class MapPlot(object):
def __init__(self):
self.map_plot = Figure(
tools="pan,wheel_zoom,tap", toolbar_location="right",
logo=None, min_border=0, min_border_left=0,
**get_paris_extent(0.6), # x_range & y_range
plot_width=1100, plot_height=650)
self.map_plot.add_tile(tile_source=OSM_TILE_SOURCE)
self.map_plot_renderer = self.map_plot.patches(
source=geo_source,
xs="xs",
ys="ys",
line_width=2,
line_color=None,
selection_line_color="firebrick",
nonselection_line_color=None,
fill_color="colors",
selection_fill_color="colors",
nonselection_fill_color="colors",
alpha=0.85,
selection_alpha=0.9,
nonselection_alpha=0.85)
self.map_plot.axis.visible = None
self.map_plot_ds = self.map_plot_renderer.data_source
def get_plot(self):
return self.map_plot
def get_data_source(self):
return self.map_plot_ds
def plotMap(lat, lon, axis_range):
x_offset, y_offset = convLL_XY(lat, lon)
x_axis_range = [-axis_range+x_offset, axis_range+x_offset]
y_axis_range = [-axis_range+y_offset, axis_range+y_offset]
x_range = Range1d(start=x_axis_range[0], end=x_axis_range[1])
y_range = Range1d(start=y_axis_range[0], end=y_axis_range[1])
p = Figure(tools='pan,wheel_zoom', x_range=x_range, y_range=y_range, plot_height=800, plot_width=800)
p.axis.visible = False
STAMEN_TONER.url = 'http://tile.stamen.com/toner-lite/{Z}/{X}/{Y}.png'
p.add_tile(STAMEN_TONER)
return p
def create_plot():
axis_range = [-10000000, 10000000]
p = Figure(tools='pan,wheel_zoom', x_range=axis_range, y_range=axis_range, plot_height=800, plot_width=800)
p.axis.visible = False
tile_source = RandomTileSource()
tile_source.urls = []
tile_source.attribution = STAMEN_TONER.attribution
tile_source.urls.append(STAMEN_TONER.url)
tile_source.urls.append('http://c.tile.openstreetmap.org/{Z}/{X}/{Y}.png')
tile_source.urls.append('http://otile1.mqcdn.com/tiles/1.0.0/sat/{Z}/{X}/{Y}.jpg')
p.add_tile(tile_source)
return p
def map():
x_range = (-10000000, -11000000)
y_range = (3500000, 5200000)
plot = Figure(
tools=TOOLS, title="Power Plant Locations", plot_width=1000, plot_height=500, x_range=x_range, y_range=y_range
)
plot.add_tile(STAMEN_TONER)
plot.axis.visible = False
plot.xgrid.grid_line_color = None
plot.ygrid.grid_line_color = None
m1 = plot.circle(x="lat", y="lon", source=source_map_bwr, size="size", fill_alpha=0, line_width=2, color="red")
m2 = plot.square(x="lat", y="lon", source=source_map_pwr, size="size", fill_alpha=0, line_width=2, color="red")
plot.select(dict(type=HoverTool)).tooltips = [("Plant Name", "@name"), ("Reactor and Containment", "@type")]
return plot
# Create plot -------------------------------
xmin = -8240227.037
ymin = 4974203.152
xmax = -8231283.905
ymax = 4979238.441
path = './data/projected.tif'
fig = Figure(x_range=(xmin, xmax),
y_range=(ymin, ymax),
plot_height=600,
plot_width=900,
tools='pan,wheel_zoom')
fig.background_fill_color = 'black'
fig.add_tile(STAMEN_TONER, alpha=0) # used to set axis ranges
fig.x_range.callback = CustomJS(code=dims_jscode, args=dict(plot=fig, dims=dims))
fig.y_range.callback = CustomJS(code=dims_jscode, args=dict(plot=fig, dims=dims))
fig.axis.visible = False
fig.grid.grid_line_alpha = 0
fig.min_border_left = 0
