Merge pull request #2 from acpaquette/master

%% 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")

# 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.': 'x', 's.': 'y',

    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:

        serial_dict[image] = sn.generate_serial_number(os.path.join(path, image + extension))

        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:

``` 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')

socet_df = socet2isis(prj_file)

images = pd.unique(socet_df['ipf_file'])

serial_dict = serial_numbers(images, path, extension)

# creates the control network

cnet = cn.to_isis('/Volumes/Blueman/cn.csv', socet_df, serial_dict)

cn.to_isis('/Volumes/Blueman/cn.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

```