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exoearth_vis_bokeh0.12.py
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exoearth_vis_bokeh0.12.py
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''' Present an interactive function explorer with slider widgets.
Scrub the sliders to change the properties of the ``sin`` curve, or
type into the title text box to update the title of the plot.
Use the ``bokeh serve`` command to run the example by executing:
bokeh serve sliders.py
at your command prompt. Then navigate to the URL
http://localhost:5006/sliders
in your browser.
this is run by typing "bokeh serve --show myapp.py" on the command line
'''
import numpy as np
import math
from astropy.table import Table
import copy
from bokeh.io import output_file, gridplot
from bokeh.plotting import Figure
from bokeh.resources import CDN
from bokeh.client import push_session
from bokeh.embed import components, file_html
from bokeh.models import ColumnDataSource, HoverTool, Range1d
from bokeh.layouts import Column, Row, WidgetBox
from bokeh.models.glyphs import Text
from bokeh.models.widgets import Slider, TextInput
from bokeh.io import hplot, vplot, curdoc
from bokeh.models.callbacks import CustomJS
targets = Table.read('data/stark_yields/run_12.0_1.00E-10_1.5_0.10_3.0.fits')
targets['TESTCOLOR'] = 'red'
col = copy.deepcopy(targets['TYPE'][0])
col[:] = 'black'
col[np.where(targets['COMPLETENESS'][0] > 0.2)] = 'red'
col[np.where(targets['COMPLETENESS'][0] > 0.5)] = 'yellow'
col[np.where(targets['COMPLETENESS'][0] > 0.8)] = 'lightgreen'
totyield = np.sum(targets['COMPLETENESS'][0] * 0.1)
star_points = ColumnDataSource(data=dict(x=targets['X'][0], y=targets['Y'][0], r=targets['DISTANCE'][0], \
stype=targets['TYPE'][0], hip=targets['HIP'][0], color=col, complete=targets['COMPLETENESS'][0]))
rad_circles = ColumnDataSource(data=dict(x=np.array([0., 0., 0., 0.]), y=np.array([0., 0., 0., 0.]), cfrac=[0., 0., 0., 0.], fillcolor=['black', 'black','black','0.342']))
# Set up plot
plot1 = Figure(plot_height=800, plot_width=800, x_axis_type = None, y_axis_type = None,
tools="pan,reset,resize,save,box_zoom,wheel_zoom", outline_line_color='black',
x_range=[-50, 50], y_range=[-50, 50], toolbar_location='right')
hover = HoverTool(names=["star_points_to_hover"], mode='mouse', point_policy="snap_to_data",
tooltips = """
<div>
<div>
<span style="font-size: 15px; font-weight: bold; color: #696">HIP</span>
<span style="font-size: 17px; font-weight: bold; color: #696">@hip</span>
</div>
<div>
<span style="font-size: 17px; font-weight: bold; color: #696">@stype</span>
<span style="font-size: 15px; font-weight: bold; color: #696">type</span>
</div>
<div>
<span style="font-size: 15px; font-weight: bold; color: #696">D = </span>
<span style="font-size: 15px; font-weight: bold; color: #696;">@r</span>
<span style="font-size: 15px; font-weight: bold; color: #696;"> pc</span>
</div>
<div>
<span style="font-size: 15px; font-weight: bold; color: #696">C = </span>
<span style="font-size: 15px; font-weight: bold; color: #696;">@complete</span>
</div>
</div>
"""
)
plot1.add_tools(hover)
hover = plot1.select(dict(type=HoverTool))
plot1.x_range=Range1d(-50,50,bounds=(-50,50))
