def print_charts(dataset, title, weekday=False):
""" Prints nice charts based on a dict {(key, value), ...} """
chart = []
keys = sorted(dataset.keys())
mean = numpy.mean(list(dataset.values()))
median = numpy.median(list(dataset.values()))
for key in keys:
if (dataset[key] >= median * 1.33):
displayed_key = "%s (\033[92m+\033[0m)" % (int_to_weekday(key) if weekday else key)
elif (dataset[key] <= median * 0.66):
displayed_key = "%s (\033[91m-\033[0m)" % (int_to_weekday(key) if weekday else key)
else:
displayed_key = (int_to_weekday(key) if weekday else key)
chart.append((displayed_key, dataset[key]))
thresholds = {
int(mean): Gre, int(mean * 2): Yel, int(mean * 3): Red,
}
data = hcolor(chart, thresholds)
graph = Pyasciigraph(
separator_length=4,
multivalue=False,
human_readable='si',
)
for line in graph.graph(title, data):
print(line)
print("")
def print_graph(dataset, title):
graph = Pyasciigraph(
separator_length=4,
multivalue=False,
human_readable='si',
)
chart = []
keys = sorted(dataset.keys())
mean = np.mean(list(dataset.values()))
# median = np.median(list(dataset.values()))
for key in keys:
chart.append((key, dataset[key]))
if (not args.no_color):
thresholds = {
int(mean): Gre,
int(mean * 2): Yel,
int(mean * 3): Red,
}
data = hcolor(chart, thresholds)
else:
data = chart
for line in graph.graph(title, data):
print(line)
def show_index(self):
graphArray = []
for coin in IndexedCoinModel.select():
graphArray.append((coin.Ticker, coin.DesiredPercentage))
pyGraph = Pyasciigraph(line_length=50,
min_graph_length=50,
separator_length=4,
multivalue=False,
human_readable='si',
graphsymbol='*',
float_format='{0:,.2f}')
thresholds = {
15: Gre,
30: Blu,
50: Yel,
60: Red,
}
data = hcolor(graphArray, thresholds)
sys.stdout.write("\n")
for line in pyGraph.graph('Index Distribution', data=data):
sys.stdout.write(line + "\n")
sys.stdout.write("\n")
def print_charts(dataset, title, args, weekday=False):
chart = []
keys = sorted(dataset.keys())
mean = numpy.mean(list(dataset.values()))
median = numpy.median(list(dataset.values()))
for key in keys:
if dataset[key] >= median * 1.33:
displayed_key = "%s (\033[92m+\033[0m)" % (int_to_weekday(key) if weekday else key)
elif dataset[key] <= median * 0.66:
displayed_key = "%s (\033[91m-\033[0m)" % (int_to_weekday(key) if weekday else key)
else:
displayed_key = (int_to_weekday(key) if weekday else key)
chart.append((displayed_key, dataset[key]))
thresholds = {
int(mean): Gre, int(mean * 2): Yel, int(mean * 3): Red,
}
data = hcolor(chart, thresholds)
graph = Pyasciigraph(
separator_length=4,
multivalue=False,
human_readable='si',
)
for line in graph.graph(title, data):
if args.no_color:
ansi_escape = re.compile(r'\x1B\[[0-?]*[ -/]*[@-~]')
line = ansi_escape.sub('', line)
print(line)
print("")
def graph_thresholds(test_data):
# H color test
# Multicolor on one line
print('\nMultiColor example:')
# Color lines according to Thresholds
thresholds = {
51: Gre,
100: Blu,
350: Yel,
500: Red,
}
data = hcolor(test_data, thresholds)
# graph with colors, power of 1000, different graph symbol,
# float formatting and a few tweaks
graph = Pyasciigraph(
line_length=120,
min_graph_length=50,
separator_length=4,
multivalue=True,
human_readable='si',
graphsymbol='*', # comment out if you want to use solid bars
float_format='{0:,.2f}',
force_max_value=2000,
)
for line in graph.graph(label='With Thresholds', data=data):
print(line)
return graph, data
def plot_bars(label, data, sym=None, threshs=None):
# float formatting and a few tweaks
graph = Pyasciigraph(line_length=100,
min_graph_length=50,
separator_length=10,
