Commit 9f0b864f authored by Adam Paquette's avatar Adam Paquette
Browse files

Moved all transformations and small update to io_controlnetwork.

parent 064ad14c

plio/io/io_controlnetwork.py

+5 −5
Original line number Diff line number Diff line
@@ -189,10 +189,10 @@ class IsisStore(object): 
        version = find_in_dict(pvl_header, 'Version')



        if version == 2:

            point_attrs = [i for i in cnf._CONTROLPOINTFILEENTRYV0002.fields_by_name if i != 'measures']

            measure_attrs = [i for i in cnf._CONTROLPOINTFILEENTRYV0002_MEASURE.fields_by_name]

            self.point_attrs = [i for i in cnf._CONTROLPOINTFILEENTRYV0002.fields_by_name if i != 'measures']

            self.measure_attrs = [i for i in cnf._CONTROLPOINTFILEENTRYV0002_MEASURE.fields_by_name]



        cols = point_attrs + measure_attrs

        cols = self.point_attrs + self.measure_attrs



        cp = cnf.ControlPointFileEntryV0002()

        self._handle.seek(header_start_byte)
@@ -204,10 +204,10 @@ class IsisStore(object): 
        pts = []

        for s in pbuf_header.pointMessageSizes:

            cp.ParseFromString(self._handle.read(s))

            pt = [getattr(cp, i) for i in point_attrs if i != 'measures']

            pt = [getattr(cp, i) for i in self.point_attrs if i != 'measures']



            for measure in cp.measures:

                meas = pt + [getattr(measure, j) for j in measure_attrs]

                meas = pt + [getattr(measure, j) for j in self.measure_attrs]

                pts.append(meas)

        df = IsisControlNetwork(pts, columns=cols)

        df.header = pvl_header

plio/spatial/transformations.py

+152 −8
Original line number Diff line number Diff line 
import os

import pvl

import math

import pyproj



import numpy as np



import plio.io.isis_serial_number as sn

from plio.utils.utils import find_in_dict



def line_sample_size(record, path):

    """
@@ -165,7 +167,7 @@ def get_axis(file): 
            files[ext[0]].append(ext[-1])



        eRadius = float(files['A_EARTH'][0])

        pRadius = eRadius * (1 - float(files['E_EARTH'][0]))

        pRadius = eRadius * math.sqrt(1 - (float(files['E_EARTH'][0]) ** 2))



        return eRadius, pRadius
@@ -219,7 +221,57 @@ def lon_ISIS_coord(record, semi_major, semi_minor): 
    coord_360 = to_360(ocentric_coord)

    return coord_360



def body_fix(record, semi_major, semi_minor, inverse = False):

def lat_socet_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

    """

    ographic_coord = oc2og(record['lat_Y_North'], semi_major, semi_minor)

    coord_180 = ((ographic_coord + 180) % 360) - 180

    return coord_180



def lon_socet_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

    """

    ographic_coord = oc2og(record['long_X_East'], semi_major, semi_minor)

    coord_180 = ((ographic_coord + 180) % 360) - 180

    return coord_180



def body_fix(record, semi_major, semi_minor, inverse = False, **kwargs):

    """

    Transforms latitude, longitude, and height of a socet point into

    a body fixed point
@@ -245,10 +297,10 @@ def body_fix(record, semi_major, semi_minor, inverse = False): 
    lla = pyproj.Proj(proj='latlon', a=semi_major, b=semi_minor)



    if inverse:

        lon, lat, height = pyproj.transform(ecef, lla, record[0], record[1], record[2])

        lon, lat, height = pyproj.transform(ecef, lla, record[0], record[1], record[2], **kwargs)

        return lon, lat, height

    else:

        y, x, z = pyproj.transform(lla, ecef, record[0], record[1], record[2])

        y, x, z = pyproj.transform(lla, ecef, record[0], record[1], record[2], **kwargs)

        return y, x, z



def stat_toggle(record):
@@ -257,7 +309,59 @@ def stat_toggle(record): 
    else:

        return False



def apply_transformations(atf_dict, df):

def apply_isis_transformations(df, eRadius, pRadius, serial_dict, extension, cub_path):

    """

    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



    """

