Updated docs and docstrings

Author: kanhereashwin

docs/source/tutorials/tutorials.rst

@@ -11,14 +11,14 @@ The tutorials below show you how to interact with our standard
 :code:`NavData` class and how to run standard baselines all with only a
 few lines of code.
 
-NavData Tutorials
+NavData Tutorial
 ---------------------
 
-This tutorial shows how to interact with our standard :code:`NavData`
+Sections of this tutorial shows how to interact with our standard :code:`NavData`
 class.
 
 .. toctree::
-   :maxdepth: 1
+   :maxdepth: 2
 
    tutorials_navdata_notebook
 

gnss_lib_py/algorithms/fde.py

@@ -11,6 +11,7 @@
 from gnss_lib_py.algorithms.residuals import solve_residuals
 from gnss_lib_py.algorithms.snapshot import solve_wls
 
+
 def solve_fde(navdata, method="residual", remove_outliers=False,
               max_faults=None, threshold=None, verbose=False,
               **kwargs):
@@ -30,8 +31,9 @@ def solve_fde(navdata, method="residual", remove_outliers=False,
         Method for fault detection and exclusion either "residual" for
         residual-based or "edm" for Euclidean Distance Matrix-based.
     remove_outliers : bool
-        If true, will remove detected faults from the returned NavData
-        instance and unknown timesteps (both 1 and 2 fault status).
+        If `True`, removes measurements with detected faults (fault status 1)
+        and measurements with unknown fault status (fault status 2)
+        from the returned NavData instance.
         If false, will detect but not exclude faults or unknowns.
     max_faults : int
         Maximum number of faults to detect and/or exclude.
@@ -44,9 +46,9 @@ def solve_fde(navdata, method="residual", remove_outliers=False,
     -------
     navdata : gnss_lib_py.parsers.navdata.NavData
         Result includes a new row of ``fault_<method>`` where a
-        value of 1 indicates a detected fault and 0 indicates that
+        value of 1 indicates a detected fault, 0 indicates that
         no fault was detected, and 2 indicates an unknown fault status
-        usually due to lack of necessary columns or information.
+        which is usually due to lack of necessary columns or information.
 
     """
 
@@ -66,6 +68,7 @@ def solve_fde(navdata, method="residual", remove_outliers=False,
 
     return navdata
 
+
 def fde_edm(navdata, max_faults=None, threshold=1.0, time_fde=False,
             verbose=False):
     """Euclidean distance matrix-based fault detection and exclusion.
@@ -249,6 +252,7 @@ def fde_edm(navdata, max_faults=None, threshold=1.0, time_fde=False,
         return navdata, timing_info
     return navdata
 
+
 def fde_greedy_residual(navdata, max_faults, threshold, time_fde=False,
                         verbose=False):
     """Residual-based fault detection and exclusion.
@@ -331,11 +335,12 @@ def fde_greedy_residual(navdata, max_faults, threshold, time_fde=False,
             chi_square = _residual_chi_square(navdata_subset, receiver_state)
 
             if verbose:
-                print("residual test statistic:",chi_square)
+                print("chi squared residual test statistic:",chi_square)
 
             # greedy removal if chi_square above detection threshold
             while chi_square > threshold:
-
+            # stop removing indexes either b/c you need at least four
+            # satellites or if maximum number of faults has been reached
                 if len(navdata_subset) < 5 or (max_faults is not None \
                                            and len(fault_idxs) >= max_faults):
                     break
@@ -353,7 +358,7 @@ def fde_greedy_residual(navdata, max_faults, threshold, time_fde=False,
                 chi_square = _residual_chi_square(navdata_subset, receiver_state)
 
                 if verbose:
-                    print("chi square:",chi_square,"after removing index:",fault_idxs)
+                    print("chi squared:",chi_square,"after removing index:",fault_idxs)
 
         fault_residual_subset = np.array([0] * subset_length)
         fault_residual_subset[fault_idxs] = 1
@@ -376,6 +381,7 @@ def fde_greedy_residual(navdata, max_faults, threshold, time_fde=False,
         return navdata, timing_info
     return navdata
 
+
 def evaluate_fde(navdata, method, fault_truth_row="fault_gt",
                  time_fde=False, verbose=False,
                  **kwargs):
@@ -418,8 +424,7 @@ def evaluate_fde(navdata, method, fault_truth_row="fault_gt",
         by the fault the ``fault_truth_row`` variable.
     method : string
         Method for fault detection and exclusion either "residual" for
-        residual-based, "ss" for solution separation or "edm" for
-        Euclidean Distance Matrix-based.
+        residual-based or "edm" for Euclidean Distance Matrix-based.
     fault_truth_row : string
         Row that indicates the ground truth for the fault status. This
         row is used to provide results on how well each method performs
@@ -570,6 +575,7 @@ def evaluate_fde(navdata, method, fault_truth_row="fault_gt",
 
     return metrics, navdata
 
+
 def _edm(points):
     """Creates a Euclidean distance matrix (EDM) from point locations.
 
