steady.js | event without performance regressions in a @ media-query | Media library

for i in range(len(Sadd)):
    m.Minimize((Sadd['Load'].iloc[i]-PV[i]+6*X2[i])*TOU[i]) 

import pandas as pd
import numpy as np
from gekko import GEKKO
m = GEKKO(remote=False) # Initialize gekko
Sadd=pd.read_csv("Sa

from gekko import GEKKO
import numpy as np
import matplotlib.pyplot as plt  

# Process model
Kp = 0.5                    # process gain
tauP = 10.0                 # process time constant

# pre-solve for steady state values
m = GEKKO()
O

from gekko import GEKKO
import numpy as np
import pandas as pd

n = 10
df1 = pd.DataFrame({'responsivness':np.random.rand(n),\
                    'affinity':np.random.rand(n),\
                    'cost':np.random.rand(n)})
print(df1.head

from gekko import GEKKO
m = GEKKO() # Initialize gekko
m.options.SOLVER=1  # APOPT is an MINLP solver

# optional solver settings with APOPT
m.solver_options = ['minlp_maximum_iterations 500', \
                    # minlp iterations with 

from gekko import GEKKO
def f(x1,x2):
    return (x1.value-3.3)**2 + (x2.value-5.7)**2
m = GEKKO() # Initialize gekko
m.options.SOLVER=1  # APOPT is an MINLP solver
x1 = m.Var(value=8,lb=1,ub=16,integer=True)
x2 = m.Var(value=8,lb=1,ub=16,

import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint
from gekko import GEKKO

# Steady State Initial Condition
u2_ss=10.0

h_ss=50.0

x0 = np.empty(1)
x0[0]= h_ss

#%% GEKKO nonlinear MPC
m = GEKKO(remote=F

from gekko import GEKKO, chemical
import json

m = GEKKO(remote=False)    

f = chemical.Flowsheet(m)
P = chemical.Properties(m)

# define compounds
c1 = P.compound('Butane')
c2 = P.compound('Propane')

# create feed streams
feed1 = f.stre

#include 
Servo myservo;
int sensorPin = A0; // select the input pin for LDR
int sensorValue = 0; // variable to store the value coming from the sensor
int pos = 1;
int barState;

void setup() {
  Serial.begin(9600); //sets serial port for