Commit ac48a1158cfebf06d48502681d5de6bbf138f8a7

Authored by Erwan Motte
1 parent 4edf0d82
Exists in master

Many Updates

source/PRO/PRO_L0btoL1a.rst
... ... @@ -8,158 +8,5 @@
8 8 Level 0b to Level 1a
9 9 *********************
10 10  
11   -l0b_to_l1a.py
12   -====================
13   -
14   -Module description
15   -------------------
16   -The goal of this module is to compute the basic observables for
17   -land applications. Nadir (nad) and Zenith (zen) subscript are used only when
18   -the processing is not generic to all channels.
19   -
20   -#. Performs additional waveform coherent averaging by arithmetic averaging.
21   - (Currently not done, Ti = t_coh)
22   -
23   - code::
24   -
25   - n_shots = int(round(t_coh/Ti))
26   - wf_co = reshape(wf, n_shots).mean(axis=1)
27   -
28   -#. Incoherent averaging is performed in power as the square of the modulus of
29   - the coherently averaged amplitude: :math:`P = <|Y|>`
30   -
31   - code::
32   -
33   - n_shots = int(round(t_incoh/t_coh))
34   - wf_pow = reshape(np.square(np.abs(wf_co)), n_shots).mean(axis=1)
35   -
36   -#. And the variance of the absolute value of the ICF
37   - :math:`\sigma(|Y_{nad}/Y_{zen|})^2` is also computed:
38   -
39   - code::
40   -
41   - n_shots = int(round(t_incoh/t_coh))
42   - icf_var = np.square(reshape(np.abs(wf_co_nad/wf_co_zen), n_shots).std
43   - (axis=1))
44   -
45   -#. The noise level is computed as the mean of channel 9 over the whole file
46   - (36s). This is expected to be representative of the noise, and then
47   - subtracted to the power: (:math:`P_{corr} = P-B`).
48   -
49   - code::
50   -
51   - # Noise level estimation
52   - pow_noise_sq = wf_pow[:, 9].mean(axis=0)
53   -
54   - # power correction with noise
55   - pow_corr = np.clip(pow - pow_noise_sq)
56   -
57   -#. Correct signal according to antenna gain pattern G as
58   - :math:`P_{ant} = P_{corr} / G`
59   -
60   - code::
61   -
62   - # Find pointing direction in antenna reference frame according
63   - # to aircraft attitude and satellite elevation and azimuth.
64   - theta_zen_res, theta_nad_res, phi_res = theta_phi_from_df(df_anc)
65   -
66   - # Interpolate antenna co-pol and cross-pol gain according to pointing
67   - G, X = find_gain('ZR', cfg, df_anc)
68   -
69   - # Correct measurement for gain
70   - pow_ant = pow_corr / G
71   -
72   -#. Compute the ICF as
73   - :math:`\frac{P_{ant,nad}}{P_{ant,zen}}`
74   -
75   - code::
76   -
77   - ICF = pow_ant_nad / pow_ant_zen
78   -
79   -#. Compute the apparent reflectivity as
80   - :math:`\Gamma' = ICF - \sigma_{ICF}^2`
81   -
82   - code::
83   -
84   - gamma = ICF - icf_var
85   -
86   -
87   -#. Finally, the total processing can be summarized by this equation
88   -
89   - .. math::
90   -
91   - \Gamma' = \frac{(<|Y_{nad}|> - B_{nad}) / G_{nad}}
92   - {(<|Y_{zen}|> - B_{zen}) / G_{zen}}
93   - - \sigma(|Y_{nad}/Y_{zen|})^2
94   -
95   -
96   -#. Merge in one file:
97   -
98   - - The Direct RHCP signal peak correlation complex amplitude
99   - - The direct estimated Doppler
100   - - The reflected LHCP signal peak correlation complex amplitude
101   - - The reflected RHCP signal peak correlation complex amplitude
