def histogram_plot(states,
height,
width,
data_top,
data_source,
n_ticks,
n_minor_ticks=0,
fill_color=None):
'''Create a bokeh histogram using quad shapes'''
from bokeh.plotting import Figure
# Create histogram object
hist_obj = Figure(plot_height=height,
plot_width=width,
title="",
toolbar_location=None)
# Data top is string of var name from data_source
fill_color = '#f0f5f5' if fill_color == None else fill_color
hist_obj.quad(top=data_top,
bottom=0,
source=data_source,
left="left",
right="right",
fill_color=fill_color,
line_color='black')
# set number of major and minor ticks
hist_obj.xaxis[0].ticker.desired_num_ticks = n_ticks
hist_obj.xaxis[0].ticker.num_minor_ticks = n_minor_ticks
hist_obj.y_range = Range1d(0, 1)
hist_obj.x_range = Range1d(states[0] - 0.5, states[-1] + 0.5)
return hist_obj
def make_precipitation_plot(source):
plot = Figure(x_axis_type="datetime",
plot_width=1000,
plot_height=125,
min_border_left=50,
min_border_right=50,
min_border_top=0,
min_border_bottom=0,
toolbar_location=None)
plot.title = None
plot.quad(top='actual_precipitation',
bottom=0,
left='left',
right='right',
color=Greens4[1],
source=source)
# fixed attributes
plot.border_fill_color = "whitesmoke"
plot.yaxis.axis_label = "Precipitation (in)"
plot.axis.major_label_text_font_size = "8pt"
plot.axis.axis_label_text_font_size = "8pt"
plot.axis.axis_label_text_font_style = "bold"
plot.x_range = DataRange1d(range_padding=0.0, bounds=None)
plot.y_range = DataRange1d(range_padding=0.0, bounds=None)
plot.grid.grid_line_alpha = 0.3
plot.grid[0].ticker.desired_num_ticks = 12
return plot
def performance():
plot = Figure(x_axis_type="datetime", tools="save", toolbar_location=None, plot_width=1000, plot_height=300)
l1 = plot.line(x="time", y="power_out", source=source_perfomance, line_color="green", name="local")
plot.add_tools(HoverTool(renderers=[l1]))
plot.select(dict(type=HoverTool)).tooltips = [("Date", "@hover_time"), ("Performance", "@power_out")]
l2 = plot.line(x="time", y="avg_perf", source=source_perfomance, line_color="red", name="global")
plot.x_range = DataRange1d(range_padding=0.0, bounds=None)
plot.title = "Plant Performance"
return plot
def createPlots():
######################################## BS Pressure Plot ########################################
sourceBuySell, sourceVolume = requestHoseData()
pBuySell = Figure(plot_width=PLOT_WIDTH, plot_height=BUYSELL_PLOT_HEIGHT, name="pltBuySell")
pBuySell.xaxis.ticker = [8.75, 9, 9.5, 10, 10.5, 11, 11.5, 13, 13.5, 14, 14.5, 14.75]
pBuySell.xaxis.major_label_overrides = {
8.5: "8:30", 8.75: "8:45", 9: "9:00", 9.5: "9:30", 10: "10:00",
10.5: "10:30", 11: "11:00", 11.5: "11:30", 13: "13:00",
13.5: "13:30", 14: "14:00", 14.5: "14:30", 14.75: "14:45"}
pBuySell.line(x='index', y='buyPressure', source=sourceBuySell, color='green',
legend_label="Tổng đặt mua", name="glyphSellPressure")
pBuySell.line(x='index', y='sellPressure', source=sourceBuySell, color='red',
legend_label="Tổng đặt bán", name="glyphBuyPressure")
wz = WheelZoomTool(dimensions="width"); pBuySell.add_tools(wz); pBuySell.toolbar.active_scroll = wz
pBuySell.toolbar.logo = None
pBuySell.axis[0].visible = False
pBuySell.legend.location = "top_left"
pBuySell.legend.click_policy = "hide"
pBuySell.legend.background_fill_alpha = 0.0
######################################## Volume Plot ########################################
pVolume = Figure(width=PLOT_WIDTH, height=VOLUME_PLOT_HEIGHT, tools="pan, reset",
name="pltVolume")
pVolume.toolbar.logo = None
wz = WheelZoomTool(dimensions="height"); pVolume.add_tools(wz); pVolume.toolbar.active_scroll = wz
pVolume.vbar(x='index', top='totalValue', width=1 /60, color='blue',
source=sourceVolume, fill_alpha=LIQUIDITY_ALPHA, line_alpha=LIQUIDITY_ALPHA,
name="glyphTotalValue", legend_label="Thanh khoản toàn tt")
pVolume.vbar(x='index', top='nnBuy', width=1/1.2/60, color='green', source=sourceVolume
,name="glyphNNBuy", legend_label="NN mua",)
pVolume.vbar(x='index', top='nnSell', width=1/1.2/60, color='red', source=sourceVolume
,name="glyphNNSell", legend_label="NN bán",)
pVolume.x_range = pBuySell.x_range
pVolume.y_range=Range1d(-10, 45)
pVolume.legend.location = "top_left"
pVolume.legend.click_policy = "hide"
pVolume.legend.background_fill_alpha = 0.0
######################################### OHLC plot #########################################
orders, source, pressure = requestPSData()
plotOhlc = createOhlcPlot(source)
pCandle, divCandle = hookupFigure(plotOhlc) # "divCustomJS" "pltOHLC" "glyphOHLCSegment"
pDebug = Paragraph(text=f"""["num_ps_orders": "{len(orders['index'])}"]\n"""
"""""",
width=DIV_TEXT_WIDTH, height=100, name="pDebug")
################################# Putting all plots together ################################
def activation_function():
pBuySell._document.add_periodic_callback(lambda: updateDoc(pBuySell._document), 500)
print("Document activated !")