fig.min_border_right = 0
fig.min_border_top = 0
fig.min_border_bottom = 0
image_source = ColumnDataSource(dict(image=[], x=[], y=[], dw=[], dh=[]))
fig.image_rgba(source=image_source,
image='image',
x='x',
y='y',
dw='dw',
throttle = setTimeout(update_dims, 100, "replace");
"""
# Create plot -------------------------------
xmin = -8240227.037
ymin = 4974203.152
xmax = -8231283.905
ymax = 4979238.441
fig = Figure(x_range=(xmin, xmax),
y_range=(ymin, ymax),
plot_height=600,
plot_width=900,
tools='pan,wheel_zoom')
fig.background_fill_color = 'black'
fig.add_tile(get_provider("STAMEN_TONER"), alpha=.3)
fig.x_range.callback = CustomJS(code=dims_jscode,
args=dict(plot=fig, dims=dims))
fig.y_range.callback = CustomJS(code=dims_jscode,
args=dict(plot=fig, dims=dims))
fig.axis.visible = False
fig.grid.grid_line_alpha = 0
fig.min_border_left = 0
fig.min_border_right = 0
fig.min_border_top = 0
fig.min_border_bottom = 0
image_source = ColumnDataSource(dict(image=[], x=[], y=[], dw=[], dh=[]))
fig.image_rgba(source=image_source,
image='image',
x='x',
throttle = setTimeout(update_dims, 100, "replace");
"""
# Create plot -------------------------------
xmin = -8240227.037
ymin = 4974203.152
xmax = -8231283.905
ymax = 4979238.441
fig = Figure(x_range=(xmin, xmax),
y_range=(ymin, ymax),
plot_height=600,
plot_width=900,
tools='pan,wheel_zoom')
fig.background_fill_color = 'black'
fig.add_tile(STAMEN_TONER, alpha=.3)
fig.x_range.callback = CustomJS(code=dims_jscode, args=dict(plot=fig, dims=dims))
fig.y_range.callback = CustomJS(code=dims_jscode, args=dict(plot=fig, dims=dims))
fig.axis.visible = False
fig.grid.grid_line_alpha = 0
fig.min_border_left = 0
fig.min_border_right = 0
fig.min_border_top = 0
fig.min_border_bottom = 0
image_source = ColumnDataSource(dict(image=[], x=[], y=[], dw=[], dh=[]))
fig.image_rgba(source=image_source, image='image', x='x', y='y', dw='dw', dh='dh', dilate=False)
time_text = Paragraph(text='Time Period: 00:00 - 00:00')
controls = HBox(children=[time_text, time_select], width=fig.plot_width)
layout = VBox(children=[fig, controls])
# Create plot -------------------------------
xmin = -8240227.037
ymin = 4974203.152
xmax = -8231283.905
ymax = 4979238.441
path = './data/projected.tif'
fig = Figure(x_range=(xmin, xmax),
y_range=(ymin, ymax),
plot_height=600,
plot_width=900,
tools='pan,wheel_zoom')
fig.background_fill_color = 'black'
fig.add_tile(STAMEN_TONER, alpha=0) # used to set axis ranges
fig.x_range.callback = CustomJS(code=dims_jscode,
args=dict(plot=fig, dims=dims))
fig.y_range.callback = CustomJS(code=dims_jscode,
args=dict(plot=fig, dims=dims))
fig.axis.visible = False
fig.grid.grid_line_alpha = 0
fig.min_border_left = 0
fig.min_border_right = 0
fig.min_border_top = 0
fig.min_border_bottom = 0
image_source = ColumnDataSource(dict(image=[], x=[], y=[], dw=[], dh=[]))
fig.image_rgba(source=image_source,
image='image',
x='x',
throttle = setTimeout(update_dims, 100, "replace");
"""
# Create plot -------------------------------
xmin = -8240227.037
ymin = 4974203.152
xmax = -8231283.905
ymax = 4979238.441
fig = Figure(x_range=(xmin, xmax),
y_range=(ymin, ymax),
plot_height=600,
