{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import sys\n",
"from functools import singledispatch\n",
"import warnings\n",
"\n",
"import pandas as pd\n",
"import numpy as np\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"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Reads a .atf file and outputs all of the \n",
"# .ipf, .gpf, .sup, .prj, and path to locate the \n",
"# .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",
" 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",
" \n",
" files = np.array(files)\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",
" \n",
" # Sets the value of IMAGE_SUP to all SUP images\n",
" files_dict['IMAGE_SUP'] = sup\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",
" \n",
" return files_dict"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"atf_dict = read_atf(get_path('CTX_Athabasca_Middle_step0.atf'))\n",
"\n",
"gpf_file = os.path.join(atf_dict['PATH'], atf_dict['GP_FILE']);\n",
"ipf_list = [os.path.join(atf_dict['PATH'], i) for i in atf_dict['IMAGE_IPF']]\n",
"\n",
"gpf_df = read_gpf(gpf_file)\n",
"ipf_df = read_ipf(ipf_list)\n",
"\n",
"point_diff = ipf_df.index.difference(gpf_df.index)\n",
"\n",
"\n",
"\n",
"if len(point_diff) != 0:\n",
" warnings.warn(\"The following points found in ipf files missing from gpf file: \\n\\n{}. \\\n",
" \\n\\nContinuing, but these points will be missing from the control network\".format(list(point_diff)))\n",
"\n",
"new_df = ipf_df.merge(gpf_df, left_on='pt_id', right_on='point_id')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import math\n",
"import pyproj\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",
"\n",
"# converts columns l. and s. to isis\n",
"def line_sample_size(record):\n",
" with open(atf_dict['PATH'] + '/' + record['ipf_file'] + '.sup') as f:\n",
" for i, line in enumerate(f):\n",
" if i == 2:\n",
" img_index = line.split('\\\\')\n",
" img_index = img_index[-1].strip()\n",
" img_index = img_index.split('.')[0]\n",
" img_index = image_dict[img_index]\n",
" \n",
" if i == 3:\n",
" line_size = line.split(' ')\n",
" line_size = line_size[-1].strip()\n",
" assert int(line_size) > 0, \"Line number {} from {} is a negative number: Invalid Data\".format(line_size, record['ipf_file'])\n",
" \n",
" if i == 4:\n",
" sample_size = line.split(' ')\n",
" sample_size = sample_size[-1].strip()\n",
" assert int(sample_size) > 0, \"Sample number {} from {} is a negative number: Invalid Data\".format(sample_size, record['ipf_file'])\n",
" break\n",
" \n",
" \n",
" line_size = int(line_size)/2.0 + record['l.'] + 1\n",
" sample_size = int(sample_size)/2.0 + record['s.'] + 1\n",
" return sample_size, line_size, img_index\n",
" \n",
"# converts known to ISIS keywords\n",
"def known(record):\n",
" if record['known'] == 0:\n",
" return 'Free'\n",
" \n",
" elif record['known'] == 1 or record['known'] == 2 or record['known'] == 3:\n",
" return 'Constrained'\n",
" \n",
"# converts +/- 180 system to 0 - 360 system\n",
"def to_360(num):\n",
" return num % 360\n",
"\n",
"# ocentric to ographic latitudes\n",
"def oc2og(dlat, dMajorRadius, dMinorRadius):\n",
" try: \n",
" dlat = math.radians(dlat)\n",
" dlat = math.atan(((dMajorRadius / dMinorRadius)**2) * (math.tan(dlat)))\n",
" dlat = math.degrees(dlat)\n",
" except:\n",
" print (\"Error in oc2og conversion\")\n",
" return dlat\n",
"\n",
"# ographic to ocentric latitudes\n",
"def og2oc(dlat, dMajorRadius, dMinorRadius):\n",
" try:\n",
" dlat = math.radians(dlat)\n",
" dlat = math.atan((math.tan(dlat) / ((dMajorRadius / dMinorRadius)**2)))\n",
" dlat = math.degrees(dlat)\n",
" except:\n",
" print (\"Error in og2oc conversion\")\n",
" return dlat\n",
"\n",
"# gets eRadius and pRadius from a .prj file\n",
"def get_axis(file):\n",
" with open(atf_dict['PATH'] + '/' + file) as f:\n",
" from collections import defaultdict\n",
"\n",
" files = defaultdict(list)\n",
" \n",
" for line in f:\n",
" \n",
" ext = line.strip().split(' ')\n",
" files[ext[0]].append(ext[-1])\n",
" \n",
" eRadius = float(files['A_EARTH'][0])\n",
" pRadius = eRadius * (1 - float(files['E_EARTH'][0]))\n",
" \n",
" return eRadius, pRadius\n",
" \n",
"# function to convert lat_Y_North to ISIS_lat\n",
"def lat_ISIS_coord(record, semi_major, semi_minor):\n",
" ocentric_coord = og2oc(record['lat_Y_North'], semi_major, semi_minor)\n",
" coord_360 = to_360(ocentric_coord)\n",
" return coord_360\n",
