ing imports in iPython notebooks. (52245c19) · Commits · aflab / astrogeology / Autocnet

notebooks/ISIS Serial Numbers.ipynb

+1 −1

Changes for notebooks/ISIS Serial Numbers.ipynb: 1 added line, 1 removed line.
Original line number	Diff line number	Diff line
		%% Cell type:code id: tags:

		``` python
		import os
		import sys
		print(os.path.abspath('../'))
		sys.path.insert(0, os.path.abspath('../'))

		from functools import reduce
		import glob
		import re

		from autocnet.graph import network
		from autocnet.fileio.sqlalchemy_json.alchemy import NestedJsonObject
		from plio.sqlalchemy_json.alchemy import NestedJsonObject
		from autocnet.utils.utils import find_in_dict

		import sqlalchemy
		from sqlalchemy.ext import declarative
		from sqlalchemy import orm

		import json
		import warnings


		import pvl
		from pvl._collections import PVLModule
		```

		%% Output

		/Users/jlaura/github/autocnet

		%% Cell type:markdown id: tags:

		## Generate the data
		The next three cells take a directory of cleaned `.trn` files (extra values like AUTO or OPTIONAL removed) and generate a `data.db` database of ISIS serial number translations.

		%% Cell type:code id: tags:

		``` python
		# Database population and a declared class

		Base = declarative.declarative_base()

		class Translations(Base):
		__tablename__ = 'isis_translations'
		id = sqlalchemy.Column(sqlalchemy.INTEGER, primary_key=True)
		mission = sqlalchemy.Column(sqlalchemy.String)
		instrument = sqlalchemy.Column(sqlalchemy.String)
		translation = sqlalchemy.Column(NestedJsonObject)

		def __init__(self, mission, instrument, translation):
		self.mission = mission
		self.instrument = instrument
		self.translation = translation

		class StringToMission(Base):
		__tablename__ = 'isis_mission_to_standard'
		id = sqlalchemy.Column(sqlalchemy.INTEGER, primary_key=True)
		key = sqlalchemy.Column(sqlalchemy.String)
		value = sqlalchemy.Column(sqlalchemy.String)

		def __init__(self, key, value):
		self.key = key
		self.value = value

		engine = sqlalchemy.create_engine('sqlite:///data.db')
		Base.metadata.bind = engine
		Base.metadata.create_all()
		session = orm.sessionmaker(bind=engine)()
		```

		%% Cell type:code id: tags:

		``` python
		files = glob.glob('../autocnet/examples/serial_number_translations/*.trn')
		for f in files:
		p = pvl.load(f)
		name = os.path.basename(f[:-16])
		try:
		v = re.findall("([a-z, 0-9])([A-Z, a-z, 0-9])", name)[0]
		mission, instrument = v
		except:
		v = re.findall("[a-z, 0-9]*", name)
		mission = v[0]
		instrument = None
		r = Translations(mission, instrument, p)
		session.add(r)
		session.commit()
		```

