-
Notifications
You must be signed in to change notification settings - Fork 8
/
Copy pathvisualization.py
184 lines (133 loc) · 6.45 KB
/
visualization.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
import requests
from bokeh.plotting import figure
from bokeh.palettes import Category20
from bokeh.models.widgets import PreText
from bokeh.models import BooleanFilter, CDSView, BoxAnnotation, Band, Span, Select, LinearAxis, DataRange1d, Range1d
from bokeh.models.formatters import PrintfTickFormatter, NumeralTickFormatter
WIDTH_PLOT = 1500
RED = Category20[7][6]
GREEN = Category20[5][4]
BLUE = Category20[3][0]
BLUE_LIGHT = Category20[3][1]
ORANGE = Category20[3][2]
PURPLE = Category20[9][8]
BROWN = Category20[11][10]
TOOLS = 'pan,wheel_zoom,reset'
# Main chart for stock prices with candlestick and Bolinger bands
def plot_stock_price(stock):
p = figure(x_axis_type="datetime", plot_width=WIDTH_PLOT, plot_height=400,
title="Stock price + Bollinger Bands (2 std)",
tools=TOOLS, toolbar_location='above')
inc = stock.data['close'] > stock.data['open']
dec = stock.data['open'] > stock.data['close']
view_inc = CDSView(source=stock, filters=[BooleanFilter(inc)])
view_dec = CDSView(source=stock, filters=[BooleanFilter(dec)])
width = 35000000
p.segment(x0='date', x1='date', y0='low', y1='high', color=RED, source=stock, view=view_inc)
p.segment(x0='date', x1='date', y0='low', y1='high', color=GREEN, source=stock, view=view_dec)
p.vbar(x='date', width=width, top='open', bottom='close', fill_color=RED, line_color=RED,
source=stock,
view=view_inc)
p.vbar(x='date', width=width, top='open', bottom='close', fill_color=GREEN, line_color=GREEN,
source=stock,
view=view_dec)
# p.line(x='date', y='close_line', line_width=1, color=BLUE, line_alpha=0.7, souce=stock)
band = Band(base='date', lower='bolling_lower', upper='bolling_upper', source=stock, level='underlay',
fill_alpha=0.5, line_width=1, line_color='black', fill_color=BLUE_LIGHT)
p.add_layout(band)
code = """
def ticker():
return "{:.0f} + {:.2f}".format(tick, tick % 1)
"""
p.yaxis.formatter = NumeralTickFormatter(format='$ 0,0[.]000')
return p
# Simple Moving Average
def plot_sma(stock):
p = figure(x_axis_type="datetime", plot_width=WIDTH_PLOT, plot_height=300,
title="Simple Moving Average (press the legend to hide/show lines)",
tools=TOOLS, toolbar_location='above')
p.line(x='date', y='SMA_5', line_width=2, color=BLUE, source=stock, legend='5 days', muted_color=BLUE,
muted_alpha=0.2)
p.line(x='date', y='SMA_10', line_width=2, color=ORANGE, source=stock, legend='10 days', muted_color=ORANGE,
muted_alpha=0.2)
p.line(x='date', y='SMA_50', line_width=2, color=PURPLE, source=stock, legend='50 days', muted_color=PURPLE,
muted_alpha=0.2)
p.line(x='date', y='SMA_100', line_width=2, color=BROWN, source=stock, legend='100 days', muted_color=BROWN,
muted_alpha=0.2)
p.legend.location = "bottom_left"
p.legend.border_line_alpha = 0
p.legend.background_fill_alpha = 0
p.legend.click_policy = "mute"
p.yaxis.formatter = NumeralTickFormatter(format='$ 0,0[.]000')
return p
# MACD (line + histogram)
def plot_macd(stock):
p = figure(x_axis_type="datetime", plot_width=WIDTH_PLOT, plot_height=200, title="MACD (line + histogram)",
tools=TOOLS, toolbar_location='above')
up = [True if val > 0 else False for val in stock.data['macd_histogram']]
down = [True if val < 0 else False for val in stock.data['macd_histogram']]
view_upper = CDSView(source=stock, filters=[BooleanFilter(up)])
view_lower = CDSView(source=stock, filters=[BooleanFilter(down)])
p.vbar(x='date', top='macd_histogram', bottom='zeros', width=30000000, color=GREEN, source=stock, view=view_upper)
p.vbar(x='date', top='zeros', bottom='macd_histogram', width=30000000, color=RED, source=stock, view=view_lower)
# Adding an extra range for the MACD lines, because using the same axis as the histogram
# sometimes flattens them too much
p.extra_y_ranges = {'macd': DataRange1d()}
p.add_layout(LinearAxis(y_range_name='macd'), 'right')
p.line(x='date', y='macd', line_width=2, color=BLUE, source=stock, legend='MACD', muted_color=BLUE,
muted_alpha=0, y_range_name='macd')
p.line(x='date', y='macd_signal', line_width=2, color=BLUE_LIGHT, source=stock, legend='Signal',
muted_color=BLUE_LIGHT, muted_alpha=0, y_range_name='macd')
p.legend.location = "bottom_left"
p.legend.border_line_alpha = 0
p.legend.background_fill_alpha = 0
p.legend.click_policy = "mute"
p.yaxis.ticker = []
p.yaxis.axis_line_alpha = 0
return p
# RSI
def plot_rsi(stock):
p = figure(x_axis_type="datetime", plot_width=WIDTH_PLOT, plot_height=200, title="RSI 15 days",
tools=TOOLS, toolbar_location='above')
p.line(x='date', y='rsi_15', line_width=2, color=BLUE, source=stock)
low_box = BoxAnnotation(top=30, fill_alpha=0.1, fill_color=RED)
p.add_layout(low_box)
high_box = BoxAnnotation(bottom=70, fill_alpha=0.1, fill_color=GREEN)
p.add_layout(high_box)
# Horizontal line
hline = Span(location=50, dimension='width', line_color='black', line_width=0.5)
p.renderers.extend([hline])
p.y_range = Range1d(0, 100)
p.yaxis.ticker = [30, 50, 70]
p.yaxis.formatter = PrintfTickFormatter(format="%f%%")
p.grid.grid_line_alpha = 0.3
return p
#### On-Balance Volume (OBV)
def plot_obv(stock):
p = figure(x_axis_type="datetime", plot_width=WIDTH_PLOT, plot_height=200, title="On-Balance Volume (OBV)",
tools=TOOLS, toolbar_location='above')
p.line(x='date', y='OBV', line_width=2, color=BLUE, source=stock)
p.yaxis.ticker = []
p.yaxis.axis_line_alpha = 0
return p
#### Volume line
def plot_volume(stock):
p = figure(x_axis_type="datetime", plot_width=WIDTH_PLOT, plot_height=200, title="Volume", tools=TOOLS,
toolbar_location='above')
p.line(x='date', y='volume', line_width=2, color=BLUE, source=stock)
return p
#### Plot of symbols to choose TICKET
def widget_symbols():
# Get all symbols
all_stocks_call = 'https://api.iextrading.com/1.0/ref-data/symbols'
response = requests.get(all_stocks_call)
respon = response.json()
symbols = []
for e in respon:
if e['type'] != 'N/A':
symbols.append(e['symbol'])
select_ticket = Select(value="AAPL", options=symbols)
return select_ticket
def widget_show_text(text):
pre = PreText(text=text, width=500, height=10)
return pre