multivalue=False,
human_readable='si',
graphsymbol=sym,
float_format='{0:,.2f}')
if threshs:
data = hcolor(data, threshs)
for line in graph.graph(label=label, data=data):
print(line)
def print_charts(dataset, title, weekday=False):
""" Prints nice charts based on a dict {(key, value), ...} """
chart = []
keys = sorted(dataset.keys())
mean = numpy.mean(list(dataset.values()))
median = numpy.median(list(dataset.values()))
if args.json is False:
export_string(title)
for key in keys:
if (dataset[key] >= median * 1.33):
displayed_key = "%s (\033[92m+\033[0m)" % (int_to_weekday(key)
if weekday else key)
elif (dataset[key] <= median * 0.66):
displayed_key = "%s (\033[91m-\033[0m)" % (int_to_weekday(key)
if weekday else key)
else:
displayed_key = (int_to_weekday(key) if weekday else key)
if args.json is False:
export_string("%s - %s" %
(dataset[key],
(int_to_weekday(key) if weekday else key)))
chart.append((displayed_key, dataset[key]))
thresholds = {
int(mean): Gre,
int(mean * 2): Yel,
int(mean * 3): Red,
}
data = hcolor(chart, thresholds)
graph = Pyasciigraph(
separator_length=4,
multivalue=False,
human_readable='si',
)
if args.json is False:
for line in graph.graph(title, data):
if not color_supported:
ansi_escape = re.compile(r'\x1B\[[0-?]*[ -/]*[@-~]')
line = ansi_escape.sub('', line)
print(line)
cprint("")
def xplot(NAMES, DATA, LABEL=None):
thresholds = {
.9: BIWhi,
.6: BIBlu,
.1: Blu,
}
graph = Pyasciigraph(
line_length=50,
min_graph_length=50,
separator_length=5,
multivalue=False,
#graphsymbol='*'
)
for line in graph.graph(label=LABEL,
data=hcolor([(NAMES[i], DATA[i])
for i in np.arange(len(NAMES))],
thresholds)):
print(line)
def plotfi(MODELimp):
sys.stdout.write(BOLD)
thresholds = {
9: BIWhi,
8: BIBlu,
6: Blu,
4: Bla,
2: BIBla,
}
graph = Pyasciigraph(
line_length=70,
min_graph_length=50,
separator_length=10,
multivalue=False,
#graphsymbol='*'
)
for line in graph.graph(
label='Feature Importance (GINI)',
data=hcolor([(MODELimp.feature[i], MODELimp.MeanDecreaseGini[i])
for i in MODELimp.head(10).index], thresholds)):
print(line)
sys.stdout.write(RESET)
return
graph = Pyasciigraph(line_length=55,
min_graph_length=50,
separator_length=4,
multivalue=False,
human_readable='si',
graphsymbol='*',
float_format='{0:,.2f}',
force_max_value=90)
pattern = [Gre, Yel, Red]
thresholds = {
51: Gre,
60: Blu,
65: Yel,
70: Red,
}
if __name__ == "__main__":
while True:
timeNow = time.time()
if timeNow - timeStart > 1:
temps = getTemps()
data = [('core1', temps[0]), ('core2', temps[1]),
('core3', temps[2]), ('core4', temps[3])]
data = hcolor(data, thresholds)
#data = vcolor(data, pattern)
timeStart = time.time()
subprocess.call("clear", shell=True)
for line in graph.graph('Temps', data):
print(line)
def stats(self):
""" Print some useful stats about the database. """
if self.args.get('list'):
print_notify(
str(len(self.db.list_collection_names())) +
' collections found in database:\n')
collstats_list = []
for name in self.db.list_collection_names():
collstats_list.append(self.db.command('collstats', name))
collstats_list[-1]['name'] = name
collstats_list = sorted(collstats_list,
key=lambda k: k['count'],
reverse=True)
print("\t{:^20}\t{:^20}".format('Name', 'Number of structures'))
for collection in collstats_list:
if not collection['name'].startswith('__'):
print("\t{:<20}\t{:>20d}".format(collection['name'],
collection['count']))
print('\n')
elif self.args.get('delete'):
target = self.args.get('db')
if isinstance(target, list) and len(target) == 1:
target = target[0]
else:
raise SystemExit(
'I will only delete one collection at a time...')