plot_width=900,
tools='pan,wheel_zoom')
fig.background_fill_color = 'black'
fig.add_tile(STAMEN_TONER, alpha=.3)
fig.x_range.callback = CustomJS(code=dims_jscode,
args=dict(plot=fig, dims=dims))
fig.y_range.callback = CustomJS(code=dims_jscode,
args=dict(plot=fig, dims=dims))
fig.axis.visible = False
fig.grid.grid_line_alpha = 0
fig.min_border_left = 0
fig.min_border_right = 0
fig.min_border_top = 0
fig.min_border_bottom = 0
image_source = ColumnDataSource(dict(image=[], x=[], y=[], dw=[], dh=[]))
fig.image_rgba(source=image_source,
image='image',
x='x',
output_backend="webgl",
)
cart_fig.background_fill_color = "grey"
cart_fig.background_fill_alpha = .5
# cb_fig = bokeh.plotting.Figure(plot_height=pw,plot_width=)
# cb_fig.toolbar.logo = None
# cb_fig.toolbar_location = None
# %%
# SCATTER
# noinspection PyUnresolvedReferences
# add tiles
tile_provider = bokeh.tile_providers.get_provider(
bokeh.tile_providers.Vendors.CARTODBPOSITRON)
map_fig.add_tile(tile_provider)
# scatter in map
map_fig.scatter('GX', 'GY', source=source_master, size='r2', color=cm)
cart_fig.line('lo', 'la', source=source_bol, color='black')
cart_fig.scatter('x', 'y', source=source_master, radius='r', color=cm)
red_scat_map = map_fig.circle_cross(
'gx',
'gy',
source=source_red_map,
# color='red',
fill_color=None,
# line_color='green',
size=20,
def plot_carto_single(self, data, frente, palette, path=FILE_OUT,
name_file="", low=0, high=100, show_plot=True):
"""
:param data: df loaded by data_load
:param frente: string, name of "partido" lowercase: diff, mas, cc, creemos, fpv, pan_bol
:param palette: ej: P_GRAD_CC
:param name_file: default:test
:param low: cmap low limit: default: -80
:param high: cmap high limit: defauilt: +80.
:param path: file out
:return: df
"""
da_col = ['HAB','PAIS','MUN','REC','X','Y','LAT','LON','x','y',
'r','r2','GX','GY'
]
cart_init_val = self.CART_SLIDER_INIT # add slider
self.process_data(cart_init_val, data)
if frente == "diff":
low = self.C_BAR_LOW
high = self.C_BAR_HIGH
frente = "d_mas_cc"
f1 = 'mas_o_cc'
f2 = 'ad_mas_cc'
_p = 'mas'
_p1 = 'cc'
da_col.append(frente)
da_col.append(f1)
da_col.append(f2)
da_col.append(_p)
da_col.append(_p1)
if frente == "d_mas_creemos":
low = self.C_BAR_LOW
high = self.C_BAR_HIGH
f1 = 'mas_o_creemos'
f2 = 'ad_mas_creemos'
da_col.append(frente)
da_col.append(f1)
da_col.append(f2)
da_col.append('mas')
da_col.append('creemos')
da_col.append(frente)
cm = linear_cmap(frente, palette=palette, low=low, high=high)
data = data[da_col]
source_master = ColumnDataSource(data)
source_red_map = ColumnDataSource({'gx': [], 'gy': []})
# la, lo = ebu.get_la_lo_bolivia()
# source_bol = ColumnDataSource({'la': la, 'lo': lo})
# source_red_car = ColumnDataSource({'lo': [], 'la': []})
# JS CODE
code_draw_red_map = """
const data = {'gx': [], 'gy': []}
const indices = cb_data.index.indices
for (var i = 0; i < indices.length; i++ ) {
data['gx'].push(source_master.data.GX[indices[i]])
data['gy'].push(source_master.data.GY[indices[i]])
}
source_red_map.data = data
"""
code_slider = """
var data = source.data;
var f = cb_obj.value
var x = data['x']
var y = data['y']
var Y = data['Y']
