diff --git a/notebooks/Socet2ISIS.ipynb b/notebooks/Socet2ISIS.ipynb
index 1d7681a240afaf6e83d53f2321d4150482ce5fd5..345a9422612be775c2b2e575ef8021661f7eb666 100644
--- a/notebooks/Socet2ISIS.ipynb
+++ b/notebooks/Socet2ISIS.ipynb
@@ -16,7 +16,8 @@
"import math\n",
"import pyproj\n",
"\n",
- "# sys.path.insert(0, \"/home/tthatcher/Desktop/Projects/Plio/plio\")\n",
+ "# Path to local plio if wanted\n",
+ "sys.path.insert(0, \"/home/tthatcher/Desktop/Projects/Plio/plio\")\n",
"\n",
"from plio.examples import get_path\n",
"from plio.io.io_bae import read_gpf, read_ipf\n",
@@ -26,7 +27,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
@@ -163,12 +164,107 @@
" coord_360 = to_360(ocentric_coord)\n",
" return coord_360\n",
"\n",
- "def body_fix(record, semi_major, semi_minor):\n",
+ "def body_fix(record, semi_major, semi_minor, inverse=False):\n",
+ " \"\"\"\n",
+ " Parameters\n",
+ " ----------\n",
+ " record : ndarray\n",
+ " (n,3) where columns are x, y, height or lon, lat, alt\n",
+ " \"\"\"\n",
+ " \n",
" ecef = pyproj.Proj(proj='geocent', a=semi_major, b=semi_minor)\n",
" lla = pyproj.Proj(proj='latlon', a=semi_major, b=semi_minor)\n",
- " lon, lat, height = pyproj.transform(lla, ecef, record['long_X_East'], record['lat_Y_North'], record['ht'])\n",
- " return lon, lat, height\n",
" \n",
+ " if inverse:\n",
+ " lon, lat, height = pyproj.transform(ecef, lla, record[0], record[1], record[2])\n",
+ " return lon, lat, height\n",
+ " else:\n",
+ " y, x, z = pyproj.transform(lla, ecef, record[0], record[1], record[2])\n",
+ " return y, x, z\n",
+ "\n",
+ "def ignore_toggle(record):\n",
+ " if record['stat'] == 0:\n",
+ " return True\n",
+ " else:\n",
+ " return False\n",
+ "\n",
+ "# TODO: Does isis cnet need a convariance matrix for sigmas? Even with a static matrix of 1,1,1,1 no output\n",
+ "def compute_sigma_covariance_matrix(lat, lon, rad, latsigma, lonsigma, radsigma, semimajor_axis):\n",
+ " \n",
+ " \"\"\"\n",
+ " Given geospatial coordinates, desired accuracy sigmas, and an equitorial radius, compute a 2x3\n",
+ " sigma covariange matrix.\n",
+ " Parameters\n",
+ " ----------\n",
+ " lat : float\n",
+ " A point's latitude in degrees\n",
+ " lon : float\n",
+ " A point's longitude in degrees\n",
+ " rad : float\n",
+ " The radius (z-value) of the point in meters\n",
+ " latsigma : float\n",
+ " The desired latitude accuracy in meters (Default 10.0)\n",
+ " lonsigma : float\n",
+ " The desired longitude accuracy in meters (Default 10.0)\n",
+ " radsigma : float\n",
+ " The desired radius accuracy in meters (Defualt: 15.0)\n",
+ " semimajor_axis : float\n",
+ " The semi-major or equitorial radius in meters (Default: 1737400.0 - Moon)\n",
+ " Returns\n",
+ " -------\n",
+ " rectcov : ndarray\n",
+ " (2,3) covariance matrix\n",
+ " \"\"\"\n",
+ " \n",
+ " lat = math.radians(lat)\n",
+ " lon = math.radians(lon)\n",
+ " \n",
+ " # SetSphericalSigmasDistance\n",
+ " scaled_lat_sigma = latsigma / semimajor_axis\n",
+ "\n",
+ " # This is specific to each lon.\n",
+ " scaled_lon_sigma = lonsigma * math.cos(lat) / semimajor_axis\n",
+ " \n",
