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Commit e2fbdf2e authored by acpaquette's avatar acpaquette Committed by GitHub
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Merge pull request #40 from tthatcher95/master 

Added isisCNET creation
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%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
import os import os
import sys import sys
from functools import singledispatch from functools import singledispatch
import warnings import warnings
import pandas as pd import pandas as pd
import numpy as np import numpy as np
import math
import pyproj
sys.path.insert(0, "/home/tthatcher/Desktop/Projects/Plio/plio") # sys.path.insert(0, "/home/tthatcher/Desktop/Projects/Plio/plio")
from plio.examples import get_path from plio.examples import get_path
from plio.io.io_bae import read_gpf, read_ipf 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: %% Cell type:code id: tags:
``` python ``` python
# Reads a .atf file and outputs all of the # Reads a .atf file and outputs all of the
# .ipf, .gpf, .sup, .prj, and path to locate the # .ipf, .gpf, .sup, .prj, and path to locate the
# .apf file (should be the same as all others) # .apf file (should be the same as all others)
def read_atf(atf_file): def read_atf(atf_file):
with open(atf_file) as f: with open(atf_file) as f:
files = [] files = []
ipf = [] ipf = []
sup = [] sup = []
files_dict = [] files_dict = []
# Grabs every PRJ, GPF, SUP, and IPF image from the ATF file # Grabs every PRJ, GPF, SUP, and IPF image from the ATF file
for line in f: 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': 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.append(line)
files = np.array(files) files = np.array(files)
# Creates appropriate arrays for certain files in the right format # Creates appropriate arrays for certain files in the right format
for file in files: for file in files:
file = file.strip() file = file.strip()
file = file.split(' ') file = file.split(' ')
# Grabs all the IPF files # Grabs all the IPF files
if file[1].endswith('.ipf'): if file[1].endswith('.ipf'):
ipf.append(file[1]) ipf.append(file[1])
# Grabs all the SUP files # Grabs all the SUP files
if file[1].endswith('.sup'): if file[1].endswith('.sup'):
sup.append(file[1]) sup.append(file[1])
files_dict.append(file) files_dict.append(file)
# Creates a dict out of file lists for GPF, PRJ, IPF, and ATF # Creates a dict out of file lists for GPF, PRJ, IPF, and ATF
files_dict = (dict(files_dict)) files_dict = (dict(files_dict))
# Sets the value of IMAGE_IPF to all IPF images # Sets the value of IMAGE_IPF to all IPF images
files_dict['IMAGE_IPF'] = ipf files_dict['IMAGE_IPF'] = ipf
# Sets the value of IMAGE_SUP to all SUP images # Sets the value of IMAGE_SUP to all SUP images
files_dict['IMAGE_SUP'] = sup files_dict['IMAGE_SUP'] = sup
# Sets the value of PATH to the path of the ATF file # Sets the value of PATH to the path of the ATF file
files_dict['PATH'] = os.path.dirname(os.path.abspath(atf_file)) files_dict['PATH'] = os.path.dirname(os.path.abspath(atf_file))
return files_dict return files_dict
```
%% Cell type:code id: tags:
``` python
atf_dict = read_atf(get_path('CTX_Athabasca_Middle_step0.atf'))
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']]
gpf_df = read_gpf(gpf_file).set_index('point_id')
ipf_df = read_ipf(ipf_list).set_index('pt_id')
point_diff = ipf_df.index.difference(gpf_df.index)
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)))
new_df = ipf_df.merge(gpf_df, left_index=True, right_index=True)
```
%% Cell type:code id: tags:
``` python
import math
import pyproj
# converts columns l. and s. to isis # converts columns l. and s. to isis
def line_sample_size(record): def line_sample_size(record, path):
with open(atf_dict['PATH'] + '/' + record['ipf_file'] + '.sup') as f: with open(os.path.join(path, record['ipf_file'] + '.sup')) as f:
for i, line in enumerate(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: if i == 3:
