volumes to ticks
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Dobromir Popov
parent
158f9ebf71
commit
2beb1d8cef
218
realtime.py
218
realtime.py
@ -1321,6 +1321,16 @@ class RealTimeChart:
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total_volume = sum(volumes)
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avg_volume = total_volume / len(volumes) if volumes else 0
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# Calculate additional volume stats
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max_volume = max(volumes) if volumes else 0
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min_volume = min(volumes) if volumes else 0
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median_volume = sorted(volumes)[len(volumes)//2] if volumes else 0
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# Calculate trade value in USDT
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trade_values = [p * v for p, v in zip(prices, volumes)]
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total_value = sum(trade_values)
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avg_trade_value = total_value / len(trade_values) if trade_values else 0
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first_timestamp = filtered_ticks[0]['timestamp']
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last_timestamp = filtered_ticks[-1]['timestamp']
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time_span_ms = last_timestamp - first_timestamp
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@ -1383,6 +1393,18 @@ class RealTimeChart:
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html.Div("Total Volume", style=label_style),
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html.Div(f"{total_volume:.8f}", style=value_style),
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html.Div(f"Avg: {avg_volume:.8f}", style=label_style)
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], style=card_style),
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html.Div([
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html.Div("Max Volume", style=label_style),
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html.Div(f"{max_volume:.8f}", style=value_style),
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html.Div("Median: {:.8f}".format(median_volume), style=label_style)
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], style=card_style),
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html.Div([
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html.Div("Total Value", style=label_style),
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html.Div(f"{total_value:.2f}", style=value_style),
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html.Div(f"Avg: {avg_trade_value:.2f}", style=label_style)
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], style=card_style)
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]
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@ -1499,8 +1521,14 @@ class RealTimeChart:
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# Get filtered ticks
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filtered_ticks = self.tick_storage.get_ticks_from_time(start_time_ms=start_time)
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# Create figure
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fig = go.Figure()
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# Create figure with 2 subplots - price and volume
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fig = make_subplots(
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rows=2, cols=1,
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shared_xaxes=True,
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vertical_spacing=0.03,
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row_heights=[0.7, 0.3],
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subplot_titles=(f"Price Movement (Last {window_seconds // 60} minutes)", "Volume")
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)
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if not filtered_ticks:
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fig.add_annotation(
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@ -1516,31 +1544,101 @@ class RealTimeChart:
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prices = [tick['price'] for tick in filtered_ticks]
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volumes = [tick.get('volume', 0) for tick in filtered_ticks]
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# Scale volumes for better visibility
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max_volume = max(volumes) if volumes else 1
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scaled_volumes = [vol * (max(prices) - min(prices)) / max_volume * 0.2 + min(prices) for vol in volumes]
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# Add price scatter plot
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fig.add_trace(
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go.Scatter(
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x=timestamps,
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y=prices,
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mode='lines',
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name='Price',
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line=dict(color='#4CAF50', width=1.5)
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),
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row=1, col=1
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)
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# Add price line
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fig.add_trace(go.Scatter(
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x=timestamps,
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y=prices,
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mode='lines',
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name='Price',
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line=dict(color='#4CAF50', width=1.5)
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))
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# Create a volume profile on the right side of the price chart
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if len(prices) > 5: # Only create profile if we have enough data
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# Group prices into bins
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price_min = min(prices)
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price_max = max(prices)
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# Create approximately 20 bins based on price range
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bin_size = max(0.01, (price_max - price_min) / 20)
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# Create a dictionary to hold volume by price level
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volume_by_price = {}
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# Group volumes by price bins
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for p, v in zip(prices, volumes):
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bin_key = round(p / bin_size) * bin_size
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if bin_key in volume_by_price:
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volume_by_price[bin_key] += v
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else:
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volume_by_price[bin_key] = v
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# Sort by price level
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sorted_bins = sorted(volume_by_price.items())
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profile_prices = [p for p, _ in sorted_bins]
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profile_volumes = [v for _, v in sorted_bins]
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# Add separate volume profile trace
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fig.add_trace(
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go.Bar(
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y=profile_prices,
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x=profile_volumes,
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orientation='h',
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name='Volume Profile',
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marker=dict(
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color=['#33CC33' if p <= latest_price else '#FF4136' for p in profile_prices],
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opacity=0.5
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),
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showlegend=True,
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hovertemplate='Price: %{y:.2f}<br>Volume: %{x:.8f}<extra></extra>'
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),
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row=1, col=1
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)
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# Add a line marking the latest price
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fig.add_shape(
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type="line",
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y0=latest_price, y1=latest_price,
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x0=0, x1=max(profile_volumes) * 1.1,
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line=dict(color="yellow", width=1, dash="dash"),
