def _add_lines(
plot: BokePlot, ot_data: pd.DataFrame, date_column: str, feature: str
) -> BokePlot:
for author, colour in zip(ot_data.index.unique(), Spectral11):
tmp = ot_data.loc[[author], [date_column, feature, "title"]].copy()
source = ColumnDataSource(tmp)
plot.circle(
date_column,
feature,
source=source,
legend_label=author,
fill_color=colour,
)
plot.line(
date_column,
feature,
source=source,
legend_label=author,
line_color=colour,
)
return plot
class TVarFigureMap(object):
def __init__(self,
tvar_name,
auto_color=False,
show_xaxis=False,
interactive=False):
self.tvar_name = tvar_name
self.show_xaxis = show_xaxis
self.interactive = interactive
#Variables needed across functions
self.fig = None
self.colors = []
self.lineglyphs = []
self.linenum = 0
self.zscale = 'linear'
self.zmin = 0
self.zmax = 1
self.callback = None
self.interactive_plot = None
self.fig = Figure(tools="pan,crosshair,reset,box_zoom",
y_axis_type=self._getyaxistype())
self._format()
def getaxistype(self):
axis_type = 'map'
link_y_axis = True
return axis_type, link_y_axis
def getfig(self):
if self.interactive:
return [self.fig, self.interactive_plot]
else:
return [self.fig]
def setsize(self, width, height):
self.fig.plot_width = width
if self.show_xaxis:
self.fig.plot_height = height + 22
else:
self.fig.plot_height = height
def add_title(self):
if 'title_text' in pytplot.tplot_opt_glob:
if pytplot.tplot_opt_glob['title_text'] != '':
title1 = Title(
text=pytplot.tplot_opt_glob['title_text'],
align=pytplot.tplot_opt_glob['title_align'],
text_font_size=pytplot.tplot_opt_glob['title_size'])
self.fig.title = title1
self.fig.plot_height += 22
def buildfigure(self):
self._setminborder()
self._setxrange()
self._setxaxis()
self._setyrange()
self._setzrange()
self._setzaxistype()
self._setbackground()
self._visdata()
self._setyaxislabel()
self._setzaxislabel()
self._addhoverlines()
self._addlegend()
self._addtimebars()
def _format(self):
#Formatting stuff
self.fig.grid.grid_line_color = None
self.fig.axis.major_tick_line_color = None
self.fig.axis.major_label_standoff = 0
self.fig.title = None
self.fig.toolbar.active_drag = 'auto'
if not self.show_xaxis:
self.fig.xaxis.major_label_text_font_size = '0pt'
self.fig.xaxis.visible = False
self.fig.lod_factor = 100
self.fig.lod_interval = 30
self.fig.lod_threshold = 100
self.fig.yaxis.axis_label_text_font_size = "10pt"
def _setxrange(self):
#Check if x range is not set, if not, set good ones
if 'map_range' not in pytplot.tplot_opt_glob:
pytplot.tplot_opt_glob['map_range'] = [0, 360]
tplot_x_range = Range1d(0, 360)
if self.show_xaxis:
pytplot.lim_info['xfull'] = tplot_x_range
pytplot.lim_info['xlast'] = tplot_x_range
#Bokeh uses milliseconds since epoch for some reason
x_range = Range1d(pytplot.tplot_opt_glob['map_range'][0],
pytplot.tplot_opt_glob['map_range'][1],
bounds=(0, 360))
self.fig.x_range = x_range
def _setyrange(self):
y_range = Range1d(-90, 90, bounds=(-90, 90))
self.fig.y_range = y_range
def _setzrange(self):
#Get Z Range
if 'z_range' in pytplot.data_quants[self.tvar_name].zaxis_opt:
self.zmin = pytplot.data_quants[
self.tvar_name].zaxis_opt['z_range'][0]
self.zmax = pytplot.data_quants[
self.tvar_name].zaxis_opt['z_range'][1]
else:
if isinstance(pytplot.data_quants[self.tvar_name].data, list):
#Check the first one
dataset_temp = pytplot.data_quants[pytplot.data_quants[
self.tvar_name].data[0]].data.replace([np.inf, -np.inf],
np.nan)
else:
dataset_temp = pytplot.data_quants[
