def gen_prob_series(intervals, data):
j_data = json.loads(data)
predicted_data = get_predicted_data(j_data['pump'])
lastCycle = int(predicted_data['cycle'])
query = esutils.query_last_prediction(j_data['pump'], 50)
response = es.search(index='predictions', body=query)
data = []
for tag in TAG_LIST:
results = esutils.get_source_vector_value(response,
tag.replace('_', ' '),
'cycle')
color = COLOR_LIST[TAG_LIST.index(tag)]
trace = Scatter(y=results[tag.replace('_', ' ')],
x=results['cycle'],
line=plotScat.Line(color=color),
name=tag,
mode='lines')
data.append(trace)
layout = Layout(
autosize=True,
yaxis=dict(range=[0, 1], fixedrange=True, title='Results'),
xaxis=dict(
#range=[max(0, lastCycle - 30), lastCycle],
autorange=True,
zeroline=False,
title='Cycle',
tickformat=',d'),
margin=plotLayout.Margin(t=45, l=50, r=50),
plot_bgcolor="#fafafa",
paper_bgcolor="#ededed",
title='Status evolution')
return Figure(data=[t for t in data], layout=layout)
def gen_pump_card(interval, data):
j_data = json.loads(data)
current_pump = j_data['pump']
current_well = j_data['well']
logging.debug('Updating current pump: %s' % (current_pump))
queryLastCycle = esutils.query_ts_sorted_values(pump=current_pump, size=1)
data = es.search(index=current_well.lower(), body=queryLastCycle)
lastCycle = esutils.get_source_value(data, 'cycle')
if lastCycle is not None:
logging.critical('Last Cycle of the pump: %s' % lastCycle)
lastPos = esutils.get_source_value(data, 'position')
lastForce = esutils.get_source_value(data, 'force')
logging.critical('Current point (%s, %s)' % (lastPos, lastForce))
if lastPos is not None and lastForce is not None:
queryCycleValues = esutils.query_cycle_values(pump=current_pump,
cycle=lastCycle)
data = es.search(index=current_well.lower(), body=queryCycleValues)
selected_cycle_values = esutils.get_source_vector_value(
data, 'position', 'force')
logging.debug("Last cycle data received:")
logging.debug("Size of vector postion = %s" %
len(selected_cycle_values['position']))
logging.debug("Size of vector force = %s" %
len(selected_cycle_values['force']))
if selected_cycle_values is not None:
cycle_trace = Scatter(x=selected_cycle_values['position'],
y=selected_cycle_values['force'],
name='Cycle %i' % (lastCycle),
mode='lines+markers')
current_point = Scatter(x=np.array(lastPos),
y=np.array(lastForce),
name='Last point',
mode='markers')
layout = Layout(height=350,
xaxis=dict(range=[0, 1],
fixedrange=True,
title='Position'),
yaxis=dict(range=[0, 1],
fixedrange=True,
zeroline=False,
title='Force'),
margin=plotLayout.Margin(t=60,
l=50,
r=40,
b=60),
plot_bgcolor="#fafafa",
paper_bgcolor="#ededed",
title='Current card plot')
return Figure(data=[cycle_trace, current_point], layout=layout)
return None
def gen_wind_direction(interval):
now = dt.datetime.now()
sec = now.second
minute = now.minute
hour = now.hour
total_time = (hour * 3600) + (minute * 60) + (sec)
con = sqlite3.connect("./Data/wind-data.db")
df = pd.read_sql_query(
"SELECT * from Wind where rowid = " + str(total_time) + ";", con)
val = df['Speed'].iloc[-1]
direction = [0, (df['Direction'][0] - 7), (df['Direction'][0] + 7), 0]
fcolor0 = '#%2x80%2x' % (0x84 + 2 * int(val), 0x86 - 2 * int(val))
fcolor1 = '#%2x80%2x' % (0x84 + 2 * int(val), 0x86 - 2 * int(val))
