def get_weather_plot(time_int=None, t_min=None, t_max=None):
plot_height = cs.plot_height
plot_width = cs.plot_width
border_left = cs.border_left
column_names = cs.column_names_weewx
column_time = cs.time_column_name_weewx
if t_max == None or t_min == None:
t_max, t_min = get_first_time_interval()
t_span = t_max - t_min
if time_int == None:
time_int = cs.time_int
data_seconds = sql_con.get_data_ws(time_int=time_int,
t_min=t_min,
t_max=t_max)
data_seconds.iloc[:, 0] = data_seconds.iloc[:, 0] * 1000
plot = Plot(
x_range=DataRange1d(start=(t_min - t_span * .1) * 1000,
end=(t_max + t_span * .1) * 1000),
y_range=DataRange1d(),
plot_width=plot_width,
plot_height=plot_height,
# x_axis_type="datetime",
min_border_left=border_left,
toolbar_location="right")
add_glyphs_to_plot(column_names, column_time, data_seconds, plot,
'source_weather')
plot.add_layout(DatetimeAxis(name="date_time_axis"), 'below')
plot.add_tools(
PanTool(),
WheelZoomTool(),
# ResizeTool(),
CrosshairTool(),
PreviewSaveTool())
Grid(plot=plot,
dimension=0,
ticker=plot.select('date_time_axis')[0].ticker)
Grid(plot=plot,
dimension=1,
ticker=plot.select(type=LinearAxis, name=column_names[0])[0].ticker)
set_legends(plot)
plot.title = cs.plot_title_weewx + ' averaged to {} seconds'.format(
time_int)
return plot
def get_weather_plot(time_int=None,t_min=None,t_max=None):
plot_height = cs.plot_height
plot_width = cs.plot_width
border_left = cs.border_left
column_names = cs.column_names_weewx
column_time = cs.time_column_name_weewx
if t_max == None or t_min == None:
t_max, t_min = get_first_time_interval()
t_span = t_max - t_min
if time_int == None:
time_int = cs.time_int
data_seconds = sql_con.get_data_ws(time_int=time_int, t_min=t_min, t_max=t_max)
data_seconds.iloc[:, 0] = data_seconds.iloc[:, 0] * 1000
plot = Plot(x_range=DataRange1d(start=(t_min-t_span*.1)*1000,
end=(t_max+t_span*.1)*1000),
y_range=DataRange1d(),
plot_width=plot_width,
plot_height=plot_height,
# x_axis_type="datetime",
min_border_left=border_left,
toolbar_location="right")
add_glyphs_to_plot(column_names, column_time, data_seconds, plot,'source_weather')
plot.add_layout(DatetimeAxis(name="date_time_axis"), 'below')
plot.add_tools(PanTool(),
WheelZoomTool(),
# ResizeTool(),
CrosshairTool(),
PreviewSaveTool()
)
Grid(plot=plot,dimension=0,ticker=plot.select('date_time_axis')[0].ticker)
Grid(plot=plot,
dimension=1,
ticker=plot.select(type=LinearAxis,name=column_names[0])[0].ticker
)
set_legends(plot)
plot.title = cs.plot_title_weewx + ' averaged to {} seconds'.format(time_int)
return plot
def save_graph(fol_path):
df = folderstats.folderstats(fol_path, ignore_hidden=True)
df.loc[list(np.where(df["folder"] == True)[0]),
"name"] = df[df["folder"] == True]["path"].apply(ret_name).values
# df["name"] = df["name"]+"."+df["extension"]
df_sorted = df.sort_values(by='id')
G = nx.Graph()
for i, row in df_sorted.iterrows():
if row.parent:
G.add_edge(row.id, row.parent)
plot = Plot(plot_width=1000,
plot_height=1000,
x_range=Range1d(-1.1, 1.1),
y_range=Range1d(-1.1, 1.1))
plot.title.text = "File System"
plot.add_tools(TapTool(), BoxSelectTool(), BoxZoomTool(), ResetTool(),
WheelZoomTool(), PanTool())
graph_renderer = from_networkx(G, nx.spring_layout, scale=2, center=(0, 0))
graph_renderer.node_renderer.data_source.data["id"] = df_sorted[
"id"].astype('str').values
graph_renderer.node_renderer.data_source.data["name"] = df_sorted["name"]
graph_renderer.node_renderer.data_source.data["links"] = df_sorted["path"]
graph_renderer.node_renderer.data_source.add(Spectral8, 'color')
graph_renderer.node_renderer.glyph = Circle(size=20, fill_color="color")
graph_renderer.node_renderer.selection_glyph = Circle(size=20,
fill_color="color")
graph_renderer.node_renderer.hover_glyph = Circle(size=20,
fill_color="color")
graph_renderer.edge_renderer.glyph = MultiLine(line_color="#CCCCCC",
line_alpha=0.8,
line_width=5)
graph_renderer.edge_renderer.selection_glyph = MultiLine(
line_color=Spectral4[2], line_width=5)
graph_renderer.edge_renderer.hover_glyph = MultiLine(
line_color=Spectral4[1], line_width=5)
graph_renderer.selection_policy = NodesAndLinkedEdges()
graph_renderer.inspection_policy = EdgesAndLinkedNodes()
pos = graph_renderer.layout_provider.graph_layout
x, y = zip(*pos.values())
url = "@links"
code = """
console.log(source.data)
var data = source.data.file;
var ind= cb_data.source.selected.indices;
console.log(data[ind])
window.open(data[ind])
//window.location.href = data[ind]
"""
source = ColumnDataSource({
'x': x,
'y': y,
'field': df_sorted["name"].values,
'file': df_sorted["path"].values
})
labels = LabelSet(x='x', y='y', text='field', source=source)
taptool = plot.select(type=TapTool)
taptool.callback = CustomJS(args=dict(source=source), code=code)
plot.renderers.append(graph_renderer)
plot.renderers.append(labels)
output_file("interactive_graphs.html")
show(plot)