plot1.y_range=Range1d(-50,50,bounds=(-50,50))
plot1.background_fill_color = "black"
plot1.background_fill_alpha = 1.0
plot1.yaxis.axis_label = 'Yield'
plot1.xaxis.axis_label = ' '
plot1.xaxis.axis_line_width = 0
plot1.yaxis.axis_line_width = 0
plot1.xaxis.axis_line_color = 'black'
plot1.yaxis.axis_line_color = 'black'
plot1.border_fill_color = "black"
plot1.min_border_left = 80
# main glyphs for planet circles
plot1.circle('x', 'y', source=star_points, name="star_points_to_hover", \
fill_color='color', line_color='color', radius=0.5, line_alpha=0.5, fill_alpha=0.7)
plot1.text(0.95*0.707*np.array([10., 20., 30., 40.]), 0.707*np.array([10., 20., 30., 40.]), \
text=['10 pc', '20 pc', '30 pc', '40 pc'], text_color="white", text_font_style='bold', text_font_size='12pt', text_alpha=0.8)
plot1.text([48.5], [47], ['Chance Of Detecting'], text_color="white", text_align="right", text_alpha=1.0)
plot1.text([48.5], [44.5], ['an Earth Twin if Present'], text_color="white", text_align="right", text_alpha=1.0)
plot1.text([48.5], [44.5], ['___________________'], text_color="white", text_align="right", text_alpha=1.0)
plot1.text(np.array([48.5]), np.array([41.5]), ["80-100%"], text_color='lightgreen', text_align="right")
plot1.text(np.array([48.5]), np.array([41.5-1*2.4]), ["50-80%"], text_color='yellow', text_align="right")
plot1.text(np.array([48.5]), np.array([41.5-2*2.4]), ["20-50%"], text_color='red', text_align="right")
plot1.text(np.array([48.5]), np.array([41.5-3*2.4]), ["Not Observed"], text_color='black', text_align="right")
plot1.circle([0], [0], radius=0.1, fill_alpha=1.0, line_color='white', fill_color='white')
plot1.circle([0], [0], radius=0.5, fill_alpha=0.0, line_color='white')
sym = plot1.circle('x', 'y', source=rad_circles, fill_color='fillcolor', line_color='white',
line_width=4, radius=[40,30,20,10], line_alpha=0.8, fill_alpha=0.0)
sym.glyph.line_dash = [6, 6]
junk_points = ColumnDataSource(data=dict(x=np.array([0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]), y=np.array([0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0])))
plot2 = Figure(plot_height=400, plot_width=450, tools="pan,resize, reset,save", outline_line_color='black',
x_range=[0, 20], y_range=[0, 1], toolbar_location='right', title='Detections of 10% Phenomena')
plot2.title.text_font_size = '14pt'
plot2.background_fill_color = "beige"
plot2.background_fill_alpha = 0.5
plot2.yaxis.axis_label = 'Probability'
plot2.xaxis.axis_label = 'Number of Detections'
plot2.xaxis.axis_line_width = 2
plot2.yaxis.axis_line_width = 2
plot2.xaxis.axis_line_color = 'black'
plot2.yaxis.axis_line_color = 'black'
plot2.border_fill_color = "white"
plot2.min_border_left = 0
plot2.circle('x', 'y', source=junk_points, \
fill_color='purple', radius=0.1, line_alpha=0.5, fill_alpha=1.0)
plot2.line('x', 'y', source=junk_points, line_color='purple', line_alpha=0.5)
rect_points = ColumnDataSource(data=dict(top=[totyield/2.-50., 9000, 9000], bottom=[-49.8, 8800, 8800], left=[-49.8, 8800, 9000], strbag=' ', right=[-45, 8800, 9200]))
plot1.quad(top="top", bottom="bottom", left="left", right="right", source=rect_points, color="lightgreen", fill_alpha=0.5, line_alpha=0.)
