def test_spinner_smallest_step(self, bokeh_model_page) -> None:
spinner = Spinner(value=0, low=0, high=1, step=1e-16, css_classes=["foo"])
spinner.js_on_change('value', CustomJS(code=RECORD("value", "cb_obj.value")))
page = bokeh_model_page(spinner)
input_el = page.driver.find_element_by_css_selector('.foo input')
enter_text_in_element(page.driver, input_el, "0.43654644333534")
results = page.results
assert results['value'] == 0.43654644333534
enter_text_in_element(page.driver, input_el, "1e-16", click=2)
results = page.results
assert results['value'] == 1e-16
assert page.has_no_console_errors()
def test_input_smallest_step(self, bokeh_model_page) -> None:
spinner = Spinner(value=0, low=0, high=1, step=1e-16, css_classes=["foo"])
spinner.js_on_change('value', CustomJS(code=RECORD("value", "cb_obj.value")))
page = bokeh_model_page(spinner)
el = page.driver.find_element_by_css_selector('.foo input')
enter_value_in_spinner(page.driver, el, 1e-16)
results = page.results
assert float(results['value']) == 1e-16
enter_value_in_spinner(page.driver, el, 0.43654644333534)
results = page.results
assert float(results['value']) == 0.43654644333534
assert page.has_no_console_errors()
# get the center/means in each direction
cp = np.mean(P_new, axis=0)
r_x, r_y, aou = calc_covariance_matrix(P_new, cp, num_trials)
# results_div.text = tdoa_results + str(aou) + "</font>"
aou_text.value = "{:.6f}".format(aou)
# st_source.data = dict(sx=Sn[:, 0, :].reshape(-1), sy=Sn[:, 1, :].reshape(-1))
etx_source.data = dict(x=P_new[:, 0]*1, y=P_new[:, 1]*1)
ctx_source.data = dict(x=[cp[0]*1], y=[cp[1]*1])
ell_source.data = dict(x=r_x*1, y=r_y*1)
# setup the event callbacks for the plot
st_source.js_on_change('patching', update_plot_callback)
ig_source.js_on_change('patching', update_plot_callback)
tx_source.js_on_change('patching', update_plot_callback)
p_err_spin.js_on_change('value', update_plot_callback)
t_err_spin.js_on_change('value', update_plot_callback)
# p_err_spin.on_change('value', update_plot)
spin_inputs = row([p_err_spin, Spacer(width=15), t_err_spin])
inputs = column([Div(text="""<B>Receiver Positions</B>""", width=220), st_datatable, Spacer(height=10), Div(text="""<B>Initial Guess</B>""", width=220),
ig_datatable, Spacer(height=10), Div(text="""<B>Emitter Position</B>""", width=220), tx_datatable, spin_inputs,
Spacer(height=10), aou_text])
layout = row(inputs, Spacer(width=20), tdoa_plot)
show(layout)
def test_spinner_spinning_events(self, bokeh_model_page) -> None:
spinner = Spinner(value=0,
low=0,
high=1,
step=0.01,
css_classes=["foo"])
spinner.js_on_change('value',
CustomJS(code=RECORD("value", "cb_obj.value")))
page = bokeh_model_page(spinner)
input_el = page.driver.find_element_by_css_selector('.foo input')
btn_up_el = page.driver.find_element_by_css_selector(
'.foo .bk-spin-btn-up')
btn_down_el = page.driver.find_element_by_css_selector(
'.foo .bk-spin-btn-down')
enter_text_in_element(page.driver, input_el, "0.5")
results = page.results
assert results['value'] == 0.5
#click btn up
actions = ActionChains(page.driver)
actions.click(on_element=btn_up_el)
actions.perform()
results = page.results
assert results['value'] == 0.51
