fixed 0 doesnt update in legend

README.md

@@ -1,10 +1,10 @@
-Fork of the original [lightweight-charts](louisnw01/lightweight-charts-python) with enhancements and supporting vectorbtpro workflow
+Fork of the original [lightweight-charts](louisnw01/lightweight-charts-python) with enhancements and supporting `vectorbtpro` workflow
 * legend color matching each line color
 * automatic color assignment if not provided
 * support for multiple scales (right, left, middle1, middle2, histogram)
-* accepts df,pd.series or vectorbtpro indicator object (including unpacking multi outputs)
+* accepts df,pd.series or `vectorbtpro indicator` object (including unpacking multi outputs)
 * new markers_set method allowing to set pd.series or dataframe as markers input
-* for quick display supports simple df/sr accessors `close.lw.plot()` for quick visualization of single panel chart
+* supports simple df/sr accessors `close.lw.plot()` for quick visualization of single panel chart
 * df accessor unpacks dataframe columns and display them accordingly (ohlcv as ohlcv, vwap on the right, rsi on the left scale etc.)
 * multipanes support `ch = chart([pane1, pane2], sync=True, title="Title", size="m")` to quickly display chart with N panes (`Panels`). Also supports syncing the Panels `sync=True` or using xloc.
   
@@ -44,13 +44,35 @@ ohlcv_complex_df.lw.plot() #df containing ohlcv and other columns
 ```
 ![alt text](image-5.png)
 ```python
-#quick few liner, displays close series with label "close" on right pricescale and rsi on left price scale, all on single Panel
+t1data.ohlcv.data["BAC"].lw.plot(left=[(t1mom,"mom"),(t1mom_tt.mom.loc[:, (20,"1T")],),(t1mom_tt.mom.loc[:, (20,"5T")],)]) #display ohlcv 1m data along with 1min momentum ind and 2 multiindexed indicators on 1M and 5m resolution on 5M (calculated as multiindex)
+
+#quickly plot vectorbtpro indicator on top of OHLCV data (with automatic unpacking)
+macd = vbt.indicator("talib:MACD").run(t1data.data["BAC"].close) 
+t1data.ohlcv.data["BAC"].lw.plot(auto_scale=macd)
+```
+![alt text](image-6.png)
+```python
+
+#ONE PANEL - quick few liner, displays close series with label "close" on right pricescale and rsi on left price scale, all on single Panel
 pane1 = Panel(
     right=[(close, "close")],
     left=[(rsi,"rsi")]
 )
 ch = chart([pane1])
 
+##ONE PANEL - quicker
+Panel(
+            auto_scale=[cdlbreakaway],
+            ohlcv=(t1data.ohlcv.data["BAC"],entries),
+            histogram=[],
+            right=[],
+            left=[],
+            middle1=[],
+            middle2=[]
+            ).chart(size="s")
+```
+![alt text](image-7.png)
+```python
 # display two Panels
 # on first displays ohlcv data, orderimbalance volume as histogram with opacity, bbands on the right pricescale and
 # sma with short_signals and short_exits on the left pricescale

lightweight_charts/abstract.py

@@ -245,9 +245,12 @@ class SeriesCommon(Pane):
         if format_cols:
             df = self._df_datetime_format(df, exclude_lowercase=self.name)
         if self.name:
-            if self.name not in df:
+            if self.name and len(df.columns) == 1: #if only one col rename it
+                df.columns = ['value']
+            elif self.name not in df:
                 raise NameError(f'No column named "{self.name}".')
-            df = df.rename(columns={self.name: 'value'})
+            else:
+                df = df.rename(columns={self.name: 'value'})
         self.data = df.copy()
         self._last_bar = df.iloc[-1]
         self.run_script(f'{self.id}.series.setData({js_data(df)}); ')
@@ -646,7 +649,7 @@ class Candlestick(SeriesCommon):
         super().__init__(chart)
         self._volume_up_color = 'rgba(83,141,131,0.8)'
         self._volume_down_color = 'rgba(200,127,130,0.8)'
-
+        self.num_decimals = 2
         self.candle_data = pd.DataFrame()
 
         # self.run_script(f'{self.id}.makeCandlestickSeries()')
@@ -750,11 +753,25 @@ class Candlestick(SeriesCommon):
         text_color: Optional[str] = None,
         entire_text_only: bool = False,
         visible: bool = True,
-        ticks_visible: bool = False,
+        ticks_visible: bool = True,
         minimum_width: int = 0
     ):
+
+    # def precision(self, precision: int):
+    #     """
+    #     Sets the precision and minMove.\n
+    #     :param precision: The number of decimal places.
+    #     """
+    #     min_move = 1 / (10**precision)
+    #     self.run_script(f'''
+    #     {self.id}.series.applyOptions({{
+    #         priceFormat: {{precision: {precision}, minMove: {min_move}}}
+    #     }})''')
+    #     self.num_decimals = precision
+
         self.run_script(f'''
             {self.id}.series.priceScale().applyOptions({{
+                priceFormat: {{ precision: 3, minMove: 0.005 }},
                 autoScale: {jbool(auto_scale)},
                 mode: {as_enum(mode, PRICE_SCALE_MODE)},
                 invertScale: {jbool(invert_scale)},
@@ -985,7 +1002,7 @@ class AbstractChart(Candlestick, Pane):
 
     def legend(self, visible: bool = False, ohlc: bool = True, percent: bool = True, lines: bool = True,
                color: str = 'rgb(191, 195, 203)', font_size: int = 11, font_family: str = 'Monaco',
-               text: str = '', color_based_on_candle: bool = False):
+               text: str = '', color_based_on_candle: bool = True):
         """
         Configures the legend of the chart.
         """

lightweight_charts/helpers.py

@@ -1,16 +1,46 @@
+from ast import parse
 from .widgets import JupyterChart
 from .util import (
     is_vbt_indicator, get_next_color
 )
 import pandas as pd
 
