def plot_terminal(data, title, xlabel, yrange):
"""
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(xlabel)
plt.ylim(*yrange)
plt.plot_size(100, 30)
plt.show()
def plot_measures(measures, offset=0):
start_timestamp = datetime.now() - timedelta(days=7)
now = datetime.now()
width, height = plt.terminal_size()
if offset:
height -= offset
if MAXIMUM_HEIGHT and MAXIMUM_HEIGHT < height:
height = MAXIMUM_HEIGHT
if MAXIMUM_WIDTH and MAXIMUM_WIDTH < width:
width = MAXIMUM_WIDTH
values_y = [m.value for m in measures]
values_x = [m.timestamp for m in measures]
plt.clear_plot()
plt.plot(values_x, values_y)
plt.nocolor()
xticks = [int(start_timestamp.strftime("%s"))]
xlabels = [start_timestamp.strftime(DATETIME_FORMAT)]
day = (start_timestamp + timedelta(days=1)).replace(hour=0,
minute=0,
second=0,
microsecond=0)
while day < now:
xticks.append(int(day.strftime("%s")))
xlabels.append(day.strftime(DATETIME_FORMAT))
day += timedelta(days=1)
plt.xlim(int(start_timestamp.strftime("%s")), int(now.strftime("%s")))
plt.xticks(xticks, xlabels)
plt.figsize(width, height)
plt.show()
def diff2plot(diff, kind=None, title='Unnamed plot'):
"""Function to plot graph to the terminal. Can be scatter or bar plot (Initial test functionality)
Works only with plotext 4.2, not above"""
# try:
# import plotext as plt
# except ModuleNotFoundError:
# # Error handling
# pass
plx.clear_plot()
diff = diff.round(2)
if kind == 'bar':
# expects a series with index being string names
mask0 = (diff.values != 0) & ~_np.isnan(diff.values)
if mask0.any():
plx.bar(diff.index.values[mask0].tolist(),
diff.values[mask0].tolist(),
orientation="h",
width=0.3)
plx.vertical_line(coordinate=0)
plx.plotsize(100, diff.shape[0] * 2 + 3)
else:
return None
else:
mask0 = ((diff.values != 0) & ~_np.isnan(diff.values)).any(axis=0)
if mask0.any():
cols = diff.columns[mask0]
x1 = plx.datetime.datetime_to_string(
diff.index.astype('timedelta64[ns]') * 1000000000 +
_J2000_ORIGIN)
for i in range(cols.shape[0]):
plx.scatter_date(x1,
diff[cols[i]].to_list(),
color=i,
marker="hd",
label=diff.columns[i])
plx.plotsize(100, 30 + 3)
else:
return None
plx.title(title)
plx.limit_size(limit_xsize=False, limit_ysize=False)
plx.show()
def main(what, calc_id: int = -1, others: int = [], webapi=False, local=False):
"""
Generic plotter for local and remote calculations.