self.tvar_name].data.replace([np.inf, -np.inf], np.nan)
self.zmax = dataset_temp.max().max()
self.zmin = dataset_temp.min().min()
#Cannot have a 0 minimum in a log scale
if self.zscale == 'log':
zmin_list = []
for column in dataset_temp.columns:
series = dataset_temp[column]
zmin_list.append(series.iloc[series.nonzero()[0]].min())
self.zmin = min(zmin_list)
def _setminborder(self):
self.fig.min_border_bottom = pytplot.tplot_opt_glob[
'min_border_bottom']
self.fig.min_border_top = pytplot.tplot_opt_glob['min_border_top']
def _addtimebars(self):
for time_bar in pytplot.data_quants[self.tvar_name].time_bar:
time_bar_line = Span(location=time_bar['location'],
dimension=time_bar['dimension'],
line_color=time_bar['line_color'],
line_width=time_bar['line_width'])
self.fig.renderers.extend([time_bar_line])
#initialize dataset variable
datasets = []
#grab tbardict
tbardict = pytplot.data_quants[self.tvar_name].time_bar
ltbar = len(tbardict)
#make sure data is in list format
if isinstance(pytplot.data_quants[self.tvar_name].data, list):
for oplot_name in pytplot.data_quants[self.tvar_name].data:
datasets.append(pytplot.data_quants[oplot_name])
else:
datasets.append(pytplot.data_quants[self.tvar_name])
for dataset in datasets:
#for location in tbar dict
for i in range(ltbar):
#get times, color, point size
test_time = pytplot.data_quants[
self.tvar_name].time_bar[i]["location"]
color = pytplot.data_quants[
self.tvar_name].time_bar[i]["line_color"]
pointsize = pytplot.data_quants[
self.tvar_name].time_bar[i]["line_width"]
#correlate given time with corresponding lat/lon points
time, latitude = pytplot.get_data(dataset.links['lat'])
time, longitude = pytplot.get_data(dataset.links['lon'])
latitude = latitude.transpose()[0]
longitude = longitude.transpose()[0]
nearest_time_index = np.abs(time - test_time).argmin()
lat_point = latitude[nearest_time_index]
lon_point = longitude[nearest_time_index]
#color = pytplot.tplot_utilities.rgb_color(color)
self.fig.circle([lon_point], [lat_point],
size=pointsize,
color=color)
return
def _setxaxis(self):
#Nothing to set for now
return
def _getyaxistype(self):
#Not going to have a log planet map
return 'linear'
def _setzaxistype(self):
if 'z_axis_type' in pytplot.data_quants[self.tvar_name].zaxis_opt:
self.zscale = pytplot.data_quants[
self.tvar_name].zaxis_opt['z_axis_type']
def _setcolors(self):
if 'colormap' in pytplot.data_quants[self.tvar_name].extras:
for cm in pytplot.data_quants[self.tvar_name].extras['colormap']:
self.colors.append(
pytplot.tplot_utilities.return_bokeh_colormap(cm))
else:
self.colors.append(
pytplot.tplot_utilities.return_bokeh_colormap('magma'))
def _setyaxislabel(self):
self.fig.yaxis.axis_label = pytplot.data_quants[
self.tvar_name].yaxis_opt['axis_label']
def _setzaxislabel(self):
self.fig.yaxis.axis_label = pytplot.data_quants[
self.tvar_name].yaxis_opt['axis_label']
def _visdata(self):
self._setcolors()
datasets = []
if isinstance(pytplot.data_quants[self.tvar_name].data, list):
for oplot_name in pytplot.data_quants[self.tvar_name].data:
datasets.append(pytplot.data_quants[oplot_name])
else:
datasets.append(pytplot.data_quants[self.tvar_name])
cm_index = 0
for dataset in datasets:
#TODO: Add a check that lon and lat are only 1D
_, x = pytplot.get_data(dataset.links['lon'])
_, y = pytplot.get_data(dataset.links['lat'])
for column_name in dataset.data.columns:
values = dataset.data[column_name].tolist()
colors = []
colors.extend(
pytplot.tplot_utilities.get_heatmap_color(