+#default settings for each pricescale
+ohlcv_cols = ['close', 'volume', 'open', 'high', 'low']
+right_cols = ['vwap']
+left_cols = ['rsi', 'cci', 'macd', 'macdsignal', "chopiness", "chopiness_ma"]
+middle1_cols = ["mom"]
+middle2_cols = ["updated", "integer"]
+histogram_cols = ['buyvolume', 'sellvolume', 'trades', 'macdhist']
+
+def append_scales(df, right, histogram, left, middle1, middle2, name = ""):
+    if isinstance(df, pd.DataFrame):
+        for col in df.columns:
+                match col:
+                    case c if c.lower() in ohlcv_cols:
+                            continue
+                    case c if c.lower() in right_cols:
+                        right.append((df[c],name+c,))
+                    case c if c.lower() in histogram_cols:
+                        histogram.append((df[c],name+c,))
+                    case c if c.lower() in left_cols:
+                        left.append((df[c],name+c,))
+                    case c if c.lower() in middle1_cols:
+                        middle1.append((df[c],name+c,))
+                    case c if c.lower() in middle2_cols:
+                        middle2.append((df[c],name+c,))
+                    case _:
+                        right.append((df[c],name+c,))
+    else: #it is series (as df multiindex can be just envelope for series)
+            right.append((df,str(df.name),))
+
 def append_or_extend(target_list, value):
     if isinstance(value, list):
         target_list.extend(value)  # Extend if it's a list
     else:
         target_list.append(value)  # Append if it's a single value
 
-def extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, kwargs):
+def extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, auto_scale, kwargs):
     """
     Mutate lists based on kwargs for accessor.
     Used when user added additional series to kwargs when using accessor.
@@ -26,7 +56,9 @@ def extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, kwargs):
     if 'middle1' in kwargs:
         append_or_extend(middle1, kwargs['middle1'])         
     if 'middle2' in kwargs:
-        append_or_extend(middle1, kwargs['middle2'])   
+        append_or_extend(middle2, kwargs['middle2'])
+    if 'auto_scale' in kwargs:
+        append_or_extend(auto_scale, kwargs['auto_scale'])    
 
     return ohlcv #as tuple is immutable
 
@@ -59,6 +91,7 @@ class PlotSRAccessor:
     def plot(self, **kwargs):
         if "size" not in kwargs:
             kwargs["size"] = "xs"
+        name = kwargs["name"] if "name" in kwargs else "line"
              
         ohlcv = ()
         right = []
@@ -66,14 +99,16 @@ class PlotSRAccessor:
         middle1 = []
         middle2 = []
         histogram = []
+        auto_scale = []
 
         #if there are additional series in kwargs add them too
         #ohlcv is returned as it is tuple thus immutable
-        ohlcv = extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, kwargs)
+        ohlcv = extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, auto_scale, kwargs)
 
-        right.append((self._obj,"line"))
+        right.append((self._obj,name))
 
         pane1 = Panel(
+            auto_scale=auto_scale,
             ohlcv=ohlcv,
             histogram=histogram,
             right=right,
@@ -124,39 +159,36 @@ class PlotDFAccessor:
         if "size" not in kwargs:
             kwargs["size"] = "xs"
 
-        #default settings for each pricescale
-        ohlcv_cols = ['close', 'volume', 'open', 'high', 'low']
-        right_cols = ['vwap']
-        left_cols = ['rsi']
-        middle1_cols = []
-        middle2_cols = []
-        histogram_cols = ['buyvolume', 'sellvolume', 'trades']
-        
         ohlcv = ()
         right = []
         left = []
         middle1 = []
         middle2 = []
         histogram = []
+        auto_scale = []
                  
-        for col in self._obj.columns:
-             if col in right_cols:
-                  right.append((self._obj[col],col,))
-             if col in histogram_cols:
-                  histogram.append((self._obj[col],col,))
-             if col in left_cols:
-                  left.append((self._obj[col],col,))
-             if col in middle1_cols:
-                  middle1_cols.append((self._obj[col],col,))
-             if col in middle2_cols:
-                  middle2_cols.append((self._obj[col],col,))
+        if isinstance(self._obj.columns, pd.MultiIndex):
+            for col_tuple in self._obj.columns:
+                # Access the data for each column tuple dynamically
+                df = self._obj.loc[:, col_tuple]
+                name = str(col_tuple)+" "
+                append_scales(df, right, histogram, left, middle1, middle2, name)
+            first_column_df = self._obj.loc[:, self._obj.columns[0]]
+            ohlcv = (first_column_df[ohlcv_cols],) if isinstance(first_column_df, pd.DataFrame) and first_column_df.columns in ohlcv else () #in case of multiindex only the first ohlcv is display only one ohlcv is allowed on the pane
 