		%% Cell type:code id: tags:

		``` python
		# Build the mission names lookup table
		v = """
		Group = MissionName
		InputKey = SpacecraftName
		InputGroup = "IsisCube,Instrument"
		InputPosition = (IsisCube, Instrument)
		Translation = (Aircraft, "Aircraft")
		Translation = (Apollo15, "APOLLO 15")
		Translation = (Apollo15, "APOLLO15")
		Translation = (Apollo16, "APOLLO 16")
		Translation = (Apollo16, "APOLLO16")
		Translation = (Apollo17, "APOLLO 17")
		Translation = (Apollo17, "APOLLO17")
		Translation = (Cassini, Cassini-Huygens)
		# Translation = (Chan1, "CHANDRAYAAN-1 ORBITER")
		# Translation = (Chan1, CHANDRAYAAN1_ORBITER)
		# Translation = (Chan1, CHANDRAYAAN-1)
		Translation = (Chandrayaan1, "CHANDRAYAAN-1 ORBITER")
		Translation = (Chandrayaan1, CHANDRAYAAN1_ORBITER)
		Translation = (Chandrayaan1, CHANDRAYAAN-1)
		Translation = (Clementine1, CLEMENTINE_1)
		Translation = (Clementine1, "CLEMENTINE 1")
		Translation = (Dawn, "DAWN")
		Translation = (Galileo, "Galileo Orbiter")
		Translation = (Hayabusa, HAYABUSA)
		Translation = (Ideal, IdealSpacecraft)
		Translation = (Kaguya, KAGUYA)
		Translation = (Kaguya, SELENE-M)
		Translation = (Lo, "Lunar Orbiter 3")
		Translation = (Lo, "Lunar Orbiter 4")
		Translation = (Lo, "Lunar Orbiter 5")
		Translation = (Lro, "LUNAR RECONNAISSANCE ORBITER")
		Translation = (Lro, "Lunar Reconnaissance Orbiter")
		Translation = (Mariner10, Mariner_10)
		Translation = (Mariner10, MARINER_10)
		Translation = (Mer, "MARS EXPLORATION ROVER 1")
		Translation = (Mer, MARS_EXPLORATION_ROVER_1)
		Translation = (Mer, "MARS EXPLORATION ROVER 2")
		Translation = (Mer, "SIMULATED MARS EXPLORATION ROVER 1")
		Translation = (Mer, "SIMULATED MARS EXPLORATION ROVER 2")
		Translation = (Messenger, MESSENGER)
		Translation = (Messenger, Messenger)
		Translation = (Mex, "MARS EXPRESS")
		Translation = (Mex, "Mars Express")
		Translation = (Mgs, MARSGLOBALSURVEYOR)
		Translation = (Mgs, "MARS GLOBAL SURVEYOR")
		Translation = (Mro, "MARS RECONNAISSANCE ORBITER")
		Translation = (Mro, Mars_Reconnaissance_Orbiter)
		Translation = (NewHorizons, "NEW HORIZONS")
		Translation = (Near, NEAR)
		Translation = (Near, "NEAR EARTH ASTEROID RENDEZVOUS")
		Translation = (Odyssey, MARS_ODYSSEY)
		Translation = (OsirisRex, OSIRIS-REX)
		Translation = (Smart1, SMART1)
		Translation = (Viking1, VIKING_ORBITER_1)
		Translation = (Viking2, VIKING_ORBITER_2)
		Translation = (Voyager1, VOYAGER_1)
		Translation = (Voyager2, VOYAGER_2)
		End_Group
		End
		"""
		p = pvl.loads(v)

		for k, v in p['MissionName'].items():
		if k == 'Translation':
		r = StringToMission(v[1], v[0])
		session.add(r)
		session.commit()
		```

		%% Cell type:markdown id: tags:

		## Sample Query

		%% Cell type:code id: tags:

		``` python
		# Sample querying the database
		for i, j, t in session.query(Translations.mission, Translations.instrument, Translations.translation):
		print(i,j)
		d = PVLModule(t)
		print(d)
		break
		```

		%% Cell type:markdown id: tags:

		## Testing code to prototype the functionality now in autocnet

		%% Cell type:code id: tags:

		``` python
		class SerialNumberDecoder(pvl.decoder.PVLDecoder):
		"""
		A PVL Decoder class to handle cube label parsing for the purpose of creating a valid ISIS
		serial number. Inherits from the PVLDecoder in planetarypy's pvl module.
		"""
		def cast_unquoated_string(self, value):
		"""
		Overrides the parent class's method so that any un-quoted string type value found in the
		parsed pvl will just return the original value. This is needed so that keyword values
		are not re-formatted from what is originally in the ISIS cube label.

		Note: This affects value types that are recognized as null, boolean, number, datetime,
		et at.
		"""
		return value.decode('utf-8')


		def get_isis_translation(label):
		"""
		Compute the ISIS serial number for a given image using
		the input cube or the label extracted from the cube.

		Parameters
		----------
		label : dict or str
		A PVL dict object or file name to extract
		the PVL object from

		Returns
		-------
		translation : dict
		A PVLModule object containing the extracted
		translation file
		"""

		if not isinstance(label, PVLModule):
		label = pvl.load(label)

		cube_obj = find_in_dict(label, 'Instrument')

		# Grab the spacecraft name and run it through the ISIS lookup
		spacecraft_name = find_in_dict(cube_obj, 'SpacecraftName')
		for row in session.query(StringToMission).filter(StringToMission.key==spacecraft_name):
		spacecraft_name = row.value.lower()

		#Try and pull an instrument identifier
		try:
		instrumentid = find_in_dict(cube_obj, 'InstrumentId').capitalize()
		except:
		instrumentid = None

		# Grab the translation PVL object using the lookup
		for row in session.query(Translations).filter(Translations.mission==spacecraft_name,
		Translations.instrument==instrumentid):
		# Convert the JSON back to a PVL object
		translation = PVLModule(row.translation)

		return translation

		def extract_subgroup(data, key_list):
		return reduce(lambda d, k: d[k], key_list, data)

		def generate_serial_number(label):

		if not isinstance(label, PVLModule):
		label = pvl.load(label, cls=SerialNumberDecoder)

		# Get the translation information
		translation = get_isis_translation(label)
		serial_number = []

		# Sort the keys to ensure proper iteration order
		keys = sorted(translation.keys())
		for k in keys:
		group = translation[k]
		search_key = group['InputKey']
		search_position = group['InputPosition']
		search_translation = {group['Translation'][1]:group['Translation'][0]}
		print(search_key, search_position, search_translation)

		sub_group = extract_subgroup(label, search_position)
		serial_entry = sub_group[search_key]
		if serial_entry in search_translation.keys():
		serial_entry = search_translation[serial_entry]
		elif '' in search_translation.keys() and search_translation[''] != '*':
		serial_entry = search_translation['*']

		serial_number.append(serial_entry)

		return '/'.join(serial_number)