+ " # SetSphericalSigmas\n",
+ " cov = np.eye(3,3)\n",
+ " cov[0,0] = scaled_lat_sigma ** 2\n",
+ " cov[1,1] = scaled_lon_sigma ** 2\n",
+ " cov[2,2] = radsigma ** 2\n",
+ " \n",
+ " # Approximate the Jacobian\n",
+ " j = np.zeros((3,3))\n",
+ " cosphi = math.cos(lat)\n",
+ " sinphi = math.sin(lat)\n",
+ " coslambda = math.cos(lon)\n",
+ " sinlambda = math.sin(lon)\n",
+ " rcosphi = rad * cosphi\n",
+ " rsinphi = rad * sinphi\n",
+ " j[0,0] = -rsinphi * coslambda\n",
+ " j[0,1] = -rcosphi * sinlambda\n",
+ " j[0,2] = cosphi * coslambda\n",
+ " j[1,0] = -rsinphi * sinlambda\n",
+ " j[1,1] = rcosphi * coslambda\n",
+ " j[1,2] = cosphi * sinlambda\n",
+ " j[2,0] = rcosphi\n",
+ " j[2,1] = 0.\n",
+ " j[2,2] = sinphi\n",
+ " mat = j.dot(cov)\n",
+ " mat = mat.dot(j.T)\n",
+ " rectcov = np.zeros((2,3))\n",
+ " rectcov[0,0] = mat[0,0]\n",
+ " rectcov[0,1] = mat[0,1]\n",
+ " rectcov[0,2] = mat[0,2]\n",
+ " rectcov[1,0] = mat[1,1]\n",
+ " rectcov[1,1] = mat[1,2]\n",
+ " rectcov[1,2] = mat[2,2]\n",
+ " \n",
+ " return rectcov\n",
+ "# return np.array([[1.0, 1.0, 1.0], [1.0, 1.0, 1.0]])\n",
+ "\n",
+ "\n",
+ "def compute_cov_matrix(record, semimajor_axis):\n",
+ " cov_matrix = compute_sigma_covariance_matrix(record['lat_Y_North'], record['long_X_East'], record['ht'], record['sig0'], record['sig1'], record['sig2'], semimajor_axis)\n",
+ " return cov_matrix.ravel().tolist()\n",
"\n",
"# applys transformations to columns\n",
"def apply_transformations(atf_dict, df):\n",
@@ -176,12 +272,18 @@
" \n",
" eRadius, pRadius = get_axis(prj_file)\n",
" \n",
+ " lla = np.array([[df['long_X_East']], [df['lat_Y_North']], [df['ht']]])\n",
+ " \n",
+ " ecef = body_fix(lla, semi_major = eRadius, semi_minor = pRadius, inverse=False)\n",
+ " \n",
" df['s.'], df['l.'], df['image_index'] = (zip(*df.apply(line_sample_size, path = atf_dict['PATH'], axis=1)))\n",
" df['known'] = df.apply(known, axis=1)\n",
- " df['lat_Y_North'] = df.apply(lat_ISIS_coord, semi_major = eRadius, semi_minor = pRadius, axis=1)\n",
- " df['long_X_East'] = df.apply(lon_ISIS_coord, semi_major = eRadius, semi_minor = pRadius, axis=1)\n",
- " df['long_X_East'], df['lat_Y_North'], df['ht'] = zip(*df.apply(body_fix, semi_major = eRadius, semi_minor = pRadius, axis = 1))\n",
- " \n",
+ " df['long_X_East'] = ecef[0][0]\n",
+ " df['lat_Y_North'] = ecef[1][0]\n",
+ " df['ht'] = ecef[2][0] \n",
+ " df['aprioriCovar'] = df.apply(compute_cov_matrix, semimajor_axis = eRadius, axis=1)\n",
+ " df['ignore'] = df.apply(ignore_toggle, axis=1)\n",
+ " \n",
"def socet2isis(prj_file):\n",
" # Read in and setup the atf dict of information\n",
" atf_dict = read_atf(prj_file)\n",
@@ -213,9 +315,10 @@
" \n",
" # Define column remap for socet dataframe\n",
" column_remap = {'l.': 'y', 's.': 'x',\n",
- " 'res_l': 'LineResidual', 'res_s': 'SampleResidual', 'known': 'Type',\n",
+ " 'res_l': 'lineResidual', 'res_s': 'sampleResidual', 'known': 'Type',\n",
" 'lat_Y_North': 'AprioriY', 'long_X_East': 'AprioriX', 'ht': 'AprioriZ',\n",
- " 'sig0': 'AprioriLatitudeSigma', 'sig1': 'AprioriLongitudeSigma', 'sig2': 'AprioriRadiusSigma'}\n",