-        ohlcv = (self._obj[ohlcv_cols],)
+        else:
+            append_scales(self._obj, right, histogram, left, middle1, middle2)
+            #add ohlcv if all columns ohlcv_cols
+            #column mapping enables either both lowercase and first upper
+            column_mapping = {key: next((col for col in self._obj.columns if col.lower() == key), None) for key in ohlcv_cols}
+            mapped_columns = [column_mapping[key] for key in ohlcv_cols if column_mapping[key] is not None]
+            ohlcv = (self._obj[mapped_columns],) if isinstance(self._obj, pd.DataFrame) and all(col in self._obj.columns.str.lower() for col in ohlcv_cols) else ()
             
         #if there are additional series in kwargs add them too
-        ohlcv = extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, kwargs)
+        ohlcv = extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, auto_scale, kwargs)
 
         pane1 = Panel(
+            auto_scale=auto_scale,
             ohlcv=ohlcv,
             histogram=histogram,
             right=right,
@@ -195,6 +227,7 @@ class Panel:
     * left : list of tuples, optional
     * middle1 : list of tuples, optional
     * middle2 : list of tuples, optional
+    * auto_scale: list of objects, optional - external objects (vbt indicators) that can be automatically parsed to given scaleID
     * xloc : str or slice, optional. Vectorbt indexing. Default is None.
     * precision: int, optional. The number of digits after the decimal point. Apply to all lines on this pane. Default is None.
 
@@ -213,6 +246,18 @@ class Panel:
 
     ch = chart([pane1])
 
+    # or simply:
+    
+    Panel(
+            auto_scale=[cdlbreakaway],
+            ohlcv=(t1data.ohlcv.data["BAC"],entries),
+            histogram=[],
+            right=[],
+            left=[],
+            middle1=[],
+            middle2=[]
+            ).chart(size="s")
+
     # Synced example
     pane1 = Panel(
         ohlcv=(t1data.data["BAC"],),  #(series, entries, exits, other_markers)
@@ -226,6 +271,7 @@ class Panel:
     )
 
     pane2 = Panel(
+        auto_scale=[macd_vbt_ind],
         ohlcv=(t1data.data["BAC"],),
         right=[],
         left=[(sma, "sma_below", short_signals, short_exits)],
@@ -257,7 +303,8 @@ class Panel:
     ch = chart([pane1], title="Chart with EntryShort/ExitShort (yellow) and EntryLong/ExitLong markers (pink)", sync=True, session=None, size="s")
     ```
     """
-    def __init__(self, ohlcv=None, right=None, left=None, middle1=None, middle2=None, histogram=None, title=None, xloc=None, precision=None):
+    def __init__(self, auto_scale=[],ohlcv=None, right=None, left=None, middle1=None, middle2=None, histogram=None, title=None, xloc=None, precision=None):
+        self.auto_scale = auto_scale
         self.ohlcv = ohlcv if ohlcv is not None else ()
         self.right = right if right is not None else []
         self.left = left if left is not None else []
@@ -268,8 +315,10 @@ class Panel:
         self.xloc = xloc
         self.precision = precision
 
+    def chart(self, **kwargs):
+        chart([self], **kwargs)
     
-def chart(panes: list[Panel], sync=False, title='', size="m", xloc=None, session: str="9:30:00, 09:30:05", precision=None, **kwargs):
+def chart(panes: list[Panel], sync=False, title='', size="s", xloc=None, session = slice("09:30:00","9:30:05"), precision=None, params_detail=False, **kwargs):
     """
     Function to fast render a chart with multiple panes. This function manipulates graphical
     output or interfaces with an external framework to display charts with synchronized
@@ -295,6 +344,8 @@ def chart(panes: list[Panel], sync=False, title='', size="m", xloc=None, session
 
         * precision (int): The number of digits after the decimal point. Defaults to None. Applies to lines on all panes, if not overriden by pane-specific precision.
 
+        * params_detail (bool): If True displays in the legend full names of multiindex columns.
+
         * xloc (str): xloc advanced filtering of vbt.xloc accessor. Defaults to None. Applies to all panes.
         Might be overriden by pane-specific xloc.
             
@@ -381,6 +432,79 @@ def chart(panes: list[Panel], sync=False, title='', size="m", xloc=None, session
                     active_chart.markers_set(markers=xloc_me(markers, xloc), type=type, color=color if color is not None else None)                  
 