var X = data['X']
var lat = data['LAT']
var lon = data['LON']
for (var i = 0; i < x.length; i++) {
y[i] = (1-f)*lat[i] + f*Y[i]
x[i] = (1-f)*lon[i] + f*X[i]
}
source.change.emit();
"""
# FIGURES
curr_time = ebu.get_bolivian_time(-3)
pw = self.FIG_WIDTH
callback_red_map = CustomJS(
args={'source_master': source_master,
'source_red_map': source_red_map, },
code=code_draw_red_map)
hover_cart = bokeh.models.HoverTool(
tooltips=self.TOOL_TIP_DIC[frente],
callback=callback_red_map,
# renderers = [red_scat_car]
)
cart_fig = Figure(plot_width=pw, plot_height=pw,
output_backend="webgl", )
cart_fig.background_fill_color = "grey"
cart_fig.background_fill_alpha = .5
cart_fig.scatter('x', 'y', source=source_master, radius='r', color=cm)
cart_fig.add_tools(hover_cart, )
title = "Última actualización: " + curr_time["datetime_val"].strftime(
"%Y-%m-%d %H:%M") + "BOT"
map_fig = Figure(plot_width=pw, plot_height=pw,
x_axis_type='mercator',
y_axis_type='mercator',
output_backend="webgl",
title=title,
)
# cb_fig = bokeh.plotting.Figure(plot_height=pw,plot_width=)
# cb_fig.toolbar.logo = None
# cb_fig.toolbar_location = None
# SCATTER
# noinspection PyUnresolvedReferences
# add tiles
tile_provider = bokeh.tile_providers.get_provider(
bokeh.tile_providers.Vendors.CARTODBPOSITRON)
map_fig.add_tile(tile_provider)
# scatter in map
map_fig.scatter(
'GX', 'GY', source=source_master, size='r2',
color=cm
)
# todo if we wont use map then we nee to delete the source
# cart_fig.line('lo', 'la', source=source_bol, color='black')
# noinspection PyUnusedLocal
red_scat_map = map_fig.circle_cross('gx', 'gy',
source=source_red_map,
fill_color=None,
size=20,
line_color="white",
line_width=4
)
# noinspection PyUnusedLocal
red_scat_map = map_fig.circle_cross('gx', 'gy',
source=source_red_map,
fill_color=None,
size=20,
line_color="red",
line_width=1
)
# red_scat_car = cart_fig.scatter('lo', 'la',
# source=source_red_car, color='green')
# add a hover tool that sets the link data for a hovered circle
# callbacks
# code = code_merged)
# callback_red_car = CustomJS(
# args={'source_master': source_master, 'source_red_car': source_red_car},
# code=code_draw_red_car)
# tools
hover_map = bokeh.models.HoverTool(
tooltips=self.TOOL_TIP_DIC[frente],
# callback=callback_red_car,
# renderers = [red_scat_map]
)
map_fig.add_tools(hover_map, )
# slider
callback_slider = CustomJS(args=dict(source=source_master),
code=code_slider)
slider = Slider(start=0, end=1, value=cart_init_val, step=.02,
title="carto")
slider.js_on_change('value', callback_slider)
# COLOR BAR
ml = {int(i): str(np.abs(i)) for i in np.arange(-80, 81, 20)}
cb = bokeh.models.ColorBar(
color_mapper=cm['transform'],
# width=int(.9 * 450),
width='auto',
location=(0, 0),
# title="DEN (N/km^2)",
# title=(BAR_TITLE),
# margin=0,padding=0,
title_standoff=10,
# ticker=bokeh.models.LogTicker(),
orientation='horizontal',
major_label_overrides=ml
)
cart_fig.add_layout(cb, 'above')
# cb.title_text_align = 'left'
cart_fig.title.text = self.BAR_TITLE_DIC[frente]
cart_fig.title.align = 'center'
# layout = row(column(slider, cart_f),map_f)
layout = bokeh.layouts.gridplot(