fcolor2 = '#%2x80%2x' % (0x84 + 2 * int(val), 0x86 - 2 * int(val))
trace0 = Scatterpolar(r=[0, val, val, 0],
theta=direction,
mode='lines',
fill='toself',
fillcolor=fcolor0,
line=dict(color='rgba(32, 32, 32, .6)', width=1))
trace1 = Scatterpolar(r=[0, val * 0.65, val * 0.65, 0],
theta=direction,
mode='lines',
fill='toself',
fillcolor='#C7D9F9',
line=dict(color='rgba(32, 32, 32, .6)', width=1))
trace2 = Scatterpolar(r=[0, val * 0.3, val * 0.3, 0],
theta=direction,
mode='lines',
fill='toself',
fillcolor='#DBDCFC',
line=dict(color='rgba(32, 32, 32, .6)', width=1))
layout = Layout(
autosize=True,
width=360,
margin=playout.Margin(t=10, b=10, r=20, l=20),
polar=dict(bgcolor='#F2F2F2',
radialaxis=dict(range=[0, 60], angle=0, dtick=10),
angularaxis=dict(showline=False, tickcolor='white')),
showlegend=False,
)
return Figure(data=[trace0, trace1, trace2], layout=layout)
def gen_wind_speed(interval):
now = dt.datetime.now()
sec = now.second
minute = now.minute
hour = now.hour
total_time = (hour * 3600) + (minute * 60) + (sec)
con = sqlite3.connect("./Data/wind-data.db")
df = pd.read_sql_query(
'SELECT Speed, SpeedError, Direction from Wind where\
rowid > "{}" AND rowid <= "{}";'.format(
total_time - 200, total_time), con)
trace = Scatter(y=df['Speed'],
line=pscatter.Line(color='#42C4F7'),
hoverinfo='skip',
error_y=pscatter.ErrorY(type='data',
array=df['SpeedError'],
thickness=1.5,
width=2,
color='#B4E8FC'),
mode='lines')
layout = Layout(height=450,
xaxis=dict(range=[200, 0],
showgrid=False,
showline=False,
zeroline=False,
fixedrange=True,
tickvals=[0, 50, 100, 150, 200],
ticktext=['200', '150', '100', '50', '0'],
title='Time Elapsed (sec)'),
yaxis=dict(range=[
min(0, min(df['Speed'])),
max(45,
max(df['Speed']) + max(df['SpeedError']))
],
showline=False,
fixedrange=True,
zeroline=False,
nticks=max(6,
round(df['Speed'].iloc[-1] / 10))),
margin=playout.Margin(t=45, l=50, r=45))
return Figure(data=[trace], layout=layout)
def gen_wind_speed(interval):
now = dt.datetime.now()
sec = now.second
minute = now.minute
hour = now.hour
#microsecond = now.microsecond
total_time = (hour * 3600) + (minute * 60) + (sec) # + (microsecond)
con = sqlite3.connect("./data/acceleration-data.db")
df = pd.read_sql_query(
'SELECT Time, X, Y, Z from acceleration where\
rowid > "{}" AND rowid <= "{}";'.format(
total_time - 200, total_time), con)
trace1 = Scatter(
#x=df['Time'],
y=df['X'],
# line=scatter.Line(
# color='#42C4F7'
#),
mode='lines',
name='X')
trace2 = Scatter(
#x=df['Time'],
y=df['Y'],
#line= scatter.Line(
# color='#42C4F7'
#),
mode='lines',
name='Y')
trace3 = Scatter(
#x=df['Time'],
y=df['Z'],
#line= scatter.Line(
# color='#42C4F7'
#),
mode='lines',
name='Z')
layout = Layout(
height=450,
xaxis=dict(range=[0, 200],
showgrid=False,
showline=False,
zeroline=False,
fixedrange=True,
tickvals=[0, 50, 100, 150, 200],
ticktext=['200', '150', '100', '50', '0'],
title='Time Elapsed (sec)'),
yaxis=dict(
range=[min(0, min(df['X'])),
max(20,
max(df['X']) + max(df['X']))],
showline=False,
fixedrange=True,
zeroline=False,
nticks=max(6, round(df['Z'].iloc[-1] / 10))),
margin=lo.Margin(t=45, l=50, r=50) #,
#transition=dict(
# duration=200,
# easing="cubic-in-out")
)
return Figure(data=[trace1, trace2, trace3], layout=layout)
def misconduct(request):
entries = load_misconduct_data()
