df and sr accessor enhancements
This commit is contained in:
David Brazda
@ -2,4 +2,4 @@ from .abstract import AbstractChart, Window
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from .chart import Chart
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from .widgets import JupyterChart
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from .polygon import PolygonChart
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from .helpers import chart, Panel, PlotAccessor
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from .helpers import chart, Panel, PlotSRAccessor, PlotDFAccessor
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@ -4,15 +4,54 @@ from .util import (
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)
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import pandas as pd
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def append_or_extend(target_list, value):
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if isinstance(value, list):
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target_list.extend(value) # Extend if it's a list
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else:
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target_list.append(value) # Append if it's a single value
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def extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, kwargs):
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"""
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Mutate lists based on kwargs for accessor.
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Used when user added additional series to kwargs when using accessor.
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"""
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if 'ohlcv' in kwargs:
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ohlcv = kwargs['ohlcv'] #ohlcv is only a tuple
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if 'left' in kwargs:
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append_or_extend(left, kwargs['left'])
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if 'right' in kwargs:
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append_or_extend(right, kwargs['right'])
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if 'histogram' in kwargs:
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append_or_extend(histogram, kwargs['histogram'])
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if 'middle1' in kwargs:
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append_or_extend(middle1, kwargs['middle1'])
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if 'middle2' in kwargs:
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append_or_extend(middle1, kwargs['middle2'])
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return ohlcv #as tuple is immutable
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# Register the custom accessor
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@pd.api.extensions.register_series_accessor("lw")
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class PlotAccessor:
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class PlotSRAccessor:
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"""
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Custom plot accessor for pandas series.
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Custom plot accessor for pandas series. Quickly displays series values as line on the single pane.
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Also additional priceseries can be added on top of them. They can be added
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for each scale in the correct format - either as tuple(OHLCV) or as list of tuple (others)
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# input parameter / expected format:
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# ohlcv=(), #(series, entries, exits, other_markers)
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# histogram=[], # [(series, name, "rgba(53, 94, 59, 0.6)", opacity)]
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# right=[],
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# left=[], #[(series, name, entries, exits, other_markers)]
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# middle1=[],
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# middle2=[],
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Usage: s
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series.lw.plot()
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series.lw.plot(size="m")
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series.lw.plot() #plot series as line
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series.lw.plot(size="m") #on medium panesize
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series.lw.plot(histogram=(trade_series, "trades")) #plot histogram with trades on top of that
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"""
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def __init__(self, pandas_obj):
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self._obj = pandas_obj
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@ -20,11 +59,123 @@ class PlotAccessor:
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def plot(self, **kwargs):
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if "size" not in kwargs:
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kwargs["size"] = "xs"
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ohlcv = ()
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right = []
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left = []
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middle1 = []
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middle2 = []
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histogram = []
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#if there are additional series in kwargs add them too
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#ohlcv is returned as it is tuple thus immutable
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ohlcv = extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, kwargs)
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right.append((self._obj,"line"))
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pane1 = Panel(
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right=[(self._obj, "line")],
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)
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ohlcv=ohlcv,
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histogram=histogram,
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right=right,
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left=left,
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middle1=middle1,
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middle2=middle2
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)
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ch = chart([pane1], **kwargs)
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@pd.api.extensions.register_dataframe_accessor("lw")
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class PlotDFAccessor:
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"""
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Custom plot accessor for dataframe. Quickly displays all columns on the single pane.
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Series type is automatically extracted for each column based on following setting:
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scale / columns
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ohlcv = ['close', 'volume', 'open', 'high', 'low']
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right = ['vwap']
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left = ['rsi']
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middle1 = []
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middle2 = []
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histogram = ['buyvolume', 'sellvolume', 'trades']
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Also additional priceseries can be added on top of them as parameters. They can be added
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for each scale in the correct format - either as tuple(OHLCV) or as list of tuple (others)
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# input parameter / expected format:
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# ohlcv=(), #(series, entries, exits, other_markers)
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# histogram=[], # [(series, name, "rgba(53, 94, 59, 0.6)", opacity)]
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# right=[],
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# left=[], #[(series, name, entries, exits, other_markers)]
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# middle1=[],
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# middle2=[],
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Usage:
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ohlcv_df.lw.plot()
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ohlcv_df.lw.plot(size="m")
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ohlcv_df.lw.plot(right=(rsi_series, "rsi"))
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ohlcv_df.lw.plot(right=[(rsi_series, "rsi"), (angle_series, "angle")])
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basic_data.data[SYMBOL].lw.plot(histogram=(basic_data.data[SYMBOL].close, "close"), size="m")
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"""
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def __init__(self, pandas_obj):
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self._obj = pandas_obj
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def plot(self, **kwargs):
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if "size" not in kwargs:
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kwargs["size"] = "xs"
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#default settings for each pricescale
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ohlcv_cols = ['close', 'volume', 'open', 'high', 'low']
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right_cols = ['vwap']
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left_cols = ['rsi']
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middle1_cols = []
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middle2_cols = []
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histogram_cols = ['buyvolume', 'sellvolume', 'trades']
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ohlcv = ()
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right = []
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left = []
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middle1 = []
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middle2 = []
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histogram = []
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for col in self._obj.columns:
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if col in right_cols:
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right.append((self._obj[col],col,))
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if col in histogram_cols:
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histogram.append((self._obj[col],col,))
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if col in left_cols:
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left.append((self._obj[col],col,))
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if col in middle1_cols:
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middle1_cols.append((self._obj[col],col,))
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if col in middle2_cols:
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middle2_cols.append((self._obj[col],col,))
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ohlcv = (self._obj[ohlcv_cols],)
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#if there are additional series in kwargs add them too
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ohlcv = extend_kwargs(ohlcv, right, left, middle1, middle2, histogram, kwargs)
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pane1 = Panel(
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ohlcv=ohlcv,
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histogram=histogram,
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right=right,
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left=left,
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middle1=middle1,
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middle2=middle2
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)
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ch = chart([pane1], **kwargs)
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# pane1 = Panel(
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# ohlcv=(), #(series, entries, exits, other_markers)
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# histogram=[], # [(series, name, "rgba(53, 94, 59, 0.6)", opacity)]
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# right=[],
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# left=[], #[(series, name, entries, exits, other_markers)]
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# middle1=[],
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# middle2=[],
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# )
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class Panel:
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"""
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A class to represent a panel in a chart.
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@ -118,7 +269,7 @@ class Panel:
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self.precision = precision
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def chart(panes: list[Panel], sync=False, title='', size="m", xloc=None, session: str="9:30:00, 09:30:05", precision=None):
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def chart(panes: list[Panel], sync=False, title='', size="m", xloc=None, session: str="9:30:00, 09:30:05", precision=None, **kwargs):
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"""
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Function to fast render a chart with multiple panes. This function manipulates graphical
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output or interfaces with an external framework to display charts with synchronized
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