line_size = line.split(' ') line_size = line.split(' ')
line_size = line_size[-1].strip() 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']) assert int(line_size) > 0, "Line number {} from {} is a negative number: Invalid Data".format(line_size, record['ipf_file'])
if i == 4: if i == 4:
sample_size = line.split(' ') sample_size = line.split(' ')
sample_size = sample_size[-1].strip() 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']) assert int(sample_size) > 0, "Sample number {} from {} is a negative number: Invalid Data".format(sample_size, record['ipf_file'])
break break
line_size = int(line_size)/2.0 + record['l.'] + 1 line_size = int(line_size)/2.0 + record['l.'] + 1
sample_size = int(sample_size)/2.0 + record['s.'] + 1 sample_size = int(sample_size)/2.0 + record['s.'] + 1
return sample_size, line_size return sample_size, line_size, img_index
# converts known to ISIS keywords # converts known to ISIS keywords
def known(record): def known(record):
if record['known'] == 0: if record['known'] == 0:
return 'Free' return 'Free'
elif record['known'] == 1 or record['known'] == 2 or record['known'] == 3: elif record['known'] == 1 or record['known'] == 2 or record['known'] == 3:
return 'Constrained' return 'Constrained'
# converts +/- 180 system to 0 - 360 system # converts +/- 180 system to 0 - 360 system
def to_360(num): def to_360(num):
return num % 360 return num % 360
# ocentric to ographic latitudes # ocentric to ographic latitudes
def oc2og(dlat, dMajorRadius, dMinorRadius): def oc2og(dlat, dMajorRadius, dMinorRadius):
try: try:
dlat = math.radians(dlat) dlat = math.radians(dlat)
dlat = math.atan(((dMajorRadius / dMinorRadius)**2) * (math.tan(dlat))) dlat = math.atan(((dMajorRadius / dMinorRadius)**2) * (math.tan(dlat)))
dlat = math.degrees(dlat) dlat = math.degrees(dlat)
except: except:
print ("Error in oc2og conversion") print ("Error in oc2og conversion")
return dlat return dlat
# ographic to ocentric latitudes # ographic to ocentric latitudes
def og2oc(dlat, dMajorRadius, dMinorRadius): def og2oc(dlat, dMajorRadius, dMinorRadius):
try: try:
dlat = math.radians(dlat) dlat = math.radians(dlat)
dlat = math.atan((math.tan(dlat) / ((dMajorRadius / dMinorRadius)**2))) dlat = math.atan((math.tan(dlat) / ((dMajorRadius / dMinorRadius)**2)))
dlat = math.degrees(dlat) dlat = math.degrees(dlat)
except: except:
print ("Error in og2oc conversion") print ("Error in og2oc conversion")
return dlat return dlat
# gets eRadius and pRadius from a .prj file # gets eRadius and pRadius from a .prj file
def get_axis(file): def get_axis(file):
with open(atf_dict['PATH'] + '/' + file) as f: with open(file) as f:
from collections import defaultdict from collections import defaultdict
files = defaultdict(list) files = defaultdict(list)
for line in f: for line in f:
ext = line.strip().split(' ') ext = line.strip().split(' ')
files[ext[0]].append(ext[-1]) files[ext[0]].append(ext[-1])
eRadius = float(files['A_EARTH'][0]) eRadius = float(files['A_EARTH'][0])
pRadius = eRadius * (1 - float(files['E_EARTH'][0])) pRadius = eRadius * (1 - float(files['E_EARTH'][0]))
return eRadius, pRadius return eRadius, pRadius
# function to convert lat_Y_North to ISIS_lat # function to convert lat_Y_North to ISIS_lat
def lat_ISIS_coord(record, semi_major, semi_minor): def lat_ISIS_coord(record, semi_major, semi_minor):
ocentric_coord = og2oc(record['lat_Y_North'], semi_major, semi_minor) ocentric_coord = og2oc(record['lat_Y_North'], semi_major, semi_minor)
coord_360 = to_360(ocentric_coord) coord_360 = to_360(ocentric_coord)
return coord_360 return coord_360
# function to convert long_X_East to ISIS_lon # function to convert long_X_East to ISIS_lon
def lon_ISIS_coord(record, semi_major, semi_minor): def lon_ISIS_coord(record, semi_major, semi_minor):
ocentric_coord = og2oc(record['long_X_East'], semi_major, semi_minor) ocentric_coord = og2oc(record['long_X_East'], semi_major, semi_minor)