return pCandle, pBuySell, pVolume, divCandle , activation_function, sourceBuySell, sourceVolume, pDebug
def make_plot(source, AverageTemp, Parcentile_5_Min, Parcentile_5_Max,
Parcentile_25_Min, Parcentile_25_Max, MinTemp, MaxTemp, plotDate,
cityName):
plot = Figure(title='Optional Task # 1 : Growing Degree-day for ' +
cityName,
x_axis_type="datetime",
plot_width=1000,
title_text_font_size='12pt',
tools="",
toolbar_location=None)
colors = Blues4[0:3]
plot.circle(MaxTemp,
MinTemp,
alpha=0.9,
color="#66ff33",
fill_alpha=0.2,
size=10,
source=source,
legend='2015')
plot.quad(top=Parcentile_5_Max,
bottom=Parcentile_5_Min,
left='left',
right='right',
source=source,
color="#e67300",
legend="Percentile 5-95")
plot.quad(top=Parcentile_25_Max,
bottom=Parcentile_25_Min,
left='left',
right='right',
source=source,
color="#66ccff",
legend="percentile 25-75")
plot.line(plotDate,
AverageTemp,
source=source,
line_color='Red',
line_width=0.75,
legend='AverageTemp')
plot.border_fill_color = "whitesmoke"
plot.xaxis.axis_label = "Months"
plot.yaxis.axis_label = "Temperature (C)"
plot.axis.major_label_text_font_size = "10pt"
plot.axis.axis_label_text_font_size = "12pt"
plot.axis.axis_label_text_font_style = "bold"
plot.x_range = DataRange1d(range_padding=0.0, bounds=None)
plot.grid.grid_line_alpha = 0.3
plot.grid[0].ticker.desired_num_ticks = 12
return plot
def utilization_bar(max_y):
plot = Figure(
plot_width=
150, # this is more for the ratio, because we have auto-width scaling
plot_height=150,
tools=[], # no tools needed for this one
title='Utilization')
plot.toolbar.logo = None # hides logo
plot.x_range = Range1d(0, 1)
plot.y_range = Range1d(
0,
max_y) # sometimes you want it to be way less than 1, to see it move
plot.xaxis.visible = False # hide x axis
# Add input buffer
manager = Manager()
plot._input_buffer = manager.dict()
return plot
def make_plot(source, title):
print("make plot")
plot = Figure(x_axis_type="datetime",
plot_width=1000,
tools="",
toolbar_location=None)
plot.title = title
colors = Blues4[0:3]
plot.quad(top='record_max_temp',
bottom='record_min_temp',
left='left',
right='right',
color=colors[2],
source=source,
legend="Record")
plot.quad(top='average_max_temp',
bottom='average_min_temp',
left='left',
right='right',
color=colors[1],
source=source,
legend="Average")
plot.quad(top='actual_max_temp',
bottom='actual_min_temp',
left='left',
right='right',
color=colors[0],
alpha=0.5,
line_color="black",
source=source,
legend="Actual")
# fixed attributes
plot.border_fill_color = "whitesmoke"
plot.xaxis.axis_label = None
plot.yaxis.axis_label = "Temperature (F)"
plot.axis.major_label_text_font_size = "8pt"
plot.axis.axis_label_text_font_size = "8pt"
plot.axis.axis_label_text_font_style = "bold"
plot.x_range = DataRange1d(range_padding=0.0, bounds=None)
plot.grid.grid_line_alpha = 0.3
plot.grid[0].ticker.desired_num_ticks = 12
return plot
def make_precipitation_plot(source):
plot = Figure(x_axis_type="datetime", plot_width=1000, plot_height=125, min_border_left=50, min_border_right=50, min_border_top=0, min_border_bottom=0, toolbar_location=None)
plot.title = None
plot.quad(top='actual_precipitation', bottom=0, left='left', right='right', color=Greens4[1], source=source)
# fixed attributes
plot.border_fill_color = "whitesmoke"
plot.yaxis.axis_label = "Precipitation (in)"
plot.axis.major_label_text_font_size = "8pt"
plot.axis.axis_label_text_font_size = "8pt"
plot.axis.axis_label_text_font_style = "bold"
plot.x_range = DataRange1d(range_padding=0.0, bounds=None)
plot.y_range = DataRange1d(range_padding=0.0, bounds=None)