102   - - The estimated delay of the reflected LHCP signal in lags
103   - - Ancillary info from L0 files
104   - - PRN
105   - - StartSOW, ifSOWread, WN,
106   - - fs,
107   - - El, Az
108   -
109   -
110   -.. csv-table:: Processing steps
111   - :stub-columns: 1
112   - :widths: 1 10 8 6 4
113   - :header: Step, Processing, Output, Variable, format
114   -
115   - 1, Read waveforms , Raw WFs , WF_NL , 2D cpx WF
116   - 2, Additional coh. avging , Coherently avgd WFs, WF_NL_co , 2D cpx WF
117   - 3, Find coh peak , peak position , NL_loc_co , 1D int
118   - 4, Store coh peak value , peak value TS , NL_pow_co , 1D cpx
119   - 5, Compute coh noise floor, noise floor level , grass_NL_co , 1D float
120   - 6, abs and correct for NF , noise free TS , NL_pow_corr_co, 1D float
121   -
122   -Inputs
123   -------
124   -
125   -Outputs
126   --------
127   -
128   -.. csv-table:: L0 to L1a output file
129   - :stub-columns: 1
130   - :widths: 4 20
131   - :header: Field, Description
132   -
133   - DateTime , Python Datetime
134   - lat_spec , Latitude of specular point
135   - lon_spec , Longitude of specular point
136   - DEM_spec , DEM at specular point location
137   - SV_elev , Elevation at specular point
138   - SV_azimuth , Azimuth at specular point
139   - ZR_amp_res , Incoherently Averaged amplitude
140   - ZR_pow_res , Incoherently averaged power
141   - ZR_var_res , Incoherently averaged variance
142   - ZR_ph_res , Incoherently averaged phase
143   - grass_ZR_sq , Mean of noise floor squared
144   - ZR_pow_corr , Power corrected for noise floor
145   - grass_ZR , Mean of noise floor
146   - ZR_amp_corr , Amplitude corrected for noise floor
147   - G_ZR , Copol Gain of antenna
148   - X_ZR , Xpol Gain of antenna
149   - ZR_amp_cal , Amplitude corrected for antenna pattern
150   - ZR_pow_cal , Power corrected for antenna pattern
151   - NL_pow_cal_xp, Power corrected for antenna gain + xpol contribution
152   - ZR_pow_coh , Coherent contribution of the power
153   - NL_pow_coh_xp, Coherent contribution of the power corrected for xpol
154   - Gamma_L , Reflection coeff : Ratio of reflected over direct
155   - Gamma_LR , Polarimetric ratio: Ratio of LHCP over RHCP
156   - Gamma_L_xp , Reflection coeff : Ratio of reflected over direct (xpol)
157   - Gamma_LR_xp , Polarimetric ratio: Ratio of LHCP over RHCP (xpol)
158   -
159   -
160   -l0b_to_l1a.py
161   -=============
162   -
163   -
164 11 .. automodule:: pyGLORI.process.l0b_to_l1a
165 12 :members:
... ...
source/PRO/PRO_L0toL0b.rst
... ... @@ -8,75 +8,10 @@
8 8 Level 0 to Level 0b
9 9 *********************
10 10  
11   -
12   -Module description
13   -------------------
14   -The goal of this module is to compute the basic observables for
15   -land applications. Nadir (nad) and Zenith (zen) subscript are used only when
16   -the processing is not generic to all channels.
17   -
18   -#. Resynchronize the data acquisitions by reading the SOW info from the
19   - navigation message and time tagging of the L0b files
20   -
21   -#. Performs waveform peak search using various techniques
22   -
23   -#. Store position of peaks and max values
24   -
25   -#. Compute and store waveforms noise floor.