 
+            def add_to_scale(series, right, histogram, left, middle1, middle2, column,name = None):
+                """
+                Assigns a series to a scaleId based on its name and pre-defined col names.
+                
+                Args:
+                -----
+                    series (pd.Series): The series to be added to a scaleId
+                    right (list): The right scale to add to
+                    histogram (list): The histogram scale to add to
+                    left (list): The left scale to add to
+                    middle1 (list): The middle1 scale to add to
+                    middle2 (list): The middle2 scale to add to
+                    name (str): The name of the series
+                    
+                Returns:
+                -------
+                    None
+                
+                Notes:
+                -----
+                The function checks if the series name is in the pre-defined column names 
+                (e.g. ohlcv_cols, right_cols, histogram_cols, etc.) and assigns the series to 
+                the corresponding scaleId. If the name is not found in any of the pre-defined 
+                column names, the series is added to the right scale by default.
+                """
+                if name is None:
+                     name = column
+                if column.lower() in ohlcv_cols:
+                    return
+                elif column.lower() in right_cols:
+                    right.append((series, name,))
+                elif column.lower() in histogram_cols:
+                    histogram.append((series, name))
+                elif column.lower() in left_cols:
+                    left.append((series, name))
+                elif column.lower() in middle1_cols:
+                    middle1.append((series, name))
+                elif column.lower() in middle2_cols:
+                    middle2.append((series, name))
+                else:
+                    right.append((series, name,))
+
+            # automatic scale assignment
+            if len(pane.auto_scale) > 0:
+                 for obj in pane.auto_scale:
+                    if is_vbt_indicator(obj): #for vbt indicators
+                        for output in obj.output_names:
+                            output_series = getattr(obj, output)
+                            output_name = obj.short_name + ':' + output
+                            output = obj.short_name if output == "real" else output
+                            #if output_series is multiindex - add each combination to respective scaleId
+                            if isinstance(output_series, pd.DataFrame) and isinstance(output_series.columns, pd.MultiIndex):
+                                for col_tuple in output_series.columns:
+                                    name=output_name + " " + str(col_tuple)
+                                    series_copy = output_series.loc[:, col_tuple].copy(deep=True)
+                                    add_to_scale(series_copy, pane.right, pane.histogram, pane.left, pane.middle1, pane.middle2, output, name)
+                            elif isinstance(output_series, pd.DataFrame): #in case of multicolumns
+                                for col in output_series.columns:
+                                    name=output_name + " " + col
+                                    series_copy = output_series.loc[:, col].copy(deep=True)
+                                    add_to_scale(series_copy, pane.right, pane.histogram, pane.left, pane.middle1, pane.middle2, output, name)
+                            # elif isinstance(output_series, pd.DataFrame): #it df with multiple columns (probably symbols)
+                            #     for col in output_series.columns:
+                            #         name=output_name + " " + col
+                            #         series_copy = output_series[col].squeeze()
+                            #         add_to_scale(series_copy, pane.right, pane.histogram, pane.left, pane.middle1, pane.middle2, output, name)
+                            else: #add output to respective scale
+                                series_copy = output_series.copy(deep=True)
+                                add_to_scale(series_copy, pane.right, pane.histogram, pane.left, pane.middle1, pane.middle2, output, output_name)
+                                
+                    # zde jsem skoncil
+                    #vbt ind
+
             if pane.ohlcv != ():
                     series, entries, exits, markers = (pane.ohlcv + (None,) * 4)[:4]
                     if series is None:
@@ -403,8 +527,19 @@ def chart(panes: list[Panel], sync=False, title='', size="m", xloc=None, session
                             kwargs['color'] = color 
                     if opacity is not None:
                             kwargs['opacity'] = opacity
-                    tmp = active_chart.create_histogram(**kwargs) #green transparent "rgba(53, 94, 59, 0.6)"
-                    tmp.set(xloc_me(series, xloc))
+                    if isinstance(series, pd.DataFrame) and isinstance(series.columns, pd.MultiIndex): #multiindex handling
+                        for col_tuple in series.columns:
+                            kwargs = {'name': name + str(col_tuple)}
+                            tmp = active_chart.create_histogram(**kwargs) #green transparent "rgba(53, 94, 59, 0.6)"
+                            tmp.set(xloc_me(series.loc[:, col_tuple], xloc))
+                    elif isinstance(series, pd.DataFrame): #it df with multiple columns (probably symbols)
+                        for col in series.columns:
+                            kwargs = {'name': name + str(col)}
+                            tmp = active_chart.create_histogram(**kwargs) #green transparent "rgba(53, 94, 59, 0.6)"
+                            tmp.set(xloc_me(series[col], xloc))                      
+                    else:
+                        tmp = active_chart.create_histogram(**kwargs) #green transparent "rgba(53, 94, 59, 0.6)"
+                        tmp.set(xloc_me(series, xloc))
 
             if pane.title is not None:
                     active_chart.topbar.textbox("title",pane.title)
@@ -412,7 +547,7 @@ def chart(panes: list[Panel], sync=False, title='', size="m", xloc=None, session
 
