--- a/atmospheric_lidar/generic.py Tue Jun 07 17:06:12 2016 +0300
+++ b/atmospheric_lidar/generic.py Tue Jun 07 17:06:32 2016 +0300
@@ -12,7 +12,7 @@
netcdf_format = 'NETCDF3_CLASSIC' # choose one of 'NETCDF3_CLASSIC', 'NETCDF3_64BIT', 'NETCDF4_CLASSIC' and 'NETCDF4'
-class BaseLidarMeasurement():
+class BaseLidarMeasurement(object):
""" This is the general measurement object.
It is meant to become a general measurement object
independent of the input files.
@@ -122,7 +122,7 @@
# The old method, kept here for reference
#dt = np.mean(np.diff(raw_start_in_seconds))
#for d in duration_list:
- # if abs(dt - d) <15: #If the difference of measuremetns is 10s near the(30 or 60) seconds
+ # if abs(dt - d) <15: #If the difference of measurements is 10s near the(30 or 60) seconds
# duration = d
duration = np.diff(raw_start_in_seconds)[0]
@@ -133,7 +133,7 @@
''' Get a measurement object containing only the channels with names
contained in the channel_sublet list '''
- m = self.__class__() # Create an object of the same type as this one.
+ m = self.__class__() # Create an object of the same type as this one.
m.channels = dict([(channel, self.channels[channel]) for channel
in channel_subset])
m.update()
@@ -166,20 +166,20 @@
m.update()
return m
-
- def r_plot(self):
- #Make a basic plot of the data.
- #Should include some dictionary with params to make plot stable.
- pass
-
- def r_pdf(self):
- # Create a pdf report using a basic plot and meta-data.
- pass
-
- def save(self):
- #Save the current state of the object to continue the analysis later.
- pass
-
+
+ def rename_channel(self, prefix="", suffix=""):
+ """ Add a prefix and a suffix in a channel name.
+
+ :param prefix: A string for the prefix
+ :param suffix: A string for the suffix
+ :return: Nothing
+ """
+ channel_names = self.channels.keys()
+
+ for channel_name in channel_names:
+ new_name = prefix + channel_name + suffix
+ self.channels[new_name] = self.channels.pop(channel_name)
+
def get_PT(self):
''' Sets the pressure and temperature at station level .
The results are stored in the info dictionary.
@@ -201,7 +201,16 @@
channel.data[measurement_time] = data - dark_profile
channel.update()
-
+
+ def set_measurement_id(self, measurement_id):
+ """
+ Sets the measurement id for the SCC file.
+ :param measurement_id: The string for measurement id
+
+ """
+ self.info['Measurement_ID'] = measurement_id
+
+
def save_as_netcdf(self, filename = None):
"""Saves the measurement in the netcdf format as required by the SCC.
Input: filename. If no filename is provided <measurement_id>.nc will
@@ -246,7 +255,10 @@
'Background_High': (('channels', ), 'd'),
'LR_Input': (('channels', ), 'i'),
'DAQ_Range': (('channels', ), 'd'),
- 'Depolarization_Factor': (('channels', ), 'd'), }
+ 'Depolarization_Factor': (('channels', ), 'd'),
+ 'Pol_Calib_Range_Min': (('channels', ), 'd'),
+ 'Pol_Calib_Range_Max': (('channels', ), 'd'),
+ }
channels = self.channels.keys()
@@ -380,8 +392,6 @@
f.RawBck_Start_Time_UT = dark_measurement.info['start_time'].strftime('%H%M%S')
f.RawBck_Stop_Time_UT = dark_measurement.info['stop_time'].strftime('%H%M%S')
-
-
def save_netcdf_extra(self, f):
pass
@@ -423,7 +433,6 @@
def calculate_rc(self, idx_min = 4000, idx_max = 5000):
background = np.mean(self.matrix[:,idx_min:idx_max], axis = 1) # Calculate the background from 30000m and above
self.rc = (self.matrix.transpose()- background).transpose() * (self.z **2)
-
def update(self):
self.start_time = min(self.data.keys())
@@ -490,7 +499,7 @@
c.data = subset_data
c.update()
return c
-
+
def profile(self,dtime, signal_type = 'rc'):
t, idx = self._nearest_dt(dtime)
if signal_type == 'rc':
