Muhammad-Yunus

import numpy as np
import matplotlib.pyplot as plt

NUM_FEATURES = 2
NUM_ITER = 100
learning_rate = 0.1

x = np.array([[0,0],[0,1],[1,0],[1,1]], np.float32)
y = np.array([0, 0, 0, 1], np.float32)

Muhammad-Yunus

for i in range(NUM_ITER):
    y_pred = np.dot(x, W) + b
        
    #apply activation
    y_pred[y_pred > 0] = 1
    y_pred[y_pred <= 0] = 0
    
    #calculate error
    err = y - y_pred
    

Muhammad-Yunus

#test
x_test = [[0,0],[0,1],[1,0],[1,1]]

for x_test_item in x_test :
    y_test = np.dot(x_test_item, W) + b
    y_test = 1 if y_test > 0 else 0
    print(str(x_test_item[0]) + ' AND ' + str(x_test_item[1]) + ' = ' + str(y_test))

Muhammad-Yunus

# plot lineary separable class (logic AND)
plot_x = np.array([np.min(x[:, 0] - 0.2), np.max(x[:, 1]+0.2)])

plot_y = - 1 / W[1] * (W[0] * plot_x + b) 
 
print('W:' + str(W))
print('b:' + str(b))
print('plot_y: '+ str(plot_y))
 
plt.scatter(x[:, 0], x[:, 1], c=y, s=100, cmap='viridis')

Muhammad-Yunus

for i in range(NUM_ITER):
    y_pred = np.dot(x, W) + b
        
    #activation sigmoid
    y_pred = 1.0 / (1.0 + np.exp(-y_pred))
            
    err = y - y_pred

        
    delta_W = learning_rate * np.dot(np.transpose(x) , err)

Muhammad-Yunus

import pandas as pd 
import numpy as np

Month_list = ['Januari', 'Februari', 'Maret', 'April', 'Mei', 'Juni', 'Juli', 'Agustus', 'September', 'Oktober', 'November', 'Desember']

CO_TS = []
CO_TS_LIST = []
for Month in Month_list :
    print("Read ISPU-di-Provinsi-DKI-Jakarta-Bulan-" + Month + ".csv")
    CSV_CO_TS = pd.read_csv("ISPU-di-Provinsi-DKI-Jakarta-Bulan-" + Month + ".csv",

Muhammad-Yunus

import matplotlib.pyplot as plt

fig, axes = plt.subplots(nrows=len(Month_list), ncols=1)
fig.subplots_adjust(hspace=0.5)

CO_TS = CO_TS[['tanggal', 'co']]

CO_TS.index = pd.to_datetime(CO_TS.tanggal)
CO_TS.drop(["tanggal"], axis=1, inplace=True)

Muhammad-Yunus

DALIY_CO = CO_TS["CO_rolling_mean"] \
                .groupby(CO_TS.index.day) \
                .agg(['min', 'max', 'mean'])

DALIY_CO.index.name = "Day"

ax = DALIY_CO.plot(title='Daily CO Aggregate')
ax.legend(loc="lower right")
ax.set_ylabel('ug/m3')
plt.fill_between(x=DALIY_CO.index, 

Muhammad-Yunus

from scipy.integrate import odeint, ode
import numpy as np
import matplotlib.pyplot as plt

np.set_printoptions(suppress=True, precision=10)

Muhammad-Yunus

def dy(y, t, zeta, w0):
    
    x, p = y[0], y[1]
    
    dx = p
    dp = -2 * zeta * w0 * p - w0**2 * x

    return [dx, dp]