26   -
27   -
28   -
29   -Inputs
30   -------
31   -
32   -The required inputs for this routine are:
33   -
34   -- A valid configuration files
35   -- L0 files in the cStarlight netcdf format (see :ref:`PRO_raw_L0`: for details)
36   -
37   -Outputs
38   --------
39   -
40   -.. csv-table:: L0 to L1a output file
41   - :stub-columns: 1
42   - :widths: 4 20
43   - :header: Field, Description
44   -
45   - DateTime , Python Datetime
46   - lat_spec , Latitude of specular point
47   - lon_spec , Longitude of specular point
48   - DEM_spec , DEM at specular point location
49   - SV_elev , Elevation at specular point
50   - SV_azimuth , Azimuth at specular point
51   - ZR_amp_res , Incoherently Averaged amplitude
52   - ZR_pow_res , Incoherently averaged power
53   - ZR_var_res , Incoherently averaged variance
54   - ZR_ph_res , Incoherently averaged phase
55   - grass_ZR_sq , Mean of noise floor squared
56   - ZR_pow_corr , Power corrected for noise floor
57   - grass_ZR , Mean of noise floor
58   - ZR_amp_corr , Amplitude corrected for noise floor
59   - G_ZR , Copol Gain of antenna
60   - X_ZR , Xpol Gain of antenna
61   - ZR_amp_cal , Amplitude corrected for antenna pattern
62   - ZR_pow_cal , Power corrected for antenna pattern
63   - NL_pow_cal_xp, Power corrected for antenna gain + xpol contribution
64   - ZR_pow_coh , Coherent contribution of the power
65   - NL_pow_coh_xp, Coherent contribution of the power corrected for xpol
66   - Gamma_L , Reflection coeff : Ratio of reflected over direct
67   - Gamma_LR , Polarimetric ratio: Ratio of LHCP over RHCP
68   - Gamma_L_xp , Reflection coeff : Ratio of reflected over direct (xpol)
69   - Gamma_LR_xp , Polarimetric ratio: Ratio of LHCP over RHCP (xpol)
70   -
71   -
72   -Functions and routines
73   -----------------------
74   -
75 11 .. automodule:: pyGLORI.process.l0_to_l0b
76 12 :members:
77 13  
78 14  
79   -
80 15 Issues / recommendations
81 16 ------------------------
82 17  
... ...
source/PRO/PRO_ancillary.rst
  1 +.. raw:: latex
  2 +
  3 + \clearpage
  4 +
1 5 .. _PRO_anc:
2 6  
3 7 *******************************
... ... @@ -23,297 +27,29 @@ and png figures with time series of ancillary information.
23 27 Description of the ancillary processing chain
24 28  
25 29  
26   -
27   -Anc_read_rtk.py
  30 +anc_read_rtk.py
28 31 ===============
29 32  
30   -Module description
31   -------------------
32   -This module reads the Ublox “raw” data (Phase, Pseudorange information, Doppler)
33   -reprocessed with rtklib. This allows to provide a more precise
34   -source of information for satellite elevation, azimuth as seen from the plane.
35   -This information will be in turn be used by the processing chain
36   -for specular point calculation and altimetric corrections.
37   -The module just reads a plain-text file using pandas read_table() function
38   -and store it into a pickled pandas file.
39   -
40   -Inputs
41   -------
42   -The processing chain configuration file specifying paths and parameters
43   -is the only needed input.
44   -The related fields in the configuration files are the following:
45   -
46   -- ubx_dir
47   -- ubx_prefix
48   -
49   -The routine will be looking for the file in the folder “ubx_dir”
50   -with filename “ubx_prefix” and extension “.azel”
51   -
52   -in order to generate the azel file, the following procedure shall be followed.
53   -
54   -1. Download the following tools :
55   -
56   - * teqc_ command line tool
57   - * RTKLIB_ graphical tool
58   -
59   -.. _teqc: https://www.unavco.org/software/data-processing/teqc/teqc.html
60   -.. _RTKLIB: http://www.rtklib.com/
61   -
62   -2. Convert the ubx raw file into rinex observation file: run the teqc tool on
63   -the raw ubx file with the following command:
64   -
65   -.. code-block:: shell
66   -
67   - tecq -ublox ubx ubxrawfile.ubx > ubxrawfile.obs
68   -
69   -3. download the gps broadcast navigation file from cddis ftp server
70   -
71   - * ftp://cddis.gsfc.nasa.gov/gnss/data/daily/YYYY/DDD/YYn/brdcDDD0.YYn.Z
72   - where YY and YYYY stand for the year number,
73   - and DDD for the day of the year (can be found on the `NOAA NGS`_).
74   - If the measurement spans over several days,
75   - several navigation files should be downloaded.
  33 +.. automodule:: pyGLORI.process.anc_read_rtk
  34 + :members:
76 35  
77   -.. _`NOAA NGS`: http://www.ngs.noaa.gov/CORS/Gpscal.shtml
78 36  
  37 +anc_read_ubx.py
  38 +===============
79 39  
80   -4. Unzip the downloaded file(s).