plot.grid.grid_line_alpha = 0.3
plot.grid[0].ticker.desired_num_ticks = 12
return plot
def make_plot(source,AverageTemp,Parcentile_5_Min,Parcentile_5_Max,Parcentile_25_Min,Parcentile_25_Max,MinTemp,MaxTemp,plotDate,cityName):
plot = Figure(title='Optional Task # 1 : Growing Degree-day for '+cityName, x_axis_type="datetime", plot_width=1000, title_text_font_size='12pt', tools="", toolbar_location=None)
colors = Blues4[0:3]
plot.circle(MaxTemp,MinTemp, alpha=0.9, color="#66ff33", fill_alpha=0.2, size=10,source=source,legend ='2015')
plot.quad(top=Parcentile_5_Max, bottom=Parcentile_5_Min, left='left',right='right',
source=source,color="#e67300", legend="Percentile 5-95")
plot.quad(top=Parcentile_25_Max, bottom=Parcentile_25_Min,left='left',right='right',
source=source,color="#66ccff",legend="percentile 25-75")
plot.line(plotDate,AverageTemp,source=source,line_color='Red', line_width=0.75, legend='AverageTemp')
plot.border_fill_color = "whitesmoke"
plot.xaxis.axis_label = "Months"
plot.yaxis.axis_label = "Temperature (C)"
plot.axis.major_label_text_font_size = "10pt"
plot.axis.axis_label_text_font_size = "12pt"
plot.axis.axis_label_text_font_style = "bold"
plot.x_range = DataRange1d(range_padding=0.0, bounds=None)
plot.grid.grid_line_alpha = 0.3
plot.grid[0].ticker.desired_num_ticks = 12
return plot
def make_plot(source, title):
plot = Figure(x_axis_type="datetime", plot_width=1000, tools="", toolbar_location=None)
plot.title = title
colors = Blues4[0:3]
plot.quad(top='record_max_temp', bottom='record_min_temp', left='left', right='right', color=colors[2], source=source, legend="Record")
plot.quad(top='average_max_temp', bottom='average_min_temp', left='left', right='right', color=colors[1], source=source, legend="Average")
plot.quad(top='actual_max_temp', bottom='actual_min_temp', left='left', right='right', color=colors[0], alpha=0.5, line_color="black", source=source, legend="Actual")
# fixed attributes
plot.border_fill_color = "whitesmoke"
plot.xaxis.axis_label = None
plot.yaxis.axis_label = "Temperature (F)"
plot.axis.major_label_text_font_size = "8pt"
plot.axis.axis_label_text_font_size = "8pt"
plot.axis.axis_label_text_font_style = "bold"
plot.x_range = DataRange1d(range_padding=0.0, bounds=None)
plot.grid.grid_line_alpha = 0.3
plot.grid[0].ticker.desired_num_ticks = 12
return plot
def histogram_plot(states, height, width, data_top, data_source, n_ticks,
n_minor_ticks=0, fill_color=None):
'''Create a bokeh histogram using quad shapes'''
from bokeh.plotting import Figure
# Create histogram object
hist_obj = Figure(plot_height=height, plot_width=width, title="",
toolbar_location=None)
# Data top is string of var name from data_source
fill_color = '#f0f5f5' if fill_color==None else fill_color
hist_obj.quad(top=data_top, bottom=0, source=data_source, left="left",
right="right", fill_color=fill_color, line_color='black')
# set number of major and minor ticks
hist_obj.xaxis[0].ticker.desired_num_ticks = n_ticks
hist_obj.xaxis[0].ticker.num_minor_ticks = n_minor_ticks
hist_obj.y_range = Range1d(0, 1)
hist_obj.x_range = Range1d(states[0]-0.5, states[-1]+0.5)
return hist_obj
#sn = (spec_dict[template_to_start_with].flux * 1.e16 * 100. ) ** 0.5
signal_to_noise = simulate_exposure(luvoir, lumos, spec_dict[template_to_start_with].wave, spec_dict[template_to_start_with].flux, 1.0)
flux_cut = spec_dict[template_to_start_with].flux
flux_cut[spec_dict[template_to_start_with].wave < lumos.lambda_range[0]] = -999.
flux_cut[spec_dict[template_to_start_with].wave > lumos.lambda_range[0]] = -999.
