diff --git a/bin/Socetnet2ISIS.py b/bin/Socetnet2ISIS.py
deleted file mode 100644
index a410606abc65d9ec3039aae5d7091ba25a5af9de..0000000000000000000000000000000000000000
--- a/bin/Socetnet2ISIS.py
+++ /dev/null
@@ -1,73 +0,0 @@
-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)
diff --git a/bin/socet2isis b/bin/socet2isis
index 44255aec300c8ad9f4aed798258a8a9cf8fb89c6..2fe05808f4f518ef9f7586cf31bd3cfb57c5cb22 100644
--- a/bin/socet2isis
+++ b/bin/socet2isis
@@ -1,15 +1,92 @@
#!/usr/bin/env python
import argparse
+import os
+import sys
+import warnings
+import csv
+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
def parse_args():
parser = argparse.ArgumentParser()
+
# Add args here
+ parser.add_argument('at_file', help='Path to the .atf file for a project.')
+ parser.add_argument('cub_file_path', help='Path to cube files related to ipf files.')
+ parser.add_argument('cub_ipf_map', help='Path to map file for all ipfs and cubes.')
+ parser.add_argument('--outpath', help='Directory for the control network to be output to.',
+ required = False)
return parser.parse_args()
def main(args):
- print('Getting some work done')
+ # Setup the at_file, path to cubes, and control network out path
+ at_file = args.at_file
+ cnet_out = os.path.split(os.path.splitext(at_file)[0])[1]
+ cub_path = args.cub_file_path
+
+ if(args.outpath):
+ outpath = args.outpath
+ else:
+ outpath = os.path.split(at_file)[0]
+
+ with open(args.cub_ipf_map) as cub_ipf_map:
+ reader = csv.reader(cub_ipf_map, delimiter = ',')
+ image_dict = dict([(row[0], row[1]) for row in reader])
+
+ # 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\n".format("\n".join(point_diff)) +
+ "Continuing, but these points will be missing from the control " +
+ "network.", stacklevel=3)
+
+ # 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(os.path.join(outpath, cnet_out + '.net'), socet_df, serial_dict)
if __name__ == '__main__':
- main(parse_args())
\ No newline at end of file
+ main(parse_args())
diff --git a/plio/examples/SocetSet/cub_map.csv b/plio/examples/SocetSet/cub_map.csv
new file mode 100644
index 0000000000000000000000000000000000000000..cca0f2c17b832f4df5ac001bafde185ca679cdd7
--- /dev/null
+++ b/plio/examples/SocetSet/cub_map.csv
@@ -0,0 +1,7 @@
+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
diff --git a/plio/spatial/transformations.py b/plio/spatial/transformations.py
index 18160eea9860e78f8ea19d6a73584d809e12b67f..efc4ad609424a1c88e4ca778370b647249655e4c 100644
--- a/plio/spatial/transformations.py
+++ b/plio/spatial/transformations.py
@@ -45,7 +45,6 @@ def line_sample_size(record, path):
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
@@ -67,7 +66,6 @@ def known(record):
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
@@ -140,7 +138,6 @@ def og2oc(dlat, dMajorRadius, dMinorRadius):
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
@@ -291,7 +288,5 @@ def serial_numbers(image_dict, path):
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
+ serial_dict[key] = sn.generate_serial_number(os.path.join(path, image_dict[key]))
return serial_dict