Many updates, started to include autodoc from code

Erwan Motte
1 parent dc66561e
Showing 11 changed files with 291 additions and 115 deletions Show diff stats
source/PRO/PRO_L0btoL1a.rst
source/PRO/PRO_L0toL0b.rst
source/PRO/PRO_L0toL1a.rst
source/PRO/PRO_L1atoL1b.rst
source/PRO/PRO_common.rst
source/PRO/PRO_index.rst
source/PRO/PRO_install.rst
source/PRO/PRO_intro.rst
source/PRO/PRO_rawtoL0.rst
source/conf.py
source/index.rst
@@ -0,0 +1,165 @@
+.. raw:: latex
+
+    \clearpage
+
+.. _PRO_L0b_L1a:
+
+*********************
+Level 0b to Level 1a
+*********************
+
+l0b_to_l1a.py
+====================
+
+Module description
+------------------
+The goal of this module is to compute the basic observables for
+land applications. Nadir (nad) and Zenith (zen) subscript are used only when
+the processing is not generic to all channels.
+
+#. Performs additional waveform coherent averaging by arithmetic averaging.
+   (Currently not done, Ti = t_coh)
+
+   code::
+
+      n_shots = int(round(t_coh/Ti))
+      wf_co = reshape(wf, n_shots).mean(axis=1)
+
+#. Incoherent averaging is performed in power as the square of the modulus of
+   the coherently averaged amplitude: :math:`P = <|Y|>`
+
+   code::
+
+      n_shots = int(round(t_incoh/t_coh))
+      wf_pow = reshape(np.square(np.abs(wf_co)), n_shots).mean(axis=1)
+
+#. And the variance of the absolute value of the ICF
+   :math:`\sigma(|Y_{nad}/Y_{zen|})^2` is also computed:
+
+   code::
+
+      n_shots = int(round(t_incoh/t_coh))
+      icf_var  = np.square(reshape(np.abs(wf_co_nad/wf_co_zen), n_shots).std
+      (axis=1))
+
+#. The noise level is computed as the mean of channel 9 over the whole file
+   (36s). This is expected to be representative of the noise, and then
+   subtracted to the power: (:math:`P_{corr} = P-B`).
+
+   code::
+
+      # Noise level estimation
+      pow_noise_sq = wf_pow[:, 9].mean(axis=0)
+
+      # power correction with noise
+      pow_corr = np.clip(pow - pow_noise_sq)
+
+#. Correct signal according to antenna gain pattern G as
+   :math:`P_{ant} = P_{corr} / G`
+
+   code::
+
+      # Find pointing direction in antenna reference frame according
+      # to aircraft attitude and satellite elevation and azimuth.
+      theta_zen_res, theta_nad_res, phi_res = theta_phi_from_df(df_anc)
+
+      # Interpolate antenna co-pol and cross-pol gain according to pointing
+      G, X = find_gain('ZR', cfg, df_anc)
+
+      # Correct measurement for gain
+      pow_ant = pow_corr / G
+
+#. Compute the ICF as
+   :math:`\frac{P_{ant,nad}}{P_{ant,zen}}`
+
+   code::
+
+      ICF = pow_ant_nad / pow_ant_zen
+
+#. Compute the apparent reflectivity as
+   :math:`\Gamma' = ICF - \sigma_{ICF}^2`
+
+   code::
+
+      gamma = ICF - icf_var
+
+
+#. Finally, the total processing can be summarized by this equation
+
+   .. math::
+
+      \Gamma' = \frac{(<|Y_{nad}|> - B_{nad}) / G_{nad}}
+                     {(<|Y_{zen}|> - B_{zen}) / G_{zen}}
+                     - \sigma(|Y_{nad}/Y_{zen|})^2
+
+
+#. Merge in one file:
+
+   - The Direct RHCP signal peak correlation complex amplitude
+   - The direct estimated Doppler
+   - The reflected LHCP signal peak correlation complex amplitude
+   - The reflected RHCP signal peak correlation complex amplitude
+   - The estimated delay of the reflected LHCP signal in lags
+   - Ancillary info from L0 files
+   - PRN
+   - StartSOW, ifSOWread, WN,
+   - fs,
+   - El, Az
+
+
+.. csv-table:: Processing steps
+   :stub-columns: 1
+   :widths: 1 10 8 6 4
+   :header: Step, Processing, Output, Variable, format
+
+    1, Read waveforms         , Raw WFs            , WF_NL         , 2D cpx WF
+    2, Additional coh. avging , Coherently avgd WFs, WF_NL_co      , 2D cpx WF
+    3, Find coh peak          , peak position      , NL_loc_co     , 1D int
