try:
return args.get(key)[0].decode("utf-8")
except:
return None
yaxis = get_arg_string('yaxis')
amp = get_arg_string('amp')
start_date = get_arg_string('start')
start_date = datetime.strptime(start_date, '%Y%m%d').strftime('%Y-%m-%d')
end_date = get_arg_string('end')
end_date = datetime.strptime(end_date, '%Y%m%d').strftime('%Y-%m-%d')
camera = get_arg_string('camera')
DATASHADE = get_arg_string('datashade')
outputs = models.get_product_metrics_by_camera(yaxis,
camera,
begin_date=start_date,
end_date=end_date)
df = pd.DataFrame(list(outputs))
colors = ['red', 'blue', 'green', 'orange']
plot = hv.Curve([])
if amp != None:
for amp in amp.split(','):
idx = int(amp) - 1
amp_name = "AMP {}".format(amp)
amp_key = "AMP{}".format(amp)
df[amp_key] = df['value'].apply(lambda x: x[idx])
if DATASHADE == 'true':
plot = plot * datashade(
hv.Curve(df, ['mjd', amp_key],
class Regression():
def __init__(self, xaxis, yaxis, start, end, camera):
self.yaxis = yaxis
self.xaxis = xaxis
self.start = datetime.strptime(start, '%Y%m%d').strftime('%Y-%m-%d')
self.end = datetime.strptime(end, '%Y%m%d').strftime('%Y-%m-%d')
self.camera = camera
self.models = QLFModels()
def render_plot(self, outputs_x, outputs_y):
metrics_path = os.path.join(qlf_root, "framework", "ql_mapping",
"metrics.json")
with open(metrics_path) as f:
metrics = json.load(f)
y_data = metrics[self.yaxis]
x_data = metrics[self.xaxis]
df_x = pd.DataFrame(list(outputs_x))
df_y = pd.DataFrame(list(outputs_y))
source = ColumnDataSource(
data=dict(x=df_x['value'].apply(lambda x: x[0]),
y=df_y['value'].apply(lambda x: x[0]),
exposure=df_x['exposure_id'],
camera=df_x['camera']))
TOOLTIPS = """
<div>
<div>
<span style="font-size: 1vw; font-weight: bold; color: #303030;">{}: </span>
<span style="font-size: 1vw; color: #515151">@y</span>
</div>
<div>
<span style="font-size: 1vw; font-weight: bold; color: #303030;">{}: </span>
<span style="font-size: 1vw; color: #515151;">@x</span>
</div>
<div>
<span style="font-size: 1vw; font-weight: bold; color: #303030;">Exposure: </span>
<span style="font-size: 1vw; color: #515151;">@exposure</span>
</div>
</div>
""".format(y_data['display'], x_data['display'])
hover = HoverTool(tooltips=TOOLTIPS)
plot = figure(
title="Camera: {}".format(self.camera),
toolbar_location='above',
active_drag="box_zoom",
plot_height=300,
# plot_width=500,
x_axis_label=x_data['display'],
y_axis_label=y_data['display'],
tools=[hover, 'box_zoom,pan,wheel_zoom,box_select,reset'],
sizing_mode='scale_width')
q = plot.circle('x',
'y',
source=source,
size=8,
fill_color='dodgerblue',
hover_fill_color='blue',
line_color='black')
font_size = "1.2vw"
plot.xaxis.major_label_text_font_size = font_size
plot.yaxis.major_label_text_font_size = font_size
plot.xaxis.axis_label_text_font_size = font_size
plot.yaxis.axis_label_text_font_size = font_size
plot.legend.label_text_font_size = font_size
plot.title.text_font_size = font_size
self.layout = plot
def render(self):
outputs_y = self.models.get_product_metrics_by_camera(
self.yaxis, self.camera, begin_date=self.start, end_date=self.end)
outputs_x = self.models.get_product_metrics_by_camera(
self.xaxis, self.camera, begin_date=self.start, end_date=self.end)
self.render_plot(outputs_x, outputs_y)
return file_html(self.layout, CDN, "Regression")
class TimeSeries():
def __init__(self, yaxis, start, end, camera, amp=None):
self.yaxis = yaxis
self.start = datetime.strptime(start, '%Y%m%d').strftime('%Y-%m-%d')
self.end = datetime.strptime(end, '%Y%m%d').strftime('%Y-%m-%d')
self.camera = camera
self.models = QLFModels()
self.amp = amp
def make_plot(self, outputs, objtype=None):
colors = ['red', 'blue', 'green', 'orange']
legends = list()
df = pd.DataFrame(list(outputs))
if self.amp != None:
for amp in self.amp.split(','):
idx = int(amp) - 1
source = ColumnDataSource(
data=dict(x=df['mjd'],
y=df['value'].apply(lambda x: x[idx]),
exposure=df['exposure_id'],
camera=df['camera'],
dateobs=df['datef']))
line = self.p.line('x',
'y',
source=source,
line_color=colors[idx])
circle = self.p.circle('x',
'y',
source=source,
size=6,
line_color=None,
fill_color=colors[idx])
legends.append(('AMP {}'.format(idx + 1), [line, circle]))
legend = Legend(items=legends, location=(0, 0))
self.p.add_layout(legend, 'below')
else:
source = ColumnDataSource(
data=dict(x=df['mjd'],
y=df['value'].apply(lambda x: x[0]),
exposure=df['exposure_id'],
camera=df['camera'],
dateobs=df['datef']))
self.p.line('x', 'y', source=source)
self.p.circle('x', 'y', source=source, size=5)
def render(self):
metrics_path = os.path.join(qlf_root, "framework", "ql_mapping",
"metrics.json")
with open(metrics_path) as f:
metrics = json.load(f)
axis_data = metrics[self.yaxis]
outputs = self.models.get_product_metrics_by_camera(
self.yaxis, self.camera, begin_date=self.start, end_date=self.end)
TOOLTIPS = """
<div>
<div>
<span style="font-size: 1vw; font-weight: bold; color: #303030;">{}: </span>
<span style="font-size: 1vw; color: #515151;">@y</span>
</div>
<div>
<span style="font-size: 1vw; font-weight: bold; color: #303030;">Exposure: </span>
<span style="font-size: 1vw; color: #515151;">@exposure</span>
</div>
<div>
<span style="font-size: 1vw; font-weight: bold; color: #303030;">Date: </span>
<span style="font-size: 1vw; color: #515151;">@dateobs</span>
</div>
</div>
""".format(axis_data['display'])
hover = HoverTool(tooltips=TOOLTIPS)
self.p = figure(
title="Camera: {}".format(self.camera),
sizing_mode='scale_width',
toolbar_location='above',
# x_axis_type="datetime",
x_axis_label='Date (mjd)',
y_axis_label=axis_data['display'],
plot_width=700,
plot_height=300,
active_drag="box_zoom",
tools=[hover, 'box_zoom,wheel_zoom,pan,reset'])
font_size = "1.2vw"
self.p.xaxis.major_label_text_font_size = font_size
self.p.yaxis.major_label_text_font_size = font_size
self.p.xaxis.axis_label_text_font_size = font_size
self.p.yaxis.axis_label_text_font_size = font_size
self.p.legend.label_text_font_size = font_size
self.p.title.text_font_size = font_size
self.make_plot(outputs)
return file_html(self.p, CDN, "Time Series")