color_map=self.colors[cm_index % len(self.colors)],
min_val=self.zmin,
max_val=self.zmax,
values=values,
zscale=self.zscale))
circle_source = ColumnDataSource(
data=dict(x=x, y=y, value=values, colors=colors))
self.fig.scatter(x='x',
y='y',
radius=1.0,
fill_color='colors',
fill_alpha=1,
line_color=None,
source=circle_source)
cm_index += 1
def _addhoverlines(self):
#Add tools
hover = HoverTool()
hover.tooltips = [("Longitude", "@x"), ("Latitude", "@y"),
("Value", "@value")]
self.fig.add_tools(hover)
def _addlegend(self):
#Add the color bar
if 'z_axis_type' in pytplot.data_quants[self.tvar_name].zaxis_opt:
if pytplot.data_quants[
self.tvar_name].zaxis_opt['z_axis_type'] == 'log':
color_mapper = LogColorMapper(palette=self.colors[0],
low=self.zmin,
high=self.zmax)
color_bar = ColorBarSideTitle(color_mapper=color_mapper,
border_line_color=None,
location=(0, 0),
ticker=LogTicker())
else:
color_mapper = LinearColorMapper(palette=self.colors[0],
low=self.zmin,
high=self.zmax)
color_bar = ColorBarSideTitle(color_mapper=color_mapper,
border_line_color=None,
location=(0, 0),
ticker=BasicTicker())
else:
color_mapper = LinearColorMapper(palette=self.colors[0],
low=self.zmin,
high=self.zmax)
color_bar = ColorBarSideTitle(color_mapper=color_mapper,
border_line_color=None,
location=(0, 0),
ticker=BasicTicker())
color_bar.width = 10
color_bar.formatter = BasicTickFormatter(precision=1)
color_bar.major_label_text_align = 'left'
color_bar.label_standoff = 5
color_bar.major_label_text_baseline = 'middle'
if 'axis_label' in pytplot.data_quants[self.tvar_name].zaxis_opt:
color_bar.title = pytplot.data_quants[
self.tvar_name].zaxis_opt['axis_label']
color_bar.title_text_font_size = '8pt'
color_bar.title_text_font_style = 'bold'
color_bar.title_standoff = 20
self.fig.add_layout(color_bar, 'right')
def _setbackground(self):
if 'alpha' in pytplot.data_quants[self.tvar_name].extras:
alpha = pytplot.data_quants[self.tvar_name].extras['alpha']
else:
alpha = 1
if 'basemap' in pytplot.data_quants[self.tvar_name].extras:
if os.path.isfile(
pytplot.data_quants[self.tvar_name].extras['basemap']):
from scipy import misc
img = misc.imread(
pytplot.data_quants[self.tvar_name].extras['basemap'],
mode='RGBA')
#Need to flip the image upside down...This will probably be fixed in
#a future release, so this will need to be deleted at some point
img = img[::-1]
self.fig.image_rgba(image=[img],
x=0,
y=-90,
dw=360,
dh=180,
alpha=alpha)
class TVarFigureAlt(object):
def __init__(self, tvar_name, auto_color, show_xaxis=False, interactive=False):
self.tvar_name = tvar_name
self.auto_color = auto_color
self.show_xaxis = show_xaxis
self.interactive = interactive
# Variables needed across functions
self.colors = ['black', 'red', 'green', 'navy', 'orange', 'firebrick', 'pink', 'blue', 'olive']
self.lineglyphs = []
self.linenum = 0
self.interactive_plot = None
self.fig = Figure(tools=pytplot.tplot_opt_glob['tools'],
y_axis_type=self._getyaxistype())
self.fig.add_tools(BoxZoomTool(dimensions='width'))
self._format()
def getaxistype(self):
axis_type = 'altitude'
link_y_axis = False
return axis_type, link_y_axis
def getfig(self):
if self.interactive:
return [self.fig, self.interactive_plot]
else:
return [self.fig]
def setsize(self, width, height):
self.fig.plot_width = width
if self.show_xaxis:
self.fig.plot_height = height + 22
else:
self.fig.plot_height = height
def add_title(self):
if 'title_text' in pytplot.tplot_opt_glob:
if pytplot.tplot_opt_glob['title_text'] != '':