@@ -601,6 +607,7 @@ def _edm(points):
         - 2.*gram + np.ones((dims,1)).dot(np.diag(gram).reshape(1,-1))
     return edm
 
+
 def _edm_from_satellites_ranges(sv_pos, ranges):
     """Creates a Euclidean distance matrix (EDM) from points and ranges.
 
@@ -640,6 +647,7 @@ def _edm_from_satellites_ranges(sv_pos, ranges):
 
     return edm
 
+
 def _edm_detection_statistic(edm):
     """Calculate the EDM FDE detection statistic [5]_.
 
@@ -685,6 +693,7 @@ def _edm_detection_statistic(edm):
 
     return detection_statistic, svd_u, svd_s, svd_v
 
+
 def _residual_chi_square(navdata, receiver_state):
     """Chi square test for residuals.
 
@@ -732,6 +741,7 @@ def _residual_chi_square(navdata, receiver_state):
 
     return chi_square
 
+
 def _residual_exclude(navdata, receiver_state):
     """Detection statistic for Residual-based fault detection.
 

notebooks/tutorials/fde.ipynb

@@ -23,6 +23,24 @@
     "navdata = glp.AndroidDerived2022(\"device_gnss.csv\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "e0888750",
+   "metadata": {},
+   "source": [
+    "For this demonstration, we limit ourselves to the first time instance. This better shows when more faults are detected and how changing different hyperparameters changes each method's behaviour."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "32531cac",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "navdata = navdata.where('gps_millis', navdata['gps_millis', 0], 'eq')"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "76ee7e5e",
@@ -88,7 +106,7 @@
    "id": "9805d5a9-5138-4588-a0af-3e5649ecef36",
    "metadata": {},
    "source": [
-    "You can channge the ``threshold`` variable to be more or less sensitive based on false alarm or missed detection system requirements. Greedy EDM FDE has a range for the threshold between 0 and 1 since the detection statistic is normalized to 1. Note that if the threshold is set to the lower limit of zero, faults are detected until only four measurements remain at each timestep."
+    "You can change the ``threshold`` variable to be more or less sensitive based on false alarm or missed detection system requirements. Greedy EDM FDE has a range for the threshold between 0 and 1 since the detection statistic is normalized to 1. Note that if the threshold is set to the lower limit of zero, faults are detected until only four measurements remain at each timestep."
    ]
   },
   {
@@ -156,9 +174,15 @@
    "id": "85df2e4f-0298-4cf6-8184-9cc13361bdfc",
    "metadata": {},
    "source": [
-    "This FDE method is based on \"Fast multiple fault exclusion with a large number of measurements.\" by Juan, Blanch, Todd Walter, and Per Enge from the ION GNSS+ 2015 conference."
+    "This FDE method is based on \"Fast multiple fault exclusion with a large number of measurements.\" by Juan Blanch, Todd Walter, and Per Enge from the ION GNSS+ 2015 conference."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "637b591a",
+   "metadata": {},
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -236,7 +260,7 @@
    "id": "cb756cd0-9382-4991-9ed0-3b41b7482841",
    "metadata": {},
    "source": [
-    "Checkout the timing difference between the too methods!"
+    "You can also compare the two methods based on the time they take."
    ]
   },
   {

notebooks/tutorials/navdata.ipynb

@@ -1,5 +1,13 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This tutorial shows how to use the `NavData` class, including how to initialize\n",
+    "instances and perform basic operations."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -27,7 +35,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Initializing"
+    "# NavData"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Initializing"
    ]
   },
   {
@@ -104,7 +119,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Accessing values"
+    "## Accessing values"
    ]
   },
   {
@@ -221,7 +236,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Setting values"
+    "## Setting values"
    ]
   },
   {
@@ -262,7 +277,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Setting new row"
+    "## Setting new row"
    ]
   },
   {
@@ -306,7 +321,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Adding new columns"
+    "## Adding new columns"
    ]
   },
   {
@@ -348,7 +363,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Find rows, shape and length"
+    "## Find rows, shape and length"
    ]
   },
   {
@@ -390,7 +405,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Removing rows or columns"
+    "## Removing rows or columns"
    ]
   },
   {
@@ -425,7 +440,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Copy"
+    "## Copy"
    ]
   },
   {
@@ -474,7 +489,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Convert to `pd.DataFrame` and save to csv"
+    "## Convert to `pd.DataFrame` and save to csv"
    ]
   },
   {
@@ -497,7 +512,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Looping"
+    "## Looping"
    ]
   },
   {