Loading bin/Socetnet2ISIS.py +69 −0 Original line number Diff line number Diff line import os import warnings import numpy as np from plio.examples import get_path from plio.io.io_bae import read_atf, read_gpf, read_ipf from plio.spatial.transformations import * import plio.io.io_controlnetwork as cn import pandas as pd # TODO: Change script to potentially handle configuration files # Setup the at_file and path to cubes cub_path = '/Volumes/Blueman/' at_file = get_path('CTX_Athabasca_Middle_step0.atf') # Define ipf mapping to cubs image_dict = {'P01_001540_1889_XI_08N204W' : 'P01_001540_1889_XI_08N204W.lev1.cub', 'P01_001606_1897_XI_09N203W' : 'P01_001606_1897_XI_09N203W.lev1.cub', 'P02_001804_1889_XI_08N204W' : 'P02_001804_1889_XI_08N204W.lev1.cub', 'P03_002226_1895_XI_09N203W' : 'P03_002226_1895_XI_09N203W.lev1.cub', 'P03_002371_1888_XI_08N204W' : 'P03_002371_1888_XI_08N204W.lev1.cub', 'P19_008344_1894_XN_09N203W' : 'P19_008344_1894_XN_09N203W.lev1.cub', 'P20_008845_1894_XN_09N203W' : 'P20_008845_1894_XN_09N203W.lev1.cub'} ## # End Config ## # Read in and setup the atf dict of information atf_dict = read_atf(at_file) # Get the gpf and ipf files using atf dict gpf_file = os.path.join(atf_dict['PATH'], atf_dict['GP_FILE']); ipf_list = [os.path.join(atf_dict['PATH'], i) for i in atf_dict['IMAGE_IPF']] # Read in the gpf file and ipf file(s) into seperate dataframes gpf_df = read_gpf(gpf_file) ipf_df = read_ipf(ipf_list) # Check for differences between point ids using each dataframes # point ids as a reference gpf_pt_idx = pd.Index(pd.unique(gpf_df['point_id'])) ipf_pt_idx = pd.Index(pd.unique(ipf_df['pt_id'])) point_diff = ipf_pt_idx.difference(gpf_pt_idx) if len(point_diff) != 0: warnings.warn("The following points found in ipf files missing from gpf file: \n\n{}. \ \n\nContinuing, but these points will be missing from the control network".format(list(point_diff))) # Merge the two dataframes on their point id columns socet_df = ipf_df.merge(gpf_df, left_on='pt_id', right_on='point_id') # Apply the transformations apply_transformations(atf_dict, socet_df) # Define column remap for socet dataframe column_remap = {'l.': 'y', 's.': 'x', 'res_l': 'LineResidual', 'res_s': 'SampleResidual', 'known': 'Type', 'lat_Y_North': 'AprioriY', 'long_X_East': 'AprioriX', 'ht': 'AprioriZ', 'sig0': 'AprioriLatitudeSigma', 'sig1': 'AprioriLongitudeSigma', 'sig2': 'AprioriRadiusSigma'} # Rename the columns using the column remap above socet_df.rename(columns = column_remap, inplace=True) images = pd.unique(socet_df['ipf_file']) serial_dict = serial_numbers(image_dict, cub_path) # creates the control network cn.to_isis('/Volumes/Blueman/test.net', socet_df, serial_dict) notebooks/Socet2ISIS.ipynb +16 −17 Original line number Diff line number Diff line %% Cell type:code id: tags: ``` python import os import sys from functools import singledispatch import warnings import pandas as pd import numpy as np import math import pyproj # sys.path.insert(0, "/home/tthatcher/Desktop/Projects/Plio/plio") from plio.examples import get_path from plio.io.io_bae import read_gpf, read_ipf import plio.io.io_controlnetwork as cn import plio.io.isis_serial_number as sn ``` %% Cell type:code id: tags: ``` python # Reads a .atf file and outputs all of the # .ipf, .gpf, .sup, .prj, and path to locate the # .apf file (should be the same as all others) def read_atf(atf_file): with open(atf_file) as f: files = [] ipf = [] sup = [] files_dict = [] # Grabs every PRJ, GPF, SUP, and IPF image from the ATF file for line in f: 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': files.append(line) files = np.array(files) # Creates appropriate arrays for certain files in the right format for file in files: file = file.strip() file = file.split(' ') # Grabs all the IPF files if file[1].endswith('.ipf'): ipf.append(file[1]) # Grabs all the SUP files if file[1].endswith('.sup'): sup.append(file[1]) files_dict.append(file) # Creates a dict out of file lists for GPF, PRJ, IPF, and ATF files_dict = (dict(files_dict)) # Sets the value of IMAGE_IPF to all IPF images files_dict['IMAGE_IPF'] = ipf # Sets the value of IMAGE_SUP to all SUP images files_dict['IMAGE_SUP'] = sup # Sets the value of PATH to the path of the ATF file files_dict['PATH'] = os.path.dirname(os.path.abspath(atf_file)) return files_dict # converts columns l. and s. to isis def line_sample_size(record, path): with open(os.path.join(path, record['ipf_file'] + '.sup')) as f: for i, line in enumerate(f): if i == 2: img_index = line.split('\\') img_index = img_index[-1].strip() img_index = img_index.split('.')