title1 = Title(text=pytplot.tplot_opt_glob['title_text'],
align=pytplot.tplot_opt_glob['title_align'],
text_font_size=pytplot.tplot_opt_glob['title_size'])
self.fig.title = title1
self.fig.plot_height += 22
def buildfigure(self):
self._setminborder()
self._setxrange()
self._setxaxis()
self._setyrange()
self._visdata()
self._setxaxislabel()
self._setyaxislabel()
self._addhoverlines()
self._addlegend()
self._addtimebars()
def _format(self):
# Formatting stuff
self.fig.grid.grid_line_color = None
self.fig.axis.major_tick_line_color = None
self.fig.axis.major_label_standoff = 0
self.fig.title = None
self.fig.toolbar.active_drag = 'auto'
if not self.show_xaxis:
self.fig.xaxis.major_label_text_font_size = '0pt'
self.fig.xaxis.visible = False
def _setxrange(self):
# Check if x range is not set, if not, set good ones
if 'alt_range' not in pytplot.tplot_opt_glob:
datasets = []
x_min_list = []
x_max_list = []
if isinstance(pytplot.data_quants[self.tvar_name].data, list):
for oplot_name in pytplot.data_quants[self.tvar_name].data:
datasets.append(pytplot.data_quants[oplot_name])
else:
datasets.append(pytplot.data_quants[self.tvar_name])
for dataset in datasets:
_, alt = pytplot.get_data(dataset.links['alt'])
x_min_list.append(np.nanmin(alt.tolist()))
x_max_list.append(np.nanmax(alt.tolist()))
pytplot.tplot_opt_glob['alt_range'] = [np.nanmin(x_min_list), np.nanmax(x_max_list)]
tplot_x_range = [np.nanmin(x_min_list), np.nanmax(x_max_list)]
if self.show_xaxis:
pytplot.lim_info['xfull'] = tplot_x_range
pytplot.lim_info['xlast'] = tplot_x_range
x_range = Range1d(pytplot.tplot_opt_glob['alt_range'][0], pytplot.tplot_opt_glob['alt_range'][1])
self.fig.x_range = x_range
def _setyrange(self):
if self._getyaxistype() == 'log':
if pytplot.data_quants[self.tvar_name].yaxis_opt['y_range'][0] < 0 \
or pytplot.data_quants[self.tvar_name].yaxis_opt['y_range'][1] < 0:
return
y_range = Range1d(pytplot.data_quants[self.tvar_name].yaxis_opt['y_range'][0],
pytplot.data_quants[self.tvar_name].yaxis_opt['y_range'][1])
self.fig.y_range = y_range
def _setminborder(self):
self.fig.min_border_bottom = pytplot.tplot_opt_glob['min_border_bottom']
self.fig.min_border_top = pytplot.tplot_opt_glob['min_border_top']
def _addtimebars(self):
for time_bar in pytplot.data_quants[self.tvar_name].time_bar:
time_bar_line = Span(location=time_bar['location'],
dimension=time_bar['dimension'],
line_color=time_bar['line_color'],
line_width=time_bar['line_width'],
text_font_size=str(pytplot.data_quants[self.tvar_name].extras['char_size'])+'pt')
self.fig.renderers.extend([time_bar_line])
# initialize dataset variable
datasets = []
# grab tbardict
tbardict = pytplot.data_quants[self.tvar_name].time_bar
ltbar = len(tbardict)
# make sure data is in list format
if isinstance(pytplot.data_quants[self.tvar_name].data, list):
for oplot_name in pytplot.data_quants[self.tvar_name].data:
datasets.append(pytplot.data_quants[oplot_name])
else:
datasets.append(pytplot.data_quants[self.tvar_name])
for dataset in datasets:
# for location in tbar dict
for i in range(ltbar):
# get times, color, point size
test_time = pytplot.data_quants[self.tvar_name].time_bar[i]["location"]
# print(test_time)
color = pytplot.data_quants[self.tvar_name].time_bar[i]["line_color"]
pointsize = pytplot.data_quants[self.tvar_name].time_bar[i]["line_width"]
# correlate given time with corresponding data/alt points
time, altitude = pytplot.get_data(dataset.links['alt'])
altitude = altitude.transpose()[0]