spectrum_template = ColumnDataSource(data=dict(w=spec_dict[template_to_start_with].wave, f=spec_dict[template_to_start_with].flux, \
w0=spec_dict[template_to_start_with].wave, f0=spec_dict[template_to_start_with].flux, \
flux_cut=flux_cut, sn=signal_to_noise))
# set up the flux plot
flux_plot = Figure(plot_height=400, plot_width=800,
tools="crosshair,hover,pan,reset,resize,save,box_zoom,wheel_zoom", outline_line_color='black',
x_range=[900, 2000], y_range=[0, 4e-16], toolbar_location='right')
flux_plot.x_range=Range1d(900,2000,bounds=(900,2000))
flux_plot.y_range=Range1d(0,4e-16,bounds=(0,None))
flux_plot.background_fill_color = "beige"
flux_plot.background_fill_alpha = 0.5
flux_plot.yaxis.axis_label = 'Flux'
flux_plot.xaxis.axis_label = 'Wavelength'
flux_plot.line('w', 'f', source=spectrum_template, line_width=3, line_color='firebrick', line_alpha=0.7, legend='Source Flux')
flux_plot.line(lumos.wave, lumos.bef, line_width=3, line_color='darksalmon', line_alpha=0.7, legend='Background')
# set up the flux plot
sn_plot = Figure(plot_height=400, plot_width=800,
tools="crosshair,hover,pan,reset,resize,save,box_zoom,wheel_zoom", outline_line_color='black',
x_range=[900, 2000], y_range=[0, 40], toolbar_location='right')
def temp(request):
month = request.GET['month']
cnx = DB.connect(host='ec500-nasa.csmyiysxb7lc.us-east-1.rds.amazonaws.com',user='******',passwd='nasaenvironment',db='environment')
cur = cnx.cursor()
#cur.execute("SELECT VERSION()")
#data = cur.fetchone()
#print "Database Version:%s" % data
sql = "SELECT * FROM environment.Temp_Deviation_Monthly WHERE Month=%s" %month
year =[]
month=[]
USCRN =[]
CLIMDIV =[]
CMBUSHCN =[]
try:
cur.execute(sql)
data=cur.fetchall()
for row in data:
year.append(row[0])
month.append(row[1])
USCRN.append(row[2])
CLIMDIV.append(row[3])
CMBUSHCN.append(row[4])
except:
print "Error: unable to fecth data"
plot = Figure(x_range=[1895,2016], y_range=[-10,8], plot_width=1000, tools="", toolbar_location=None)
plot.title = "Plot of temprature of month %s from 1895-2015" % month[0]
colors = Blues4[0:3]
plot.border_fill_color = "whitesmoke"
plot.xaxis.axis_label = "Year"
plot.yaxis.axis_label = "Temperature (F)"
plot.axis.major_label_text_font_size = "8pt"
plot.axis.axis_label_text_font_size = "8pt"
plot.axis.axis_label_text_font_style = "bold"
plot.x_range = DataRange1d(range_padding=0.0, bounds=None)
plot.grid.grid_line_alpha = 0.3
plot.grid[0].ticker.desired_num_ticks = 12
plot.line(year, USCRN, color='#A6CEE3', legend='AAPL')
plot.line(year, CLIMDIV, color='#B2DF8A', legend='GOOG')
plot.line(year, CMBUSHCN, color='#33A02C', legend='IBM')
#fig=plt.figure(figsize=(16,12))
#plt.xlabel('Year')
#plt.ylabel('Temprature')
#plt.style.use('ggplot')
#plt.plot(year,USCRN,'ro-')
#plt.plot(year,CLIMDIV,'go-')
#plt.plot(year,CMBUSHCN,'bo-')
#plt.axis([1895,2016,-10,8])
#plt.title('Plot of temprature of month %s from 1895-2015' %month[0])
#os.remove(os.getcwd() + '\Temprature.png')
#plt.savefig(os.path.join(BASE_DIR, 'static\img\Temprature.png'),dpi=80)
#plt.savefig(os.path.join(BASE_DIR, 'static\img\Temprature2.png'),dpi=80)
#fig.clf()
#plt.close(fig)
#img=open(os.getcwd() + '\Temprature.png',"rb")
#response = django.http.HttpResponse(content_type="image/png")
#plt.savefig(response, format="png")
#img=open("Temprature.png", "rb")
#img.save(response, "PNG")
#img.close()
#image_bytes = requests.get(os.path.join(BASE_DIR, 'static\img\Temprature.png').content
#image_bytes.save(response,"PNG")#lambda x: x.startswith('Temprature')
#f = open(os.path.join(BASE_DIR, 'static\img\Temprature.png'),"rb")
#img = f.read()
#f.close()
cur.close()
cnx.close()
script,div=components(plot)
return render(request, "temp.html",{"this_script": script, "this_div": div})