		```

		%% Output

		SpacecraftName ['IsisCube', 'Instrument'] {'*': 'APOLLO15'}
		InstrumentId ['IsisCube', 'Instrument'] {'': ''}
		StartTime ['IsisCube', 'Instrument'] {'': ''}
		APOLLO15/METRIC/1971-07-31T01:24:36.970

		%% Cell type:markdown id: tags:

		Edit below code for the correct path to an Apollo cube and uncomment to test. Must remain commented out for a non-failing build server-side.

		%% Cell type:code id: tags:

		``` python
		#serial = generate_serial_number('/Users/jlaura/Desktop/Apollo15/AS15-M-0296_sub4.cub')
		#print(serial)
		```

notebooks/Testing Slopes.ipynb

+2 −2

Changes for notebooks/Testing Slopes.ipynb: 2 added lines, 2 removed lines.
Original line number	Diff line number	Diff line
		%% Cell type:markdown id: tags:

		This notebook demonstrates a test of refining the fundamental matrix using the slopes between keypoints.

		%% Cell type:code id: tags:

		``` python
		import os
		import pandas as pd
		import sys
		sys.path.insert(0, os.path.abspath('..'))

		import unittest

		from autocnet.examples import get_path
		from autocnet.fileio.io_controlnetwork import to_isis
		from autocnet.fileio.io_controlnetwork import write_filelist
		from plio.io.io_controlnetwork import to_isis
		from plio.io.io_controlnetwork import write_filelist
		from autocnet.graph.network import CandidateGraph
		from autocnet.utils import utils

		%pylab inline
		```

		%% Output

		Populating the interactive namespace from numpy and matplotlib

		%% Cell type:code id: tags:

		``` python
		serial_numbers = {'AS15-M-0295_SML.png': '1971-07-31T01:24:11.754',
		'AS15-M-0296_SML.png': '1971-07-31T01:24:36.970',
		'AS15-M-0297_SML.png': '1971-07-31T01:25:02.243',
		'AS15-M-0298_SML.png': '1971-07-31T01:25:27.457',
		'AS15-M-0299_SML.png': '1971-07-31T01:25:52.669',
		'AS15-M-0300_SML.png': '1971-07-31T01:26:17.923'}

		for k, v in serial_numbers.items():
		serial_numbers[k] = 'APOLLO15/METRIC/{}'.format(v)
		```

		%% Cell type:code id: tags:

		``` python
		adjacency = get_path('two_image_adjacency.json')
		basepath = get_path('Apollo15')
		cg = CandidateGraph.from_adjacency(adjacency, basepath=basepath)

		cg.extract_features(method='sift', extractor_parameters={"nfeatures":500})
		cg.match_features(k=2)
		```

		%% Cell type:code id: tags:

		``` python
		for source, destination, edge in cg.edges_iter(data=True):
		# Perform the symmetry check
		edge.symmetry_check()
		# Perform the ratio test
		edge.ratio_check(clean_keys=['symmetry'])
		```

		%% Output

		/Users/jlaura/anaconda3/envs/autocnet/lib/python3.5/site-packages/pandas/core/frame.py:1997: UserWarning: Boolean Series key will be reindexed to match DataFrame index.
		"DataFrame index.", UserWarning)

		%% Cell type:code id: tags:

		``` python
		cg.apply_func_to_edges("compute_fundamental_matrix", clean_keys=['symmetry', 'ratio'])
		```

		%% Cell type:code id: tags:

		``` python
		f = cg.edge[0][1].fundamental_matrix
		```

		%% Cell type:code id: tags:

		``` python
		df=utils.calculate_slope(f.x1, f.x2)
		len(np.asarray(df).ravel())
		```

		%% Output

		11

		%% Cell type:code id: tags:

		``` python
		f.mask[f.mask==True].equals(f.mask[f.mask])
		```