nearest_time_index = np.abs(time - test_time).argmin()
data_point = dataset.data.iloc[nearest_time_index][0]
alt_point = altitude[nearest_time_index]
# color = pytplot.tplot_utilities.rgb_color(color)
self.fig.circle([alt_point], [data_point], size=pointsize, color=color)
return
def _setxaxis(self):
# Nothing to set for now
return
def _getyaxistype(self):
if 'y_axis_type' in pytplot.data_quants[self.tvar_name].yaxis_opt:
return pytplot.data_quants[self.tvar_name].yaxis_opt['y_axis_type']
else:
return 'linear'
def _setcolors(self):
if 'line_color' in pytplot.data_quants[self.tvar_name].extras:
self.colors = pytplot.data_quants[self.tvar_name].extras['line_color']
def _setxaxislabel(self):
self.fig.xaxis.axis_label = 'Altitude'
self.fig.xaxis.axis_label_text_font_size = str(pytplot.data_quants[self.tvar_name].extras['char_size'])+'pt'
def _setyaxislabel(self):
self.fig.yaxis.axis_label = pytplot.data_quants[self.tvar_name].yaxis_opt['axis_label']
self.fig.yaxis.axis_label_text_font_size = str(pytplot.data_quants[self.tvar_name].extras['char_size'])+'pt'
def _visdata(self):
self._setcolors()
datasets = []
if isinstance(pytplot.data_quants[self.tvar_name].data, list):
for oplot_name in pytplot.data_quants[self.tvar_name].data:
datasets.append(pytplot.data_quants[oplot_name])
else:
datasets.append(pytplot.data_quants[self.tvar_name])
for dataset in datasets:
# Get Linestyle
line_style = None
if 'linestyle' in pytplot.data_quants[self.tvar_name].extras:
line_style = pytplot.data_quants[self.tvar_name].extras['linestyle']
t_link, x = pytplot.get_data(dataset.links['alt'])
# Create lines from each column in the dataframe
for column_name in dataset.data.columns:
y = dataset.data[column_name]
t_tvar = dataset.data.index.values
y = dataset.data[column_name].values
while t_tvar[-1] > t_link[-1]:
t_tvar = np.delete(t_tvar, -1)
y = np.delete(y, -1)
while t_tvar[0] < t_link[0]:
t_tvar = np.delete(t_tvar, 0)
y = np.delete(y, 0)
if self._getyaxistype() == 'log':
y.loc[y <= 0] = np.NaN
line_source = ColumnDataSource(data=dict(x=x, y=y))
if self.auto_color:
line = Line(x='x', y='y', line_color=self.colors[self.linenum % len(self.colors)],
**pytplot.data_quants[self.tvar_name].line_opt)
else:
line = Line(x='x', y='y', **pytplot.data_quants[self.tvar_name].line_opt)
if 'line_style' not in pytplot.data_quants[self.tvar_name].line_opt:
if line_style is not None:
line.line_dash = line_style[self.linenum % len(line_style)]
else:
line.line_dash = pytplot.data_quants[self.tvar_name].line_opt['line_style']
self.lineglyphs.append(self.fig.add_glyph(line_source, line))
self.linenum += 1
def _addhoverlines(self):
# Add tools
hover = HoverTool()
hover.tooltips = [("Value", "@y")]
self.fig.add_tools(hover)
def _addlegend(self):
# Add the Legend if applicable
if 'legend_names' in pytplot.data_quants[self.tvar_name].yaxis_opt:
legend_names = pytplot.data_quants[self.tvar_name].yaxis_opt['legend_names']
if len(legend_names) != self.linenum:
print("Number of lines do not match length of legend names")
legend = Legend()
legend.location = (0, 0)
legend_items = []
j = 0
for legend_name in legend_names:
legend_items.append((legend_name, [self.lineglyphs[j]]))
j = j+1
if j >= len(self.lineglyphs):
break
legend.items = legend_items
legend.label_text_font_size = str(pytplot.data_quants[self.tvar_name].extras['char_size'])+'pt'
legend.border_line_color = None
legend.glyph_height = int(self.fig.plot_height / (len(legend_items) + 1))
self.fig.add_layout(legend, 'right')