[0] if i == 3: line_size = line.split(' ') line_size = line_size[-1].strip() assert int(line_size) > 0, "Line number {} from {} is a negative number: Invalid Data".format(line_size, record['ipf_file']) if i == 4: sample_size = line.split(' ') sample_size = sample_size[-1].strip() assert int(sample_size) > 0, "Sample number {} from {} is a negative number: Invalid Data".format(sample_size, record['ipf_file']) break line_size = int(line_size)/2.0 + record['l.'] + 1 sample_size = int(sample_size)/2.0 + record['s.'] + 1 return sample_size, line_size, img_index # converts known to ISIS keywords def known(record): if record['known'] == 0: return 'Free' elif record['known'] == 1 or record['known'] == 2 or record['known'] == 3: return 'Constrained' # converts +/- 180 system to 0 - 360 system def to_360(num): return num % 360 # ocentric to ographic latitudes def oc2og(dlat, dMajorRadius, dMinorRadius): try: dlat = math.radians(dlat) dlat = math.atan(((dMajorRadius / dMinorRadius)**2) * (math.tan(dlat))) dlat = math.degrees(dlat) except: print ("Error in oc2og conversion") return dlat # ographic to ocentric latitudes def og2oc(dlat, dMajorRadius, dMinorRadius): try: dlat = math.radians(dlat) dlat = math.atan((math.tan(dlat) / ((dMajorRadius / dMinorRadius)**2))) dlat = math.degrees(dlat) except: print ("Error in og2oc conversion") return dlat # gets eRadius and pRadius from a .prj file def get_axis(file): with open(file) as f: from collections import defaultdict files = defaultdict(list) for line in f: ext = line.strip().split(' ') files[ext[0]].append(ext[-1]) eRadius = float(files['A_EARTH'][0]) pRadius = eRadius * (1 - float(files['E_EARTH'][0])) return eRadius, pRadius # function to convert lat_Y_North to ISIS_lat def lat_ISIS_coord(record, semi_major, semi_minor): ocentric_coord = og2oc(record['lat_Y_North'], semi_major, semi_minor) coord_360 = to_360(ocentric_coord) return coord_360 # function to convert long_X_East to ISIS_lon def lon_ISIS_coord(record, semi_major, semi_minor): ocentric_coord = og2oc(record['long_X_East'], semi_major, semi_minor) coord_360 = to_360(ocentric_coord) return coord_360 def body_fix(record, semi_major, semi_minor): ecef = pyproj.Proj(proj='geocent', a=semi_major, b=semi_minor) lla = pyproj.Proj(proj='latlon', a=semi_major, b=semi_minor) lon, lat, height = pyproj.transform(lla, ecef, record['long_X_East'], record['lat_Y_North'], record['ht']) return lon, lat, height # applys transformations to columns def apply_transformations(atf_dict, df): prj_file = os.path.join(atf_dict['PATH'], atf_dict['PROJECT'].split('\\')[-1]) eRadius, pRadius = get_axis(prj_file) df['s.'], df['l.'], df['image_index'] = (zip(*df.apply(line_sample_size, path = atf_dict['PATH'], axis=1))) df['known'] = df.apply(known, axis=1) df['lat_Y_North'] = df.apply(lat_ISIS_coord, semi_major = eRadius, semi_minor = pRadius, axis=1) df['long_X_East'] = df.apply(lon_ISIS_coord, semi_major = eRadius, semi_minor = pRadius, axis=1) df['long_X_East'], df['lat_Y_North'], df['ht'] = zip(*df.apply(body_fix, semi_major = eRadius, semi_minor = pRadius, axis = 1)) def socet2isis(prj_file): # Read in and setup the atf dict of information atf_dict = read_atf(prj_file) # Get the gpf and ipf files using atf dict gpf_file = os.path.join(atf_dict['PATH'], atf_dict['GP_FILE']); ipf_list = [os.path.join(atf_dict['PATH'], i) for i in atf_dict['IMAGE_IPF']] # Read in the gpf file and ipf file(s) into seperate dataframes gpf_df = read_gpf(gpf_file) ipf_df = read_ipf(ipf_list) # Check for differences between point ids using each dataframes # point ids as a reference gpf_pt_idx = pd.Index(pd.unique(gpf_df['point_id'])) ipf_pt_idx = pd.Index(pd.unique(ipf_df['pt_id'])) point_diff = ipf_pt_idx.difference(gpf_pt_idx) if len(point_diff) != 0: warnings.warn("The following points found in ipf files missing from gpf file: \n\n{}. \ \n\nContinuing, but these points will be missing from the control network".format(list(point_diff))) # Merge the two dataframes on their point id columns socet_df = ipf_df.merge(gpf_df, left_on='pt_id', right_on='point_id') # Apply the transformations apply_transformations(atf_dict, socet_df) # Define column remap for socet dataframe column_remap = {'l.': 'y', 's.': 'x', 'res_l': 'LineResidual', 'res_s': 'SampleResidual', 'known': 'Type', 'lat_Y_North': 'AprioriY', 'long_X_East': 'AprioriX', 'ht': 'AprioriZ', 'sig0': 'AprioriLatitudeSigma', 'sig1': 'AprioriLongitudeSigma', 'sig2': 'AprioriRadiusSigma'} # Rename the columns using the column remap above socet_df.rename(columns = column_remap, inplace=True) # Return the socet dataframe to be converted to a control net return socet_df # creates a dict of serial numbers with the cub being the key def serial_numbers(images, path, extension): def serial_numbers(image_dict, path): serial_dict = dict() for image in images: snum = sn.generate_serial_number(os.path.join(path, image + extension)) for key in image_dict: snum = sn.generate_serial_number(os.path.join(path, image_dict[key])) snum = snum.replace('Mars_Reconnaissance_Orbiter', 'MRO') serial_dict[image] = snum serial_dict[key] = snum return serial_dict ``` %% Cell type:code id: tags: ``` python # Setup stuffs for the cub information namely the path and extension path = '/Volumes/Blueman/' extension = '.lev1.cub' prj_file = get_path('CTX_Athabasca_Middle_step0.atf') atf_file = get_path('CTX_Athabasca_Middle_step0.atf') socet_df = socet2isis(prj_file) image_dict = {'P01_001540_1889_XI_08N204W' : 'P01_001540_1889_XI_08N204W.lev1.cub', 'P01_001606_1897_XI_09N203W' : 'P01_001606_1897_XI_09N203W.lev1.cub', 'P02_001804_1889_XI_08N204W' : 'P02_001804_1889_XI_08N204W.lev1.cub', 'P03_002226_1895_XI_09N203W' : 'P03_002226_1895_XI_09N203W.lev1.cub', 'P03_002371_1888_XI_08N204W' : 'P03_002371_1888_XI_08N204W.lev1.cub', 'P19_008344_1894_XN_09N203W' : 'P19_008344_1894_XN_09N203W.lev1.cub', 'P20_008845_1894_XN_09N203W' : 'P20_008845_1894_XN_09N203W.lev1.cub'} socet_df = socet2isis(atf_file) images = pd.unique(socet_df['ipf_file']) serial_dict = serial_numbers(images, path, extension) serial_dict = serial_numbers(image_dict, path) # creates the control network cn.to_isis('/Volumes/Blueman/cn.net', socet_df, serial_dict) cn.to_isis('/Volumes/Blueman/banana.net', socet_df, serial_dict) ``` %% Output /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: ['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']. Continuing, but these points will be missing from the control network %% Cell type:code id: tags: ``` python ``` plio/spatial/transformations.py 0 → 100644 +297 −0 Original line number Diff line number Diff line import os import math import pyproj import plio.io.isis_serial_number as sn def line_sample_size(record, path): """ Converts columns l. and s. to sample size, line size, and generates an image index Parameters ---------- record : object Pandas series object path : str Path to the associated sup files for a socet project Returns ------- : list A list of sample_size, line_size, and img_index """ with open(os.path.join(path, record['ipf_file'] + '.sup')) as f: for i, line in enumerate(f): if i == 2: img_index = line.split('\\') img_index = img_index[-1].strip() img_index = img_index.split('.')[0] if i == 3: line_size = line.split(' ') line_size = line_size[-1].strip() assert int(line_size) > 0, "Line number {} from {} is a negative number: Invalid Data".format(line_size, record['ipf_file']) if i == 4: sample_size = line.split(' ') sample_size = sample_size[-1].strip() assert int(sample_size) > 0, "Sample number {} from {} is a negative number: Invalid Data".format(sample_size, record['ipf_file']) break line_size = int(line_size)/2.0 + record['l.'] + 1 sample_size = int(sample_size)/2.0 + record['s.'] + 1 return sample_size, line_size, img_index # converts known to ISIS keywords def known(record): """ Converts the known field from a socet dataframe into the isis point_type column Parameters ---------- record : object Pandas series object Returns ------- : str String representation of a known field """ if record['known'] == 0: return 'Free' elif record['known'] == 1 or record['known'] == 2 or record['known'] == 3: return 'Constrained' # converts +/- 180 system to 0 - 360 system def to_360(num): """ Transforms a given number into 0 - 360 space Parameters ---------- num : int A given integer Returns ------- : int num moduloed by 360 """ return num % 360 def oc2og(dlat, dMajorRadius, dMinorRadius): """ Ocentric to ographic latitudes Parameters ---------- dlat : float Latitude to convert dMajorRadius : float Radius from the center of the body to the equater dMinorRadius : float Radius from the pole to the center of mass Returns ------- dlat : float Converted latitude into ographic space """ try: dlat = math.radians(dlat) dlat = math.atan(((dMajorRadius / dMinorRadius)**2) * (math.tan(dlat))) dlat = math.degrees(dlat) except: print ("Error in oc2og conversion") return dlat def og2oc(dlat, dMajorRadius, dMinorRadius): """ Ographic to ocentric latitudes Parameters ---------- dlat : float Latitude to convert dMajorRadius : float Radius from the center of the body to the equater dMinorRadius : float Radius from the pole to the center of mass Returns ------- dlat : float Converted latitude into ocentric space """ try: dlat = math.radians(dlat) dlat = math.atan((math.tan(dlat) / ((dMajorRadius / dMinorRadius)**2))) dlat = math.degrees(dlat) except: print ("Error in og2oc conversion") return dlat # gets eRadius and pRadius from a .prj file def get_axis(file): """ Gets eRadius and pRadius from a .prj file Parameters ---------- file : str file with path to a given socet project file Returns ------- : list A list of the eRadius and pRadius of the project file """ with open(file) as f: from collections import defaultdict files = defaultdict(list) for line in f: ext = line.strip().split(' ') files[ext[0]].append(ext[-1]) eRadius = float(files['A_EARTH'][0]) pRadius = eRadius * (1 - float(files['E_EARTH'][0])) return eRadius, pRadius def lat_ISIS_coord(record, semi_major, semi_minor): """ Function to convert lat_Y_North to ISIS_lat Parameters ---------- record : object Pandas series object semi_major : float Radius from the center of the body to the equater semi_minor : float Radius from the pole to the center of mass Returns ------- coord_360 : float Converted latitude into ocentric space, and mapped into 0 to 360 """ ocentric_coord = og2oc(record['lat_Y_North'], semi_major, semi_minor) coord_360 = to_360(ocentric_coord) return coord_360 def lon_ISIS_coord(record, semi_major, semi_minor): """ Function to convert long_X_East to ISIS_lon Parameters ---------- record : object Pandas series object semi_major : float Radius from the center of the body to the equater semi_minor : float Radius from the pole to the center of mass Returns ------- coord_360 : float Converted longitude into ocentric space, and mapped into 0 to 360 """ ocentric_coord = og2oc(record['long_X_East'], semi_major, semi_minor) coord_360 = to_360(ocentric_coord) return coord_360 def body_fix(record, semi_major, semi_minor): """ Transforms latitude, longitude, and height of a socet point into a body fixed point Parameters ---------- record : object Pandas series object semi_major : float Radius from the center of the body to the equater semi_minor : float Radius from the pole to the center of mass Returns ------- : list Body fixed lat, lon and height coordinates as lat, lon, ht """ ecef = pyproj.Proj(proj='geocent', a=semi_major, b=semi_minor) lla = pyproj.Proj(proj='latlon', a=semi_major, b=semi_minor) lon, lat, height = pyproj.transform(lla, ecef, record['long_X_East'], record['lat_Y_North'], record['ht']) return lon, lat, height def apply_transformations(atf_dict, df): """ Takes a atf dictionary and a socet dataframe and applies the necessary transformations to convert that dataframe into a isis compatible dataframe Parameters ---------- atf_dict : dict Dictionary containing information from an atf file df : object Pandas dataframe object """ prj_file = os.path.join(atf_dict['PATH'], atf_dict['PROJECT'].split('\\')[-1]) eRadius, pRadius = get_axis(prj_file) df['s.'], df['l.'], df['image_index'] = (zip(*df.apply(line_sample_size, path = atf_dict['PATH'], axis=1))) df['known'] = df.apply(known, axis=1) df['lat_Y_North'] = df.apply(lat_ISIS_coord, semi_major = eRadius, semi_minor = pRadius, axis=1) df['long_X_East'] = df.apply(lon_ISIS_coord, semi_major = eRadius, semi_minor = pRadius, axis=1) df['long_X_East'], df['lat_Y_North'], df['ht'] = zip(*df.apply(body_fix, semi_major = eRadius, semi_minor = pRadius, axis = 1)) def serial_numbers(image_dict, path): """ Creates a dict of serial numbers with the cub being the key Parameters ---------- images : list path : str extension : str Returns ------- serial_dict : dict """ serial_dict = dict() for key in image_dict: snum = sn.generate_serial_number(os.path.join(path, image_dict[key])) snum = snum.replace('Mars_Reconnaissance_Orbiter', 'MRO') serial_dict[key] = snum return serial_dict Loading