             #iterate over keys - they are all priceScaleId except of these
             for att_name, att_value_tuple in vars(pane).items():
-                    if att_name in ["ohlcv","histogram","title","xloc","precision"]:
+                    if att_name in ["ohlcv","histogram","title","xloc","precision", "auto_scale"]:
                             continue
                     for tup in att_value_tuple:
                             series, name, entries, exits, markers = (tup + (None, None, None, None, None))[:5]
@@ -424,12 +559,71 @@ def chart(panes: list[Panel], sync=False, title='', size="m", xloc=None, session
                                 series = series.xloc[xloc] if xloc is not None else series
                                 for output in series.output_names:
                                     output_series = getattr(series, output)
-                                    output = name + ':' + output if name is not None else output       
-                                    tmp = active_chart.create_line(name=output, priceScaleId=att_name)#, color="blue")
-                                    tmp.set(output_series)
+                                    output = name + ':' + output if name is not None else series.short_name + ":" + output  
+                                    #if output_series is multiindex - create aline for each combination
+                                    if isinstance(output_series, pd.DataFrame) and isinstance(output_series.columns, pd.MultiIndex):
+                                        for col_tuple in output_series.columns:
+
+                                            tmp = active_chart.create_line(name=output + " " + str(col_tuple), priceScaleId=att_name)#, color="blue")
+                                            tmp.set(output_series.loc[:, col_tuple])
+                                    elif isinstance(output_series, pd.DataFrame): #it df with multiple columns (probably symbols)
+                                        for col in output_series.columns:
+                                            tmp = active_chart.create_line(name=output + " " + str(col), priceScaleId=att_name)#, color="blue")
+                                            tmp.set(output_series[col])                            
+                                    else:  
+                                        tmp = active_chart.create_line(name=output, priceScaleId=att_name)#, color="blue")
+                                        tmp.set(output_series)
+                            #if multiindex then unpack them all with tuple as names
+                            elif isinstance(series, pd.DataFrame) and isinstance(series.columns, pd.MultiIndex):
+                                for col_tuple in series.columns:
+                                    #if required show all multiindex names
+                                    if params_detail:   
+                                        # Access MultiIndex level names
+                                        index_names = series.columns.names
+                                        # Build the name string by combining level names and their corresponding values
+                                        col_name_str = " ".join([f"{index_names[i]}: {col_val}" for i, col_val in enumerate(col_tuple)])
+                                        # Use this name in the chart, adding the provided name if it exists
+                                        final_name = col_name_str if name is None else f"{name} {col_name_str}"
+                                    else:
+                                        final_name = str(col_tuple) if name is None else name+" "+str(col_tuple)
+                                    tmp = active_chart.create_line(name=final_name, priceScaleId=att_name)#, color="blue")
+                                    tmp.set(xloc_me(series.loc[:, col_tuple], xloc))
+                            elif isinstance(series, pd.DataFrame): #it df with multiple columns (probably symbols)
+                                
+                        #recursive df handling - but make sure it
+                                def traverse_dataframe(series, att_name, xloc, active_chart, name=""):
+                                    nonlocal tmp
+                                    # Check if the input is a DataFrame
+                                    if isinstance(series, pd.DataFrame):
+                                        for col in series.columns:
+                                            col_name = name + " " + col if name else col
+                                            # Recursively call the function for each column
+                                            traverse_dataframe(series[col], att_name, xloc, active_chart, col_name)
+                                    elif isinstance(series, pd.Series):
+                                        # Once we hit the series level, create the result_name and call the active_chart method
+                                        result_name = name.strip()  # Remove any leading/trailing spaces from column name
+                                        result_series = series.squeeze()  # Extract the series data
+
+                                        # Now call the `active_chart.create_line()` as per your requirement
+                                        tmp = active_chart.create_line(name=result_name, priceScaleId=att_name)
+                                        tmp.set(xloc_me(result_series, xloc))  # Call the xloc_me function for setting xloc
+
+                                    else:
+                                        raise ValueError(f"Unexpected type {type(series)} encountered")
+                                    
+                                if name is None:
+                                      name = "no_name" if not hasattr(series, 'name') or series.name is None else str(series.name)
+
+                                traverse_dataframe(series, att_name, xloc, active_chart, name)
+
+                                # for col in series.columns:
+                                #     name=name + " " + col 
+                                #     series_copy = output_series[col].squeeze()
+                                #     tmp = active_chart.create_line(name=name, priceScaleId=att_name)#, color="blue")
+                                #     tmp.set(xloc_me(series_copy, xloc))
                             else:
                                 if name is None:
-                                      name = "no_name"
+                                      name = "no_name" if not hasattr(series, 'name') or series.name is None else str(series.name)
 
                                 tmp = active_chart.create_line(name=name, priceScaleId=att_name)#, color="blue")
                                 tmp.set(xloc_me(series, xloc))
@@ -447,8 +641,22 @@ def chart(panes: list[Panel], sync=False, title='', size="m", xloc=None, session
             active_chart.legend(True)
             active_chart.fit()
             if session is not None and session:
-                last_used_series = output_series if is_vbt_indicator(series) else series #pokud byl posledni series vbt, pak pouzijeme jeho outputy
-                active_chart.vertical_span(start_time=xloc_me(last_used_series, xloc).vbt.xloc[session].obj.index.to_list(), color="rgba(252, 255, 187, 0.42)")
+                try:
+                    last_used_series = output_series.loc[:, col_tuple] if isinstance(output_series, pd.DataFrame) and isinstance(output_series.columns, pd.MultiIndex) else output_series if is_vbt_indicator(series) else series #pokud byl posledni series vbt, pak pouzijeme jeho outputy
+                    last_used_series = last_used_series.iloc[:,0] if isinstance(last_used_series, pd.DataFrame) else last_used_series #if df then use just first column
+                    t1 = xloc_me(last_used_series, xloc)
+                    t1 = t1.vbt.xloc[session]
+                    target_data = t1.obj
+                    #we dont know the exact time of market start +- 3 seconds thus we find mark first row after 9:30
+                    # Resample the data to daily frequency and get the first entry of each day
+                    first_row_indexes = target_data.resample('D').apply(lambda x: x.index[0] if not x.empty else None).dropna()
+
+                    # Convert the indexes to a list
+                    session_starts = first_row_indexes.to_list()
+
+                    active_chart.vertical_span(start_time=session_starts, color="rgba(252, 255, 187, 0.42)")
+                except Exception as e:
+                    print("Error fetching main session")
 
     if not main_title_set:
             chartX.topbar.textbox("title",title)

lightweight_charts/util.py

@@ -113,7 +113,7 @@ def is_vbt_indicator(variable):
     # Get the module path of the variable's type
     module_path = variable.__class__.__module__
     # Check if it starts with 'vectorbtpro.indicators'
-    return module_path.startswith('vectorbtpro.indicators')
+    return module_path.startswith('vectorbtpro.indicators') or module_path.startswith('indicators.')
 