[[slider, None], [cart_fig, map_fig]], sizing_mode='scale_width',
merge_tools=False)
layout.max_width = 1400
# layout = bokeh.layouts.column([slider, cart_fig])
cart_fig.x_range.start = self.CXS
cart_fig.x_range.end = self.CXE
cart_fig.y_range.start = self.CYS
cart_fig.y_range.end = self.CYE
_ll = ebu.lola_to_cart(lo=[self.MXS, self.MXE], la=[self.MYS, self.MYE])
map_fig.x_range.start = _ll[0][0]
map_fig.x_range.end = _ll[0][1]
map_fig.y_range.start = _ll[1][0]
map_fig.y_range.end = _ll[1][1]
cart_fig.xaxis.major_tick_line_color = None
# turn off x-axis major ticks
cart_fig.xaxis.minor_tick_line_color = None
# turn off x-axis minor ticks
cart_fig.yaxis.major_tick_line_color = None
# turn off y-axis major ticks
cart_fig.yaxis.minor_tick_line_color = None
cart_fig.xaxis.major_label_text_font_size = '0pt'
# turn off x-axis tick labels
cart_fig.yaxis.major_label_text_font_size = '0pt'
# turn off y-axis tick labels
nam = 'z037_' + frente + '_' + name_file + '.html'
nam_lat = 'z037_' + frente + '_' + 'latest' + '.html'
nam1 = os.path.join(path, nam)
nam2 = os.path.join(os.path.dirname(ebu.DIR), 'docs',
'graficas_htmls',
nam_lat)
# bokeh.plotting.output_file(nam2)
if show_plot:
bokeh.plotting.show(layout)
bokeh.plotting.save(layout, nam1)
bokeh.plotting.save(layout, nam2)
return data
tools=["wheel_zoom", "pan"],
x_range=(-13000000, -7000000),
y_range=(2750000, 6250000),
webgl=True,
active_scroll="wheel_zoom")
fig.axis.visible = False
STAMEN_TONER_BACKGROUND = WMTSTileSource(
url='http://tile.stamen.com/toner-background/{Z}/{X}/{Y}.png',
attribution=
('Map tiles by <a href="http://stamen.com">Stamen Design</a>, '
'under <a href="http://creativecommons.org/licenses/by/3.0">CC BY 3.0</a>.'
'Data by <a href="http://openstreetmap.org">OpenStreetMap</a>, '
'under <a href="http://www.openstreetmap.org/copyright">ODbL</a>'))
fig.add_tile(STAMEN_TONER_BACKGROUND)
accidents.loc[accidents.DRUNK_DR != 0, "DRUNK_DR"] = "YES"
accidents.loc[accidents.DRUNK_DR == 0, "DRUNK_DR"] = "NO"
accidents.loc[accidents.SP != 0, "SP"] = "YES"
accidents.loc[accidents.SP == 0, "SP"] = "NO"
accidents.loc[accidents.WEATHER.isin([0, 1, 8, 10, 98, 99]),
"WEATHER"] = "Clear"
accidents.loc[accidents.WEATHER == 2, "WEATHER"] = "Rain"
accidents.loc[accidents.WEATHER == 3, "WEATHER"] = "Sleet/Hail"
accidents.loc[accidents.WEATHER == 4, "WEATHER"] = "Snow"
accidents.loc[accidents.WEATHER == 5, "WEATHER"] = "Fog/Smog/Smoke"
accidents.loc[accidents.WEATHER == 6, "WEATHER"] = "Severe Crosswinds"
accidents.loc[accidents.WEATHER == 7, "WEATHER"] = "Blowing Sand, Soil, Dirt"
accidents.loc[accidents.WEATHER == 11, "WEATHER"] = "Blowing Snow"
accidents.loc[accidents.WEATHER == 12, "WEATHER"] = "Freezing Rain"
fig = Figure(plot_width=1100, plot_height=650, tools=["wheel_zoom", "pan"],
x_range=(-13000000, -7000000), y_range=(2750000, 6250000), webgl=True,
active_scroll="wheel_zoom")
fig.axis.visible = False
STAMEN_TONER_BACKGROUND = WMTSTileSource(
url='http://tile.stamen.com/toner-background/{Z}/{X}/{Y}.png',
attribution=(
'Map tiles by <a href="http://stamen.com">Stamen Design</a>, '
'under <a href="http://creativecommons.org/licenses/by/3.0">CC BY 3.0</a>.'
