def generate_periodic_assets(N):
rp_dir = 'jupyter/data/'
graph_dir = 'jupyter/data/_graphs/'
freq = 2
amp = 2
time_start = 0
time_stop = 1
duty1 = 0.3
duty2 = 0.5
for i in range(N):
# RP Variables
D = random.randint(2, 5)
d = random.randint(2, 4)
size = 720 + (D-1)*d
t_freq = freq + round(random.uniform(0, 1.5),4)
t_amp = amp + round(random.uniform(0, 1.5), 4)
t_time_start = time_start
t_time_stop = time_stop + round(random.uniform(0, 7), 2)
t_duty1 = duty1 + round(random.uniform(-0.15, 0.55), 3)
t_duty2 = duty2 + round(random.uniform(-0.35, 0.35), 3)
time = np.linspace(t_time_start, t_time_stop, size)
signal1 = t_amp*np.sin(2*np.pi*t_freq*time)
signal2 = t_amp*sg.square(2*np.pi*t_freq*time, duty=t_duty1)
signal3 = t_amp*sg.sawtooth(2*np.pi*t_freq*time, width=t_duty2)
signal1_fileName = 'periodic_graph_' + str(i*3) + '.png'
signal2_fileName = 'periodic_graph_' + str(i*3+1) + '.png'
signal3_fileName = 'periodic_graph_' + str(i*3+2) + '.png'
generate_and_save_graph(range(0, size), signal1,
signal1_fileName, rp_dir, "periodic")
generate_and_save_graph(range(0, size), signal2,
signal2_fileName, rp_dir, "periodic")
generate_and_save_graph(range(0, size), signal3,
signal3_fileName, rp_dir, "periodic")
### Generating RP
dow1 = rp(D, d, signal1, 1, 17.5, 2.5)
dow1.draw_diagram()
create_new_file('plotpic.png', 'rp_graph_' +
str(i*3) + '.png', graph_dir)
dow2 = rp(D, d, signal2, 1, 17.5, 2.5)
dow2.draw_diagram()
create_new_file('plotpic.png', 'rp_graph_' +
str(i*3+1) + '.png', graph_dir)
dow3 = rp(D, d, signal3, 1, 17.5, 2.5)
dow3.draw_diagram()
create_new_file('plotpic.png', 'rp_graph_' +
str(i*3+2) + '.png', graph_dir)
def generate_trend_assets(N):
rp_dir = 'jupyter/data/'
graph_dir = 'jupyter/data/_graphs/'
lower_bound = 0
upper_bound = 60
batch_number = 33
batch_size = 22
rate_up = 5
exponent = 1.02
exponent_increment = round((exponent - 1)/N*2, 10)
print(exponent_increment)
for i in range(N):
t_rate_up = round(rate_up + random.uniform(-2,2), 2)
data = generate_data_with_trend(lower_bound, upper_bound, \
batch_number, batch_size, \
t_rate_up, exponent)
graph_fileName = 'trend_graph_' + str(i) + '.png'
generate_and_save_graph(
data[0], data[1], graph_fileName, graph_dir, "trend")
dow=rp(4,2,data[1] , 1 , 17.5 ,3)
dow.draw_diagram()
create_new_file('plotpic.png', 'rp_graph_' +
str(i) + '.png', rp_dir)
exponent -= exponent_increment
def generate_chaotic_assets(N):
rp_dir = 'jupyter/data/'
graph_dir = 'jupyter/data/_graphs/'
for i in range(N):
data = []
# RP Variables
D = random.randint(2, 5)
d = random.randint(2, 4)
size = 720 + (D-1)*d
for _ in range(size):
data.append(random.randint(0,random.randint(50,1500)))
graph_fileName = 'chaos_graph_' + str(i) + '.png'
generate_and_save_graph(range(0, size), data,
graph_fileName, graph_dir, "chaotic")
dow1 = rp(D, d, data, 1, 17.5, 2.5)
dow1.draw_diagram()
create_new_file('plotpic.png', 'rp_graph_' +
str(i) + '.png', rp_dir)
dowData.append(float(row[5]))
dowLabels.append(pd.to_datetime(row[0]))
if (len(dowData) >= 1100):
break
# afont = {'family':'monospace'}
fig, ax = plt.subplots() # Create a figure containing a single axes.
ax.xaxis.set_major_formatter(
mdates.DateFormatter('%Y')) # Use "2020-01-01" instead of "2020"
ax.plot(dowLabels, dowData) # Plot data on the axes.
fig.autofmt_xdate()
ax.set_title(
"Dow Jones Induastrial Average adjusted for infaltion\n in USD (2015-07-01 to 2020-01-01)"
)
ax.set_xlabel("Date")
ax.grid()
dow = rp(
4,
2,
dowData,
0,
17.5,
3,
)
dow.draw_diagram()
print(dow.r)
plt.show()
csvData=[]
plt.rcParams.update({'font.size': 16})
time = np.arange(0, 20, 0.05)
amplitude = np.round(np.sin(time), 10)
path = os.path.dirname(os.path.realpath(__file__))
with open(path + "/assets/DJI.csv") as csvfile:
csvfile.readline() # skip the first line of headers
reader = csv.reader(csvfile)
for row in reader:
csvData.append(float(row[4]))
if (len(csvData)>=720): break
dow = rp(1, 1, amplitude, 1, 17.5, 0)
dow.draw_diagram()
print(dow.r)
title = "Generated sine signal"
fig, ax = plt.subplots() # Create a figure containing a single axes.
ax.plot(list(range(len(csvData))), csvData) # Plot data on the axes.
ax.set_title(title)
ax.grid()
plt.savefig('plotgraph.png')
# round_to_tenths = [round(num, 6) for num in amplitude]
# print(round_to_tenths)