#dbl click btn down
actions = ActionChains(page.driver)
actions.double_click(on_element=btn_down_el)
actions.perform()
results = page.results
assert results['value'] == 0.49
#arrow up
actions = ActionChains(page.driver)
actions.click(on_element=input_el)
actions.send_keys(Keys.ARROW_UP)
actions.perform()
results = page.results
assert results['value'] == 0.50
#arrow down
actions = ActionChains(page.driver)
actions.click(on_element=input_el)
actions.key_down(Keys.ARROW_DOWN)
actions.perform()
results = page.results
assert results['value'] == 0.49
#page up
actions = ActionChains(page.driver)
actions.click(on_element=input_el)
actions.key_down(Keys.PAGE_UP)
actions.perform()
results = page.results
assert results['value'] == 0.59
#page down
actions = ActionChains(page.driver)
actions.click(on_element=input_el)
actions.key_down(Keys.PAGE_DOWN)
actions.perform()
results = page.results
assert results['value'] == 0.49
assert page.has_no_console_errors()
import numpy as np
from bokeh.io import show
from bokeh.layouts import column, row
from bokeh.models import ColumnDataSource, CustomJS, Spinner
from bokeh.plotting import Figure
data = np.random.rand(10, 2)
cds = ColumnDataSource(data=dict(x=data[:, 0], y=data[:, 1]))
p = Figure(x_range=(0, 1), y_range=(0, 1))
points = p.scatter(x='x', y='y', source=cds)
w = Spinner(title="Glyph size", low=1, high=20, step=0.1, value=4, width=100)
cb = CustomJS(args={'points': points},
code="""
points.glyph.size = cb_obj.value
""")
points.glyph.size = w.value
w.js_on_change('value', cb)
show(row(column(w, width=100), p))
import numpy as np
from bokeh.io import show
from bokeh.plotting import Figure
from bokeh.models import ColumnDataSource, CustomJS, Spinner
from bokeh.layouts import row, widgetbox
data = np.random.rand(10, 2)
cds = ColumnDataSource(data=dict(x=data[:, 0], y=data[:, 1]))
p = Figure(x_range=(0, 1), y_range=(0, 1))
points = p.scatter(x='x', y='y', source=cds)
w = Spinner(title="Glyph size", low=1, high=20, step=0.1, value=4, width=100)
cb = CustomJS(args={'points': points}, code="""
points.glyph.size = cb_obj.value
""")
points.glyph.size = w.value
w.js_on_change('value', cb)
show(row([widgetbox(w, width=100), p]))
def plotfits(dirname):
session.modifeid = True
session['pathname'] = app.config['UPLOAD_FOLDER']+'/'+dirname+'/'
session['stats'] = {}
session['date'] = {} # pegar a data para converter em juliana e inserir nas análises
with open(session['pathname']+'data.json') as f:
dirdata = json.load(f)
r = dirdata['r']
session['r'] = r
celestial = False
# Faz logo algumas estatísticas da imagem
for fil in BANDAS:
for fname in dirdata[fil]:
img, header = fits.getdata(session['pathname']+fname, header=True)
session['stats'][fil+':'+fname] = sigma_clipped_stats(img,sigma=3.0)
if not celestial:
celestial = WCS(header).has_celestial
session['wcs'] = session['pathname']+fname
session['date'][fil+':'+fname] = Time(header['DATE-OBS']).jd # a data de observação de cada imagem
# Abrindo coordenadas se salvas
try:
cordata = pd.read_excel(session['pathname']+'data.xlsx')
# Dados que serão usados para fazer computação e visualizar os pontos
source = ColumnDataSource(cordata)
print('Coordenadas carregadas.')