+    4, Store coh peak value   , peak value TS      , NL_pow_co     , 1D cpx
+    5, Compute coh noise floor, noise floor level  , grass_NL_co   , 1D float
+    6, abs and correct for NF , noise free TS      , NL_pow_corr_co, 1D float
+
+Inputs
+------
+
+Outputs
+-------
+
+.. csv-table:: L0 to L1a output file
+   :stub-columns: 1
+   :widths: 4 20
+   :header: Field, Description
+
+   DateTime     , Python Datetime
+   lat_spec     , Latitude of specular point
+   lon_spec     , Longitude of specular point
+   DEM_spec     , DEM at specular point location
+   SV_elev      , Elevation at specular point
+   SV_azimuth   , Azimuth at specular point
+   ZR_amp_res   , Incoherently Averaged amplitude
+   ZR_pow_res   , Incoherently averaged power
+   ZR_var_res   , Incoherently averaged variance
+   ZR_ph_res    , Incoherently averaged phase
+   grass_ZR_sq  , Mean of noise floor squared
+   ZR_pow_corr  , Power corrected for noise floor
+   grass_ZR     , Mean of noise floor
+   ZR_amp_corr  , Amplitude corrected for noise floor
+   G_ZR         , Copol Gain of antenna
+   X_ZR         , Xpol Gain of antenna
+   ZR_amp_cal   , Amplitude corrected for antenna pattern
+   ZR_pow_cal   , Power corrected for antenna pattern
+   NL_pow_cal_xp, Power corrected for antenna gain + xpol contribution
+   ZR_pow_coh   , Coherent contribution of the power
+   NL_pow_coh_xp, Coherent contribution of the power corrected for xpol
+   Gamma_L      , Reflection coeff : Ratio of reflected over direct
+   Gamma_LR     , Polarimetric ratio: Ratio of LHCP over RHCP
+   Gamma_L_xp   , Reflection coeff : Ratio of reflected over direct (xpol)
+   Gamma_LR_xp  , Polarimetric ratio: Ratio of LHCP over RHCP (xpol)
+
+
+l0b_to_l1a.py
+=============
+
+
+.. automodule:: pyGLORI.process.l0b_to_l1a
+   :members:
@@ -0,0 +1,82 @@
+.. raw:: latex
+
+    \clearpage
+
+.. _PRO_L0_L0b:
+
+*********************
+Level 0 to Level 0b
+*********************
+
+
+Module description
+------------------
+The goal of this module is to compute the basic observables for
+land applications. Nadir (nad) and Zenith (zen) subscript are used only when
+the processing is not generic to all channels.
+
+#. Resynchronize the data acquisitions by reading the SOW info from the
+   navigation message and time tagging of the L0b files
+
+#. Performs waveform peak search using various techniques
+
+#. Store position of peaks and max values
+
+#. Compute and store waveforms noise floor.
+
+
+
+Inputs
+------
+
+The required inputs for this routine are:
+
+- A valid configuration files
+- L0 files in the cStarlight netcdf format (see :ref:`PRO_raw_L0`: for details)
+
+Outputs
+-------
+
+.. csv-table:: L0 to L1a output file
+   :stub-columns: 1
+   :widths: 4 20
+   :header: Field, Description
+
+   DateTime     , Python Datetime
+   lat_spec     , Latitude of specular point
+   lon_spec     , Longitude of specular point
+   DEM_spec     , DEM at specular point location
+   SV_elev      , Elevation at specular point
+   SV_azimuth   , Azimuth at specular point
+   ZR_amp_res   , Incoherently Averaged amplitude
+   ZR_pow_res   , Incoherently averaged power
+   ZR_var_res   , Incoherently averaged variance
+   ZR_ph_res    , Incoherently averaged phase
+   grass_ZR_sq  , Mean of noise floor squared
+   ZR_pow_corr  , Power corrected for noise floor
+   grass_ZR     , Mean of noise floor
+   ZR_amp_corr  , Amplitude corrected for noise floor
+   G_ZR         , Copol Gain of antenna
+   X_ZR         , Xpol Gain of antenna
+   ZR_amp_cal   , Amplitude corrected for antenna pattern
+   ZR_pow_cal   , Power corrected for antenna pattern
+   NL_pow_cal_xp, Power corrected for antenna gain + xpol contribution
+   ZR_pow_coh   , Coherent contribution of the power
+   NL_pow_coh_xp, Coherent contribution of the power corrected for xpol