# initialize the plot data
update_source_data(True)
# make the plot responsive to slider changes
standard_deviation_slider.on_change(
'value', lambda attr, old_value, new_value: update_source_data(True))
cutoff_slider.on_change(
'value', lambda attr, old_value, new_value: update_source_data(False))
# create the figure
p = Figure(title='Normal Distribution')
p.scatter(source=source,
x='x',
y='y',
color='green',
alpha='alpha',
radius=0.1)
p.x_range = Range1d(start=-8, end=8)
p.y_range = Range1d(start=-8, end=8)
content = column(standard_deviation_slider, cutoff_slider, p)
# register the figure
curdoc().add_root(content)
curdoc().title = 'Normal Distribution'
def temp(request):
month = request.GET['month']
cnx = DB.connect(
host='ec500-nasa.csmyiysxb7lc.us-east-1.rds.amazonaws.com',
user='******',
passwd='nasaenvironment',
db='environment')
cur = cnx.cursor()
#cur.execute("SELECT VERSION()")
#data = cur.fetchone()
#print "Database Version:%s" % data
sql = "SELECT * FROM environment.Temp_Deviation_Monthly WHERE Month=%s" % month
year = []
month = []
USCRN = []
CLIMDIV = []
CMBUSHCN = []
try:
cur.execute(sql)
data = cur.fetchall()
for row in data:
year.append(row[0])
month.append(row[1])
USCRN.append(row[2])
CLIMDIV.append(row[3])
CMBUSHCN.append(row[4])
except:
print "Error: unable to fecth data"
plot = Figure(x_range=[1895, 2016],
y_range=[-10, 8],
plot_width=1000,
tools="",
toolbar_location=None)
plot.title = "Plot of temprature of month %s from 1895-2015" % month[0]
colors = Blues4[0:3]
plot.border_fill_color = "whitesmoke"
plot.xaxis.axis_label = "Year"
plot.yaxis.axis_label = "Temperature (F)"
plot.axis.major_label_text_font_size = "8pt"
plot.axis.axis_label_text_font_size = "8pt"
plot.axis.axis_label_text_font_style = "bold"
plot.x_range = DataRange1d(range_padding=0.0, bounds=None)
plot.grid.grid_line_alpha = 0.3
plot.grid[0].ticker.desired_num_ticks = 12
plot.line(year, USCRN, color='#A6CEE3', legend='AAPL')
plot.line(year, CLIMDIV, color='#B2DF8A', legend='GOOG')
plot.line(year, CMBUSHCN, color='#33A02C', legend='IBM')
#fig=plt.figure(figsize=(16,12))
#plt.xlabel('Year')
#plt.ylabel('Temprature')
#plt.style.use('ggplot')
#plt.plot(year,USCRN,'ro-')
#plt.plot(year,CLIMDIV,'go-')
#plt.plot(year,CMBUSHCN,'bo-')
#plt.axis([1895,2016,-10,8])
#plt.title('Plot of temprature of month %s from 1895-2015' %month[0])
#os.remove(os.getcwd() + '\Temprature.png')
#plt.savefig(os.path.join(BASE_DIR, 'static\img\Temprature.png'),dpi=80)
#plt.savefig(os.path.join(BASE_DIR, 'static\img\Temprature2.png'),dpi=80)
#fig.clf()
#plt.close(fig)
#img=open(os.getcwd() + '\Temprature.png',"rb")
#response = django.http.HttpResponse(content_type="image/png")
#plt.savefig(response, format="png")
#img=open("Temprature.png", "rb")
#img.save(response, "PNG")
#img.close()
#image_bytes = requests.get(os.path.join(BASE_DIR, 'static\img\Temprature.png').content
#image_bytes.save(response,"PNG")#lambda x: x.startswith('Temprature')
#f = open(os.path.join(BASE_DIR, 'static\img\Temprature.png'),"rb")
#img = f.read()
#f.close()
cur.close()
cnx.close()
script, div = components(plot)
return render(request, "temp.html", {
"this_script": script,
"this_div": div
})
source = ColumnDataSource(data=dict())
tools = 'pan,wheel_zoom,xbox_select,reset'
corr = Figure(plot_width=400, plot_height=400, title='',
title_text_font_size='10pt', tools='pan,wheel_zoom,box_select,reset')
corr.circle('t1_returns', 't2_returns', size=2, source=source,
selection_color="orange", selection_alpha=0.5)
ts1 = Figure(plot_width=800, plot_height=200, title='', tools=tools,
x_axis_type='datetime', title_text_font_size='8pt')
ts1.circle('date', 't1', size=2, source=source, selection_color="orange")
