diff --git a/notebooks/Socet2ISIS.ipynb b/notebooks/Socet2ISIS.ipynb
index f9ff8e2dd784c0c36eca6a96d8133d847e531657..a0e578889f8f89a93fed0d8d1f25978b9cc08d4c 100644
--- a/notebooks/Socet2ISIS.ipynb
+++ b/notebooks/Socet2ISIS.ipynb
@@ -16,10 +16,9 @@
"import math\n",
"import pyproj\n",
"\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",
+ "from collections import defaultdict\n",
"import plio.io.io_controlnetwork as cn\n",
"import plio.io.isis_serial_number as sn"
]
@@ -35,45 +34,50 @@
"# .apf file (should be the same as all others) \n",
"def read_atf(atf_file):\n",
" with open(atf_file) as f:\n",
- "\n",
- " files = []\n",
- " ipf = []\n",
- " sup = []\n",
- " files_dict = []\n",
" \n",
- " # Grabs every PRJ, GPF, SUP, and IPF image from the ATF file\n",
+ " # Extensions of files we want\n",
+ " files_ext = ['.prj', '.sup', '.ipf', '.gpf']\n",
+ " files_dict = []\n",
+ " files = defaultdict(list)\n",
+ "\n",
" for line in f:\n",
- " if line[-4:-1] == 'prj' or line[-4:-1] == 'gpf' or line[-4:-1] == 'sup' or line[-4:-1] == 'ipf' or line[-4:-1] == 'atf':\n",
- " files.append(line)\n",
+ " ext = os.path.splitext(line)[-1].strip()\n",
+ " \n",
+ " # Check is needed for split as all do not have a space\n",
+ " if ext in files_ext:\n",
+ " \n",
+ " # If it is the .prj file, it strips the directory away and grabs file name\n",
+ " if ext == '.prj':\n",
+ " files[ext].append(line.strip().split(' ')[1].split('\\\\')[-1])\n",
+ " \n",
+ " # If the ext is in the list of files we care about, it addes to the dict\n",
+ " files[ext].append(line.strip().split(' ')[-1])\n",
+ " \n",
+ " else:\n",
+ " \n",
+ " # Adds to the dict even if not in files we care about\n",
+ " files[ext.strip()].append(line)\n",
" \n",
- " files = np.array(files)\n",
+ " # Gets the base filepath\n",
+ " files['basepath'] = os.path.dirname(os.path.abspath(atf_file))\n",
" \n",
- " # Creates appropriate arrays for certain files in the right format\n",
- " for file in files:\n",
- " file = file.strip()\n",
- " file = file.split(' ')\n",
- "\n",
- " # Grabs all the IPF files\n",
- " if file[1].endswith('.ipf'):\n",
- " ipf.append(file[1])\n",
- "\n",
- " # Grabs all the SUP files\n",
- " if file[1].endswith('.sup'):\n",
- " sup.append(file[1])\n",
- "\n",
- " files_dict.append(file)\n",
- "\n",
" # Creates a dict out of file lists for GPF, PRJ, IPF, and ATF\n",
" files_dict = (dict(files_dict))\n",
" \n",
" # Sets the value of IMAGE_IPF to all IPF images\n",
- " files_dict['IMAGE_IPF'] = ipf\n",
+ " files_dict['IMAGE_IPF'] = files['.ipf']\n",
" \n",
" # Sets the value of IMAGE_SUP to all SUP images\n",
- " files_dict['IMAGE_SUP'] = sup\n",
+ " files_dict['IMAGE_SUP'] = files['.sup']\n",
+ " \n",
+ " # Sets value for GPF file\n",
+ " files_dict['GP_FILE'] = files['.gpf'][0]\n",
+ " \n",
+ " # Sets value for PRJ file\n",
+ " files_dict['PROJECT'] = files['.prj'][0]\n",
" \n",
" # Sets the value of PATH to the path of the ATF file\n",
- " files_dict['PATH'] = os.path.dirname(os.path.abspath(atf_file))\n",
+ " files_dict['PATH'] = files['basepath']\n",
" \n",
" return files_dict\n",
"\n",
@@ -163,25 +167,126 @@
" 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 \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",
- " prj_file = os.path.join(atf_dict['PATH'], atf_dict['PROJECT'].split('\\\\')[-1])\n",
+ " prj_file = os.path.join(atf_dict['PATH'], atf_dict['PROJECT'])\n",
" \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 +318,10 @@
" \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",
@@ -224,44 +330,42 @@
" return socet_df\n",
"\n",
"# creates a dict of serial numbers with the cub being the key\n",
- "def serial_numbers(image_dict, path):\n",
+ "def serial_numbers(images, path, extension):\n",
" serial_dict = dict()\n",
- "\n",
- " for key in image_dict:\n",
- " snum = sn.generate_serial_number(os.path.join(path, image_dict[key]))\n",
+ " \n",
+ " for image in images:\n",
+ " snum = sn.generate_serial_number(os.path.join(path, image + extension))\n",
" snum = snum.replace('Mars_Reconnaissance_Orbiter', 'MRO')\n",
- " serial_dict[key] = snum\n",
