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Commit 5ca49f90 authored by Luise Odenthal's avatar Luise Odenthal
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exceptions in database added

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navipy/database/__init__.py
+ 146
− 59
View file @ 5ca49f90
......@@ -84,12 +84,15 @@ import pandas as pd
import sqlite3
import io
import warnings
import navipy.processing.tools as tools
def adapt_array(arr):
"""
http://stackoverflow.com/a/31312102/190597 (SoulNibbler)
"""
if array is None:
raise ValueError('array must not be None')
out = io.BytesIO()
np.save(out, arr)
out.seek(0)
......@@ -97,6 +100,8 @@ def adapt_array(arr):
def convert_array(text):
if text is None:
raise ValueError('text must not be None')
out = io.BytesIO(text)
out.seek(0)
return np.load(out)
......@@ -118,8 +123,11 @@ It creates three sql table on initialisation.
"""Initialisation of the database """
if not isinstance(filename, str):
raise TypeError('filename should be a string')
if not isinstance(channels, list):
raise TypeError('nb_channel should be an integer')
if (not isinstance(channels, list) or not isinstance(channels,np.array)):
raise TypeError('nb_channel should be a list or np array')
"""for c in channels:
if not c in ['R','G','B','D']:
raise ValueError('channels must be either R,G,B or D (Distance)')"""
self.filename = filename
self.channels = channels
self.normalisation_columns = list()
......@@ -150,9 +158,9 @@ It creates three sql table on initialisation.
timeout=10)
self.db_cursor = self.db.cursor()
for tablename, _ in self.tablecolumns.items():
assert self.table_exist(tablename),\
'{} does not contain a table named {}'.format(
filename, tablename)
if not self.table_exist(tablename):
raise Exception('{} does not contain a table named {}'.format(
filename, tablename))
elif self.create:
# Create database
self.db = sqlite3.connect(
......@@ -177,7 +185,8 @@ It creates three sql table on initialisation.
self.viewing_directions[..., 1] = ma
def table_exist(self, tablename):
assert isinstance(tablename, str), 'tablename should be a string'
if not isinstance(tablename, str):
raise TypeError('tablename should be a string')
self.db_cursor.execute(
"""
SELECT count(*)
......@@ -187,6 +196,12 @@ It creates three sql table on initialisation.
return bool(self.db_cursor.fetchone())
def check_data_validity(self, rowid):
if not isinstance(rowid,int):
raise TypeError('rowid must be an integer')
if rowid <= 0:
raise ValueError('rowid must be greater zero')
if rowid is np.nan:
raise ValueError('rowid must not be nan')
self.db_cursor.execute(
"""
SELECT count(*)
......@@ -210,9 +225,28 @@ It creates three sql table on initialisation.
valid = valid and bool(self.db_cursor.fetchone()[0])
return valid
def posid(self, posorient):
assert isinstance(posorient, pd.Series),\
'posorient should be a pandas Series'
def get_posid(self, posorient):
if no isinstance(posorient, pd.Series):
('posorient should be a pandas Series')
if posorient is not None:
if not isinstance(posorient, pd.Series):
raise TypeError('posorient should be a pandas Series')
if posorient.empty:
raise Exception('position must not be empty')
if 'x' not in posorient.index:
raise ValueError('missing index x')
if 'y' not in posorient.index:
raise ValueError('missing index y')
if 'z' not in posorient.index:
raise ValueError('missing index z')
if 'alpha_0' not in posorient.index:
raise ValueError('missing index alpha_0')
if 'alpha_1' not in posorient.index:
raise ValueError('missing index alpha_1')
if 'alpha_2' not in posorient.index:
raise ValueError('missing index alpha_2')
if not ~np.any(pd.isnull(posorient)):
raise ValueError('posorient must not contain nan')
where = """x>=? and x<=?"""
where += """and y>=? and y<=?"""
where += """and z>=? and z<=?"""