ts2 = Figure(plot_width=800, plot_height=200, title='', tools=tools,
x_axis_type='datetime', title_text_font_size='8pt')
ts2.x_range = ts1.x_range
ts2.circle('date', 't2', size=2, source=source, selection_color="orange")
# set up callbacks
def ticker1_change(attrname, old, new):
ticker2.options = nix(new, DEFAULT_TICKERS)
update()
def ticker2_change(attrname, old, new):
ticker1.options = nix(new, DEFAULT_TICKERS)
update()
def update(selected=None):
t1, t2 = ticker1.value, ticker2.value
cratio=Cratio * 1e9,
spec=spec * 1e9,
downerr=(spec - sig) * 1e9,
uperr=(spec + sig) * 1e9))
################################
# BOKEH PLOTTING
################################
snr_plot = Figure(plot_height=400,
plot_width=750,
tools="crosshair,pan,reset,resize,save,box_zoom,wheel_zoom",
x_range=[0.3, 2.7],
y_range=[0, 1],
toolbar_location='right')
snr_plot.x_range = Range1d(0.3, 2.7, bounds=(0.3, 2.7))
snr_plot.y_range = Range1d(0.0, 1.2, bounds=(0.3, 5.0))
snr_plot.background_fill_color = "beige"
snr_plot.background_fill_alpha = 0.5
snr_plot.yaxis.axis_label = 'F_p/F_s (x10^9)'
snr_plot.xaxis.axis_label = 'Wavelength [micron]'
snr_plot.line('lam',
'cratio',
source=planet,
line_width=2.0,
color="green",
alpha=0.7)
snr_plot.circle('lam',
'spec',
source=planet,
<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
star_syms = 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)
</div>
<div>
<span style="font-size: 15px; font-weight: bold; color: #696">S/N = </span>
<span style="font-size: 15px; font-weight: bold; color: #696;">@y</span>
</div>
</div>
""")
# Set up plot
snr_plot = Figure(plot_height=400,
plot_width=800,
tools="crosshair,pan,reset,resize,save,box_zoom,wheel_zoom",
x_range=[120, 2300],
y_range=[0, 40],
toolbar_location='right')
snr_plot.x_range = Range1d(120, 2300, bounds=(120, 2300))
snr_plot.add_tools(hover)
snr_plot.background_fill_color = "beige"
snr_plot.background_fill_alpha = 0.5
snr_plot.yaxis.axis_label = 'SNR'
snr_plot.xaxis.axis_label = 'Wavelength (nm)'
snr_plot.text(5500, 20, text=['V'], text_align='center', text_color='red')
snr_plot.line('x', 'y', source=source, line_width=3, line_alpha=1.0)
snr_plot.circle('x',
'y',
source=source,
fill_color='white',
line_color='blue',
size=10)
left='timel',
right='timer',
source=source,
alpha=0.5,
color='RoyalBlue',
line_color="black",
line_alpha=0.5,
legend='Min/Max')
p.line(x='time',
y='mean_t',
source=source,
color='red',
line_width=1.5,
alpha=0.8,
legend='Average')
p.x_range = DataRange1d(range_padding=0, bounds=None)
p.yaxis.axis_label = "Temperature (C)"
p.xaxis.axis_label = 'Month'
# Select Data based on input info
def select_data():
#p.title = p.title + str(' (Wait..)')
global station_IDs
# Make Stations ID's as a list
station_IDs = []
[station_IDs.append(int(n)) for n in station_IDs_str.value.split()]
# Select Data based on input info
logic_str = ('WHERE year=' + str(selected_year.value) +
' AND station_id=' + str(station_IDs[0]))
source1 = ColumnDataSource(data=dict(x=data_x[0], y=data_y[0]))
source2 = ColumnDataSource(data=dict(x=data_x[1], y=data_y[1]))
source3 = ColumnDataSource(data=dict(x=data_x[2], y=data_y[2]))
return [source1, source2, source3]
source = init_source()
oSource = list(source)
# dessin
p = Figure(plot_width=400, plot_height=400)
# Axes
p.y_range = Range1d(start=0, end=100)
p.x_range = Range1d(start=0, end=50)
# dessin
for i in range(3):
p.line(x='x', y='y', line_width=2, line_color=color[i], source=source[i])
# création du bouton
bt = Button(label="Lance", button_type="success")
# fonction de callback
callback = CustomJS(args=dict(source=source, p=p, anim=anim),
code="""
var x = new Array(source.length)
var y = new Array(source.length)
var c = new Array(source.length) // coefficient de la droite