- " return serial_dict"
+ " serial_dict[image] = snum\n",
+ " return serial_dict\n",
+ "\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
- "scrolled": false
+ "scrolled": true
},
"outputs": [],
"source": [
"# Setup stuffs for the cub information namely the path and extension\n",
- "path = '/Volumes/Blueman/'\n",
- "atf_file = get_path('CTX_Athabasca_Middle_step0.atf')\n",
+ "path = '/path/where/cub/files/are/'\n",
+ "\n",
+ "# Extension of your cub files\n",
+ "extension = '.something.cub'\n",
"\n",
- "image_dict = {'P01_001540_1889_XI_08N204W' : 'P01_001540_1889_XI_08N204W.lev1.cub',\n",
- " 'P01_001606_1897_XI_09N203W' : 'P01_001606_1897_XI_09N203W.lev1.cub',\n",
- " 'P02_001804_1889_XI_08N204W' : 'P02_001804_1889_XI_08N204W.lev1.cub',\n",
- " 'P03_002226_1895_XI_09N203W' : 'P03_002226_1895_XI_09N203W.lev1.cub',\n",
- " 'P03_002371_1888_XI_08N204W' : 'P03_002371_1888_XI_08N204W.lev1.cub',\n",
- " 'P19_008344_1894_XN_09N203W' : 'P19_008344_1894_XN_09N203W.lev1.cub',\n",
- " 'P20_008845_1894_XN_09N203W' : 'P20_008845_1894_XN_09N203W.lev1.cub'}\n",
+ "# Path to atf file\n",
+ "atf_file = ('/path/to/atf/file')\n",
"\n",
"socet_df = socet2isis(atf_file)\n",
"\n",
"images = pd.unique(socet_df['ipf_file'])\n",
"\n",
- "serial_dict = serial_numbers(image_dict, path)\n",
+ "serial_dict = serial_numbers(images, path, extension)\n",
"\n",
"# creates the control network\n",
- "cn.to_isis('/Volumes/Blueman/banana.net', socet_df, serial_dict)"
+ "cn.to_isis('/path/you/want/the/cnet/to/be/in/cn.net', socet_df, serial_dict)"
]
},
{
@@ -288,7 +392,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.3"
+ "version": "3.6.4"
}
},
"nbformat": 4,
diff --git a/plio/io/io_controlnetwork.py b/plio/io/io_controlnetwork.py
index 87b877a604648018d03daedd4f8695890c28ea40..a52d58097723627958bf7bbc54c847e57c8f60e0 100644
--- a/plio/io/io_controlnetwork.py
+++ b/plio/io/io_controlnetwork.py
@@ -1,6 +1,7 @@
from time import gmtime, strftime
import pandas as pd
+import numpy as np
import pvl
from plio.io import ControlNetFileV0002_pb2 as cnf
@@ -189,19 +190,19 @@ class IsisStore(object):
if version == 2:
point_attrs = [i for i in cnf._CONTROLPOINTFILEENTRYV0002.fields_by_name if i != 'measures']
measure_attrs = [i for i in cnf._CONTROLPOINTFILEENTRYV0002_MEASURE.fields_by_name]
-
+
cols = point_attrs + measure_attrs
cp = cnf.ControlPointFileEntryV0002()
self._handle.seek(header_start_byte)
pbuf_header = cnf.ControlNetFileHeaderV0002()
pbuf_header.ParseFromString(self._handle.read(header_bytes))
-
+
self._handle.seek(point_start_byte)
cp = cnf.ControlPointFileEntryV0002()
pts = []
for s in pbuf_header.pointMessageSizes:
- cp.ParseFromString(self._handle.read(s))
+ cp.ParseFromString(self._handle.read(s))
pt = [getattr(cp, i) for i in point_attrs if i != 'measures']
for measure in cp.measures:
@@ -267,24 +268,24 @@ class IsisStore(object):
# As per protobuf docs for assigning to a repeated field.
if attr == 'aprioriCovar':
arr = g.iloc[0]['aprioriCovar']
- point_spec.aprioriCovar.extend(arr.ravel().tolist())
+ if isinstance(arr, np.ndarray):
+ arr = arr.ravel().tolist()
+
+ point_spec.aprioriCovar.extend(arr)
else:
setattr(point_spec, attr, attrtype(g.iloc[0][attr]))
- point_spec.type = 2 # Hardcoded to free
+ point_spec.type = 2 # Hardcoded to free this is bad
# The reference index should always be the image with the lowest index
point_spec.referenceIndex = 0
-
# A single extend call is cheaper than many add calls to pack points
measure_iterable = []
-
for node_id, m in g.iterrows():
measure_spec = point_spec.Measure()
# For all of the attributes, set if they are an dict accessible attr of the obj.
for attr, attrtype in self.measure_attrs:
if attr in g.columns:
setattr(measure_spec, attr, attrtype(m[attr]))
-
measure_spec.serialnumber = serials[m.image_index]
measure_spec.sample = m.x
measure_spec.line = m.y
@@ -298,7 +299,6 @@ class IsisStore(object):
point_message = point_spec.SerializeToString()
point_sizes.append(point_spec.ByteSize())
point_messages.append(point_message)
-
return point_messages, point_sizes
def create_buffer_header(self, networkid, targetname,