bin/Socetnet2ISIS.py +69 −0 Original line number Diff line number Diff line import os import warnings import numpy as np from plio.examples import get_path from plio.io.io_bae import read_atf, read_gpf, read_ipf from plio.spatial.transformations import * import plio.io.io_controlnetwork as cn import pandas as pd # TODO: Change script to potentially handle configuration files # Setup the at_file and path to cubes cub_path = '/Volumes/Blueman/' at_file = get_path('CTX_Athabasca_Middle_step0.atf') # Define ipf mapping to cubs image_dict = {'P01_001540_1889_XI_08N204W' : 'P01_001540_1889_XI_08N204W.lev1.cub', 'P01_001606_1897_XI_09N203W' : 'P01_001606_1897_XI_09N203W.lev1.cub', 'P02_001804_1889_XI_08N204W' : 'P02_001804_1889_XI_08N204W.lev1.cub', 'P03_002226_1895_XI_09N203W' : 'P03_002226_1895_XI_09N203W.lev1.cub', 'P03_002371_1888_XI_08N204W' : 'P03_002371_1888_XI_08N204W.lev1.cub', 'P19_008344_1894_XN_09N203W' : 'P19_008344_1894_XN_09N203W.lev1.cub', 'P20_008845_1894_XN_09N203W' : 'P20_008845_1894_XN_09N203W.lev1.cub'} ## # End Config ## # Read in and setup the atf dict of information atf_dict = read_atf(at_file) # Get the gpf and ipf files using atf dict gpf_file = os.path.join(atf_dict['PATH'], atf_dict['GP_FILE']); ipf_list = [os.path.join(atf_dict['PATH'], i) for i in atf_dict['IMAGE_IPF']] # Read in the gpf file and ipf file(s) into seperate dataframes gpf_df = read_gpf(gpf_file) ipf_df = read_ipf(ipf_list) # Check for differences between point ids using each dataframes # point ids as a reference gpf_pt_idx = pd.Index(pd.unique(gpf_df['point_id'])) ipf_pt_idx = pd.Index(pd.unique(ipf_df['pt_id'])) point_diff = ipf_pt_idx.difference(gpf_pt_idx) if len(point_diff) != 0: warnings.warn("The following points found in ipf files missing from gpf file: \n\n{}. \ \n\nContinuing, but these points will be missing from the control network".format(list(point_diff))) # Merge the two dataframes on their point id columns socet_df = ipf_df.merge(gpf_df, left_on='pt_id', right_on='point_id') # Apply the transformations apply_transformations(atf_dict, socet_df) # Define column remap for socet dataframe column_remap = {'l.': 'y', 's.': 'x', 'res_l': 'LineResidual', 'res_s': 'SampleResidual', 'known': 'Type', 'lat_Y_North': 'AprioriY', 'long_X_East': 'AprioriX', 'ht': 'AprioriZ', 'sig0': 'AprioriLatitudeSigma', 'sig1': 'AprioriLongitudeSigma', 'sig2': 'AprioriRadiusSigma'} # Rename the columns using the column remap above socet_df.rename(columns = column_remap, inplace=True) images = pd.unique(socet_df['ipf_file']) serial_dict = serial_numbers(image_dict, cub_path) # creates the control network cn.to_isis('/Volumes/Blueman/test.net', socet_df, serial_dict)
notebooks/Socet2ISIS.ipynb +16 −17 Original line number Diff line number Diff line %% Cell type:code id: tags: ``` python import os import sys from functools import singledispatch import warnings import pandas as pd import numpy as np import math import pyproj # sys.path.insert(0, "/home/tthatcher/Desktop/Projects/Plio/plio") from plio.examples import get_path from plio.io.io_bae import read_gpf, read_ipf import plio.io.io_controlnetwork as cn import plio.io.isis_serial_number as sn ``` %% Cell type:code id: tags: ``` python # Reads a .atf file and outputs all of the # .ipf, .gpf, .sup, .prj, and path to locate the # .apf file (should be the same as all others) def read_atf(atf_file): with open(atf_file) as f: files = [] ipf = [] sup = [] files_dict = [] # Grabs every PRJ, GPF, SUP, and IPF image from the ATF file for line in f: 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': files.append(line) files = np.array(files) # Creates appropriate arrays for certain files in the right format for file in files: file = file.strip() file = file.split(' ') # Grabs all the IPF files if file[1].endswith('.ipf'): ipf.append(file[1]) # Grabs all the SUP files if file[1].endswith('.sup'): sup.append(file[1]) files_dict.append(file) # Creates a dict out of file lists for GPF, PRJ, IPF, and ATF files_dict = (dict(files_dict)) # Sets the value of IMAGE_IPF to all IPF images files_dict['IMAGE_IPF'] = ipf # Sets the value of IMAGE_SUP to all SUP images files_dict['IMAGE_SUP'] = sup # Sets the value of PATH to the path of the ATF file files_dict['PATH'] = os.path.dirname(os.path.abspath(atf_file)) return files_dict # converts columns l. and s. to isis def line_sample_size(record, path): with open(os.path.join(path, record['ipf_file'] + '.sup')) as f: for i, line in enumerate(f): if i == 2: img_index = line.split('\\') img_index = img_index[-1].strip() img_index = img_index.split('.')