 class Pane:
     def __init__(self, window):

setup.py

@@ -5,7 +5,7 @@ with open('README.md', 'r', encoding='utf-8') as f:
 
 setup(
     name='lightweight_charts',
-    version='2.2.0',
+    version='2.2.29',
     packages=find_packages(),
     python_requires='>=3.8',
     install_requires=[

src/general/handler.ts

@@ -40,7 +40,7 @@ export class Handler {
 
     public chart: IChartApi;
     public scale: Scale;
-    public precision: number = 2;
+    public precision: number = 3;
 
     public series: ISeriesApi<SeriesType>;
     public volumeSeries: ISeriesApi<SeriesType>;

src/general/legend.ts

@@ -1,7 +1,6 @@
 import { ISeriesApi, LineData, Logical, MouseEventParams, PriceFormatBuiltIn, SeriesType } from "lightweight-charts";
 import { Handler } from "./handler";
 
-
 interface LineElement {
     name: string;
     div: HTMLDivElement;
@@ -14,6 +13,11 @@ interface LineElement {
 export class Legend {
     private handler: Handler;
     public div: HTMLDivElement;
+    public contentWrapper: HTMLDivElement;
+    private collapseButton: HTMLDivElement;
+    private toggleAllButton: HTMLDivElement;
+    private isCollapsed: boolean = false;
+    private allVisible: boolean = true;
 
     private ohlcEnabled: boolean = false;
     private percentEnabled: boolean = false;
@@ -24,7 +28,6 @@ export class Legend {
     private candle: HTMLDivElement;
     public _lines: LineElement[] = [];
 
-
     constructor(handler: Handler) {
         this.legendHandler = this.legendHandler.bind(this)
     
@@ -36,62 +39,203 @@ export class Legend {
     
         this.div = document.createElement('div');
         this.div.classList.add('legend');
-        this.div.style.maxWidth = `${(handler.scale.width * 100) - 8}vw`
+        this.div.style.maxWidth = '300px';
+        this.div.style.minWidth = '200px';
+        this.div.style.maxHeight = '300px';
+        this.div.style.overflowY = 'auto';
+        this.div.style.overflowX = 'hidden';
+        this.div.style.position = 'absolute';
+        this.div.style.backgroundColor = 'rgba(19, 23, 34, 0)';
+        this.div.style.color = '#D1D4DC';
+        this.div.style.padding = '1px';
+        this.div.style.borderRadius = '4px';
+        //this.div.style.border = '1px solid rgba(42, 46, 57, 0.85)';
+        this.div.style.boxShadow = '0 2px 5px rgba(0,0,0,0.3)';
+        this.div.style.fontFamily = '-apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif';
+        this.div.style.fontSize = '12px';
+        this.div.style.zIndex = '5';
         this.div.style.display = 'none';
+        this.div.style.pointerEvents = 'all';
 
-        this.text = document.createElement('span')
-        this.text.style.lineHeight = '1.8'
-        this.candle = document.createElement('div')
+        const buttonsContainer = document.createElement('div');
+        buttonsContainer.style.position = 'absolute';
+        buttonsContainer.style.right = '8px';
+        buttonsContainer.style.top = '8px';
+        buttonsContainer.style.display = 'flex';
+        buttonsContainer.style.gap = '2px';
+        buttonsContainer.style.zIndex = '6';
+        buttonsContainer.style.pointerEvents = 'all';
 
-        this.div.appendChild(this.text)
-        this.div.appendChild(this.candle)
-        handler.div.appendChild(this.div)
+        this.collapseButton = document.createElement('div');
+        this.collapseButton.style.cursor = 'pointer';
+        this.collapseButton.style.width = '20px';
+        this.collapseButton.style.height = '20px';
+        this.collapseButton.style.display = 'flex';
+        this.collapseButton.style.alignItems = 'center';
+        this.collapseButton.style.justifyContent = 'center';
+        this.collapseButton.style.color = '#D1D4DC';
+        this.collapseButton.style.fontSize = '16px';
+        this.collapseButton.style.userSelect = 'none';
+        this.collapseButton.style.pointerEvents = 'all';
+        this.collapseButton.innerHTML = '−';
+        this.collapseButton.addEventListener('click', (e) => {
+            e.stopPropagation();
+            this.toggleCollapse();
+        });
 
-        // this.makeSeriesRows(handler);
+        this.toggleAllButton = document.createElement('div');
+        this.toggleAllButton.style.cursor = 'pointer';
+        this.toggleAllButton.style.width = '20px';
+        this.toggleAllButton.style.height = '20px';
+        this.toggleAllButton.style.display = 'flex';
+        this.toggleAllButton.style.alignItems = 'center';
+        this.toggleAllButton.style.justifyContent = 'center';
+        this.toggleAllButton.style.color = '#D1D4DC';
+        this.toggleAllButton.style.fontSize = '14px';
+        this.toggleAllButton.style.userSelect = 'none';
+        this.toggleAllButton.style.pointerEvents = 'all';
+        this.toggleAllButton.innerHTML = '👁️';
+        this.toggleAllButton.title = 'Toggle all';
+        this.toggleAllButton.addEventListener('click', (e) => {
+            e.stopPropagation();
+            this.toggleAll();
+        });
+
+        buttonsContainer.appendChild(this.toggleAllButton);
+        buttonsContainer.appendChild(this.collapseButton);
+        
+        const style = document.createElement('style');
+        style.textContent = `
+            .legend::-webkit-scrollbar {
+                width: 6px;
+            }
+            .legend::-webkit-scrollbar-track {
+                background: #2A2E39;
+            }
+            .legend::-webkit-scrollbar-thumb {
+                background: #434651;
+                border-radius: 3px;
+            }
+            .legend::-webkit-scrollbar-thumb:hover {
+                background: #545861;
+            }
+            .legend-toggle-switch {
+                cursor: pointer;
+                margin-left: 8px;
+            }
+        `;
+        document.head.appendChild(style);
+        
+        this.contentWrapper = document.createElement('div');
+        this.contentWrapper.style.minHeight = '100%';
+        this.contentWrapper.style.width = '100%';
+        this.contentWrapper.style.display = 'flex';
+        this.contentWrapper.style.flexDirection = 'column';
+        this.contentWrapper.style.gap = '1px';
+        this.contentWrapper.style.marginTop = '20px';
+        this.contentWrapper.style.pointerEvents = 'all';
+    
+        this.text = document.createElement('span');
+        this.text.style.lineHeight = '1';
+        this.text.style.display = 'block';
+        this.text.style.color = '#D1D4DC';
+        
+        this.candle = document.createElement('div');
+        this.candle.style.color = '#D1D4DC';
+        this.candle.style.width = '100%';
+    
+        this.contentWrapper.appendChild(this.text);
+        this.contentWrapper.appendChild(this.candle);
+        this.div.appendChild(buttonsContainer);
+        this.div.appendChild(this.contentWrapper);
+        handler.div.appendChild(this.div);
     