if target is None:
raise SystemExit('Please specify a collection to delete.')
if target not in self.db.list_collection_names():
raise SystemExit(
'No collection named {} was found'.format(target))
from getpass import getuser
user = getuser()
if user not in target:
raise SystemExit(
'I cannot delete a collection that\'s name does not start with '
'your username, {}'.format(user))
stats = self.db.command('collstats', target)
if self.args.get('no_quickstart'):
answer = 'y'
else:
answer = input(
'Are you sure you want to delete collection {} containing {} '
'structures? [y/n]\n'.format(target, stats['count']))
if answer.lower() == 'y':
if target == 'repo':
raise SystemExit(
'I\'m sorry Dave, I\'m afraid I can\'t do that...')
print('Deleting collection {}...'.format(target))
self.db[target].drop()
print('and its changelog...')
self.db['__changelog_{}'.format(target)].drop()
else:
raise SystemExit('Nevermind then!')
else:
comp_list = dict()
stats_dict = dict()
stats_dict['count'] = 0
stats_dict['avgObjSize'] = 0
stats_dict['storageSize'] = 0
stats_dict['totalIndexSize'] = 0
for collection in self.collections:
db_stats_dict = self.db.command('collstats', collection)
stats_dict['count'] += db_stats_dict['count']
stats_dict['avgObjSize'] += db_stats_dict['avgObjSize']
stats_dict['storageSize'] += db_stats_dict['storageSize']
stats_dict['totalIndexSize'] += db_stats_dict['totalIndexSize']
print((
"The collection(s) queried in {} contain {} structures at {:.1f} kB each "
"totalling {:.1f} MB with a further {:.1f} MB of indexes."
).format(self.db.name, stats_dict['count'],
stats_dict['avgObjSize'] / (1024),
stats_dict['storageSize'] / (1024**2),
stats_dict['totalIndexSize'] / (1024**2)))
for collname in self.collections:
cursor = self.collections[collname].find()
for doc in cursor:
temp = ''
for ind, elem in enumerate(sorted(doc['stoichiometry'])):
temp += str(elem[0])
if ind != len(doc['stoichiometry']) - 1:
temp += '+'
if temp not in comp_list:
comp_list[temp] = 0
comp_list[temp] += 1
keys = list(comp_list.keys())
vals = list(comp_list.values())
comp_list = list(zip(keys, vals))
comp_list.sort(key=lambda t: t[1], reverse=True)
small_count = 0
first_ind = 1000
cutoff = 100
for ind, comp in enumerate(comp_list):
if comp[1] < cutoff:
if ind < first_ind:
first_ind = ind
small_count += comp[1]
comp_list = comp_list[:first_ind]
comp_list.append(['others < ' + str(cutoff), small_count])
comp_list.sort(key=lambda t: t[1], reverse=True)
try:
from ascii_graph import Pyasciigraph
from ascii_graph.colors import Gre, Blu, Red
from ascii_graph.colordata import hcolor
except ImportError:
print(
"ascii_graph dependency not found, not creating histogram."
