def print_plot(items,
x,
y=None,
sort=None,
fillx=False,
title=None,
grid=False,
marker=None,
color=None,
background_color=None,
axes_color=None):
df = items_to_dataframe(items, sort=sort)
x_list = df[x].tolist()
y_list = df[y].tolist() if y else None
_x = df['timestamp'].tolist() if x in DATE_FIELDS else df[x]
if y is None:
plt.scatter(_x, marker=marker, color=color, fillx=fillx)
else:
plt.plot(_x, y_list, marker=marker, color=color, fillx=fillx)
plt.xticks(_x, x_list)
if title is not None:
plt.title(title)
if grid:
plt.grid(True, True)
if background_color is not None:
plt.canvas_color(background_color)
plt.axes_color(background_color)
if axes_color is not None:
plt.ticks_color(axes_color)
plt.show()
def print_diff(diff, show_plot=False):
mean_prefix = '+' if diff.r1['mean'] < diff.r2['mean'] else '-'
median_prefix = '+' if diff.r1['percentile']['50'] < diff.r2['percentile'][
'50'] else '-'
print(
f'| Version | Mean ± Stdev | Min | Median | Q3 | Max |'
)
print(
f"| V1 | {diff.r1['mean']:10.3f} ± {diff.r1['stdev']:8.3f} | {diff.r1['min']:10.3f} | {diff.r1['percentile']['50']:10.3f} | {diff.r1['percentile']['75']:10.3f} | {diff.r1['max']:10.3f} |"
)
print(
f"| V2 | {diff.r2['mean']:10.3f} ± {diff.r2['stdev']:8.3f} | {diff.r2['min']:10.3f} | {diff.r2['percentile']['50']:10.3f} | {diff.r2['percentile']['75']:10.3f} | {diff.r2['max']:10.3f} |"
)
print(
f'├---------┴-------------------------┴------------┴------------┴------------┴------------┘'
)
print(
f"| {mean_prefix}{diff.mean_diff:7.2f}% {median_prefix}{diff.median_diff:7.2f}% "
)
print(f'{diff.ptext}')
print(f'{diff.significance}')
print('')
if show_plot:
plt.subplots(2, 1)
plt.subplot(1, 1)
plt.scatter(diff.r1.get('samples', diff.r1['mean']), label='v1')
plt.subplot(2, 1)
plt.scatter(diff.r2.get('samples', diff.r2['mean']), label='v2')
plt.show()
def plot_score_trace(self, t, R_scores):
r = R_scores.shape[0]
plt.clear_plot()
plt.set_output_file(self._logfile)
for i in range(self.g.p["mcmc"]["n_indep"]):
if t < r:
plt.scatter(R_scores[:t, i], label=str(i), line_color="red")
else:
plt.scatter(R_scores[np.r_[(t % r):r, 0:(t % r)], i],
label=str(i),
line_color="red")
plt.figsize(80, 20)
plt.ticks(4, 4)
if t < 1000:
xticks = [int(w * t) for w in np.arange(0, 1 + 1 / 3, 1 / 3)]
xlabels = [str(round(x / 1000, 1)) + "k" for x in xticks]
else:
xticks = [0, 333, 666, 999]
xlabels = [str(round((x + t) / 1000, 1)) + "k" for x in xticks]
plt.xticks(xticks, xlabels)
plt.canvas_color("none")
plt.axes_color("none")
plt.ticks_color("none")
plt.show()
print(file=self._logfile)
self._logfile.flush()
def plot_terminal(data, title, xtitle):
"""
Plot data to the terminal using plotext
"""
import plotext as plt
x = data.index.tolist()
y = data[title].tolist()
plt.scatter(x, y)
plt.title(title)
plt.xlabel(xtitle)
plt.plot_size(100, 30)
plt.show()
# Current is the last index of all trades
current = y[-1]
# Show red or green chart if price has declined since opening
if current >= opening:
color = "green"
else:
color = "tomato"
#For formating
plt.clear_plot()
plt.clear_terminal()
plt.scatter(y,
point_color=color,
fill=True,
label=ticker + "- Open:" + str(opening) + " Current:" +
str(current) + "1d High:" +
str(current_high)) # Labled as Open: , Current: , High:
#Most recent hours of trades will be highlighted blue
plt.scatter(list(range(540, 600)),
y[-60:],
fill=True,
label="Current Hour",
point_color="blue")
#More formating
plt.canvas_color('none')
plt.axes_color("none")
plt.grid(False, False)
plt.axes(False, False)
yield count_lines(govc(*args))
if __name__ == '__main__':
counts = 200 # number of data points
interval = 0 # seconds per count
xs = range(1, counts + 1)
ys = []
plt.title("GOVC Session Count")
plt.clc()
plt.xlim(xs[0], xs[-1])
plt.xticks(ticks=[1, 20, 40, 60, 80, 100, 120, 140, 160, 180, 200])
for y in generate_counts("session.ls"):
ys.append(y)
while len(ys) > counts:
ys.pop(0)
y_min, y_max = min(ys), max(ys) + 1