'Data by <a href="http://openstreetmap.org">OpenStreetMap</a>, '
'under <a href="http://www.openstreetmap.org/copyright">ODbL</a>'
)
)
fig.add_tile(STAMEN_TONER_BACKGROUND)
accidents.loc[accidents.DRUNK_DR != 0, "DRUNK_DR"] = "YES"
accidents.loc[accidents.DRUNK_DR == 0, "DRUNK_DR"] = "NO"
accidents.loc[accidents.SP != 0, "SP"] = "YES"
accidents.loc[accidents.SP == 0, "SP"] = "NO"
accidents.loc[accidents.WEATHER.isin([0,1,8,10,98,99]), "WEATHER"] = "Clear"
accidents.loc[accidents.WEATHER == 2, "WEATHER"] = "Rain"
accidents.loc[accidents.WEATHER == 3, "WEATHER"] = "Sleet/Hail"
accidents.loc[accidents.WEATHER == 4, "WEATHER"] = "Snow"
accidents.loc[accidents.WEATHER == 5, "WEATHER"] = "Fog/Smog/Smoke"
accidents.loc[accidents.WEATHER == 6, "WEATHER"] = "Severe Crosswinds"
accidents.loc[accidents.WEATHER == 7, "WEATHER"] = "Blowing Sand, Soil, Dirt"
accidents.loc[accidents.WEATHER == 11, "WEATHER"] = "Blowing Snow"
accidents.loc[accidents.WEATHER == 12, "WEATHER"] = "Freezing Rain"
# Create plot -------------------------------
xmin = -8240227.037
ymin = 4974203.152
xmax = -8231283.905
ymax = 4979238.441
path = './data/projected.tif'
fig = Figure(x_range=(xmin, xmax),
y_range=(ymin, ymax),
plot_height=600,
plot_width=900,
tools='pan,wheel_zoom')
fig.background_fill_color = 'black'
fig.add_tile(get_provider("STAMEN_TONER"),
alpha=0) # used to set axis ranges
fig.x_range.callback = CustomJS(code=dims_jscode,
args=dict(plot=fig, dims=dims))
fig.y_range.callback = CustomJS(code=dims_jscode,
args=dict(plot=fig, dims=dims))
fig.axis.visible = False
fig.grid.grid_line_alpha = 0
fig.min_border_left = 0
fig.min_border_right = 0
fig.min_border_top = 0
fig.min_border_bottom = 0
image_source = ColumnDataSource(dict(image=[], x=[], y=[], dw=[], dh=[]))
fig.image_rgba(source=image_source,
image='image',
x='x',
def plot_carto_single(self,
data,
frente,
palette,
name_file="test.html",
low=0,
high=100):
"""
:param data: df loaded by data_load
:param frente: string, name of "partido" lowercase: diff, mas, cc, creemos, fpv, panbol
:param palette: ej: P_GRAD_CC
:param name_file: default:test
:param low: cmap low limit: default: -80
:param high: cmap high limit: defauilt: +80.
