_decision_by_signals(self, signal_decisions: dict) -> dict:

@@ -85,0 +71,4 @@
+        if matrix_dict['amounts'] != None:
+            self.matrix_amounts = pd.DataFrame.from_dict(y['amounts'], orient='tight')
+        if matrix_dict['probability'] != None:
+            self.matrix_probability = pd.DataFrame.from_dict(y['probability'], orient='tight')

@@ -61,3 +62,3 @@
 
-test.getOnlineAns(sigAgrData, 0.0)
+test.get_online_answer(sig_agr_data, 0.0)

@@ -0,0 +10,4 @@
+    instrument_service = tinkoff_grpc.InstrumentsService(tinkoff_channel)
+    currencies = instrument_service.get_currencies(market_trade.constants.DEFAULT_INSTRUMENT_STATUS)
+    for currency in currencies:
+        print(currency.figi, currency.iso_code)