plot1.quad(top=49.9, bottom=-49.9, left=-49.8, right=-45, line_color="lightgreen", line_width=3, fill_alpha=0.0) # open box
plot1.circle([-47.4], 'top',source=rect_points, radius=1.8, fill_alpha=0.5, fill_color='lightgreen')
plot1.text([-47.5], [-50], ['0'], text_color="white", text_align="center")
plot1.text([-47.5], [-25], ['50'], text_color="white", text_align="center")
plot1.text([-47.5], [0], ['100'], text_color="white", text_align="center")
plot1.text([-47.5], [25], ['150'], text_color="white", text_align="center")
plot1.text([-47.5], [47], ['200'], text_color="white", text_align="center")
plot1.text([-42.5], [47], ['ExoEarth Yield'], text_color="white", text_align="left")
def update_data(attrname, old, new):
# Get the current slider values
a = aperture.value
c = contrast.value
i = iwa.value
print 'APERTURE A = ', a, ' CONTRAST C = ', c, ' IWA I = ', i
apertures = {'4.0':'4.0','4':'4.0','8':'8.0','12':'12.0','12.0':'12.0','16':'16.0', '20':'20.0'}
contrasts = {'-11':'1.00E-11','-10':'1.00E-10','-9':'1.00E-09'}
targets = Table.read('data/stark_yields/'+'run_'+apertures[str(a)]+'_'+contrasts[str(c)]+'_1.5_0.10_3.0.fits')
star_points.data['complete'] = np.array(targets['COMPLETENESS'][0])
# total yields updated here
col = copy.deepcopy(targets['TYPE'][0])
col[:] = 'black'
col[np.where(targets['COMPLETENESS'][0] > 0.2)] = 'red'
col[np.where(targets['COMPLETENESS'][0] > 0.5)] = 'yellow'
col[np.where(targets['COMPLETENESS'][0] > 0.8)] = 'lightgreen'
star_points.data['color'] = col
yield_now = np.sum(targets['COMPLETENESS'][0]) * 0.1
rect_points.data['top'] = np.array([yield_now,a,a])/2. - 50.
rect_points.data['strbag'] = str(np.sum(np.array(targets['COMPLETENESS'][0])))
# can simply modify star_points, no need to regenerate it from scratch
d = np.random.binomial(yield_now, 0.1, 10000)
d0 = np.size(np.where(d == 0)) / 10000.
d1 = np.size(np.where(d == 1)) / 10000.
d2 = np.size(np.where(d == 2)) / 10000.
d3 = np.size(np.where(d == 3)) / 10000.
d4 = np.size(np.where(d == 4)) / 10000.
d5 = np.size(np.where(d == 5)) / 10000.
d6 = np.size(np.where(d == 6)) / 10000.
d7 = np.size(np.where(d == 7)) / 10000.
d8 = np.size(np.where(d == 8)) / 10000.
d9 = np.size(np.where(d == 9)) / 10000.
d10= np.size(np.where(d == 10)) / 10000.
d11= np.size(np.where(d == 11)) / 10000.
d12= np.size(np.where(d == 12)) / 10000.
d13= np.size(np.where(d == 13)) / 10000.
d14= np.size(np.where(d == 14)) / 10000.
d15= np.size(np.where(d == 15)) / 10000.
d16= np.size(np.where(d == 16)) / 10000.
d17= np.size(np.where(d == 17)) / 10000.
d18= np.size(np.where(d == 18)) / 10000.
d19= np.size(np.where(d == 19)) / 10000.
d20= np.size(np.where(d == 20)) / 10000.
junk_points.data['y'] = np.array([d0,d1,d2,d3,d4,d5,d6,d7,d8,d9,d10,d11,d12,d13,d14,d15,d16,d17,d18,d19,d20])
source = ColumnDataSource(data=dict(value=[]))
source.on_change('data', update_data)
# Set up widgets
aperture= Slider(title="Aperture (meters)", value=12., start=4., end=20.0, step=4.0, callback_policy='mouseup')
aperture.callback = CustomJS(args=dict(source=source), code="""
source.data = { value: [cb_obj.value] }
""")
contrast = Slider(title="Log (Contrast)", value=-10, start=-11.0, end=-9, step=1.0, callback_policy='mouseup')
contrast.callback = CustomJS(args=dict(source=source), code="""
source.data = { value: [cb_obj.value] }
""")
iwa = Slider(title="Inner Working Angle (l/D)", value=1.5, start=1.5, end=4.0, step=0.5, callback_policy='mouseup')
iwa.callback = CustomJS(args=dict(source=source), code="""
source.data = { value: [cb_obj.value] }
""")
# iterate on changes to parameters
#for w in [aperture, contrast]:
# w.on_change('value', update_data)
# Set up layouts and add to document
inputs = Column(children=[aperture, contrast, plot2])
curdoc().add_root(Row(children=[inputs, plot1], width=1800))
curdoc().add_root(source)