+   Gamma_L      , Reflection coeff : Ratio of reflected over direct
+   Gamma_LR     , Polarimetric ratio: Ratio of LHCP over RHCP
+   Gamma_L_xp   , Reflection coeff : Ratio of reflected over direct (xpol)
+   Gamma_LR_xp  , Polarimetric ratio: Ratio of LHCP over RHCP (xpol)
+
+
+Functions and routines
+----------------------
+
+.. automodule:: pyGLORI.process.l0_to_l0b
+   :members:
+
+
+
+Issues / recommendations
+------------------------
+
@@ -1,91 +0,0 @@
-.. _PRO_L0_L1a:
-
-*********************
-Level 0 to Level 1a
-*********************
-
-Process_L0_to_L1A.py
-====================
-
-Module description
-------------------
-The goal of this module is to compute the basic observables for land applications:
-
-#. Resynchronize the data acquisitions by reading the SOW info from the navigation message
-#. Performs additional coherent averaging by performing phase aware integration
-#. Correct coherent signal according to Antenna gain pattern and measurement noise.
-#. Compute ICF as
-
-   .. math::
-
-      ICF_{corr} = \frac{G_d}{G_r} \frac{Y_{r,max}-B_r}{Y_{d,max}-B_d}
-      e^{j(\phi_{r,max}-\phi_{d,max})}
-#. Performs incoherent averaging
-#. Compute phase variance
-#. Merge in one file:
-
-   - The Direct RHCP signal peak correlation complex amplitude
-   - The direct estimated Doppler
-   - The reflected LHCP signal peak correlation complex amplitude
-   - The reflected RHCP signal peak correlation complex amplitude
-   - The estimated delay of the reflected LHCP signal in lags
-   - Ancillary info from L0 files
-   - PRN
-   - StartSOW, ifSOWread, WN,
-   - fs,
-   - El, Az
-
-
-.. csv-table:: Processing steps
-   :stub-columns: 1
-   :widths: 1 10 8 6 4
-   :header: Step, Processing, Output, Variable, format
-
-    1, Read waveforms         , Raw WFs            , WF_NL         , 2D cpx WF
-    2, Additional coh. avging , Coherently avgd WFs, WF_NL_co      , 2D cpx WF
-    3, Find coh peak          , peak position      , NL_loc_co     , 1D int
-    4, Store coh peak value   , peak value TS      , NL_pow_co     , 1D cpx
-    5, Compute coh noise floor, noise floor level  , grass_NL_co   , 1D float
-    6, abs and correct for NF , noise free TS      , NL_pow_corr_co, 1D float
-
-Inputs
-------
-
-Outputs
--------
-
-.. csv-table:: L0 to L1a output file
-   :stub-columns: 1
-   :widths: 4 20
-   :header: Field, Description
-
-   DateTime     , Python Datetime
-   lat_spec     , Latitude of specular point
-   lon_spec     , Longitude of specular point
-   DEM_spec     , DEM at specular point location
-   SV_elev      , Elevation at specular point
-   SV_azimuth   , Azimuth at specular point
-   ZR_amp_res   , Incoherently Averaged amplitude
-   ZR_pow_res   , Incoherently averaged power
-   ZR_var_res   , Incoherently averaged variance
-   ZR_ph_res    , Incoherently averaged phase
-   grass_ZR_sq  , Mean of noise floor squared
-   ZR_pow_corr  , Power corrected for noise floor
-   grass_ZR     , Mean of noise floor
-   ZR_amp_corr  , Amplitude corrected for noise floor
-   G_ZR         , Copol Gain of antenna
-   X_ZR         , Xpol Gain of antenna
-   ZR_amp_cal   , Amplitude corrected for antenna pattern
-   ZR_pow_cal   , Power corrected for antenna pattern
-   NL_pow_cal_xp, Power corrected for antenna gain + xpol contribution
-   ZR_pow_coh   , Coherent contribution of the power
-   NL_pow_coh_xp, Coherent contribution of the power corrected for xpol
-   Gamma_L      , Reflection coeff : Ratio of reflected over direct
-   Gamma_LR     , Polarimetric ratio: Ratio of LHCP over RHCP
-   Gamma_L_xp   , Reflection coeff : Ratio of reflected over direct (xpol)
-   Gamma_LR_xp  , Polarimetric ratio: Ratio of LHCP over RHCP (xpol)
-
-
-Issues / recommendations
-------------------------
-
+.. raw:: latex
+
+    \clearpage
+
 .. _PRO_L1a_L1b:
  