alpha_p1=alpha_P1,
alpha_p2=alpha_P2,
beta_p0=beta_P0,
beta_p1=beta_P1,
beta_p2=beta_P2,
sarah_p0=sarah_P0,
sarah_p1=sarah_P1,
sarah_p2=sarah_P2))
p = Figure(tools='', toolbar_location=None, height=800, width=850)
p.grid.grid_line_color = None
p.axis.visible = False
p.grid.grid_line_color = None
p.axis.visible = False
p.y_range = Range1d(-.25, 1.35)
p.x_range = Range1d(-.15, 1.55)
# plot simplex
left_corner = [0.0, 0.0]
right_corner = [np.sqrt(2), 0.0]
top_corner = [np.sqrt(2) / 2.0, np.sqrt(6) / 2.0]
p.line([left_corner[0], top_corner[0]], [left_corner[1], top_corner[1]],
color='black',
line_width=2)
p.line([right_corner[0], top_corner[0]], [right_corner[1], top_corner[1]],
color='black',
line_width=2)
p.line([left_corner[0], right_corner[0]], [left_corner[1], right_corner[1]],
color='black',
line_width=2)
# Set up plot
box_select = BoxSelectTool()
plot1 = Figure(plot_height=500,
plot_width=770,
x_axis_type=None,
y_axis_type=None,
tools=["pan,reset,tap,wheel_zoom,save", box_select],
x_range=[-75, 75],
y_range=[-50, 50],
toolbar_location='left')
plot1.image_url(url=["http://luvoir.stsci.edu/M83.jpeg"],
x=[-75],
y=[50],
w=150,
h=100)
plot1.x_range = Range1d(-75, 75, bounds=(-75, 75))
plot1.y_range = Range1d(-50, 50, bounds=(-50, 50))
shutters = plot1.square('x',
'y',
source=shutter_positions,
fill_color='yellow',
fill_alpha=0.2,
line_color=None,
size=20,
name="my_shutters")
shutters.selection_glyph = Square(fill_alpha=0.5,
fill_color="green",
line_color='green',
line_width=3)
shutters.nonselection_glyph = Square(fill_alpha=0.2,
fill_color="yellow",
grate4=ColumnDataSource(dict(x=londf.values[:,0]-kgx*kmult,y=londf.values[:,2]-kgy*kmult))
grate5=ColumnDataSource(dict(x=londf.values[:,0]-kgx,y=londf.values[:,2]))
grate6=ColumnDataSource(dict(x=londf.values[:,0]+kgx,y=londf.values[:,2]))
grate7=ColumnDataSource(dict(x=londf.values[:,0],y=londf.values[:,2]+kgy))
grate8=ColumnDataSource(dict(x=londf.values[:,0],y=londf.values[:,2]-kgy))
p.line(x='x',y='y',source=grate1, color="red",line_width=5)
p.line(x='x',y='y',source=grate2, color="red",line_width=5)
p.line(x='x',y='y',source=grate3, color="red",line_width=5)
p.line(x='x',y='y',source=grate4, color="red",line_width=5)
p.line(x='x',y='y',source=grate5, color="red",line_width=5)
p.line(x='x',y='y',source=grate6, color="red",line_width=5)
p.line(x='x',y='y',source=grate7, color="red",line_width=5)
p.line(x='x',y='y',source=grate8, color="red",line_width=5)
p.x_range=Range1d(-1 , 1)
p.y_range=Range1d(-1 , 1)
def update():
tilt=float(tiltin.value)*np.pi/180
wl=2.997e4/float(freqin.value)
wlout.text='Wavelength = '+str(wl)+' cm'
kgy=wl/float(dyin.value)
if lattice.value=='Triangular':
kgx=2*wl/float(dxin.value)
kmult=0.5
else:
kgx=wl/float(dxin.value)
kmult=1
kgxout.text='kgx = '+str(kgx)
SNR = cp*Dts/np.sqrt((cp + 2*cb)*Dts)
# Calculate 1-sigma errors
sig= Cratio/SNR
# Add gaussian noise to flux ratio
spec = Cratio + np.random.randn(len(Cratio))*sig
planet = ColumnDataSource(data=dict(lam=lam, cratio=Cratio*1e9, spec=spec*1e9, downerr=(spec-sig)*1e9, uperr=(spec+sig)*1e9))
################################
# BOKEH PLOTTING
################################
snr_plot = Figure(plot_height=400, plot_width=750,
tools="crosshair,pan,reset,resize,save,box_zoom,wheel_zoom",
x_range=[0.3, 2.7], y_range=[0, 1], toolbar_location='right')
snr_plot.x_range = Range1d(0.3, 2.7, bounds=(0.3, 2.7))
snr_plot.y_range = Range1d(0.0, 1.2, bounds=(0.3, 5.0))
snr_plot.background_fill_color = "beige"
snr_plot.background_fill_alpha = 0.5
snr_plot.yaxis.axis_label='F_p/F_s (x10^9)'
snr_plot.xaxis.axis_label='Wavelength [micron]'
snr_plot.line('lam','cratio',source=planet,line_width=2.0, color="green", alpha=0.7)