......@@ -277,6 +311,13 @@ class DataBaseLoad(DataBase):
def __init__(self, filename, channels=['R', 'G', 'B', 'D']):
"""Initialise the DataBaseLoader"""
if not isinstance(filename, str):
raise TypeError('filename should be a string')
if (not isinstance(channels, list) or not isinstance(channels,np.array)):
raise TypeError('nb_channel should be a list or np array')
for c in channels:
if not c in ['R','G','B','D']:
raise ValueError('channels must be either R,G,B or D (Distance)')
DataBase.__init__(self, filename, channels=channels)
@property
......@@ -315,10 +356,37 @@ database
return posorient
def read_posorient(self, posorient=None, rowid=None):
assert (posorient is None) or (rowid is None),\
'posorient and rowid can not be both None'
if no isinstance(posorient, pd.Series):
('posorient should be a pandas Series')
if posorient is not None:
rowid = self.posid(posorient)
if not isinstance(posorient, pd.Series):
raise TypeError('posorient should be a pandas Series')
if posorient.empty:
raise Exception('position must not be empty')
if 'x' not in posorient.index:
raise ValueError('missing index x')
if 'y' not in posorient.index:
raise ValueError('missing index y')
if 'z' not in posorient.index:
raise ValueError('missing index z')
if 'alpha_0' not in posorient.index:
raise ValueError('missing index alpha_0')
if 'alpha_1' not in posorient.index:
raise ValueError('missing index alpha_1')
if 'alpha_2' not in posorient.index:
raise ValueError('missing index alpha_2')
if not ~np.any(pd.isnull(posorient)):
raise ValueError('posorient must not contain nan')
if not isinstance(rowid,int):
raise TypeError('rowid must be an integer')
if rowid <= 0:
raise ValueError('rowid must be greater zero')
if rowid is np.nan:
raise ValueError('rowid must not be nan')
if (posorient is None) and (rowid is None):
Exception('posorient and rowid can not be both None')
if posorient is not None:
rowid = self.get_posid(posorient)
# Read images
tablename = 'position_orientation'
toreturn = pd.read_sql_query(
......@@ -333,26 +401,9 @@ database
toreturn = toreturn.astype(float)
return toreturn
def scene(self, posorient=None, rowid=None):
""" Return a scene at a position orientation or given rowid \
in a given database.
:param database: a DataBaseLoad class \
:param posorient: a pandas Series with index: \
['x','y','z','alpha_0,'alpha_1,'alpha_2'] (default None, i.e. not used)
:param rowid: a row identification integer for directly reading \
in the database (default None, i.e. not used).
:returns: a scene [elevation, azimuth, channel, 1] or \
[ommatidia,channel,1].
:rtype: np.ndarray
.. literalinclude:: example/database/scene.py
:lines: 14-15
.. plot:: example/database/scene.py
"""
if (posorient is None) and (rowid is None):
raise ValueError('posorient and rowid can not be both None')
def read_image(self, posorient=None, rowid=None):
if no isinstance(posorient, pd.Series):
('posorient should be a pandas Series')
if posorient is not None:
if not isinstance(posorient, pd.Series):
raise TypeError('posorient should be a pandas Series')
......@@ -372,16 +423,29 @@ database
raise ValueError('missing index alpha_2')
if not ~np.any(pd.isnull(posorient)):
raise ValueError('posorient must not contain nan')
rowid = self.posid(posorient)
if rowid is not None:
if not isinstance(rowid, int):
raise TypeError('rowid must be of type integer')
if rowid <= 0:
raise ValueError('rowid must be greater zero')
if rowid is np.nan:
raise ValueError('rowid must not be nan')
if not isinstance(rowid,int):
raise TypeError('rowid must be an integer')
if rowid <= 0:
raise ValueError('rowid must be greater zero')
if rowid is np.nan:
raise ValueError('rowid must not be nan')
if (posorient is None) and (rowid is None):
raise Exception('posorient and rowid can not be both None')
if posorient is not None:
rowid = self.get_posid(posorient)
"""Read an image at a given position-orientation or given id of row in the \
database.