 *********************
@@ -14,11 +14,17 @@ geom.py
  
 Geometry related functions
  
+.. automodule:: pyGLORI.common.glori_geom
+   :members:
+
  
 glori_antennas.py
 =================
  
-antenna related functions
+Antennas related functions
+
+.. automodule:: pyGLORI.common.glori_antennas
+   :members:
  
  
 glori_common.py
@@ -26,6 +32,9 @@ glori_common.py
  
 general purpose functions (related with time manipulation among others)
  
+.. automodule:: pyGLORI.common.glori_common
+   :members:
+
  
 glori_io.py
 ===========
@@ -33,8 +42,6 @@ glori_io.py
 I/O related routines, linked to netCDF, HDF and Pickle specific formats for
 L0, L1a and L1b
  
+.. automodule:: pyGLORI.common.glori_io
+   :members:
  
-local_angle.py
-==============
-
-Functions related to calculation of angle differences and rotations.
@@ -13,7 +13,8 @@ GLORI Processing Chain
    PRO_common
    PRO_ancillary
    PRO_rawtoL0
-   PRO_L0toL1a
+   PRO_L0toL0b
+   PRO_L0btoL1a
    PRO_L1atoL1b
    PRO_plot
    PRO_ToDo
 \ No newline at end of file
@@ -83,6 +83,11 @@ Linux packages install
 - hdf5-devel
 - netcdf-devel
  
+for documentation
+
+- texlive
+- texlive-collections-latexextra
+
 All these packages can be installed at once with the following commands::
  
   sudo dnf install gcc-gfortran blas-devel lapack-devel atlas-devel
@@ -95,9 +100,11 @@ Python module installation
 ..........................
  
 - h5py, netCDF4
-- pandas
-- geopandas
+- pandas, geopandas
 - fiona, shapely, pyproj, transforms3d
+- SRTM.py, requests
+- PyUblox (in process folder), pynmea2
+- simplekml
  
 Python module installation with anaconda
 ----------------------------------------
@@ -39,7 +39,10 @@ The Processing chain is based in the following subsystems
 - :ref:`PRO_raw_L0`: Reads, converts and processes Raw ADC data
   to provide uncalibrated waveforms.
  
-- :ref:`PRO_L0_L1a`: Integrates L0 data to reduce noise, add ancillary
+- :ref:`PRO_L0_L0b`: Time tag the files with GPS time read from the data.
+  Extract waveform maximums.
+
+- :ref:`PRO_L0b_L1a`: Integrates L0 data to reduce noise, add ancillary
   information to the file. Check and interpolate time information.
  
