def __str__(self):
head = "Pyaerocom {}".format(type(self).__name__)
s = "\n{}\n{}".format(head, len(head) * "-")
s += ('\naltitude: {}'
'\ndata: {}'
'\ndata_err: {}'.format(list_to_shortstr(self.altitude),
list_to_shortstr(self.data),
list_to_shortstr(self.data_err)))
arrays = ''
for k, v in self.__dict__.items():
if k.startswith('_'):
continue
if isinstance(v, dict) and len(v) > 0:
s += "\n{} (dict)".format(k)
s = dict_to_str(v, s)
elif isinstance(v, list):
s += "\n{} (list, {} items)".format(k, len(v))
s += list_to_shortstr(v)
elif isinstance(v, np.ndarray) and v.ndim == 1:
arrays += "\n{} (array, {} items)".format(k, len(v))
arrays += list_to_shortstr(v)
else:
s += "\n%s: %s" % (k, v)
s += arrays
return s
def __str__(self):
head = "Pyaerocom {}".format(type(self).__name__)
s = "\n{}\n{}".format(head, len(head) * "-")
arrays = ''
series = ''
for k, v in self.items():
if k[0] == '_':
continue
if isinstance(v, dict):
s += "\n{} ({})".format(k, type(v))
s = dict_to_str(v, s)
elif isinstance(v, list):
s += "\n{} (list, {} items)".format(k, len(v))
s += list_to_shortstr(v)
elif isinstance(v, np.ndarray) and v.ndim == 1:
arrays += "\n{} (array, {} items)".format(k, len(v))
arrays += list_to_shortstr(v)
elif isinstance(v, np.ndarray):
arrays += "\n{} (array, shape {})".format(k, v.shape)
arrays += "\n{}".format(v)
elif isinstance(v, pd.Series):
series += "\n{} (Series, {} items)".format(k, len(v))
else:
s += "\n%s: %s" % (k, v)
if arrays:
s += '\n\nData arrays\n.................'
s += arrays
if series:
s += '\nPandas Series\n.................'
s += series
return s
def __str__(self):
head = "Pyaerocom {}".format(type(self).__name__)
s = "\n{}\n{}".format(head, len(head) * "-")
plot_s = '\nPlotting settings\n......................'
for k, v in self.__dict__.items():
if k in self.plot_info_keys:
if v is None:
continue
if isinstance(v, dict):
plot_s += "\n{} (dict)".format(k)
plot_s = dict_to_str(v, plot_s, indent=3, ignore_null=True)
elif isinstance(v, list):
plot_s += "\n{} (list, {} items)".format(k, len(v))
plot_s += list_to_shortstr(v)
else:
plot_s += "\n%s: %s" % (k, v)
else:
if isinstance(v, dict):
s += "\n{} (dict)".format(k)
s = dict_to_str(v, s, indent=3, ignore_null=True)
elif isinstance(v, list):
s += "\n{} (list, {} items)".format(k, len(v))
s += list_to_shortstr(v)
else:
s += "\n%s: %s" % (k, v)
s += plot_s
return s
def __str__(self):
head = "Pyaerocom {}".format(type(self).__name__)
s = "\n{}\n{}\n".format(head, len(head)*"-")
for k, v in self.__dict__.items():
if k.startswith('_'):
pass
if k=='VAR_PARAM':
s += '\n{}\n{}'.format(k, list_to_shortstr(v.all_vars))
elif isinstance(v, dict):
s += "\n%s (dict)" %k
elif isinstance(v, list):
s += "\n%s (list)" %k
s += list_to_shortstr(v)
else:
s += "\n%s: %s" %(k, v)
return s
def __str__(self):
head = "Pyaerocom {}".format(type(self).__name__)
s = "\n{}\n{}".format(head, len(head) * "-")
arrays = ''
for k, v in self.items():
if isinstance(v, dict):
s += "\n{} (dict)".format(k)
s = dict_to_str(v, s)
elif isinstance(v, list):
s += "\n{} (list, {} items)".format(k, len(v))
s += list_to_shortstr(v)
elif isinstance(v, np.ndarray) and v.ndim == 1:
arrays += "\n{} (array, {} items)".format(k, len(v))
arrays += list_to_shortstr(v)
else:
s += "\n%s: %s" % (k, v)
s += arrays
return s
def __str__(self):
s = super(StationData, self).__str__()
s_data = ''
for k, v in self._data_coords.items():
if v is not None:
if isinstance(v, list):
s_data += "\n{} (list, {} items)".format(k, len(v))
s_data += list_to_shortstr(v)
elif isinstance(v, np.ndarray) and v.ndim == 1:
s_data += "\n{} (array, {} items)".format(k, len(v))
s_data += list_to_shortstr(v)
elif isinstance(v, pd.Series):
s_data += "\n{} (Series, {} items)".format(k, len(v))
else:
s_data += "\n%s: %s" % (k, v)
if s_data:
s += '\n\nData coordinates\n.................'
s += s_data
return s
def get_file_list(self, pattern=None):
"""Search all files to be read
Uses :attr:`_FILEMASK` (+ optional input search pattern, e.g.
station_name) to find valid files for query.
Parameters
----------
pattern : str, optional
file name pattern applied to search
Returns
-------
list
list containing retrieved file locations
Raises
------
IOError
if no files can be found
"""
if isinstance(pattern, str):
pattern = (pattern + self._FILEMASK).replace('**', '*')
else:
pattern = self._FILEMASK
if pattern is None:
const.print_log.warning(
'_FILEMASK attr. must not be None...'
'using default pattern *.* for file search')
pattern = '*.*'
self.logger.info('Fetching data files. This might take a while...')
files = sorted(glob.glob(os.path.join(self.DATASET_PATH, pattern)))
if not len(files) > 0:
all_str = list_to_shortstr(os.listdir(self.DATASET_PATH))
raise DataSourceError(
'No files could be detected matching file '
'mask {} in dataset {}, files in folder {}:\n'
'Files in folder:{}'.format(pattern, self.dataset_to_read,
self.DATASET_PATH, all_str))
self.files = files
return files