import plotly.graph_objs as go
import plotly.graph_objs.layout as go_layout
from plotly.offline import plot
# Break out consequences into their own list.
consequences = sum((entry['consequences'] for entry in entries), [])
last_consequence_year = max(cons['date_year'] for cons in consequences)
# Make a common x-axis of decades starting with the first full year of the Congress,
# which happens to be an even decade.
x = [(1790 + 10 * x)
for x in range(0, (last_consequence_year - 1790) // 10 + 1)]
xlab = [str(year) + 's' for year in x]
bar_chart_layout = go.Layout(barmode='stack',
margin=go_layout.Margin(l=25,
r=20,
b=10,
t=0,
pad=0),
legend={"orientation": "h"})
def make_chart(title, universe, bars, year_of):
stacks = []
def decade_of(entry):
return year_of(entry) - (year_of(entry) % 10)
for tag, label in bars:
y = [
sum(1 for entry in universe
if decade_of(entry) == decade and tag in entry['tags'])
for decade in x
]
stacks.append(go.Bar(x=xlab, y=y, name=label))
return {
"title":
title,
"figure":
plot(go.Figure(data=stacks, layout=bar_chart_layout),
output_type="div",
include_plotlyjs=False,
show_link=False)
}
charts = [
make_chart(
title="Types of misconduct and alleged misconduct over time",
universe=entries,
bars=misconduct_type_tags,
year_of=lambda entry: entry['consequences'][0]['date_year'],
),
make_chart(
title="Consequences of misconduct and alleged misconduct over time",
universe=consequences,
bars=misconduct_consequence_tags,
year_of=lambda entry: entry['date_year'],
),
]
return {
"entries": entries,
"tags": misconduct_tag_filters,
"charts": charts,
}
def gen_wind_speed(interval):
accel_x, accel_y, accel_z = sensor.accelerometer
t = dt.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')
X.append(accel_x)
Y.append(accel_y)
Z.append(accel_z)
Time.append(t)
trace1 = go.Scatter(
x=[Time],
y=[X],
# line=scatter.Line(
# color='#42C4F7'
#),
mode='lines',
name='X')
trace2 = go.Scatter(
x=[Time],
y=[Y],
#line= scatter.Line(
# color='#42C4F7'
#),
mode='lines',
name='Y')
trace3 = go.Scatter(
x=[Time],
y=[Z],
#line= scatter.Line(
# color='#42C4F7'
#),
mode='lines',
name='Z')
layout = go.Layout(
height=450,
xaxis=dict(range=[0, 200],
showgrid=False,
showline=False,
zeroline=False,
fixedrange=True,
tickvals=[0, 50, 100, 150, 200],
ticktext=['200', '150', '100', '50', '0'],
title='Time Elapsed (sec)'),
yaxis=dict(range=[min(0, min(X)),
max(20,
max(X) + max(X))],
showline=False,
fixedrange=True,
zeroline=False,
nticks=6),
margin=lo.Margin(t=45, l=50, r=50)
#,
# transition=dict(
# duration=500,
# easing="cubic-in-out")
)
return go.Figure(data=[trace1, trace2, trace3], layout=layout)
scl = [ [0,"rgb(5, 10, 172)"],[0.35,"rgb(40, 60, 190)"],[0.5,"rgb(70, 100, 245)"],\
[0.6,"rgb(90, 120, 245)"],[0.7,"rgb(106, 137, 247)"],[1,"rgb(220, 220, 220)"] ]
data = [ dict(
type = 'scattergeo',
locationmode = 'USA-states',
lon = df['long'],
lat = df['lat'],
text = df['text'],
mode = 'markers'
)]
map_layout = dict(
title = 'Title',
margin=plot_layout.Margin(
l=10,r=10, b=10, t=50, pad=4
),
geo = dict(
scope='world',
showframe = True,
projection = dict(type='enumerated : "equirectangular"'),