 - :ref:`PRO_L1a_L1b`: calibrates L1A signal for attitude,
@@ -4,9 +4,6 @@
 Raw to Level 0
 *********************
  
-raw_to_l0.py
-============
-
 Module description
 ------------------
 This module performs the basic observable computation (correlation waveforms)
@@ -48,17 +45,16 @@ Outputs
 Issues / recommendations
 ------------------------
  
-cStarlight.py
-=============
  
-Module description
-------------------
+Functions and routines
+----------------------
  
-Inputs
-------
+.. automodule:: pyGLORI.process.raw_to_l0
+   :members:
  
-Outputs
--------
  
-Issues / recommendations
-------------------------
+Functions and routines
+----------------------
+
+.. automodule:: pyGLORI.process.cstarlight
+   :members:
 \ No newline at end of file
@@ -18,7 +18,7 @@ import os
 # If extensions (or modules to document with autodoc) are in another directory,
 # add these directories to sys.path here. If the directory is relative to the
 # documentation root, use os.path.abspath to make it absolute, like shown here.
-#sys.path.insert(0, os.path.abspath('.'))
+sys.path.insert(0, os.path.abspath('../../processing/python_code/'))
  
 # -- General configuration ------------------------------------------------
  
@@ -36,6 +36,7 @@ extensions = [
     'sphinx.ext.coverage',
     'sphinx.ext.mathjax',
     'sphinx.ext.ifconfig',
+	'sphinx.ext.napoleon',
     # 'rst2pdf.pdfbuilder',
 ]
  
@@ -215,7 +216,7 @@ htmlhelp_basename = &#39;GLORI_docdoc&#39;
  
 latex_elements = {
 # The paper size ('letterpaper' or 'a4paper').
-#'papersize': 'letterpaper',
+'papersize': 'a4paper',
  
 # The font size ('10pt', '11pt' or '12pt').
 #'pointsize': '10pt',
@@ -10,6 +10,7 @@ Contents:
  
 .. toctree::
    :maxdepth: 2
+   :numbered:
  