:return: df
"""
if frente == "diff":
low = self.C_BAR_LOW
high = self.C_BAR_HIGH
frente = "d_mas_cc"
bokeh.plotting.output_file(self.FILE_OUT + '_' + frente + '_' +
name_file)
cart_init_val = self.CART_SLIDER_INIT # add slider
data['x'] = data['LON'] * (1 -
cart_init_val) + data['X'] * cart_init_val
data['y'] = data['LAT'] * (1 -
cart_init_val) + data['Y'] * cart_init_val
cm = linear_cmap(frente, palette=palette, low=low, high=high)
data['mas'] = data['MAS'] / data['VV'] * 100
data['cc'] = data['CC'] / data['VV'] * 100
data['pdc'] = data['PDC'] / data['VV'] * 100
#data['creemos'] = data['CREEMOS'] / data['VV'] * 100
#data['fpv'] = data['FPV'] / data['VV'] * 100
#data['panbol'] = data['PANBOL'] / data['VV'] * 100
data['ad_mas_cc'] = data['d_mas_cc'].abs()
data['mas_o_cc'] = 'n'
data.loc[data['d_mas_cc'] >= 0, 'mas_o_cc'] = 'MAS'
data.loc[data['d_mas_cc'] < 0, 'mas_o_cc'] = 'CC'
source_master = ColumnDataSource(data)
source_red_map = ColumnDataSource({'gx': [], 'gy': []})
la, lo = ebu.get_la_lo_bolivia()
source_bol = ColumnDataSource({'la': la, 'lo': lo})
# source_red_car = ColumnDataSource({'lo': [], 'la': []})
# JS CODE
code_draw_red_map = """
const data = {'gx': [], 'gy': []}
const indices = cb_data.index.indices
for (var i = 0; i < indices.length; i++ ) {
data['gx'].push(source_master.data.GX[indices[i]])
data['gy'].push(source_master.data.GY[indices[i]])
}
source_red_map.data = data
"""
code_draw_red_car = """
const data = {'lo': [], 'la': []}
const indices = cb_data.index.indices
for (var i = 0; i < indices.length; i++) {
data['lo'].push(source_master.data.x[indices[i]])
data['la'].push(source_master.data.y[indices[i]])
}
source_red_car.data = data
"""
code_merged = """
const data_map = {'lo': [], 'la': []}
const data_car = {'gx': [], 'gy': []}
const indices = cb_data.index.indices
for (var i = 0; i < indices.length; i++) {
data_map['lo'].push(source_master.data.x[indices[i]])
data_map['la'].push(source_master.data.y[indices[i]])
data_car['gx'].push(source_master.data.GX[indices[i]])
data_car['gy'].push(source_master.data.GY[indices[i]])
}
source_red_car.data = data_car
source_red_map.data = data_map
"""
code_slider = """
var data = source.data;
var f = cb_obj.value
var x = data['x']
var y = data['y']
var Y = data['Y']
var X = data['X']
var lat = data['LAT']
var lon = data['LON']
for (var i = 0; i < x.length; i++) {
y[i] = (1-f)*lat[i] + f*Y[i]
x[i] = (1-f)*lon[i] + f*X[i]
}
source.change.emit();
"""
# FIGURES
pw = self.FIG_WIDTH
cart_fig = Figure(plot_width=pw,
plot_height=pw,
output_backend="webgl")
map_fig = Figure(
plot_width=pw,
plot_height=pw,
x_axis_type='mercator',
y_axis_type='mercator',
output_backend="webgl",
)
cart_fig.background_fill_color = "grey"
cart_fig.background_fill_alpha = .5
# cb_fig = bokeh.plotting.Figure(plot_height=pw,plot_width=)
# cb_fig.toolbar.logo = None
# cb_fig.toolbar_location = None
# SCATTER
# noinspection PyUnresolvedReferences
# add tiles
tile_provider = bokeh.tile_providers.get_provider(
bokeh.tile_providers.Vendors.CARTODBPOSITRON)
map_fig.add_tile(tile_provider)