"""
if what.startswith('POLYGON'):
plt = plot_wkt(what)
plt.show()
return
if what == 'examples':
help_msg = ['Examples of possible plots:']
for k, v in globals().items():
if k.startswith('make_figure_'):
help_msg.append(v.__doc__)
raise SystemExit(''.join(help_msg))
if '?' not in what:
raise SystemExit('Missing ? in %r' % what)
prefix, rest = what.split('?', 1)
if prefix in 'hcurves hmaps' and 'imt=' not in rest:
raise SystemExit('Missing imt= in %r' % what)
elif prefix == 'uhs' and 'imt=' in rest:
raise SystemExit('Invalid IMT in %r' % what)
elif prefix in 'hcurves uhs disagg' and 'site_id=' not in rest:
what += '&site_id=0'
if prefix == 'disagg' and 'poe_id=' not in rest:
what += '&poe_id=0'
if local:
xs = [WebExtractor(calc_id, 'http://localhost:8800', '')]
for other_id in others:
xs.append(WebExtractor(other_id), 'http://localhost:8800', '')
elif webapi:
xs = [WebExtractor(calc_id)]
for other_id in others:
xs.append(WebExtractor(other_id))
else:
xs = [Extractor(calc_id)]
for other_id in others:
xs.append(Extractor(other_id))
make_figure = globals()['make_figure_' + prefix]
plt = make_figure(xs, what)
plt.show()
def main(filea, fileb):
if filea is None:
# take the second most recent
profiling_files = parse_and_sort_profiling_files()
filea = profiling_files[-2]
if fileb is None:
# take the most recent
profiling_files = parse_and_sort_profiling_files()
fileb = profiling_files[-1]
profile_a = pd.read_pickle(filea)
profile_b = pd.read_pickle(fileb)
merged = pd.merge(
profile_a,
profile_b,
how='left',
on=['document_length','document_depth', 'working_depth', 'item_length']
)
plt.clp()
bins = 30
plt.hist(merged['tottime_x'], bins, label="profile a")
plt.hist(merged['tottime_y'], bins, label="profile b")
plt.title("tottime distribution")
plt.xlabel("time bins")
plt.ylabel("frequency")
plt.canvas_color("none")
plt.axes_color("none")
plt.ticks_color("cloud")
plt.figsize(50, 15)
plt.show()
merged['diff'] = merged['tottime_x'] - merged['tottime_y']
print("")
print(f"## avg improvement: {merged['diff'].mean()} seconds ##")
print("")
#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)
# Adds padding to right side
plt.xlim([0, 625])
plt.ticks(0, 10)
# Render graph every 1m (API only updates at 1m intervals)
plt.show()
sleep(60)
def metrics(self):
# available metrics
metrics = ('node_cpu_usage', 'node_memory_usage', 'node_disk_usage',
'pod_memory_usage', 'pod_cpu_usage')
# column in prom2df dataframe for given metric group
metric_group_column = {
'node': 'node',
'pod': 'pod_name',
}
metric_name = (self.args.get('<metric_name>') or '').replace('-', '_')
since = self.args.get('--since') or None
start = self.args.get('--start') or None
end = self.args.get('--end') or None
step = self.args.get('--step') or None
should_plot = self.args.get('--plot')
# check if we have a valid metric
if metric_name in metrics:
# get default range, if any
if since:
if any(since.endswith(v) for v in 'hms'):
# a relative time spec
unit = dict(h='hours', m='minutes',
s='seconds').get(since[-1])
delta = int(since[0:-1])
start = datetime.utcnow() - timedelta(**{unit: delta})
else:
# absolute time
start = pd.to_datetime(since, utc=True)
if start:
start = pd.to_datetime(start, utc=True)
if end:
end = pd.to_datetime(end, utc=True)
if start and not end:
end = datetime.utcnow()
if end and not start:
start = (end - timedelta(minutes=10)).isoformat()
if (start or end) and not step:
step = '5m'
# query
om = self.om
auth = self._restapi_auth()
data = self._get_metric(metric_name,
auth,
start=start,
end=end,
step=step)
try:
df = prom2df(data['objects'], metric_name)
except:
print("No data could be found. Check the time range.")
return
if should_plot:
import plotext as plx
# as returned by plx.get_colors
colors = 'red', 'green', 'yellow', 'organge', 'blue', 'violet', 'cyan'
metric_group = metric_group_column[metric_name.split('_',
1)[0]]
for i, (g, gdf) in enumerate(df.groupby(metric_group)):
x = range(0, len(gdf))
y = gdf['value'].values
plx.plot(x, y, line_color=colors[i])
plx.show()
else:
print(tabulate(df, headers='keys'))
else:
print("Available metrics:", metrics)
'''
small auxiliary script that uses the lammps log parser to quickly plot data
to terminal
usage:
plot_thermo.py <thermo_key>
'''
import lammps_log_parser as lmp
import plotext as pt
import sys
yvar = sys.argv[1]
data = lmp.parse_log_to_pandas_df('*log')
pt.plot(data['Step'], data[yvar])
pt.xlabel('simulation steps')
pt.ylabel(yvar)
pt.nocolor()
pt.figsize(160, 40)
pt.show()
def animate(self):
"""
Animates the rocket's movement according to the data in the logs.