coord_360 = to_360(ocentric_coord) coord_360 = to_360(ocentric_coord)
return coord_360 return coord_360
def body_fix(record, semi_major, semi_minor): def body_fix(record, semi_major, semi_minor):
ecef = pyproj.Proj(proj='geocent', a=semi_major, b=semi_minor) ecef = pyproj.Proj(proj='geocent', a=semi_major, b=semi_minor)
lla = pyproj.Proj(proj='latlon', 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']) lon, lat, height = pyproj.transform(lla, ecef, record['long_X_East'], record['lat_Y_North'], record['ht'])
return lon, lat, height return lon, lat, height
def socet2isis(prj_file):
# 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) eRadius, pRadius = get_axis(prj_file)
new_df['s.'], new_df['l.'] = (zip(*new_df.apply(sample_size, axis=1)))
new_df['known'] = new_df.apply(known, axis=1)
new_df['lat_Y_North'] = new_df.apply(lat_ISIS_coord, semi_major = eRadius, semi_minor = pRadius, axis=1)
new_df['long_X_East'] = new_df.apply(lon_ISIS_coord, semi_major = eRadius, semi_minor = pRadius, axis=1)
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))
socet2isis('CTX_Athabasca_Middle.prj') 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))
%% Cell type:code id: tags: def socet2isis(prj_file):
# Read in and setup the atf dict of information
atf_dict = read_atf(prj_file)
``` python # Get the gpf and ipf files using atf dict
new_df 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):
serial_dict = dict()
for image in images:
snum = sn.generate_serial_number(os.path.join(path, image + extension))
snum = snum.replace('Mars_Reconnaissance_Orbiter', 'MRO')
serial_dict[image] = snum
return serial_dict
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
@singledispatch # Setup stuffs for the cub information namely the path and extension
def read_ipf(arg): path = '/Volumes/Blueman/'
return str(arg) extension = '.lev1.cub'
# new_df['known'] = new_df.apply(known, axis=1) prj_file = get_path('CTX_Athabasca_Middle_step0.atf')
@read_ipf.register(str)
def read_ipf_str(input_data):
"""
Read a socet ipf file into a pandas data frame
Parameters
----------
input_data : str
path to the an input data file
Returns
-------
df : pd.DataFrame
containing the ipf data with appropriate column names and indices
"""
# Check that the number of rows is matching the expected number
with open(input_data, 'r') as f:
for i, l in enumerate(f):
if i == 1:
cnt = int(l)
elif i == 2:
col = l
break
columns = np.genfromtxt(input_data, skip_header=2, dtype='unicode',
max_rows = 1, delimiter = ',')
# TODO: Add unicode conversion
d = [line.split() for line in open(input_data, 'r')]
d = np.hstack(np.array(d[3:]))
d = d.reshape(-1, 12)
df = pd.DataFrame(d, columns=columns)
file = os.path.split(os.path.splitext(input_data)[0])[1]
df['ipf_file'] = pd.Series(np.full((len(df['pt_id'])), file), index = df.index)
assert int(cnt) == len(df), 'Dataframe length {} does not match point length {}.'.format(int(cnt), len(df)) socet_df = socet2isis(prj_file)
# Soft conversion of numeric types to numerics, allows str in first col for point_id images = pd.unique(socet_df['ipf_file'])
df = df.apply(pd.to_numeric, errors='ignore')
return df serial_dict = serial_numbers(images, path, extension)
@read_ipf.register(list) # creates the control network
def read_ipf_list(input_data_list): cn.to_isis('/Volumes/Blueman/cn.net', socet_df, serial_dict)
""" ```
Read a socet ipf file into a pandas data frame
Parameters
----------
input_data_list : list
list of paths to the a set of input data files
Returns %% Output
-------
df : pd.DataFrame
containing the ipf data with appropriate column names and indices
"""
frames = []
for input_file in input_data_list: /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:
frames.append(read_ipf(input_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
df = pd.concat(frames) %% Cell type:code id: tags:
return df ``` python
``` ```
......
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