"\n",
"# function to convert long_X_East to ISIS_lon\n",
"def lon_ISIS_coord(record, semi_major, semi_minor):\n",
" ocentric_coord = og2oc(record['long_X_East'], semi_major, semi_minor)\n",
" coord_360 = to_360(ocentric_coord)\n",
" return coord_360\n",
"\n",
"def body_fix(record, semi_major, semi_minor):\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",
"# applys transformations to columns\n",
"def socet2isis(prj_file):\n",
" eRadius, pRadius = get_axis(prj_file)\n",
" new_df['s.'], new_df['l.'], new_df['image_index'] = (zip(*new_df.apply(line_sample_size, axis=1)))\n",
" new_df['known'] = new_df.apply(known, axis=1)\n",
" new_df['lat_Y_North'] = new_df.apply(lat_ISIS_coord, semi_major = eRadius, semi_minor = pRadius, axis=1)\n",
" new_df['long_X_East'] = new_df.apply(lon_ISIS_coord, semi_major = eRadius, semi_minor = pRadius, axis=1)\n",
" new_df['long_X_East'], new_df['lat_Y_North'], new_df['ht'] = zip(*new_df.apply(body_fix, semi_major = eRadius, semi_minor = pRadius, axis = 1))\n",
"socet2isis('CTX_Athabasca_Middle.prj')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"new_df['image_index']"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"column_remap = {'l.': 'x', 's.': 'y',\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",
"\n",
"new_df.rename(columns=column_remap, inplace=True)\n",
"\n",
"new_df"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import plio.io.io_controlnetwork as cn\n",
"import plio.io.isis_serial_number as sn\n",
"\n",
"# creates a dict of serial numbers with the cub being the key\n",
"def serial_numbers():\n",
" serial_dict = {}\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",
" \n",
" for key in image_dict:\n",
" serial_dict[image_dict[key]] = sn.generate_serial_number('/home/tthatcher/Desktop/Projects/Plio/' + image_dict[key])\n",
" return serial_dict\n",
"\n",
"# serial number dictionary\n",
"serial_dict = serial_numbers()\n",
"\n",
"print(serial_dict)\n",
"\n",
"# creates the control network\n",
"cnet = cn.to_isis('/home/tthatcher/Desktop/Projects/Plio/cn.csv', new_df, serial_dict)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"@singledispatch\n",
"def read_ipf(arg):\n",
" return str(arg)\n",
"# new_df['known'] = new_df.apply(known, axis=1)\n",
"\n",
"@read_ipf.register(str)\n",
"def read_ipf_str(input_data):\n",
" \"\"\"AttributeError: 'Series' object has no attribute 'image_index'\n",
"\n",
" Read a socet ipf file into a pandas data frame\n",
"\n",
" Parameters\n",
" ----------\n",
" input_data : str\n",
" path to the an input data file\n",
"\n",
" Returns\n",
" -------\n",
" df : pd.DataFrame\n",
" containing the ipf data with appropriate column names and indices\n",
" \"\"\"\n",
"\n",
" # Check that the number of rows is matching the expected number\n",
" with open(input_data, 'r') as f:\n",
" for i, l in enumerate(f):\n",
" if i == 1:/home/tthatcher/Desktop/Projects/Plio/plio\n",
" cnt = int(l)\n",
" elif i == 2:\n",
" col = l\n",
" break\n",
" \n",
" columns = np.genfromtxt(input_data, skip_header=2, dtype='unicode',\n",
" max_rows = 1, delimiter = ',')\n",
"\n",
" # TODO: Add unicode conversion\n",
" d = [line.split() for line in open(input_data, 'r')]\n",
" d = np.hstack(np.array(d[3:]))\n",
" \n",
" d = d.reshape(-1, 12)\n",
" \n",
" df = pd.DataFrame(d, columns=columns)\n",
" file = os.path.split(os.path.splitext(input_data)[0])[1]\n",
" df['ipf_file'] = pd.Series(np.full((len(df['pt_id'])), file), index = df.index)\n",
"\n",
" assert int(cnt) == len(df), 'Dataframe length {} does not match point length {}.'.format(int(cnt), len(df))\n",
" \n",
" # Soft conversion of numeric types to numerics, allows str in first col for point_id\n",
" df = df.apply(pd.to_numeric, errors='ignore')\n",
"\n",
" return df\n",
"\n",
"@read_ipf.register(list)\n",
"def read_ipf_list(input_data_list):\n",
" \"\"\"\n",
" Read a socet ipf file into a pandas data frame\n",
"\n",
" Parameters\n",
" ----------\n",
" input_data_list : list\n",
" list of paths to the a set of input data files\n",
"\n",
" Returns\n",
" -------\n",
" df : pd.DataFrame\n",
" containing the ipf data with appropriate column names and indices\n",
" \"\"\"\n",
" frames = []\n",
"\n",
" for input_file in input_data_list:\n",
" frames.append(read_ipf(input_file))\n",
"\n",
" df = pd.concat(frames)\n",
"\n",
" return df"
]
}
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