		%% Output

		True

		%% Cell type:code id: tags:

		``` python
		nbr_inliers = 20
		fp = np.array(np.random.standard_normal((nbr_inliers, 2))) # inliers
		static_F = np.array([[4, 0.5, 10], [0.25, 1, 5], [0.2, 0.1, 1]])
		fph = np.hstack((fp, np.ones((nbr_inliers, 1))))
		tp = static_F.dot(fph.T)
		# normalize hom. coordinates
		tp /= tp[-1, :np.newaxis]
		df1 = pd.DataFrame(fp, columns=['x', 'y'])
		df2 = pd.DataFrame(tp.T[:, :2], columns=['x', 'y'])
		```

		%% Cell type:code id: tags:

		``` python
		df1
		```

		%% Output

		x y
		0 1.633181 0.662958
		1 -0.652132 0.815878
		2 -0.438907 1.047533
		3 -0.339436 1.383948
		4 -0.958286 0.682298
		5 0.235437 -0.778398
		6 -0.456880 -1.248944
		7 0.235843 -0.454797
		8 -0.189979 2.118751
		9 0.944133 0.408296
		10 -0.337530 -1.455450
		11 -0.835177 0.469812
		12 0.764976 1.178681
		13 2.096332 0.580255
		14 0.780332 -1.046638
		15 0.325916 0.629410
		16 -0.780760 0.846021
		17 0.477673 0.395407
		18 1.575866 0.773803
		19 -0.036507 0.557871

		%% Cell type:code id: tags:

		``` python
		df2
		```

		%% Output

		x y
		0 12.106982 4.358614
		1 8.199881 5.943098
		2 8.621809 5.838713
		3 8.719442 5.884208
		4 7.424377 6.209099
		5 10.887362 4.416272
		6 9.630884 4.640421
		7 10.697907 4.596401
		8 8.773865 6.023836
		9 11.369585 4.590168
		10 10.066923 4.396940
		11 7.834798 5.978798
		12 10.740136 5.012282
		13 12.641683 4.132114
		14 11.982098 3.945629
		15 10.298838 5.062288
		16 7.862533 6.086306
		17 10.667482 4.858555
		18 11.985440 4.429107
		19 9.664326 5.292150

		%% Cell type:code id: tags:

		``` python
		mask = df1.x > 0
		mask
		```

		%% Output

		0 True
		1 False
		2 False
		3 False
		4 False
		5 True
		6 False
		7 True
		8 False
		9 True
		10 False
		11 False
		12 True
		13 True
		14 True
		15 True
		16 False
		17 True
		18 True
		19 False
		Name: x, dtype: bool

		%% Cell type:code id: tags:

		``` python
		df1[mask]
		```

		%% Output

		x y
		0 1.633181 0.662958
		5 0.235437 -0.778398
		7 0.235843 -0.454797
		9 0.944133 0.408296
		12 0.764976 1.178681
		13 2.096332 0.580255
		14 0.780332 -1.046638
		15 0.325916 0.629410
		17 0.477673 0.395407
		18 1.575866 0.773803

		%% Cell type:code id: tags:

		``` python
		df2[mask]
		```

		%% Output

		x y
		0 12.106982 4.358614
		5 10.887362 4.416272
		7 10.697907 4.596401
		9 11.369585 4.590168
		12 10.740136 5.012282
		13 12.641683 4.132114
		14 11.982098 3.945629
		15 10.298838 5.062288
		17 10.667482 4.858555
		18 11.985440 4.429107

		%% Cell type:code id: tags:

		``` python
		df1[mask] = df2[mask]
		```

		%% Cell type:code id: tags:

		``` python
		df1
		```

		%% Output

		x y
		0 12.106982 4.358614
		1 -0.652132 0.815878
		2 -0.438907 1.047533
		3 -0.339436 1.383948
		4 -0.958286 0.682298
		5 10.887362 4.416272
		6 -0.456880 -1.248944
		7 10.697907 4.596401
		8 -0.189979 2.118751
		9 11.369585 4.590168
		10 -0.337530 -1.455450
		11 -0.835177 0.469812
		12 10.740136 5.012282
		13 12.641683 4.132114
		14 11.982098 3.945629
		15 10.298838 5.062288
		16 -0.780760 0.846021
		17 10.667482 4.858555
		18 11.985440 4.429107
		19 -0.036507 0.557871

notebooks/Tutorial with Visualization.ipynb

+1 −1

Changes for notebooks/Tutorial with Visualization.ipynb: 1 added line, 1 removed line.
Original line number	Diff line number	Diff line
		@@ -480,7 +480,7 @@
		"name": "python",
		"nbconvert_exporter": "python",
		"pygments_lexer": "ipython3",
		"version": "3.5.1"
		"version": "3.5.2"
		}
		},
		"nbformat": 4,