:param posorient: a pandas Series with index \
['x','y','z','alpha_0','alpha_1','alpha_2']
:param rowid: an integer
:returns: an image
:rtype: numpy.ndarray
"""
if (posorient is None) and (rowid is None):
Exception('posorient and rowid can not be both None')
if posorient is not None:
rowid = self.get_posid(posorient)
# Read images
tablename = 'image'
self.db_cursor.execute(
......@@ -399,24 +463,37 @@ database
FROM {}
WHERE (rowid={})
""".format(tablename, rowid), self.db)
assert cmaxminrange.shape[0] == 1,\
'Error while reading normalisation factors'
if cmaxminrange.shape[0] != 1:
raise Exception('Error while reading normalisation factors')
cmaxminrange = cmaxminrange.iloc[0, :]
cmaxminrange.name = cmaxminrange.id
cmaxminrange.drop('id')
cmaxminrange = cmaxminrange.astype(float)
scene = self.denormalise_image(image, cmaxminrange)
scene = scene[..., np.newaxis]
return scene
return self.denormalise_image(image, cmaxminrange)
def denormalise_image(self, image, cmaxminrange):
assert len(image.shape) == 3,\
'image should be 3D array'
assert image.shape[2] == len(self.channels),\
'image does not have the required number of channels {}'.format(
len(self.channels))
assert isinstance(cmaxminrange, pd.Series),\
'cmaxminrange should be a pandas Series'
if len(image.shape) != 3:
raise Exception('image should be 3D array')
if image.shape[2] != len(self.channels):
raise Exception('image does not have the required number of channels {}'.format(
len(self.channels)))
if not isinstance(cmaxminrange, pd.Series):
raise Exception('cmaxminrange should be a pandas Series')
if cmaxminrange.empty:
raise Exception('cmaxminrange must not be empty')
for chan_n in self.channels:
if str(chan_n) + '_max' not in posorient.index:
raise ValueError('cminmax range is missing index '+str(chan_n) + '_max')
if str(chan_n) + '_min' not in posorient.index:
raise ValueError('cminmax range is missing index '+str(chan_n) + '_min')
if str(chan_n) + '_range' not in posorient.index:
raise ValueError('cminmax range is missing index '+str(chan_n) + '_range')
if any(np.isnan(cmaxminrange.loc[str(chan_n) + '_max'])):
raise ValueError('cmaxminrange contains nans')
if any(np.isnan(cmaxminrange.loc[str(chan_n) + '_min'])):
raise ValueError('cmaxminrange contains nans')
if any(np.isnan(cmaxminrange.loc[str(chan_n) + '_range'])):
raise ValueError('cmaxminrange contains nans')
denormed_im = np.zeros(image.shape, dtype=np.float)
maxval_nim = np.iinfo(image.dtype).max
#
......@@ -453,7 +530,7 @@ class DataBaseSave(DataBase):
def write_image(self, posorient, image):
normed_im, cmaxminrange = self.normalise_image(image, self.arr_dtype)
rowid = self.posid(posorient)
rowid = self.get_posid(posorient)
# Write image
tablename = 'image'
params = dict()
......@@ -469,10 +546,10 @@ class DataBaseSave(DataBase):
self.insert_replace(tablename, params)
def insert_replace(self, tablename, params):
assert isinstance(tablename, str),\
'table are named by string'
assert isinstance(params, dict),\
'params should be dictionary columns:val'
if not isinstance(tablename, str):
raise ValueError('table are named by string')
if not isinstance(params, dict):
raise ValueError('params should be dictionary columns:val')
params_list = list()
columns_str = ''
for key, val in params.items():
......@@ -498,6 +575,16 @@ class DataBaseSave(DataBase):
self.db.commit()
def normalise_image(self, image, dtype=np.uint8):
if not isinstance(image,np.ndarray):
raise TypeError('image must be np.array')
if any(np.isnan(image)):
raise ValueError('image must not contain nan values')
if image.shape[0]<=0 or image.shape[1]<=0:
raise Exception('image dimensions incorrect')
if image.shape[2]!=len(self.channels):
raise Exception('image channels number differs from given channel number')
if not tools.is_numeric_array(scene):
raise TypeError('scene is of non numeric type')
normed_im = np.zeros(image.shape, dtype=dtype)
maxval_nim = np.iinfo(normed_im.dtype).max
#
......
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