def plot_data(fnames, column, savefig=None):
if niutils.check_iter(fnames):
df = merge_tables(fnames)
tab_for_format = fnames[0]
ntab = len(fnames)
else:
df = read_table(fnames)
tab_for_format = fname
ntab = 1
if column is None:
raise ValueError("Column can not be None")
df = add_datetime_col(df)
fig, ax = plt.subplots(1, 1, figsize=(12*ntab, 6))
ax = niutils.plotparams(ax)
if not niutils.check_iter(column):
column = [column]
mask = [ np.where(df[column[i]] != -9999.9)[0]
for i in range(len(column)) ]
colors = niutils.get_colors()['br_colors']
colors = [colors[0], colors[2]]
ax.plot(df['datetime'][mask[0]], df[column[0]][mask[0]],
color=colors[0], label=column[0])
ax.set_xlabel("Date", fontsize=20)
ax.set_ylabel(format_ace_column(column[0], table=tab_for_format),
fontsize=20)
if len(column) > 1:
ax, ax1 = niutils.DoubleY(ax, colors=(colors[0], colors[1]))
ax1.plot(df['datetime'][mask[1]], df[column[1]][mask[1]],
color=colors[1], label=column[1])
ax1.set_ylabel(format_ace_column(column[1], table=tab_for_format),
fontsize=20)
if max(df['day']) > 180:
ax.xaxis.set_minor_locator(MonthLocator())
else:
ax.xaxis.set_major_locator(MonthLocator())
ax.xaxis.set_minor_locator(MonthLocator(bymonthday=15))
myfmt = DateFormatter('%Y-%m')
ax.xaxis.set_major_formatter(myfmt)
if savefig is None:
plt.show()
else:
fig.savefig(savefig)
def plot_data_split(fnames, column, savefig=None):
if niutils.check_iter(fnames):
df_list = [read_table(f) for f in fnames]
else:
raise ValueError("Must input multiple filenames")
if column is None:
raise ValueError("Column can not be None")
df_list = [add_datetime_col(df) for df in df_list]
fig, ax = plt.subplots(len(df_list), 1, figsize=(12, 5.2*len(df_list)))
plt.subplots_adjust(top=.98, bottom=.07)
for a in ax: a = niutils.plotparams(a)
if not niutils.check_iter(column):
column = [column]
colors = niutils.get_colors()['br_colors']
colors = [colors[0], colors[2]]
for i in range(len(df_list)):
df = df_list[i]
mask = [ np.where(df[column[i]] != -9999.9)[0]
for i in range(len(column)) ]
ax[i].plot(df['datetime'][mask[0]], df[column[0]][mask[0]],
color=colors[0], label=column[0])
ax[i].set_xlabel("Date", fontsize=20)
ax[i].set_ylabel(format_ace_column(column[0], table=fnames[0]),
fontsize=20)
if len(column) > 1:
ax[i], ax1 = niutils.DoubleY(ax[i], colors=(colors[0], colors[1]))
ax1.plot(df['datetime'][mask[1]], df[column[1]][mask[1]],
color=colors[1], label=column[1])
ax1.set_ylabel(format_ace_column(column[1],
table=fnames[0]), fontsize=20)
if max(df['day']) > 180:
ax[i].xaxis.set_minor_locator(MonthLocator())
else:
ax[i].xaxis.set_major_locator(MonthLocator())
ax[i].xaxis.set_minor_locator(MonthLocator(bymonthday=15))
myfmt = DateFormatter('%Y-%m')
ax[i].xaxis.set_major_formatter(myfmt)
if savefig is None:
plt.show()
else:
fig.savefig(savefig)
def main(mail_file, jobs_to_check):
if not niutils.check_iter(jobs_to_check):
jobs_to_check = [jobs_to_check]
#Get all cron log output
job_groups = np.array(read_log(mail_file))
job_names = np.array([identify_job(g) for g in job_groups])
idx_to_check = []
#For each job we're interested in
for job in jobs_to_check:
#Find which cron lines match
idx = [i for i in range(len(job_names)) if job in job_names[i]]
if len(idx) == 0:
log.warning("No cron jobs found matching {0}".format(job))
#only want to do error search on most recent
idx_to_check.append(idx[-1])
bad_lines = [check_errors(job_groups[i]) for i in idx_to_check]
for i, j in zip(idx_to_check, jobs_to_check):
log.info("Errors/Warnings for {}".format(j))
bad_lines = check_errors(job_groups[i])
for l in bad_lines:
print(l.strip('\n'))
def get_exposure(sources, user, passwd):
df = print_nicer_segment(username=user, password=passwd)
if not niutils.check_iter(sources):
sources = [sources]
else:
pass
exp_list = []
n_obsIDs = []
for s in sources:
df_selection = df[df['Target Name'] == s]
n_obsIDs.append(len(df_selection))
exp_list.append(np.sum(df_selection['Good Expo[s]']))
return exp_list, n_obsIDs
def check_split(evt, fnames):
if not os.path.isfile(evt):
raise FileNotFoundError("Event file not found")
if not niutils.check_iter(fnames):
raise TypeError("fnames must be iterable")
for f in fnames:
if not os.path.isfile(f):
raise FileNotFoundError("{0} not found".format(f))
full_tab = Table.read(evt, hdu=1)
total_length = len(full_tab)
summed = 0
for split_evt in fnames:
tab = Table.read(split_evt, hdu=1)
summed += len(tab)
return summed == total_length
def run_datadownload(sourcename,
heasarc_user,
heasarc_pwd,
outdir,
decryptkey,
clobber=False,
obsIDs=None,
silent_curl=False):
if outdir == "./":
if not os.getcwd().endswith(sourcename):
if not outdircheck(sourcename):
return 0
else:
if not (outdir.endswith(sourcename or sourcename + "/")):
if not outdircheck(soucename):
return 0
cmd = [
'custom_data_download.py', sourcename, heasarc_user, heasarc_pwd,
'--outdir', outdir, '--decryptkey', decryptkey, '--unzip'
]
if clobber:
cmd.append('--clobber')
if obsIDs is not None:
if not niutils.check_iter(obsIDs):
obsIDs = [obsIDs]
cmd.append('--obsIDs')
cmd.extend(obsIDs)
if silent_curl:
cmd.append("--silent_curl")
subprocess.call(cmd)