    intro
    blocks
...	...	@@ -0,0 +1,165 @@
	1	+.. raw:: latex
	2	+
	3	+ \clearpage
	4	+
	5	+.. _PRO_L0b_L1a:
	6	+
	7	+*********************
	8	+Level 0b to Level 1a
	9	+*********************
	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	+.. automodule:: pyGLORI.process.l0b_to_l1a
	165	+ :members:
...	...
...	...	@@ -0,0 +1,82 @@
	1	+.. raw:: latex
	2	+
	3	+ \clearpage
	4	+
	5	+.. _PRO_L0_L0b:
	6	+
	7	+*********************
	8	+Level 0 to Level 0b
	9	+*********************
	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	+.. automodule:: pyGLORI.process.l0_to_l0b
	76	+ :members:
	77	+
	78	+
	79	+
	80	+Issues / recommendations
	81	+------------------------
	82	+
...	...
...	...	@@ -1,91 +0,0 @@
1		-.. _PRO_L0_L1a:
2		-
3		-*********************
4		-Level 0 to Level 1a
5		-*********************
6		-
7		-Process_L0_to_L1A.py
8		-====================
9		-
10		-Module description
11		-------------------
12		-The goal of this module is to compute the basic observables for land applications:
13		-
14		-#. Resynchronize the data acquisitions by reading the SOW info from the navigation message
15		-#. Performs additional coherent averaging by performing phase aware integration
16		-#. Correct coherent signal according to Antenna gain pattern and measurement noise.
17		-#. Compute ICF as
18		-
19		- .. math::
20		-
21		- ICF_{corr} = \frac{G_d}{G_r} \frac{Y_{r,max}-B_r}{Y_{d,max}-B_d}
22		- e^{j(\phi_{r,max}-\phi_{d,max})}
23		-#. Performs incoherent averaging
24		-#. Compute phase variance
25		-#. Merge in one file:
26		-
27		- - The Direct RHCP signal peak correlation complex amplitude
28		- - The direct estimated Doppler
29		- - The reflected LHCP signal peak correlation complex amplitude
30		- - The reflected RHCP signal peak correlation complex amplitude
31		- - The estimated delay of the reflected LHCP signal in lags
32		- - Ancillary info from L0 files
33		- - PRN
34		- - StartSOW, ifSOWread, WN,
35		- - fs,
36		- - El, Az
37		-
38		-
39		-.. csv-table:: Processing steps
40		- :stub-columns: 1
41		- :widths: 1 10 8 6 4
42		- :header: Step, Processing, Output, Variable, format
43		-
44		- 1, Read waveforms , Raw WFs , WF_NL , 2D cpx WF
45		- 2, Additional coh. avging , Coherently avgd WFs, WF_NL_co , 2D cpx WF
46		- 3, Find coh peak , peak position , NL_loc_co , 1D int
47		- 4, Store coh peak value , peak value TS , NL_pow_co , 1D cpx
48		- 5, Compute coh noise floor, noise floor level , grass_NL_co , 1D float
49		- 6, abs and correct for NF , noise free TS , NL_pow_corr_co, 1D float
50		-
51		-Inputs
52		-------
53		-
54		-Outputs
55		--------
56		-
57		-.. csv-table:: L0 to L1a output file
58		- :stub-columns: 1
59		- :widths: 4 20
60		- :header: Field, Description
61		-
62		- DateTime , Python Datetime
63		- lat_spec , Latitude of specular point
64		- lon_spec , Longitude of specular point
65		- DEM_spec , DEM at specular point location
66		- SV_elev , Elevation at specular point
67		- SV_azimuth , Azimuth at specular point
68		- ZR_amp_res , Incoherently Averaged amplitude
69		- ZR_pow_res , Incoherently averaged power
70		- ZR_var_res , Incoherently averaged variance
71		- ZR_ph_res , Incoherently averaged phase
72		- grass_ZR_sq , Mean of noise floor squared
73		- ZR_pow_corr , Power corrected for noise floor
74		- grass_ZR , Mean of noise floor
75		- ZR_amp_corr , Amplitude corrected for noise floor
76		- G_ZR , Copol Gain of antenna
77		- X_ZR , Xpol Gain of antenna
78		- ZR_amp_cal , Amplitude corrected for antenna pattern
79		- ZR_pow_cal , Power corrected for antenna pattern
80		- NL_pow_cal_xp, Power corrected for antenna gain + xpol contribution
81		- ZR_pow_coh , Coherent contribution of the power
82		- NL_pow_coh_xp, Coherent contribution of the power corrected for xpol
83		- Gamma_L , Reflection coeff : Ratio of reflected over direct
84		- Gamma_LR , Polarimetric ratio: Ratio of LHCP over RHCP
85		- Gamma_L_xp , Reflection coeff : Ratio of reflected over direct (xpol)
86		- Gamma_LR_xp , Polarimetric ratio: Ratio of LHCP over RHCP (xpol)
87		-
88		-
89		-Issues / recommendations
90		-------------------------
91		-
	1	+.. raw:: latex
	2	+
	3	+ \clearpage
	4	+
1	5	.. _PRO_L1a_L1b:
2	6
3	7	*********************
...	...
...	...	@@ -14,11 +14,17 @@ geom.py
14	14
15	15	Geometry related functions
16	16
	17	+.. automodule:: pyGLORI.common.glori_geom