showcountries=True,
showsubunits=True,
showocean=True,
countrycolor='green',
oceancolor='#aec6cf'
)
)
fig = dict(data=data, layout=map_layout)
def show_histogram(image):
def hg_trace(name, color, hg):
line = go.Scatter(
x=list(range(0, 256)),
y=hg,
name=name,
line=dict(color=(color)),
mode="lines",
showlegend=False,
)
fill = go.Scatter(
x=list(range(0, 256)),
y=hg,
mode="lines",
name=name,
line=dict(color=(color)),
fill="tozeroy",
hoverinfo="none",
)
return line, fill
hg = image.histogram()
if image.mode == "RGBA":
rhg = hg[0:256]
ghg = hg[256:512]
bhg = hg[512:768]
ahg = hg[768:]
data = [
*hg_trace("Red", "#FF4136", rhg),
*hg_trace("Green", "#2ECC40", ghg),
*hg_trace("Blue", "#0074D9", bhg),
*hg_trace("Alpha", "gray", ahg),
]
title = "RGBA Histogram"
elif image.mode == "RGB":
# Returns a 768 member array with counts of R, G, B values
rhg = hg[0:256]
ghg = hg[256:512]
bhg = hg[512:768]
data = [
*hg_trace("Red", "#FF4136", rhg),
*hg_trace("Green", "#2ECC40", ghg),
*hg_trace("Blue", "#0074D9", bhg),
]
title = "RGB Histogram"
else:
data = [*hg_trace("Gray", "gray", hg)]
title = "Grayscale Histogram"
layout = go.Layout(
autosize=True,
title=title,
margin=go.Margin(l=50, r=30),
legend=dict(x=0, y=1.15, orientation="h"),
paper_bgcolor="#31343a",
plot_bgcolor="#272a31",
font=dict(color="darkgray"),
xaxis=dict(gridcolor="#43454a"),
yaxis=dict(gridcolor="#43454a"),
)
return go.Figure(data=data, layout=layout)
enc_format="jpeg",
)
GRAPH_PLACEHOLDER = dcc.Graph(
id="interactive-image",
figure={
"data": [],
"layout": {
"autosize":
True,
"paper_bgcolor":
"#272a31",
"plot_bgcolor":
"#272a31",
"margin":
go.Margin(l=40, b=40, t=26, r=10),
"xaxis": {
"range": (0, 1527),
"scaleanchor": "y",
"scaleratio": 1,
"color": "white",
"gridcolor": "#43454a",
"tickwidth": 1,
},
"yaxis": {
"range": (0, 1200),
"color": "white",
"gridcolor": "#43454a",
"tickwidth": 1,
},
"images": [{
def InteractiveImagePIL(image_id,
image,
enc_format="png",
dragmode="select",
verbose=False,
**kwargs):
if enc_format == "jpeg":
if image.mode == "RGBA":
image = image.convert("RGB")
encoded_image = pil_to_b64(image,
enc_format=enc_format,
verbose=verbose,
quality=80)
else:
encoded_image = pil_to_b64(image,
enc_format=enc_format,
verbose=verbose)
width, height = image.size
return dcc.Graph(
id=image_id,
figure={
"data": [],
"layout": {
"autosize":
True,
"paper_bgcolor":
"#272a31",
"plot_bgcolor":
"#272a31",
"margin":
go.Margin(l=40, b=40, t=26, r=10),
"xaxis": {
"range": (0, width),
"scaleanchor": "y",
"scaleratio": 1,
"color": "white",
"gridcolor": "#43454a",
"tickwidth": 1,
},
"yaxis": {
"range": (0, height),
"color": "white",
"gridcolor": "#43454a",
"tickwidth": 1,
},
"images": [{
"xref": "x",
"yref": "y",
"x": 0,
"y": 0,
"yanchor": "bottom",
"sizing": "stretch",
"sizex": width,
"sizey": height,
"layer": "below",
"source": HTML_IMG_SRC_PARAMETERS + encoded_image,
}],
"dragmode":
dragmode,
},
},
config={
"modeBarButtonsToRemove": [
"sendDataToCloud",
"autoScale2d",
"toggleSpikelines",
"hoverClosestCartesian",
"hoverCompareCartesian",
"zoom2d",
]
},
**_omit(["style"], kwargs),
)