81   -
82   -5. Open RTKLib RTKplot
83   -
84   - * Select **File>Open Obs Data** and load the ubxrawfile.obs
85   - * Select **File>Open nav data** and select the brdcDDD0.YYn.n file(s)
86   - * Check in the skyplot and elevation plots that azimut
87   - and elevations are correctly computed
88   - * save the azel file in File>Save AZ/EL/SNR/MP… and name it ubxrawfile.azel
89   -
90   -Outputs
91   --------
92   -One file in the pickled pandas format is generated:
93   -- **{Flight_id}_rtk.p**: Space Vehicles Azimuth and elevation from
94   -GLORI Ublox receiver processed by RTKLib
95   -
96   -.. csv-table:: Anc_read_rtk.py output file
97   - :stub-columns: 1
98   - :widths: 2 4 8
99   - :header: Field, Unit, Description
100   -
101   - DateTime, Python DateTime, Date and time of the sample
102   - sv, N/A, Satellite Space Vehicle ID (PRN ID for GPS)
103   - azim_te, integer degrees, GLORI UBlox RTKLib processed SV azimuth
104   - elev_te, integer degrees, GLORI UBlox RTKLib processed SV elevation
  40 +.. automodule:: pyGLORI.process.anc_read_ubx
  41 + :members:
105 42  
106 43  
107   -Anc_read_UBX_v2.py
  44 +anc_read_safire.py
108 45 ==================
109 46  
110   -Module description
111   -------------------
112   -The purpose of this module is to read the data recorded by the
113   -Ublox GPS receiver included in the GLORI instrument.
114   -Depending on the version of the instrument, data was saved
115   -in different formats (UBX + NMEA for the first campaign,
116   -UBX only for the second campaign). The module is based on
117   -the pyUblox_ and pynmea2_ packages.
118   -
119   -.. _pyUblox: https://github.com/tridge/pyUblox
120   -.. _pynmea2: https://github.com/Knio/pynmea2
121   -
122   -Inputs
123   -------
124   -The processing chain configuration file specifying paths and parameters
125   -is the only needed input.
126   -The related fields in the configuration files are the following:
127   -
128   -- ubx_dir
129   -- ubx_prefix
130   -- ubx_type ('UBX+NMEA' or ‘UBX_ONLY’)
131   -
132   -Outputs
133   --------
134   -2 files are generated by the anc_read_UBX_v2.py module,
135   -in the pickled pandas format:
136   -
137   -- **{Flight_id}_ubx_pos.p**: 3D position GLORI from Ublox receiver
138   -
139   -.. csv-table:: {Flight_id}_ubx_pos.p output file
140   - :stub-columns: 1
141   - :widths: 2 4 8
142   - :header: Field, Unit, Description
143   -
144   -
145   - DateTime, Python DateTime, Date and time of the sample
146   - sow , seconds , GPS Time of the Week of the sample
147   - lat , decimal degrees, GLORI UBlox-based latitude
148   - lon , decimal degrees, GLORI UBlox-based longitude
149   - hMSL , m , GLORI UBlox-based height over mean sea level
150   - hOE , m , GLORI UBlox-based height over Ellipsoid
151   - course , decimal degrees, GLORI UBlox-based course
152   - gSpeed , m/s , GLORI UBlox-based ground speed
153   - hAcc , m , GLORI UBlox-based horizontal Accuracy
154   - vAcc , m , GLORI UBlox-based vertical Accuracy
  47 +.. automodule:: pyGLORI.process.anc_read_safire
  48 + :members:
155 49  
156   -- **{Flight_id}_ubx_SVs.p**: Space Vehicles information from GLORI Ublox receiver
157   -
158   -.. csv-table:: {Flight_id}_ubx_SVs.p output file
159   - :stub-columns: 1
160   - :widths: 2 4 8
161   - :header: Field, Unit, Description
162   -
163   - DateTime, Python DateTime, Date and time of the sample
164   - sow , seconds , GPS Time of the Week of the sample
165   - sv , N/A , Satellite Space Vehicle ID (PRN ID for GPS)
166   - azim , integer degrees, GLORI UBlox-based SV azimuth
167   - elev , integer degrees, GLORI UBlox-based SV elevation
168   - cn0 , dB , GLORI UBlox-based SV Carrier to Noise Ratio
169   - cpMes , radians , GLORI UBlox-based SV Code Phase
170   - doMes , Hz , GLORI UBlox-based SV Doppler
171   - prMes , m , GLORI UBlox-based SV PseudoRange
172   -
173   -Issues / Recommendations
174   -------------------------
175   -- Various format and time resolution depending on campaigns (UBX+NMEA, UBX only)
176   -
177   - - Solution: Create specific cases for each configuration
178   -
179   -- Issues in the computation of the UTC time (jumps of 16s in one case.)