         handler.chart.subscribeCrosshairMove(this.legendHandler)
     }
 
+    private toggleCollapse() {
+        this.isCollapsed = !this.isCollapsed;
+        
+        if (this.isCollapsed) {
+            this.contentWrapper.style.display = 'none';
+            this.div.style.maxHeight = '40px'; // Changed from 'auto' to fixed height for buttons
+            this.div.style.height = '40px';    // Added fixed height
+            this.collapseButton.innerHTML = '+';
+        } else {
+            this.contentWrapper.style.display = 'flex';
+            this.div.style.maxHeight = '300px';
+            this.div.style.height = 'auto';    // Reset height to auto
+            this.collapseButton.innerHTML = '−';
+        }
+    }
+
+    private toggleAll() {
+        this.allVisible = !this.allVisible;
+        
+        this._lines.forEach(line => {
+            line.series.applyOptions({
+                visible: this.allVisible
+            });
+
+            const group = line.toggle.querySelector('g');
+            if (group) {
+                if (this.allVisible) {
+                    group.innerHTML = this.openEyeSvg(line.solid);
+                } else {
+                    group.innerHTML = this.closedEyeSvg(line.solid);
+                }
+            }
+        });
+
+        this.toggleAllButton.style.opacity = this.allVisible ? '1' : '0.5';
+    }
+
+    private openEyeSvg(strokeColor: string): string {
+        return `
+            <path style="fill:none;stroke-width:2;stroke-linecap:round;stroke-linejoin:round;stroke:${strokeColor};stroke-opacity:1;stroke-miterlimit:4;" d="M 21.998437 12 C 21.998437 12 18.998437 18 12 18 C 5.001562 18 2.001562 12 2.001562 12 C 2.001562 12 5.001562 6 12 6 C 18.998437 6 21.998437 12 21.998437 12 Z M 21.998437 12 " transform="matrix(0.833333,0,0,0.833333,0,0)"/>
+            <path style="fill:none;stroke-width:2;stroke-linecap:round;stroke-linejoin:round;stroke:${strokeColor};stroke-opacity:1;stroke-miterlimit:4;" d="M 15 12 C 15 13.654687 13.654687 15 12 15 C 10.345312 15 9 13.654687 9 12 C 9 10.345312 10.345312 9 12 9 C 13.654687 9 15 10.345312 15 12 Z M 15 12 " transform="matrix(0.833333,0,0,0.833333,0,0)"/>
+        `;
+    }
+
+    private closedEyeSvg(strokeColor: string): string {
+        return `
+            <path style="fill:none;stroke-width:2;stroke-linecap:round;stroke-linejoin:round;stroke:${strokeColor};stroke-opacity:1;stroke-miterlimit:4;" d="M 20.001562 9 C 20.001562 9 19.678125 9.665625 18.998437 10.514062 M 12 14.001562 C 10.392187 14.001562 9.046875 13.589062 7.95 12.998437 M 12 14.001562 C 13.607812 14.001562 14.953125 13.589062 16.05 12.998437 M 12 14.001562 L 12 17.498437 M 3.998437 9 C 3.998437 9 4.354687 9.735937 5.104687 10.645312 M 7.95 12.998437 L 5.001562 15.998437 M 7.95 12.998437 C 6.689062 12.328125 5.751562 11.423437 5.104687 10.645312 M 16.05 12.998437 L 18.501562 15.998437 M 16.05 12.998437 C 17.38125 12.290625 18.351562 11.320312 18.998437 10.514062 M 5.104687 10.645312 L 2.001562 12 M 18.998437 10.514062 L 21.998437 12 " transform="matrix(0.833333,0,0,0.833333,0,0)"/>
+        `;
+    }
+
     toJSON() {
-        // Exclude the chart attribute from serialization
         const {_lines, handler, ...serialized} = this;
         return serialized;
     }
 