except FileNotFoundError:
print('Não há coordenadas salvas em %s' % session['pathname'])
# Dados que serão usados para fazer computação e visualizar os pontos
source = ColumnDataSource(dict(
ra=[],
dec=[],
x=[],
y=[],
flux = [],
j = [],
k = [],
tipo=[], # se é obj, src ou sky
banda=[], # o filtro da imagem e arquivo
sid=[], # id da estrela copiada
colors=[], # para colorir de acordo o tipo de objeto
))
# Constrói a tabaela de table que poderá ser usada para designar as posições do objeto, estrela e céu
tabela = DataTable(source=source,columns=[
TableColumn(field='x',title='x'),
TableColumn(field='y',title='y'),
TableColumn(field='ra',title='ra'),
TableColumn(field='dec',title='dec'),
TableColumn(field='j',title='j'),
TableColumn(field='k',title='k'),
TableColumn(field='flux',title='flux'),
TableColumn(field='tipo',title='tipo'),
TableColumn(field='banda',title='banda'),
TableColumn(field='sid',title='sid')
], editable=True)
P = [] # lista de gráficos para o plot
Nimg = [] # lista de imagens normalizadas para o contraste
for fil in BANDAS:
for fname in dirdata[fil]:
img = fits.getdata(session['pathname']+fname)
stretch = HistEqStretch(img) # Histograma, melhor função para granular a imagem
h,w = img.shape # número de linhas e colunas da matriz da imagem
nimg = stretch(normal(img)).tolist()
p = figure(plot_width=700, active_scroll='wheel_zoom')
p.image(image=[nimg], x=0, y=0, dw=w, dh=h, palette='Greys256', level="image")
p.x_range.range_padding = p.y_range.range_padding = 0
p.grid.grid_line_width = 0
view = CDSView(source=source,filters=[GroupFilter(column_name='banda', group=fil+':'+fname)])
c = p.circle('x','y', source=source, view=view, color='colors', fill_color=None, radius=r, line_width=2)
cd = p.circle_dot('x','y', source=source, view=view, color='colors', size=2)
tool = PointDrawTool(renderers=[c,cd],empty_value='na')
p.add_tools(tool)
p.toolbar.active_tap = tool
p.toolbar.active_inspect = None
tab = Panel(child=p, title=fil+':'+fname)
P.append(tab)
Nimg.append(nimg)
graficos = Tabs(tabs=P)
graficos.js_on_change('active', CustomJS(code='''
tabs_onchange(cb_obj);
'''))
contrast = Slider(start=-1, end=6, value=1, step=0.05, title="Contraste")
contrast.js_on_change('value',CustomJS(args = dict(tabs=graficos.tabs, im=Nimg), code = '''
contrast_onchange(cb_obj,tabs,im);
'''))
# Selecionar o tipo de fonte luminosa: obj, src ou sky
radio_title = Paragraph(text='Escolha o tipo:')
LABELS = ['obj','src','sky']
radio_group = RadioGroup(labels=LABELS, active=0)
# Evento de mudança da tabela de table, para inserir table padrão nas colunas inalteradas
source.js_on_change('data', CustomJS(args=dict(radio=radio_group, graficos=graficos), code='''
source_onchange(cb_obj, radio, graficos);
'''))
# Muda o raio da abertura fotométrica
spinner = Spinner(title="Raio", low=1, high=40, step=0.5, value=r, width=80)
spinner.js_on_change('value', CustomJS(args=dict(source=source, tabs=graficos.tabs), code='''
radius_onchange(cb_obj,source,tabs);
'''))
# Coluna de requisição
text1 = Div(text='<b>Instruções:</b><p>1. Digite a chave do Astrometry.net')
apikey_input = TextInput(title='Apikey do Astrometry.net', placeholder='digite a chave aqui')
text2 = Div(text='''<p>2. Selecione qual imagem será usada como referência para o astrometry.net e
para o cálculo das coordenadas celestes</p>''')
seletor = Select(title='Escolha a imagem de referência', options=[*session['stats'].keys()])
text3 = Div(text='3. Clique abaixo pra requisitar a correção WCS')
send_astrometry = Toggle(label='Solução de placa do astrometry.net', disabled=celestial)
send_astrometry.js_on_click(CustomJS(args=dict(key=apikey_input, source=source, selected=seletor), code='''
send_astrometry(cb_obj,key,source,selected);
'''))
# o Botão de salvar irá enviar um json para o servidor que irá ler e fazer os procedimentos posteriores
text4 = Div(text='4. Salve a tabela de table clicando em salvar.')
salvar = Button(label='Salvar tabela', button_type="success")
salvar.js_on_click(CustomJS(args=dict(source=source), code='''
salvar_onclick(source);
'''))
reset = Button(label='Limpar', button_type='success')
reset.js_on_click(CustomJS(args=dict(source=source), code='''
reset_onclick(source);
'''))
copiar = Button(label='Copiar coordenadas', button_type='success')
copiar.js_on_click(CustomJS(args=dict(source=source, ref=seletor, active=graficos), code='''
add_data(source,ref,active);
'''))
div, script = components(row(column(contrast,spinner,radio_title,radio_group),\
column(row(reset,copiar,salvar), graficos, tabela, sizing_mode='stretch_both'),
column(text1,apikey_input,text2,seletor,text3,send_astrometry,text4)))
return render_template('plot.html', the_div=div, the_script=script,filename=dirdata['name'])