snr_plot.circle('lam', 'spec', source=planet, fill_color='red', line_color='black', size=8)
snr_plot.segment('lam', 'downerr', 'lam', 'uperr', source=planet, line_width=1, line_color='grey', line_alpha=0.5)
def change_filename(attrname, old, new):
format_button_group.active = None
instruction0 = Div(text="""Choose a file rootname here
Yb = gamma.ppf(1 - PFA, N)
K = 1 * N
xdBseries = np.array([x * 0.1 for x in range(0, 501)])
xdBseries = xdBseries - 10
vprobdet = np.vectorize(pd.probdet)
PDseries = vprobdet(N, Yb, K, xdBseries)
source = ColumnDataSource(data=dict(snr=xdBseries, pd=PDseries))
plot = Figure(plot_width=435, plot_height=400)
plot.line('snr', 'pd', source=source)
plot.x_range = Range1d(-10, 40)
def update(attrname, old, new):
PFA = float(pfa.value)
N = slider1.value
Yb = gamma.ppf(1 - PFA, N)
if case.value == "Case 1":
K = 1
elif case.value == "Case 2":
K = N
elif case.value == "Case 3":
K = 2
elif case.value == "Case 4":
K = 2 * N
fill_color='pink',
line_width=0)
p1.patch([0.003, 0.04, 0.04, 0.003, 0.003], [100, 100, 30000., 30000., 10000.],
alpha=0.6,
fill_color='lightblue',
line_width=0)
p1.patch([3, 3000, 3000, 30, 3], [300, 300, 30000., 30000., 300.],
alpha=0.6,
fill_color='purple',
line_width=0)
p1.yaxis.axis_label = 'Planet Mass / Earth'
p1.xaxis.axis_label = 'Semi-major Axis / Snow Line'
p1.xaxis.axis_label_text_font_style = 'bold'
p1.yaxis.axis_label_text_font_style = 'bold'
p1.xaxis[0].formatter = NumeralTickFormatter(format="0.00")
p1.x_range = Range1d(0.003, 3000, bounds=(0.003, 3000))
p1.y_range = Range1d(0.01, 30000, bounds=(0.01, 30000))
techniques = [
'RV', 'Space Transits', 'Ground Transits', 'Microlensing', 'Direct Imaging'
]
checkbox_button_group = CheckboxGroup(
labels=["RV", "Transits", "Microlensing", "Direct Imaging"],
active=[0, 1, 2, 3])
# transits - ground
tground = Table.read(
'/Users/tumlinson/Dropbox/LUVOIR_STDT/luvoir_simtools/planetspace/transit_ground.dat',
format='ascii',
names=['name', 'msini', 'semi', 'mstar'])
spec=spec * 1e9,
downerr=(spec - sig) * 1e9,
uperr=(spec + sig) * 1e9))
################################
# BOKEH PLOTTING
################################
snr_plot = Figure(plot_height=400,
plot_width=800,
title="LUVOIR Coronagraphic Simulator",
tools="crosshair,pan,reset,resize,save,box_zoom,wheel_zoom",
x_range=[0.2, 3.0],
y_range=[0, 1],
toolbar_location='right')
snr_plot.x_range = Range1d(0.2, 3, bounds=(0.2, 3))
snr_plot.background_fill_color = "beige"
snr_plot.background_fill_alpha = 0.5
snr_plot.yaxis.axis_label = 'F_p/F_s (x10^9)'
snr_plot.xaxis.axis_label = 'Wavelength [micron]'
snr_plot.line('lam',
'cratio',
source=planet,
line_width=2.0,
color="green",
alpha=0.7)
snr_plot.circle('lam',
'spec',
source=planet,
fill_color='red',
plot_height=240,
tools=[skr_hover, "pan,box_zoom,reset,crosshair, lasso_select"])
p1.line('wl', 'med_resid', source=skyres_source)
p2 = Figure(title='WAVG_RESID_WAVE',
x_axis_label='Angstrom',
plot_width=720,
plot_height=240,
tools=[wavg_hover, "pan,box_zoom,reset,crosshair, lasso_select"])
p2.line('wl', 'wavg_resid', source=skyres_source)
'''p1.circle('wl', 'med_resid', source=skyres_source, alpha = 0, size=1,
hover_alpha=1,
hover_fill_color='orange', hover_line_color='red') '''
'''p2.circle('wl', 'wavg_resid', source=skyres_source, alpha=0, size=1,
hover_alpha=1,
hover_fill_color='orange', hover_line_color='red')'''
p1.x_range = p2.x_range
info, nlines = write_info('skyresid', tests['skyresid'])
txt = PreText(text=info, height=nlines * 20, width=p2.plot_width)
info_col = Div(text=write_description('skyresid'), width=p2.plot_width)
p2txt = column(widgetbox(info_col), p1, p2)
#layout=column(p1,p2)
curdoc().add_root(p2txt)
curdoc().title = "SKYRESID"