plt.yticks(ticks=range(y_min, y_max))
plt.ylim(y_min, y_max)
#plt.ylim(150,165)
plt.cld()
plt.clt()
plt.scatter(xs, ys, marker="dot")
plt.sleep(interval)
plt.show()
import plotext as plt
# format: <<ID:default_value>>
scatter_size = <<SCATTER_SIZE:1>>
labels = <<LABELS:None>>
h = <<HEIGHT:None>>
w = <<WIDTH:None>>
vv = <<DATA:[]>>
if w is not None:
plt.figure(figsize=(w*cm, h*cm))
# scatter
for ii in range(len(vv)):
v = vv[ii]
x = [v[2*i] for i in range(len(v)//2)]
y = [v[2*i+1] for i in range(len(v)//2) if 2*i + 1 < len(v)]
if labels and ii < len(labels):
label = labels[ii]
plt.scatter(x, y, label=label)
else:
plt.scatter(x, y)
plt.canvas_color('black')
plt.axes_color('black')
plt.ticks_color('white')
if w is not None:
plt.plot_size(w, h)
plt.show()
# count number of filtered sequences
filter_data_size = len(filter_list)
###################################
print('-' * 45)
print('[Number of total sequences]:\t ' + str(data_size))
print('[Minimum sequence length]:\t ' + str(min_length_def) + ' bp')
print('[Maximum sequence length]:\t ' + str(max_length_def) + ' bp')
print('-' * 45)
print('[Number of filtered sequences]:\t ' + str(filter_data_size))
print('[Minimum sequence length (user)]: ' + str(min_length) + ' bp')
print('[Maximum sequence length (user)]: ' + str(input_length_max) + ' bp')
print('-' * 45)
###################################
# plot in terminal
import plotext as plt
plt.scatter(length_list)
plt.plotsize(40, 20)
plt.show()
###################################
# input file close
input.close()
# output file close
if args.output is not None:
out.close()
###################################
# End of script
def show_statistics(rule_file=None, rule_set=None, indx=None):
interface = None
if rule_set == "-e":
interface = "external"
elif rule_set == "-i":
interface = "internal"
logs = utils.load_logs('logs.json')
print("")
print("-" * 13, "OVERALL FIREWALL STATISTICS", "-" * 13)
print("TOTAL PACkETS RECEIVED BY THE FIREWALL: ", logs["total_packets"])
print("TOTAL PACkETS DROPPED BY THE FIREWALL: ", logs["total_dropped"])
if rule_file != None:
if interface != None:
print("")
print("-" * 12, interface.upper(), "INTERFACE STATISTICS",
"-" * 12)
print("TOTAL PACKETS RECEIVED ON", interface.upper(),
"INTERFACE: ", logs[rule_file][interface]["total_packets"])
print("TOTAL PACKETS DROPPED ON", interface.upper(), "INTERFACE: ",
logs[rule_file][interface]["total_dropped"])
if indx != None:
if indx in logs[rule_file][interface]:
print("\nTOTAL PACKETS DROPPED DUE TO RULE", indx, "ON",
interface.upper(), "INTERFACE :",
logs[rule_file][interface][indx])
else:
print("Invalid rule index!")
else:
print("")
print("-" * 12, "EXTERNAL INTERFACE STATISTICS", "-" * 12)
print("TOTAL PACKETS RECEIVED ON EXTERNAL INTERFACE: ",
logs[rule_file]["external"]["total_packets"])
print("TOTAL PACKETS DROPPED ON EXTERNAL INTERFACE: ",
logs[rule_file]["external"]["total_dropped"])
print("")
print("-" * 12, "INTERNAL INTERFACE STATISTICS", "-" * 12)
print("TOTAL PACKETS RECEIVED ON INTERNAL INTERFACE: ",
logs[rule_file]["internal"]["total_packets"])
print("TOTAL PACKETS DROPPED ON INTERNAL INTERFACE: ",
logs[rule_file]["internal"]["total_dropped"])
else:
print("")
print("-" * 16, "ICMP FLOOD STATISTICS", "-" * 16)
print("FLOODS ENCOUNTERED SO FAR: ", logs["icmp_floods"])
print("PACKETS DROPPED DURING ICMP BLOCK:", logs["icmp_dropped"])
print("")
print("-" * 22, "PPS INFO", "-" * 22)
print("MAXIMUM PPS SO FAR: ", logs["max_pps"])
print("")
title = "-" * 18 + "NETWORK TRAFFIC" + "-" * 18
net_traffic = logs["traffic"]
max_sec = max(np.array(list(net_traffic.keys())).astype(int))
packets_num = np.zeros(max_sec + 1)
for i in net_traffic:
packets_num[int(i)] = net_traffic[i]
packets_num = packets_num.astype(int)
plt.scatter(np.arange(max_sec + 1), packets_num, fillx=True)
plt.figsize(80, 20)
plt.title(title)
plt.xlabel("Time")
plt.ylabel("Packets")
plt.show()