[0] if i == 3: line_size = line.split(' ') line_size = line_size[-1].strip() assert int(line_size) > 0, "Line number {} from {} is a negative number: Invalid Data".format(line_size, record['ipf_file']) if i == 4: sample_size = line.split(' ') sample_size = sample_size[-1].strip() assert int(sample_size) > 0, "Sample number {} from {} is a negative number: Invalid Data".format(sample_size, record['ipf_file']) break line_size = int(line_size)/2.0 + record['l.'] + 1 sample_size = int(sample_size)/2.0 + record['s.'] + 1 return sample_size, line_size, img_index # converts known to ISIS keywords def known(record): if record['known'] == 0: return 'Free' elif record['known'] == 1 or record['known'] == 2 or record['known'] == 3: return 'Constrained' # converts +/- 180 system to 0 - 360 system def to_360(num): return num % 360 # ocentric to ographic latitudes def oc2og(dlat, dMajorRadius, dMinorRadius): try: dlat = math.radians(dlat) dlat = math.atan(((dMajorRadius / dMinorRadius)**2) * (math.tan(dlat))) dlat = math.degrees(dlat) except: print ("Error in oc2og conversion") return dlat # ographic to ocentric latitudes def og2oc(dlat, dMajorRadius, dMinorRadius): try: dlat = math.radians(dlat) dlat = math.atan((math.tan(dlat) / ((dMajorRadius / dMinorRadius)**2))) dlat = math.degrees(dlat) except: print ("Error in og2oc conversion") return dlat # gets eRadius and pRadius from a .prj file def get_axis(file): with open(file) as f: from collections import defaultdict files = defaultdict(list) for line in f: ext = line.strip().split(' ') files[ext[0]].append(ext[-1]) eRadius = float(files['A_EARTH'][0]) pRadius = eRadius * (1 - float(files['E_EARTH'][0])) return eRadius, pRadius # function to convert lat_Y_North to ISIS_lat def lat_ISIS_coord(record, semi_major, semi_minor): ocentric_coord = og2oc(record['lat_Y_North'], semi_major, semi_minor) coord_360 = to_360(ocentric_coord) return coord_360 # function to convert long_X_East to ISIS_lon def lon_ISIS_coord(record, semi_major, semi_minor): ocentric_coord = og2oc(record['long_X_East'], semi_major, semi_minor) coord_360 = to_360(ocentric_coord) return coord_360 def body_fix(record, semi_major, semi_minor): ecef = pyproj.Proj(proj='geocent', a=semi_major, b=semi_minor) lla = pyproj.Proj(proj='latlon', a=semi_major, b=semi_minor) lon, lat, height = pyproj.transform(lla, ecef, record['long_X_East'], record['lat_Y_North'], record['ht']) return lon, lat, height # applys transformations to columns def apply_transformations(atf_dict, df): prj_file = os.path.join(atf_dict['PATH'], atf_dict['PROJECT'].split('\\')[-1]) eRadius, pRadius = get_axis(prj_file) df['s.'], df['l.'], df['image_index'] = (zip(*df.apply(line_sample_size, path = atf_dict['PATH'], axis=1))) df['known'] = df.apply(known, axis=1) df['lat_Y_North'] = df.apply(lat_ISIS_coord, semi_major = eRadius, semi_minor = pRadius, axis=1) df['long_X_East'] = df.apply(lon_ISIS_coord, semi_major = eRadius, semi_minor = pRadius, axis=1) df['long_X_East'], df['lat_Y_North'], df['ht'] = zip(*df.apply(body_fix, semi_major = eRadius, semi_minor = pRadius, axis = 1)) def socet2isis(prj_file): # Read in and setup the atf dict of information atf_dict = read_atf(prj_file) # Get the gpf and ipf files using atf dict gpf_file = os.path.join(atf_dict['PATH'], atf_dict['GP_FILE']); ipf_list = [os.path.join(atf_dict['PATH'], i) for i in atf_dict['IMAGE_IPF']] # Read in the gpf file and ipf file(s) into seperate dataframes gpf_df = read_gpf(gpf_file) ipf_df = read_ipf(ipf_list) # Check for differences between point ids using each dataframes # point ids as a reference gpf_pt_idx = pd.Index(pd.unique(gpf_df['point_id'])) ipf_pt_idx = pd.Index(pd.unique(ipf_df['pt_id'])) point_diff = ipf_pt_idx.difference(gpf_pt_idx) if len(point_diff) != 0: warnings.warn("The following points found in ipf files missing from gpf file: \n\n{}. \ \n\nContinuing, but these points will be missing from the control network".format(list(point_diff))) # Merge the two dataframes on their point id columns socet_df = ipf_df.merge(gpf_df, left_on='pt_id', right_on='point_id') # Apply the transformations apply_transformations(atf_dict, socet_df) # Define column remap for socet dataframe column_remap = {'l.': 'y', 's.': 'x', 'res_l': 'LineResidual', 'res_s': 'SampleResidual', 'known': 'Type', 'lat_Y_North': 'AprioriY', 'long_X_East': 'AprioriX', 'ht': 'AprioriZ', 'sig0': 'AprioriLatitudeSigma', 'sig1': 'AprioriLongitudeSigma', 'sig2': 'AprioriRadiusSigma'} # Rename the columns using the column remap above socet_df.rename(columns = column_remap, inplace=True) # Return the socet dataframe to be converted to a control net return socet_df # creates a dict of serial numbers with the cub being the key def serial_numbers(images, path, extension): def serial_numbers(image_dict, path): serial_dict = dict() for image in images: snum = sn.generate_serial_number(os.path.join(path, image + extension)) for key in image_dict: snum = sn.generate_serial_number(os.path.join(path, image_dict[key])) snum = snum.replace('Mars_Reconnaissance_Orbiter', 'MRO') serial_dict[image] = snum serial_dict[key] = snum return serial_dict ``` %% Cell type:code id: tags: ``` python # Setup stuffs for the cub information namely the path and extension path = '/Volumes/Blueman/' extension = '.lev1.cub' prj_file = get_path('CTX_Athabasca_Middle_step0.atf') atf_file = get_path('CTX_Athabasca_Middle_step0.atf') socet_df = socet2isis(prj_file) image_dict = {'P01_001540_1889_XI_08N204W' : 'P01_001540_1889_XI_08N204W.lev1.cub', 'P01_001606_1897_XI_09N203W' : 'P01_001606_1897_XI_09N203W.lev1.cub', 'P02_001804_1889_XI_08N204W' : 'P02_001804_1889_XI_08N204W.lev1.cub', 'P03_002226_1895_XI_09N203W' : 'P03_002226_1895_XI_09N203W.lev1.cub', 'P03_002371_1888_XI_08N204W' : 'P03_002371_1888_XI_08N204W.lev1.cub', 'P19_008344_1894_XN_09N203W' : 'P19_008344_1894_XN_09N203W.lev1.cub', 'P20_008845_1894_XN_09N203W' : 'P20_008845_1894_XN_09N203W.lev1.cub'} socet_df = socet2isis(atf_file) images = pd.unique(socet_df['ipf_file']) serial_dict = serial_numbers(images, path, extension) serial_dict = serial_numbers(image_dict, path) # creates the control network cn.to_isis('/Volumes/Blueman/cn.net', socet_df, serial_dict) cn.to_isis('/Volumes/Blueman/banana.net', socet_df, serial_dict) ``` %% Output /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: ['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']. Continuing, but these points will be missing from the control network %% Cell type:code id: tags: ``` python ```
plio/spatial/transformations.py 0 → 100644 +297 −0 Original line number Diff line number Diff line import os import math import pyproj import plio.io.isis_serial_number as sn def line_sample_size(record, path): """ Converts columns l. and s. to sample size, line size, and generates an image index Parameters ---------- record : object Pandas series object path : str Path to the associated sup files for a socet project Returns ------- : list A list of sample_size, line_size, and img_index """ with open(os.path.join(path, record['ipf_file'] + '.sup')) as f: for i, line in enumerate(f): if i == 2: img_index = line.split('\\') img_index = img_index[-1].strip() img_index = img_index.split('.')[0] if i == 3: line_size = line.split(' ') line_size = line_size[-1].strip() assert int(line_size) > 0, "Line number {} from {} is a negative number: Invalid Data".format(line_size, record['ipf_file']) if i == 4: sample_size = line.split(' ') sample_size = sample_size[-1].strip() assert int(sample_size) > 0, "Sample number {} from {} is a negative number: Invalid Data".format(sample_size, record['ipf_file']) break line_size = int(line_size)/2.0 + record['l.'] + 1 sample_size = int(sample_size)/2.0 + record['s.'] + 1 return sample_size, line_size, img_index # converts known to ISIS keywords def known(record): """ Converts the known field from a socet dataframe into the isis point_type column Parameters ---------- record : object Pandas series object Returns ------- : str String representation of a known field """ if record['known'] == 0: return 'Free' elif record['known'] == 1 or record['known'] == 2 or record['known'] == 3: return 'Constrained' # converts +/- 180 system to 0 - 360 system def to_360(num): """ Transforms a given number into 0 - 360 space Parameters ---------- num : int A given integer Returns ------- : int num moduloed by 360 """ return num % 360 def oc2og(dlat, dMajorRadius, dMinorRadius): """ Ocentric to ographic latitudes Parameters ---------- dlat : float Latitude to convert dMajorRadius : float Radius from the center of the body to the equater dMinorRadius : float Radius from the pole to the center of mass Returns ------- dlat : float Converted latitude into ographic space """ try: dlat = math.radians(dlat) dlat = math.atan(((dMajorRadius / dMinorRadius)**2) * (math.tan(dlat))) dlat = math.degrees(dlat) except: print ("Error in oc2og conversion") return dlat def og2oc(dlat, dMajorRadius, dMinorRadius): """ Ographic to ocentric latitudes Parameters ---------- dlat : float Latitude to convert dMajorRadius : float Radius from the center of the body to the equater dMinorRadius : float Radius from the pole to the center of mass Returns ------- dlat : float Converted latitude into ocentric space """ try: dlat = math.radians(dlat) dlat = math.atan((math.tan(dlat) / ((dMajorRadius / dMinorRadius)**2))) dlat = math.degrees(dlat) except: print ("Error in og2oc conversion") return dlat # gets eRadius and pRadius from a .prj file def get_axis(file): """ Gets eRadius and pRadius from a .prj file Parameters ---------- file : str file with path to a given socet project file Returns ------- : list A list of the eRadius and pRadius of the project file """ with open(file) as f: from collections import defaultdict files = defaultdict(list) for line in f: ext = line.strip().split(' ') files[ext[0]].append(ext[-1]) eRadius = float(files['A_EARTH'][0]) pRadius = eRadius * (1 - float(files['E_EARTH'][0])) return eRadius, pRadius def lat_ISIS_coord(record, semi_major, semi_minor): """ Function to convert lat_Y_North to ISIS_lat Parameters ---------- record : object Pandas series object semi_major : float Radius from the center of the body to the equater semi_minor : float Radius from the pole to the center of mass Returns ------- coord_360 : float Converted latitude into ocentric space, and mapped into 0 to 360 """ ocentric_coord = og2oc(record['lat_Y_North'], semi_major, semi_minor) coord_360 = to_360(ocentric_coord) return coord_360 def lon_ISIS_coord(record, semi_major, semi_minor): """ Function to convert long_X_East to ISIS_lon Parameters ---------- record : object Pandas series object semi_major : float Radius from the center of the body to the equater semi_minor : float Radius from the pole to the center of mass Returns ------- coord_360 : float Converted longitude into ocentric space, and mapped into 0 to 360 """ ocentric_coord = og2oc(record['long_X_East'], semi_major, semi_minor) coord_360 = to_360(ocentric_coord) return coord_360 def body_fix(record, semi_major, semi_minor): """ Transforms latitude, longitude, and height of a socet point into a body fixed point Parameters ---------- record : object Pandas series object semi_major : float Radius from the center of the body to the equater semi_minor : float Radius from the pole to the center of mass Returns ------- : list Body fixed lat, lon and height coordinates as lat, lon, ht """ ecef = pyproj.Proj(proj='geocent', a=semi_major, b=semi_minor) lla = pyproj.Proj(proj='latlon', a=semi_major, b=semi_minor) lon, lat, height = pyproj.transform(lla, ecef, record['long_X_East'], record['lat_Y_North'], record['ht']) return lon, lat, height def apply_transformations(atf_dict, df): """ Takes a atf dictionary and a socet dataframe and applies the necessary transformations to convert that dataframe into a isis compatible dataframe Parameters ---------- atf_dict : dict Dictionary containing information from an atf file df : object Pandas dataframe object """ prj_file = os.path.join(atf_dict['PATH'], atf_dict['PROJECT'].split('\\')[-1]) eRadius, pRadius = get_axis(prj_file) df['s.'], df['l.'], df['image_index'] = (zip(*df.apply(line_sample_size, path = atf_dict['PATH'], axis=1))) df['known'] = df.apply(known, axis=1) df['lat_Y_North'] = df.apply(lat_ISIS_coord, semi_major = eRadius, semi_minor = pRadius, axis=1) df['long_X_East'] = df.apply(lon_ISIS_coord, semi_major = eRadius, semi_minor = pRadius, axis=1) df['long_X_East'], df['lat_Y_North'], df['ht'] = zip(*df.apply(body_fix, semi_major = eRadius, semi_minor = pRadius, axis = 1)) def serial_numbers(image_dict, path): """ Creates a dict of serial numbers with the cub being the key Parameters ---------- images : list path : str extension : str Returns ------- serial_dict : dict """ serial_dict = dict() for key in image_dict: snum = sn.generate_serial_number(os.path.join(path, image_dict[key])) snum = snum.replace('Mars_Reconnaissance_Orbiter', 'MRO') serial_dict[key] = snum return serial_dict
