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._addtimebars()
self._setbackground()
self._visdata()
self._setyaxislabel()
self._setzaxislabel()
self._addhoverlines()
self._addlegend()
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):
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])
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],
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 TVarFigureMap(object):
def __init__(self,
tvar_name,
auto_color=False,
show_xaxis=False,
slice=False):
self.tvar_name = tvar_name
self.show_xaxis = show_xaxis
self.slice = slice
# 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()
@staticmethod
def get_axis_label_color():
if pytplot.tplot_opt_glob['black_background']:
text_color = '#000000'
else:
text_color = '#FFFFFF'
return text_color
@staticmethod
def getaxistype():
axis_type = 'map'
link_y_axis = True
return axis_type, link_y_axis
def getfig(self):
if self.slice:
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'],
text_color=self.get_axis_label_color())
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._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
self.fig.lod_factor = 100
self.fig.lod_interval = 30
self.fig.lod_threshold = 100
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].attrs['plot_options']['zaxis_opt']:
self.zmin = pytplot.data_quants[self.tvar_name].attrs[
'plot_options']['zaxis_opt']['z_range'][0]
self.zmax = pytplot.data_quants[self.tvar_name].attrs[
'plot_options']['zaxis_opt']['z_range'][1]
else:
dataset_temp = pytplot.data_quants[self.tvar_name].where(
pytplot.data_quants[self.tvar_name] != np.inf)
dataset_temp = dataset_temp.where(
pytplot.data_quants[self.tvar_name] != -np.inf)
self.zmax = np.float(dataset_temp.max(skipna=True).values)
self.zmin = np.float(dataset_temp.min(skipna=True).values)
# Cannot have a 0 minimum in a log scale
if self.zscale == 'log':
df = pytplot.tplot_utilities.convert_tplotxarray_to_pandas_dataframe(
self.tvar_name, no_spec_bins=True)
zmin_list = []
for column in df.columns:
series = df[column]
zmin_list.append(
series.iloc[series.to_numpy().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].attrs['plot_options']['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])
# grab tbardict
tbardict = pytplot.data_quants[
self.tvar_name].attrs['plot_options']['time_bar']
ltbar = len(tbardict)
# make sure data is in list format
datasets = [pytplot.data_quants[self.tvar_name]]
for oplot_name in pytplot.data_quants[
self.tvar_name].attrs['plot_options']['overplots']:
datasets.append(pytplot.data_quants[oplot_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].attrs[
'plot_options']['time_bar'][i]["location"]
color = pytplot.data_quants[self.tvar_name].attrs[
'plot_options']['time_bar'][i]["line_color"]
pointsize = pytplot.data_quants[self.tvar_name].attrs[
'plot_options']['time_bar'][i]["line_width"]
# correlate given time with corresponding lat/lon points
time = pytplot.data_quants[dataset.attrs['plot_options']
['links']['lat']].coords['time']
latitude = pytplot.data_quants[dataset.attrs['plot_options']
['links']['lat']].values
longitude = pytplot.data_quants[dataset.attrs['plot_options']
['links']['lon']].values
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].attrs['plot_options']['zaxis_opt']:
self.zscale = pytplot.data_quants[self.tvar_name].attrs[
'plot_options']['zaxis_opt']['z_axis_type']
def _setcolors(self):
if 'colormap' in pytplot.data_quants[
self.tvar_name].attrs['plot_options']['extras']:
for cm in pytplot.data_quants[self.tvar_name].attrs[
'plot_options']['extras']['colormap']:
self.colors.append(
pytplot.tplot_utilities.return_bokeh_colormap(cm))
else:
self.colors.append(
pytplot.tplot_utilities.return_bokeh_colormap('magma'))
def _setxaxislabel(self):
self.fig.xaxis.axis_label = 'Longitude'
self.fig.xaxis.axis_label_text_font_size = str(
pytplot.data_quants[self.tvar_name].attrs['plot_options']['extras']
['char_size']) + 'pt'
self.fig.xaxis.axis_label_text_color = self.get_axis_label_color()
def _setyaxislabel(self):
self.fig.yaxis.axis_label = 'Latitude'
self.fig.yaxis.axis_label_text_font_size = str(
pytplot.data_quants[self.tvar_name].attrs['plot_options']['extras']
['char_size']) + 'pt'
self.fig.yaxis.axis_label_text_color = self.get_axis_label_color()
def _visdata(self):
self._setcolors()
datasets = [pytplot.data_quants[self.tvar_name]]
for oplot_name in pytplot.data_quants[
self.tvar_name].attrs['plot_options']['overplots']:
datasets.append(pytplot.data_quants[oplot_name])
cm_index = 0
for dataset in datasets:
# TODO: Add a check that lon and lat are only 1D
coords = pytplot.tplot_utilities.return_interpolated_link_dict(
dataset, ['lon', 'lat'])
t_link_lon = coords['lon'].coords['time'].values
x = coords['lon'].values
t_link_lat = coords['lat'].coords['time'].values
y = coords['lon'].values
df = pytplot.tplot_utilities.convert_tplotxarray_to_pandas_dataframe(
dataset.name, no_spec_bins=True)
for column_name in df.columns:
data = df[column_name].values
# Need to trim down the data points to fit within the link
t_tvar = df.index.values
while t_tvar[-1] > t_link_lon[-1]:
t_tvar = np.delete(t_tvar, -1)
data = np.delete(data, -1)
while t_tvar[0] < t_link_lon[0]:
t_tvar = np.delete(t_tvar, 0)
data = np.delete(data, 0)
while t_tvar[-1] > t_link_lat[-1]:
t_tvar = np.delete(t_tvar, -1)
data = np.delete(data, -1)
while t_tvar[0] < t_link_lat[0]:
t_tvar = np.delete(t_tvar, 0)
data = np.delete(data, 0)
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=data.tolist(),
zscale=self.zscale))
circle_source = ColumnDataSource(
data=dict(x=x, y=y, value=data.tolist(), 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].attrs['plot_options']['zaxis_opt']:
if pytplot.data_quants[self.tvar_name].attrs['plot_options'][
'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'
color_bar.title = pytplot.data_quants[
self.tvar_name].attrs['plot_options']['zaxis_opt']['axis_label']
color_bar.title_text_font_size = str(
pytplot.data_quants[self.tvar_name].attrs['plot_options']['extras']
['char_size']) + 'pt'
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].attrs['plot_options']['extras']:
alpha = pytplot.data_quants[
self.tvar_name].attrs['plot_options']['extras']['alpha']
else:
alpha = 1
if 'basemap' in pytplot.data_quants[
self.tvar_name].attrs['plot_options']['extras']:
if os.path.isfile(
pytplot.data_quants[self.tvar_name].attrs['plot_options']
['extras']['basemap']):
from scipy import misc
img = misc.imread(pytplot.data_quants[
self.tvar_name].attrs['plot_options']['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)