# scatter in map
map_fig.scatter('GX', 'GY', source=source_master, size='r2', color=cm)
# todo if we wont use map then we nee to delete the source
# cart_fig.line('lo', 'la', source=source_bol, color='black')
cart_fig.scatter('x', 'y', source=source_master, radius='r', color=cm)
red_scat_map = map_fig.circle_cross(
'gx',
'gy',
source=source_red_map,
# color='red',
fill_color=None,
# line_color='green',
size=20,
line_color="white",
line_width=4)
red_scat_map = map_fig.circle_cross(
'gx',
'gy',
source=source_red_map,
# color='red',
fill_color=None,
# line_color='green',
size=20,
line_color="red",
line_width=1)
# red_scat_car = cart_fig.scatter('lo', 'la',
# source=source_red_car, color='green')
# add a hover tool that sets the link data for a hovered circle
# callbacks
callback_red_map = CustomJS(
args={
'source_master': source_master,
'source_red_map': source_red_map,
# 'source_red_car':source_red_car
},
code=code_draw_red_map)
# code = code_merged)
# callback_red_car = CustomJS(
# args={'source_master': source_master, 'source_red_car': source_red_car},
# code=code_draw_red_car)
# tools
hover_cart = bokeh.models.HoverTool(
tooltips=self.TOOL_TIP_DIC[frente],
callback=callback_red_map,
# renderers = [red_scat_car]
)
cart_fig.add_tools(hover_cart, )
hover_map = bokeh.models.HoverTool(
tooltips=self.TOOL_TIP_DIC[frente],
# callback=callback_red_car,
# renderers = [red_scat_map]
)
map_fig.add_tools(hover_map, )
# slider
callback_slider = CustomJS(args=dict(source=source_master),
code=code_slider)
slider = Slider(start=0,
end=1,
value=cart_init_val,
step=.02,
title="carto")
slider.js_on_change('value', callback_slider)
# COLOR BAR
ml = {int(i): str(np.abs(i)) for i in np.arange(-80, 81, 20)}
cb = bokeh.models.ColorBar(
color_mapper=cm['transform'],
width=int(.9 * self.FIG_WIDTH),
location=(0, 0),
# title="DEN (N/km^2)",
# title=(BAR_TITLE),
# margin=0,padding=0,
title_standoff=10,
# ticker=bokeh.models.LogTicker(),
orientation='horizontal',
major_label_overrides=ml)
cart_fig.add_layout(cb, 'above')
# cb.title_text_align = 'left'
cart_fig.title.text = self.BAR_TITLE_DIC[frente]
cart_fig.title.align = 'center'
# layout = row(column(slider, cart_f),map_f)
layout = bokeh.layouts.gridplot([[slider, None], [cart_fig, map_fig]],
merge_tools=False)
# layout = bokeh.layouts.column([slider, cart_fig])
cart_fig.x_range.start = self.CXS
cart_fig.x_range.end = self.CXE
cart_fig.y_range.start = self.CYS
cart_fig.y_range.end = self.CYE
_ll = ebu.lola_to_cart(lo=[self.MXS, self.MXE],
la=[self.MYS, self.MYE])
map_fig.x_range.start = _ll[0][0]
map_fig.x_range.end = _ll[0][1]
map_fig.y_range.start = _ll[1][0]
map_fig.y_range.end = _ll[1][1]
cart_fig.xaxis.major_tick_line_color = None # turn off x-axis major ticks
cart_fig.xaxis.minor_tick_line_color = None # turn off x-axis minor ticks
cart_fig.yaxis.major_tick_line_color = None # turn off y-axis major ticks
cart_fig.yaxis.minor_tick_line_color = None
cart_fig.xaxis.major_label_text_font_size = '0pt' # turn off x-axis tick labels
cart_fig.yaxis.major_label_text_font_size = '0pt' # turn off y-axis tick labels
bokeh.plotting.show(layout)
return data