-    // makeSeriesRows(handler: Handler) {
-    //     if (this.linesEnabled) handler._seriesList.forEach(s => this.makeSeriesRow(s))
-    // }
-
     makeSeriesRow(name: string, series: ISeriesApi<SeriesType>) {
         const strokeColor = series.options().color;
-        let openEye = `
-    <path style="fill:none;stroke-width:2;stroke-linecap:round;stroke-linejoin:round;stroke:${strokeColor};stroke-opacity:1;stroke-miterlimit:4;" d="M 21.998437 12 C 21.998437 12 18.998437 18 12 18 C 5.001562 18 2.001562 12 2.001562 12 C 2.001562 12 5.001562 6 12 6 C 18.998437 6 21.998437 12 21.998437 12 Z M 21.998437 12 " transform="matrix(0.833333,0,0,0.833333,0,0)"/>
-    <path style="fill:none;stroke-width:2;stroke-linecap:round;stroke-linejoin:round;stroke:${strokeColor};stroke-opacity:1;stroke-miterlimit:4;" d="M 15 12 C 15 13.654687 13.654687 15 12 15 C 10.345312 15 9 13.654687 9 12 C 9 10.345312 10.345312 9 12 9 C 13.654687 9 15 10.345312 15 12 Z M 15 12 " transform="matrix(0.833333,0,0,0.833333,0,0)"/>\`
-    `
-        let closedEye = `
-    <path style="fill:none;stroke-width:2;stroke-linecap:round;stroke-linejoin:round;stroke:${strokeColor};stroke-opacity:1;stroke-miterlimit:4;" d="M 20.001562 9 C 20.001562 9 19.678125 9.665625 18.998437 10.514062 M 12 14.001562 C 10.392187 14.001562 9.046875 13.589062 7.95 12.998437 M 12 14.001562 C 13.607812 14.001562 14.953125 13.589062 16.05 12.998437 M 12 14.001562 L 12 17.498437 M 3.998437 9 C 3.998437 9 4.354687 9.735937 5.104687 10.645312 M 7.95 12.998437 L 5.001562 15.998437 M 7.95 12.998437 C 6.689062 12.328125 5.751562 11.423437 5.104687 10.645312 M 16.05 12.998437 L 18.501562 15.998437 M 16.05 12.998437 C 17.38125 12.290625 18.351562 11.320312 18.998437 10.514062 M 5.104687 10.645312 L 2.001562 12 M 18.998437 10.514062 L 21.998437 12 " transform="matrix(0.833333,0,0,0.833333,0,0)"/>
-    `
-
         let row = document.createElement('div')
         row.style.display = 'flex'
         row.style.alignItems = 'center'
+        row.style.padding = '0px 0'
+        row.style.color = '#D1D4DC'
+        row.style.width = '100%'
+        row.style.pointerEvents = 'all'
+        row.style.cursor = 'default'
+
         let div = document.createElement('div')
+        div.style.flex = '1'
         let toggle = document.createElement('div')
         toggle.classList.add('legend-toggle-switch');
 
-
         let svg = document.createElementNS("http://www.w3.org/2000/svg", "svg");
         svg.setAttribute("width", "22");
         svg.setAttribute("height", "16");
 
         let group = document.createElementNS("http://www.w3.org/2000/svg", "g");
-        group.innerHTML = openEye
+        group.innerHTML = this.openEyeSvg(strokeColor);
 
         let on = true
         toggle.addEventListener('click', () => {
             if (on) {
                 on = false
-                group.innerHTML = closedEye
+                group.innerHTML = this.closedEyeSvg(strokeColor);
                 series.applyOptions({
                     visible: false
                 })
@@ -100,7 +244,7 @@ export class Legend {
                 series.applyOptions({
                     visible: true
                 })
-                group.innerHTML = openEye
+                group.innerHTML = this.openEyeSvg(strokeColor);
             }
         })
 
@@ -108,7 +252,7 @@ export class Legend {
         toggle.appendChild(svg);
         row.appendChild(div)
         row.appendChild(toggle)
-        this.div.appendChild(row)
+        this.contentWrapper.appendChild(row)
 
         const color = series.options().color;
         this._lines.push({
@@ -121,7 +265,9 @@ export class Legend {
         });
     }
 
-    legendItemFormat(num: number, decimal: number) { return num.toFixed(decimal).toString().padStart(8, ' ') }
+    legendItemFormat(num: number, decimal: number) { 
+        return num.toFixed(decimal).toString().padStart(8, ' ') 
+    }
 
     shorthandFormat(num: number) {
         const absNum = Math.abs(num)
@@ -132,7 +278,6 @@ export class Legend {
         }
         return num.toString().padStart(8, ' ');
     }
-
     legendHandler(param: MouseEventParams, usingPoint= false) {
         if (!this.ohlcEnabled && !this.linesEnabled && !this.percentEnabled) return;
         const options: any = this.handler.series.options()
@@ -159,7 +304,7 @@ export class Legend {
         }
     
         this.candle.style.color = ''
-        let str = '<span style="line-height: 1.8;">'
+        let str = '<span style="line-height: 1.0;">'
         if (data) {
             if (this.ohlcEnabled) {
                 str += `O ${this.legendItemFormat(data.open, this.handler.precision)} `
@@ -209,13 +354,13 @@ export class Legend {
             else {
                 data = param.seriesData.get(e.series) as LineData
             }
-            if (!data?.value) return;
+            if (data === undefined || data.value === undefined) return;
             let price;
             if (e.series.seriesType() == 'Histogram') {
                 price = this.shorthandFormat(data.value)
             } else {
                 const format = e.series.options().priceFormat as PriceFormatBuiltIn
-                price = this.legendItemFormat(data.value, format.precision)   // couldn't this just be line.options().precision?
+                price = this.legendItemFormat(data.value, format.precision)
             }
             e.div.innerHTML = `<span style="color: ${e.solid};">▨ ${e.name} : ${price}</span>`
         })