180   -
181   - - Recompute time from received iTOW
182   -
183   -Anc_read_SAFIRE_v2.py
184   -=====================
185   -
186   -Module description
187   -------------------
188   -The purpose of this module is to read the data recorded by SAFIRE ATR-42
189   -on-board instrumentation, i.e. from an AIRINS system.
190   -This mainly include information from an independant GPS receiver attached
191   -to an Inertial Navigation System (INS) as well as a Radio Altimeter
192   -providing independent estimate of range under the plane track.
193   -It has to be noted that depending on the flights, data fields,
194   -data frequency and data format was changed.
195   -See Post-Campaign instrument analysis document for more information.
196   -
197   -Inputs
198   -------
199   -The processing chain configuration file specifying paths
200   -and parameters is the only needed input.
201   -The related fields in the configuration files are the following:
202   -
203   -- SAFIRE_dir
204   -- SAFIRE_file
205   -- SAFIRE_type ('xls', ‘txt_v1’ or ‘txt_v2’)
206   -
207   -
208   -Outputs
209   --------
210   -1 file is generated by the anc_read_SAFIRE_v2.py module,
211   -in the pickled pandas format:
212   -- **{Flight_id}_saf.p**: SAFIRE ancillary information
213   -
214   -.. csv-table:: {Flight_id}_saf.p output file
215   - :stub-columns: 1
216   - :widths: 2 4 8
217   - :header: Field, Unit, Description
218   -
219   - DateTime , Python DateTime, Date and time of the sample
220   - lat_ins , decimal degrees, SAFIRE AIRINS-based latitude
221   - lon_ins , decimal degrees, SAFIRE AIRINS-based longitude
222   - hMSL_ins , m , SAFIRE AIRINS-based height over mean sea level
223   - heading_ins, m , SAFIRE AIRINS-based aircraft heading
224   - pitch_ins , decimal degrees, SAFIRE AIRINS-based aircraft pitch
225   - roll_ins , m/s , SAFIRE AIRINS-based aircraft roll
226   - alt_ra , m , SAFIRE Radio altimeter range
227 50  
228 51 Anc_post_process.py
229 52 ===================
230 53  
231   -Module description
232   -------------------
233   -
234   -This modules takes the output of the Anc_read_UBX.py and Anc_read_SAFIRE.py
235   -modules in order to generate consolidated ancillary data files
236   -ready to be used by other procedures. It performs the following tasks:
237   -
238   -- Process Plane position info
239   -- Read Ublox information
240   -- Filter data for a minimum flight altitude
241   -- SRTM DEM lookup for the flight path (using `strm.py`_ )
242   -- Read Safire information
243   -- Compute Zenith Antenna Elevation and Azimuth from Attitude information
244   -- Interpolate SAFIRE according to Ublox position info
245   -- Process SVs info
246   -- Filter for SV elevation angle and SV type
247   -- Compute the approximate footprint location for the filtered SVs, using pyProj
248   -- SRTM DEM lookup for the Specular point location
249   -
250   -.. _strm.py: https://github.com/tkrajina/srtm.py
251   -
252   -Inputs
253   -------
254   -The processing chain configuration file specifying
255   -paths and parameters is the only needed input
256   -
257   -Outputs
258   --------
259   -3 files are generated by the anc_post_process.py module,
260   -all of them inthe pickled pandas format:
261   -
262   -- **{Flight_id}_post_pos.p**: GLORI Ublox position +
263   - SAFIRE INS attitude information +
264   - DEM information interpolated (nearest neighbour) at the Ublox GPS rate
265   -
266   -.. csv-table:: {Flight_id}_post_pos.p output file
267   - :stub-columns: 1
268   - :widths: 2 4 8
269   - :header: Field, Unit, Description
270   -
271   - DateTime , Python DateTime, Date and time of the sample