"""
# Ideally we'd use something other than matplotlib. It really wasn't designed for
# this sort of application.
import matplotlib.pyplot as plt
import matplotlib.patches as patches
from matplotlib.animation import FuncAnimation
import numpy as np
import quaternion as q
cm_positions = self.logs['cm_position'].get_data()
cm_orientations = self.logs['cm_orientation'].get_data()
frame_rel_positions = self.logs['frame_position'].get_data()
frame_rel_orientations = self.logs['frame_orientation'].get_data()
mount_rel_positions = self.logs['mount_position'].get_data()
mount_rel_orientations = self.logs['mount_orientation'].get_data()
thrust = self.logs['thrust'].get_data()
fig, ax = plt.subplots(2, 2)
ax[0, 0].set_xlim(-21, 21)
ax[0, 0].set_ylim(-2, 20)
ax[0, 1].set_xlim(-21, 21)
ax[0, 1].set_ylim(-2, 20)
ax[1, 0].set_xlim(-21, 21)
ax[1, 0].set_ylim(-21, 21)
# Rockets definition
rocket_xz = patches.Rectangle((0, 0.5), 0.2, 1)
rocket_yz = patches.Rectangle((0, 0.5), 0.2, 1)
rocket_xy = patches.Rectangle((0, 0), 0.2, 0.2)
# Thrust definition
thrust_xz = patches.Rectangle((0, 0), 0.1, -1, facecolor='r')
thrust_yz = patches.Rectangle((0, 0), 0.1, -1, facecolor='r')
# Floor
floor_xz = patches.Rectangle((-50, 0), 100, -2, facecolor='g')
floor_yz = patches.Rectangle((-50, 0), 100, -2, facecolor='g')
def init():
ax[0, 0].add_patch(rocket_xz)
ax[0, 0].add_patch(thrust_xz)
ax[0, 0].add_patch(floor_xz)
ax[0, 1].add_patch(rocket_yz)
ax[0, 1].add_patch(thrust_yz)
ax[0, 1].add_patch(floor_yz)
ax[1, 0].add_patch(rocket_xy)
return rocket_xz, thrust_xz, floor_xz, rocket_yz, thrust_yz, floor_yz, rocket_xy
def update(frame_count):
cm_position = cm_positions[frame_count]
cm_orientation = cm_orientations[frame_count]
frame_position = cm_position + q.rotate_vectors(
cm_orientation, frame_rel_positions[frame_count] +
np.array([-0.1, -0.1, -0.5]))
frame_direction = q.rotate_vectors(
frame_rel_orientations[frame_count] * cm_orientation,
np.array([0, 0, 1]))
mount_position = cm_position + q.rotate_vectors(
cm_orientation, mount_rel_positions[frame_count])
mount_direction = q.rotate_vectors(
mount_rel_orientations[frame_count] * cm_orientation,
np.array([0, 0, 1]))
frame_angle_xz = np.rad2deg(
math.atan2(frame_direction[0], frame_direction[2]))
frame_angle_yz = np.rad2deg(
math.atan2(frame_direction[1], frame_direction[2]))
# Rockets update
rocket_xz.set_xy(frame_position[[0, 2]])
rocket_xz.angle = frame_angle_xz
rocket_yz.set_xy(frame_position[[1, 2]])
rocket_yz.angle = frame_angle_yz
rocket_xy.set_xy(frame_position[[0, 1]])
thrust_angle_xz = np.rad2deg(
math.atan2(mount_direction[0], mount_direction[2]))
thrust_angle_yz = np.rad2deg(
math.atan2(mount_direction[1], mount_direction[2]))
thrust_xz.set_xy(mount_position[[0, 2]])
thrust_xz.angle = thrust_angle_xz
thrust_yz.set_xy(mount_position[[1, 2]])
thrust_yz.angle = thrust_angle_yz
return rocket_xz, thrust_xz, floor_xz, rocket_yz, thrust_yz, floor_yz, rocket_xy
anim = FuncAnimation(fig,
update,
init_func=init,
frames=len(cm_positions),
interval=20,
blit=True)
plt.show()
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()