    # Convert from geocentered coords (x, y, z), to lat lon coords (latitude, longitude, alltitude)

    ecef = np.array([[df['long_X_East']], [df['lat_Y_North']], [df['ht']]])

    lla = body_fix(ecef, semi_major = eRadius, semi_minor = pRadius, inverse=True)

    df['long_X_East'], df['lat_Y_North'], df['ht'] = lla[0][0], lla[1][0], lla[2][0]



    # df['lat_Y_North'] = df.apply(lat_socet_coord, semi_major = eRadius, semi_minor = pRadius, axis=1)

    # df['long_X_East'] = df.apply(lon_socet_coord, semi_major = eRadius, semi_minor = pRadius, axis=1)



    # Update the stat fields and add the val field as it is just a clone of stat

    df['stat'] = df.apply(ignore_toggle, axis = 1)

    df['val'] = df['stat']



    # Update the known field, add the ipf_file field for saving, and

    # update the line, sample using data from the cubes

    df['known'] = df.apply(reverse_known, axis = 1)

    df['ipf_file'] = df['serialnumber'].apply(lambda serial_number: serial_dict[serial_number])

    df['l.'], df['s.'] = zip(*df.apply(fix_sample_line, serial_dict = serial_dict,

                                       extension = extension,

                                       cub_path = cub_path, axis = 1))



    # Add dummy for generic value setting

    x_dummy = lambda x: np.full(len(df), x)



    df['sig0'] = x_dummy(1)

    df['sig1'] = x_dummy(1)

    df['sig2'] = x_dummy(1)



    df['res0'] = x_dummy(0)

    df['res1'] = x_dummy(0)

    df['res2'] = x_dummy(0)



    df['fid_x'] = x_dummy(0)

    df['fid_y'] = x_dummy(0)



    df['no_obs'] = x_dummy(1)

    df['fid_val'] = x_dummy(0)



def apply_socet_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
@@ -276,6 +380,9 @@ def apply_transformations(atf_dict, df): 


    eRadius, pRadius = get_axis(prj_file)



    # 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)



    lla = np.array([[df['long_X_East']], [df['lat_Y_North']], [df['ht']]])



    ecef = body_fix(lla, semi_major = eRadius, semi_minor = pRadius, inverse=False)
@@ -343,7 +450,6 @@ def compute_sigma_covariance_matrix(lat, lon, rad, latsigma, lonsigma, radsigma, 
    rectcov : ndarray

              (2,3) covariance matrix

    """



    lat = math.radians(lat)

    lon = math.radians(lon)
@@ -355,8 +461,8 @@ def compute_sigma_covariance_matrix(lat, lon, rad, latsigma, lonsigma, radsigma, 


    # SetSphericalSigmas

    cov = np.eye(3,3)

    cov[0,0] = scaled_lat_sigma ** 2

    cov[1,1] = scaled_lon_sigma ** 2

    cov[0,0] = math.radians(scaled_lat_sigma) ** 2

    cov[1,1] = math.radians(scaled_lon_sigma) ** 2

    cov[2,2] = radsigma ** 2



    # Approximate the Jacobian
@@ -391,3 +497,41 @@ def compute_sigma_covariance_matrix(lat, lon, rad, latsigma, lonsigma, radsigma, 
def compute_cov_matrix(record, semimajor_axis):

    cov_matrix = compute_sigma_covariance_matrix(record['lat_Y_North'], record['long_X_East'], record['ht'], record['sig0'], record['sig1'], record['sig2'], semimajor_axis)

    return cov_matrix.ravel().tolist()



def reverse_known(record):

    """

    Converts the known field from an isis dataframe into the

    socet known column



    Parameters

    ----------

    record : object

             Pandas series object



    Returns

    -------

    : str

      String representation of a known field

    """

    record_type = record['known']

    if record_type == 0 or record_type == 2:

        return 0



    elif record_type == 1 or record_type == 3 or record_type == 4:

        return 3



def fix_sample_line(record, serial_dict, extension, cub_path):

    # Cube location to load

    cube = pvl.load(os.path.join(cub_path, serial_dict[record['serialnumber']] + extension))

    line_size = find_in_dict(cube, 'Lines')

    sample_size = find_in_dict(cube, 'Samples')



    new_line = record['l.'] - (int(line_size)/2.0) - 1

    new_sample = record['s.'] - (int(sample_size)/2.0) - 1

    return new_line, new_sample



def ignore_toggle(record):

    if record['stat'] == True:

        return 0

    else:

        return 1