272   - sow , seconds , GPS Time of the Week of the sample
273   - lat , decimal degrees, GLORI UBlox-based latitude
274   - lon , decimal degrees, GLORI UBlox-based longitude
275   - gSpeed , m/s , GLORI UBlox-based ground speed
276   - hMSL , m , GLORI UBlox-based height over mean sea level
277   - course , decimal degrees, UBlox-based true course
278   - DEM , m , Digital Elevation Model (SRTM) under the track
279   - heading_ins, decimal degrees, SAFIRE AIRINS-based aircraft heading
280   - pitch_ins , decimal degrees, SAFIRE AIRINS-based aircraft pitch
281   - roll_ins , decimal degrees, SAFIRE AIRINS-based aircraft roll
282   - lat_ins , decimal degrees, SAFIRE AIRINS-based aircraft latitude
283   - lon_ins , decimal degrees, SAFIRE AIRINS-based aircraft longitude
284   - hMSL_ins , m , SAFIRE AIRINS-based aircraft altitude over MSL
285   - alt_ra , m , SAFIRE Radio altimeter estimated range
286   - el_zen , decimal degrees, Zenith antenna boresight elevation angle
287   - az_zen , decimal degrees, Zenith antenna boresight azimuth direction
288   -
289   -
290   -- **{Flight_id}_post_SVs.p**: GLORI Ublox-based Space Vehicles information:
291   - Approximate azimuth and elevation relative to plane,
292   - and related computed position of specular point on ground.
293   -
294   -.. csv-table:: {Flight_id}_post_SVs.p output file
295   - :stub-columns: 1
296   - :widths: 2 4 8
297   - :header: Field, Unit, Description
298   -
299   - sow , seconds , GPS Time of the Week of the sample
300   - sv , N/A , Satellite Space Vehicle ID (PRN ID for GPS)
301   - azim , integer degrees, GLORI UBlox-based satellite azimuth
302   - elev , integer degrees, GLORI UBlox-based satellite elevation
303   - speclat , decimal degrees, Computed specular point approximate latitude
304   - speclon , decimal degrees, Computed specular point approximate longitude
305   - specDEM , m , DEM (SRTM) value at the specular point location
306   - heightOG, m , Height difference between DEM and flight altitude
307   -
308   -- **{Flight_id}_post_SVs.p**: Same fields as above, but with a reduced
309   - temporal resolution defined by cfg[‘lowres_step’], typically 2 seconds.
310   - File used for generating kml files.
311   -
312   -Issues / recommendations
313   -------------------------
314   -- Data rate and interpolation need to be checked for output files.
315   - Maybe set a common frequency (5Hz?) for each output measurement
316   - could be a good way to get uniform ancillary datasets.
317   -
318   - - Compare SV az/el against CStarlight-derived az/el
319   -
320 54 \ No newline at end of file
  55 +.. automodule:: pyGLORI.process.anc_post_process
  56 + :members:
... ...
source/PRO/PRO_common.rst
  1 +.. raw:: latex
  2 +
  3 + \clearpage
  4 +
1 5 .. _PRO_common:
2 6  
3 7 *********************
... ... @@ -9,10 +13,8 @@ pyGLORI project. It contains several functions that are used
9 13 at various stage of the processing
10 14  
11 15  
12   -geom.py
13   -=======
14   -
15   -Geometry related functions
  16 +glori_geom.py
  17 +=============
16 18  
17 19 .. automodule:: pyGLORI.common.glori_geom
18 20 :members:
... ... @@ -21,8 +23,6 @@ Geometry related functions
21 23 glori_antennas.py
22 24 =================
23 25  
24   -Antennas related functions
25   -
26 26 .. automodule:: pyGLORI.common.glori_antennas
27 27 :members:
28 28  
... ... @@ -39,9 +39,6 @@ general purpose functions (related with time manipulation among others)
39 39 glori_io.py
40 40 ===========
41 41  
42   -I/O related routines, linked to netCDF, HDF and Pickle specific formats for
43   -L0, L1a and L1b
44   -
45 42 .. automodule:: pyGLORI.common.glori_io
46 43 :members:
47 44  
... ...