+ " 'sig0': 'AprioriLatitudeSigma', 'sig1': 'AprioriLongitudeSigma', 'sig2': 'AprioriRadiusSigma',\n",
+ " 'sig_l': 'linesigma', 'sig_s': 'samplesigma'}\n",
" \n",
" # Rename the columns using the column remap above\n",
" socet_df.rename(columns = column_remap, inplace=True)\n",
@@ -231,42 +334,37 @@
" snum = sn.generate_serial_number(os.path.join(path, image + extension))\n",
" snum = snum.replace('Mars_Reconnaissance_Orbiter', 'MRO')\n",
" serial_dict[image] = snum\n",
- " return serial_dict"
+ " return serial_dict\n",
+ "\n"
]
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 6,
"metadata": {
- "scrolled": false
+ "scrolled": true
},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/Users/adampaquette/anaconda/envs/pysat/lib/python3.6/site-packages/ipykernel_launcher.py:173: UserWarning: The following points found in ipf files missing from gpf file: \n",
- "\n",
- "['P03_002226_1895_XI_09N203W_15', 'P03_002226_1895_XI_09N203W_16', 'P03_002226_1895_XI_09N203W_17', 'P03_002226_1895_XI_09N203W_18', 'P03_002226_1895_XI_09N203W_19', 'P03_002226_1895_XI_09N203W_20', 'P03_002226_1895_XI_09N203W_21', 'P03_002226_1895_XI_09N203W_22', 'P03_002226_1895_XI_09N203W_24', 'P03_002226_1895_XI_09N203W_26', 'P03_002226_1895_XI_09N203W_30', 'P03_002226_1895_XI_09N203W_31', 'P03_002226_1895_XI_09N203W_32', 'P03_002226_1895_XI_09N203W_34', 'P03_002226_1895_XI_09N203W_36', 'P03_002226_1895_XI_09N203W_37', 'P03_002226_1895_XI_09N203W_44', 'P03_002226_1895_XI_09N203W_48', 'P03_002226_1895_XI_09N203W_49', 'P03_002226_1895_XI_09N203W_56', 'P03_002226_1895_XI_09N203W_57', 'P03_002226_1895_XI_09N203W_61', 'P03_002226_1895_XI_09N203W_62', 'P03_002226_1895_XI_09N203W_63', 'P03_002226_1895_XI_09N203W_65', 'P19_008344_1894_XN_09N203W_4', 'P20_008845_1894_XN_09N203W_15']. \n",
- "\n",
- "Continuing, but these points will be missing from the control network\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
+ "# path = '/home/tthatcher/Desktop/Projects/plio_imgs/quest_imgs/'\n",
+ "# extension = '.lev1.cub'\n",
+ "# atf_file = ('/home/tthatcher/Desktop/Projects/plio_imgs/quest_imgs/CTX_Athabasca_Middle_step0.atf')\n",
+ "\n",
"# Setup stuffs for the cub information namely the path and extension\n",
- "path = '/Volumes/Blueman/'\n",
- "extension = '.lev1.cub'\n",
- "prj_file = get_path('CTX_Athabasca_Middle_step0.atf')\n",
+ "path = '/home/tthatcher/Desktop/Projects/plio_imgs/correct_imgs/'\n",
+ "extension = '.8bit.cub'\n",
+ "atf_file = ('/where/y')\n",
"\n",
- "socet_df = socet2isis(prj_file)\n",
+ "socet_df = socet2isis(atf_file)\n",
"\n",
"images = pd.unique(socet_df['ipf_file'])\n",
"\n",
"serial_dict = serial_numbers(images, path, extension)\n",
"\n",
"# creates the control network\n",
- "cn.to_isis('/Volumes/Blueman/cn.net', socet_df, serial_dict)"
+ "cn.to_isis('/path/you/want/the/cnet/to/be/in/cn.net', socet_df, serial_dict)\n",
+ "\n",
+ "# cn.to_isis('/home/tthatcher/Desktop/Projects/plio_imgs/quest_imgs/cn.net', socet_df, serial_dict)"
]
},
{
@@ -293,7 +391,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.3"
+ "version": "3.6.4"
}
},
"nbformat": 4,