	18	+ :members:
	19	+
17	20
18	21	glori_antennas.py
19	22	=================
20	23
21		-antenna related functions
	24	+Antennas related functions
	25	+
	26	+.. automodule:: pyGLORI.common.glori_antennas
	27	+ :members:
22	28
23	29
24	30	glori_common.py
...	...	@@ -26,6 +32,9 @@ glori_common.py
26	32
27	33	general purpose functions (related with time manipulation among others)
28	34
	35	+.. automodule:: pyGLORI.common.glori_common
	36	+ :members:
	37	+
29	38
30	39	glori_io.py
31	40	===========
...	...	@@ -33,8 +42,6 @@ glori_io.py
33	42	I/O related routines, linked to netCDF, HDF and Pickle specific formats for
34	43	L0, L1a and L1b
35	44
	45	+.. automodule:: pyGLORI.common.glori_io
	46	+ :members:
36	47
37		-local_angle.py
38		-==============
39		-
40		-Functions related to calculation of angle differences and rotations.
...	...
...	...	@@ -13,7 +13,8 @@ GLORI Processing Chain
13	13	PRO_common
14	14	PRO_ancillary
15	15	PRO_rawtoL0
16		- PRO_L0toL1a
	16	+ PRO_L0toL0b
	17	+ PRO_L0btoL1a
17	18	PRO_L1atoL1b
18	19	PRO_plot
19	20	PRO_ToDo
20	21	\ No newline at end of file
...	...
...	...	@@ -83,6 +83,11 @@ Linux packages install
83	83	- hdf5-devel
84	84	- netcdf-devel
85	85
	86	+for documentation
	87	+
	88	+- texlive
	89	+- texlive-collections-latexextra
	90	+
86	91	All these packages can be installed at once with the following commands::
87	92
88	93	sudo dnf install gcc-gfortran blas-devel lapack-devel atlas-devel
...	...	@@ -95,9 +100,11 @@ Python module installation
95	100	..........................
96	101
97	102	- h5py, netCDF4
98		-- pandas
99		-- geopandas
	103	+- pandas, geopandas
100	104	- fiona, shapely, pyproj, transforms3d
	105	+- SRTM.py, requests
	106	+- PyUblox (in process folder), pynmea2
	107	+- simplekml
101	108
102	109	Python module installation with anaconda
103	110	----------------------------------------
...	...
...	...	@@ -39,7 +39,10 @@ The Processing chain is based in the following subsystems
39	39	- :ref:`PRO_raw_L0`: Reads, converts and processes Raw ADC data
40	40	to provide uncalibrated waveforms.
41	41
42		-- :ref:`PRO_L0_L1a`: Integrates L0 data to reduce noise, add ancillary
	42	+- :ref:`PRO_L0_L0b`: Time tag the files with GPS time read from the data.
	43	+ Extract waveform maximums.
	44	+
	45	+- :ref:`PRO_L0b_L1a`: Integrates L0 data to reduce noise, add ancillary
43	46	information to the file. Check and interpolate time information.
44	47
45	48	- :ref:`PRO_L1a_L1b`: calibrates L1A signal for attitude,
...	...
...	...	@@ -4,9 +4,6 @@
4	4	Raw to Level 0
5	5	*********************
6	6
7		-raw_to_l0.py
8		-============
9		-
10	7	Module description
11	8	------------------
12	9	This module performs the basic observable computation (correlation waveforms)
...	...	@@ -48,17 +45,16 @@ Outputs
48	45	Issues / recommendations
49	46	------------------------
50	47
51		-cStarlight.py
52		-=============
53	48
54		-Module description
55		-------------------
	49	+Functions and routines
	50	+----------------------
56	51
57		-Inputs
58		-------
	52	+.. automodule:: pyGLORI.process.raw_to_l0
	53	+ :members:
59	54
60		-Outputs
61		--------
62	55
63		-Issues / recommendations
64		-------------------------
	56	+Functions and routines
	57	+----------------------
	58	+
	59	+.. automodule:: pyGLORI.process.cstarlight
	60	+ :members:
65	61	\ No newline at end of file
...	...
...	...	@@ -18,7 +18,7 @@ import os
18	18	# If extensions (or modules to document with autodoc) are in another directory,
19	19	# add these directories to sys.path here. If the directory is relative to the
20	20	# documentation root, use os.path.abspath to make it absolute, like shown here.
21		-#sys.path.insert(0, os.path.abspath('.'))
	21	+sys.path.insert(0, os.path.abspath('../../processing/python_code/'))
22	22
23	23	# -- General configuration ------------------------------------------------
24	24
...	...	@@ -36,6 +36,7 @@ extensions = [
36	36	'sphinx.ext.coverage',
37	37	'sphinx.ext.mathjax',
38	38	'sphinx.ext.ifconfig',
	39	+ 'sphinx.ext.napoleon',
39	40	# 'rst2pdf.pdfbuilder',
40	41	]
41	42
...	...	@@ -215,7 +216,7 @@ htmlhelp_basename = 'GLORI_docdoc'
215	216
216	217	latex_elements = {
217	218	# The paper size ('letterpaper' or 'a4paper').
218		-#'papersize': 'letterpaper',
	219	+'papersize': 'a4paper',
219	220
220	221	# The font size ('10pt', '11pt' or '12pt').
221	222	#'pointsize': '10pt',
...	...