source/PRO/PRO_config.rst
  1 +.. raw:: latex
  2 +
  3 + \clearpage
  4 +
1 5 .. _PRO_config:
2 6  
3 7 *********************
... ...
source/PRO/PRO_install.rst
No preview for this file type
source/PRO/PRO_intro.rst
  1 +.. raw:: latex
  2 +
  3 + \clearpage
  4 +
1 5 .. _PRO_intro:
2 6  
3 7 ******************************************
... ...
source/PRO/PRO_rawtoL0.rst
  1 +.. raw:: latex
  2 +
  3 + \clearpage
  4 +
1 5 .. _PRO_raw_L0:
2 6  
3 7 *********************
4 8 Raw to Level 0
5 9 *********************
6 10  
7   -Module description
8   -------------------
9   -This module performs the basic observable computation (correlation waveforms)
10   -from raw data. As for september 2015, it is based on the cStarlight package
11   -provided with Starlab’s Oceanpal instrument.
12   -Inputs and outputs are documented in Oceanpal user manual,
13   -but will be described again in the present document for the sake of clarity.
14   -
15   -- Open the plane track file and keep unique points
16   -- Check and list the raw files covered by ancillary data
17   - (already filtered on altitude)
18   -- Download the yuma file corresponding to the beginning of the flight
19   -- for each raw file in the list
20   -
21   - - Generate a generic string based on the raw file name
22   - - Check for the existence of a timepos file,
23   - that would tell that the file has already processed
24   - - if it is not the case, or if the “reprocess” keyword is set to True
25   - in the config file, start the actual processing:
26   -
27   - - Generate a new timepos file with segment median
28   - latitude, longitude and altitude.
29   - - Decompress and convert the raw datafiles into
30   - a cStarlight compatible format (1Bit real non zero IF),
31   - using the binary pointed by ‘decompress_exe’ in the config file
32   - - Update the cStarlight L0_gps_settings.txt config file with the altitude
33   - - Erase previously generated L0 files
34   - - Build cStarlight command for both LHCP and RHCP
35   - - Run both channels at the same time and wait for their completion
36   - - Delete uncompressed files
37   -
38   -
39   -Inputs
40   -------
41   -
42   -Outputs
43   --------
44   -
45   -Issues / recommendations
46   -------------------------
47   -
48   -
49   -Functions and routines
50   -----------------------
51   -
52 11 .. automodule:: pyGLORI.process.raw_to_l0
53 12 :members:
54 13  
55   -
56   -Functions and routines
57   -----------------------
  14 +CStarlight
  15 +----------
58 16  
59 17 .. automodule:: pyGLORI.process.cstarlight
60   - :members:
61 18 \ No newline at end of file
  19 + :members:
  20 +
  21 +Issues / recommendations
  22 +------------------------
  23 +
  24 +TBD.
... ...
source/VAL/VAL_instru_frontend
source/conf.py
... ... @@ -29,6 +29,7 @@ sys.path.insert(0, os.path.abspath(&#39;../../processing/python_code/&#39;))
29 29 # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
30 30 # ones.
31 31 extensions = [
  32 + 'matplotlib.sphinxext.plot_directive',
32 33 'sphinx.ext.autodoc',
33 34 'sphinx.ext.doctest',
34 35 'sphinx.ext.intersphinx',
... ... @@ -118,7 +119,7 @@ todo_include_todos = True
118 119 # The theme to use for HTML and HTML Help pages. See the documentation for
119 120 # a list of builtin themes.
120 121 html_theme = 'alabaster'
121   -html_theme = 'sphinx_rtd_theme'
  122 +#html_theme = 'sphinx_rtd_theme'
122 123  
123 124 # Theme options are theme-specific and customize the look and feel of a theme
124 125 # further. For a list of options available for each theme, see the
... ... @@ -367,4 +368,4 @@ epub_exclude_files = [&#39;search.html&#39;]
367 368 # Example configuration for intersphinx: refer to the Python standard library.
368 369 intersphinx_mapping = {'https://docs.python.org/': None}
369 370  
370   -#pdf_documents = [('index', u'rst2pdf', u'GLORI doc pdf', u'Erwan Motte'), ]
371 371 \ No newline at end of file
  372 +#pdf_documents = [('index', u'rst2pdf', u'GLORI doc pdf', u'Erwan Motte'), ]
... ...