)
else:
graph = Pyasciigraph(line_length=80, multivalue=False)
thresholds = {
int(stats_dict['count'] / 40): Gre,
int(stats_dict['count'] / 10): Blu,
int(stats_dict['count'] / 4): Red
}
data = hcolor(comp_list, thresholds)
for line in graph.graph(label=None, data=data):
print(line)
print('\n')
for comp in comp_list:
print(comp)
# Multicolor with all the values displayed
graph = Pyasciigraph(separator_length=4, human_readable='cs')
for line in graph.graph('test graph', test):
print(line)
# Multicolor with only the max value displayed
graph = Pyasciigraph(separator_length=4, multivalue=False, human_readable='cs')
for line in graph.graph('test graph mono value', test):
print(line)
# Coloring data according to thresholds
from ascii_graph.colordata import hcolor
test = [('testval0', 6003), ('testval1', 900), ('testval2', 4920),
('testval3', 400), ('testval4', 30), ('testval5', 200),
('testval6', 1025), ('testval7', 5023)]
thresholds = {
51: Gre,
100: Blu,
350: Yel,
500: Red,
}
data = hcolor(test, thresholds)
for line in graph.graph('hcolor test', data):
print(line)
exit(0)
# Multicolor with only the max value displayed
graph = Pyasciigraph(separator_length=4, multivalue=False)
for line in graph.graph('test graph mono value', test):
print(line)
# Coloring data according to thresholds
from ascii_graph.colordata import hcolor
test = [('testval0', 600),
('testval1', 500),
('testval2', 400),
('testval3', 400),
('testval4', 300),
('testval5', 200),
('testval6', 100),
('testval7', 50 )]
thresholds = {
51: Gre,
100: Blu,
350: Yel,
500: Red,
}
data = hcolor(test, thresholds)
for line in graph.graph('hcolor test', data):
print(line)
exit(0)
def top(podName,
namespaceName,
cmdString,
isAllNamespaces=False,
doAsciiGraph=False):
output = getTop(podName, namespaceName, cmdString, isAllNamespaces)
topOutput = output
if doAsciiGraph == True:
from ascii_graph import Pyasciigraph
from ascii_graph.colors import Gre, Yel, Red
from ascii_graph.colordata import vcolor
from ascii_graph.colordata import hcolor
graphSymbol = '*'
titleBarSymbol = '-'
graph = Pyasciigraph(titlebar=titleBarSymbol, graphsymbol=graphSymbol)
output = ""
#get data from top output
cpuUsage = []
memoryUsage = []
cpuUsagePercentForNode = []
memoryUsagePercentForNode = []
lines = topOutput.split("\n")[1:]
podName = None
for line in lines:
if (len(line) == 0):
continue
fields = line.split()
if cmdString.find("-c") > -1:
podName = fields[0]
cpuUse = (fields[1], int(fields[2].replace("m", "")))
memUse = (fields[1], int(fields[3].replace("Mi", "")))
elif cmdString.find("-n") > -1:
#nodes, must be before isAllNamespaces check
cpuUse = (fields[0], int(fields[1].replace("m", "")))
memUse = (fields[0], int(fields[3].replace("Mi", "")))
cpuUsagePercentForNode.append(
(fields[0], int(fields[2].replace("%", ""))))
memoryUsagePercentForNode.append(
(fields[0], int(fields[4].replace("%", ""))))
elif isAllNamespaces == True:
rowTitle = "%s/%s" % (fields[0], fields[1])
cpuUse = (rowTitle, int(fields[2].replace("m", "")))
memUse = (rowTitle, int(fields[3].replace("Mi", "")))
else:
cpuUse = (fields[0], int(fields[1].replace("m", "")))
memUse = (fields[0], int(fields[2].replace("Mi", "")))
cpuUsage.append(cpuUse)
memoryUsage.append(memUse)
cpuTitle = 'CPU (millicores)'
if podName != None:
cpuTitle = "%s - %s" % (cpuTitle, podName)
for line in graph.graph(cpuTitle, cpuUsage):
output = output + line + "\n"
memTitle = 'Memory (Mi bytes)'
if podName != None:
memTitle = "%s - %s" % (memTitle, podName)
output = output + "\n"
for line in graph.graph(memTitle, memoryUsage):
output = output + line + "\n"
if cmdString.find("-n") > -1:
#add percents for nodes
pattern = [Gre, Yel, Red]
# Color lines according to Thresholds
thresholds = {0: Gre, 50: Yel, 80: Red}
data = hcolor(cpuUsagePercentForNode, thresholds)
graph = Pyasciigraph(force_max_value=100,
titlebar=titleBarSymbol,
graphsymbol=graphSymbol)
data = cpuUsagePercentForNode
output = output + "\n"
cpuTitle = 'CPU (%)'
for line in graph.graph(cpuTitle, data):
output = output + line + "\n"
output = output + "\n"
memTitle = 'Memory (%)'
for line in graph.graph(memTitle, memoryUsagePercentForNode):
output = output + line + "\n"
return output