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row=1, col=1
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)
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# Add volume bars
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fig.add_trace(go.Bar(
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x=timestamps,
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y=scaled_volumes,
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name='Volume',
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marker=dict(color='rgba(128, 128, 255, 0.3)'),
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opacity=0.5,
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yaxis='y2'
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))
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# Add volume bars in separate subplot
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# Color volume bars green for price increases, red for decreases
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if len(timestamps) > 1:
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# Compare each price with the previous to determine color
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colors = []
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for i in range(len(prices)):
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if i == 0:
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colors.append('#33CC33') # Default to green for first tick
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else:
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if prices[i] >= prices[i-1]:
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colors.append('#33CC33') # Green for price increase/same
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else:
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colors.append('#FF4136') # Red for price decrease
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else:
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colors = ['#33CC33'] # Default green if only one tick
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fig.add_trace(
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go.Bar(
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x=timestamps,
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y=volumes,
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name='Volume',
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marker=dict(color=colors)
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),
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row=2, col=1
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)
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# Compute stats for annotations
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latest_price = prices[-1] if prices else 0
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total_volume = sum(volumes)
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max_volume = max(volumes) if volumes else 0
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avg_volume = total_volume / len(volumes) if volumes else 0
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# Add annotations for latest price
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latest_price = prices[-1] if prices else 0
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fig.add_annotation(
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x=timestamps[-1] if timestamps else 0,
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y=latest_price,
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@ -1551,41 +1649,63 @@ class RealTimeChart:
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arrowwidth=2,
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arrowcolor="#4CAF50",
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font=dict(size=12, color="#4CAF50"),
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xshift=50
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xshift=50,
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row=1, col=1
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)
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# Add annotations for volume stats
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fig.add_annotation(
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x=timestamps[-1] if timestamps else 0,
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y=max_volume,
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text=f"Max: {max_volume:.8f}",
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showarrow=False,
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font=dict(size=10, color="rgba(128, 128, 255, 1)"),
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xshift=50,
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row=2, col=1
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)
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# Update layout
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fig.update_layout(
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title=f"{self.symbol} Price Movement (Last {window_seconds // 60} minutes)",
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title_text=f"{self.symbol} Tick Data",
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title_x=0.5,
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xaxis=dict(
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title="Time",
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showgrid=True,
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gridcolor='rgba(128,128,128,0.2)'
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),
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yaxis=dict(
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title="Price (USDT)",
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showgrid=True,
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gridcolor='rgba(128,128,128,0.2)'
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),
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yaxis2=dict(
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title="Volume",
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overlaying='y',
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side='right',
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showgrid=False,
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showticklabels=False
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),
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template='plotly_dark',
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paper_bgcolor='rgba(0,0,0,0)',
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plot_bgcolor='rgba(25,25,50,1)',
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height=500,
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margin=dict(l=40, r=40, t=50, b=40),
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height=600, # Increased height for better visualization
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margin=dict(l=40, r=40, t=80, b=40),
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legend=dict(
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yanchor="top",
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y=0.99,
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xanchor="left",
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x=0.01
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)
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orientation="h",
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yanchor="bottom",
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y=1.02,
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xanchor="right",
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x=1
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),
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hovermode="x unified" # Show all data points at the same x-coordinate
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)
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# Update x-axis to be shared
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fig.update_xaxes(
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showgrid=True,
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gridwidth=1,
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gridcolor='rgba(128,128,128,0.2)',
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rangeslider_visible=False
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)
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# Update y-axes
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fig.update_yaxes(
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title_text="Price (USDT)",
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showgrid=True,
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gridwidth=1,
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gridcolor='rgba(128,128,128,0.2)',
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row=1, col=1
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)
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fig.update_yaxes(
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title_text="Volume",
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showgrid=True,
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gridwidth=1,
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gridcolor='rgba(128,128,128,0.2)',
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row=2, col=1
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)
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return fig
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