class StatusWorker(Thread):
def __init__(self, main_window):
Thread.__init__(self)
self._main_window = main_window
self.d = Datasource()
self.d.token()
self.start()
def run(self):
while True:
result = self.d.action("status", {})
wx.PostEvent(self._main_window, ResultEvent(GET_STATUS_ID, result) )
time.sleep(1)
class DataWorker(Thread):
def __init__(self, main_window):
Thread.__init__(self)
self._main_window = main_window
self.d = Datasource()
self.d.token()
self.start()
def run(self):
while True:
result = self.d.action("exchange_rate", {})
wx.PostEvent(self._main_window, ResultEvent(GET_EXCHANGE_RATE_ID, result) )
time.sleep(1)
def classify_XOR():
#Load Dataset
P, T, Ptest, Ttest = dts.loadDataset_XOR()
input_shape = (P.shape[1], )
output_shape = T.shape[1] # Number of Dense neurons at output layer
### Build Model
dendral_neurons = 6
lr = 0.08971484393708822
activation = 'tanh'
model = bm.build_HybridModel_MLNN(dendral_neurons, activation, input_shape,
output_shape)
[hist, train_time] = bm.train_HybridModel_MLNN(model,
lr,
P,
T,
Ptest,
Ttest,
batch_size=512,
nb_epoch=100,
v_verbose=False)
print("\n\t Dataset XOR: ")
print("\n\t Classificacion: " + str(hist.history['val_acc'][-1]))
plt_util.my_plot_train_loss(hist)
def load_tile(t_query):
"""load a single tile (image)
Gets the image path from the \
:data:`TileQuery.RUNTIME`. ``IMAGE`` attribute.
Gets the position of the image with the whole \
volume from :meth:`TileQuery.all_scales`, \
:meth:`TileQuery.tile_origin`, and \
:meth:`TileQuery.blocksize`.
Arguments
-----------
t_query: :class:`TileQuery`
With file path and image position
Returns
--------
numpy.ndarray
1/H/W image volume
"""
# call superclass
Datasource.load_tile(t_query)
# Get needed field from t_query
boss_field = t_query.RUNTIME.IMAGE.SOURCE.BOSS
# Get parameters from t_query
tile_start = boss_field.INFO.START.VALUE
path_dict = boss_field.PATHS.VALUE
i_z, i_y, i_x = t_query.index_zyx + tile_start
# Attempt to get path from dictionary
z_path = path_dict.get(i_z, {})
if type(z_path) is dict:
# Get path from dictionary
path = z_path.get(i_y, {}).get(i_x, '')
else:
# Get path from string
path = z_path.format(column=i_x, row=i_y)
# Sanity check returns empty tile
if not len(path) or not os.path.exists(path):
return []
# Read the image from the file
return BossGrid.imread(path)[np.newaxis]
def load_tile(t_query):
"""load a single tile (image)
Gets the image path from the \
:data:`TileQuery.RUNTIME`. ``IMAGE`` attribute.
Gets the position of the image with the whole \
volume from :meth:`TileQuery.all_scales`, \
:meth:`TileQuery.tile_origin`, and \
:meth:`TileQuery.blocksize`.
Arguments
-----------
t_query: :class:`TileQuery`
With file path and image position
Returns
--------
numpy.ndarray
1/H/W image volume
"""
# call superclass
Datasource.load_tile(t_query)
# Get needed field from t_query
boss_field = t_query.RUNTIME.IMAGE.SOURCE.BOSS
# Get parameters from t_query
tile_start = boss_field.INFO.START.VALUE
path_dict = boss_field.PATHS.VALUE
i_z, i_y, i_x = t_query.index_zyx + tile_start
# Attempt to get path from dictionary
z_path = path_dict.get(i_z,{})
if type(z_path) is dict:
# Get path from dictionary
path = z_path.get(i_y,{}).get(i_x,'')
else:
# Get path from string
path = z_path.format(column=i_x, row=i_y)
# Sanity check returns empty tile
if not len(path) or not os.path.exists(path):
return []
# Read the image from the file
return BossGrid.imread(path)[np.newaxis]
def preload_source(t_query):
"""load info from example tile (image)
Arguments
-----------
t_query: :class:`TileQuery`
Only the file path is needed
Returns
--------
dict
* :data:`OUTPUT.INFO`.``TYPE.NAME`` -- \
numpy datatype of any given tile
* :data:`RUNTIME.IMAGE`.``BLOCK.NAME`` -- \
numpy 3x1 array of any given tile shape
* :data:`OUTPUT.INFO`.``SIZE.NAME`` -- \
numpy 3x1 array of full volume shape
"""
# read all tifs in tifs folder
search = os.path.join(t_query.path, '*')
depth = len(list(glob.glob(search)))
# Should count files on filesystem
N_FILES = np.uint32([depth, 1, 1])
tile_0 = ImageStack.load_tile(t_query)
# Return empty if can't load first tile
if not len(tile_0):
return {}
# Get properties from example tile
FILE_SIZE = tile_0.shape
FULL_SIZE = FILE_SIZE * N_FILES
DATA_TYPE = str(tile_0.dtype)
# 'block-size', 'dimensions', and 'data-type'
k_block = t_query.RUNTIME.IMAGE.BLOCK.NAME
k_size = t_query.OUTPUT.INFO.SIZE.NAME
k_type = t_query.OUTPUT.INFO.TYPE.NAME
# Combine results with parent method
common = Datasource.preload_source(t_query)
return dict(
common, **{
k_block: np.uint32([FILE_SIZE]),
k_size: np.uint32(FULL_SIZE),
k_type: DATA_TYPE,
})
def preload_source(t_query):
"""load info from example tile (image)
Arguments
-----------
t_query: :class:`TileQuery`
Only the file path is needed
Returns
--------
dict
* :data:`OUTPUT.INFO`.``TYPE.NAME`` -- \
numpy datatype of any given tile
* :data:`RUNTIME.IMAGE`.``BLOCK.NAME`` -- \
numpy 3x1 array of any given tile shape
* :data:`OUTPUT.INFO`.``SIZE.NAME`` -- \
numpy 3x1 array of full volume shape
"""
# read all tifs in tifs folder
search = os.path.join(t_query.path, '*')
depth = len(list(glob.glob(search)))
# Should count files on filesystem
N_FILES = np.uint32([depth, 1, 1])
tile_0 = ImageStack.load_tile(t_query)
# Return empty if can't load first tile
if not len(tile_0):
return {}
# Get properties from example tile
FILE_SIZE = tile_0.shape
FULL_SIZE = FILE_SIZE * N_FILES
DATA_TYPE = str(tile_0.dtype)
# 'block-size', 'dimensions', and 'data-type'
k_block = t_query.RUNTIME.IMAGE.BLOCK.NAME
k_size = t_query.OUTPUT.INFO.SIZE.NAME
k_type = t_query.OUTPUT.INFO.TYPE.NAME
# Combine results with parent method
common = Datasource.preload_source(t_query)
return dict(common, **{
k_block: np.uint32([FILE_SIZE]),
k_size: np.uint32(FULL_SIZE),
k_type: DATA_TYPE,
})
def preload_source(t_query):
"""load info from example tile (image)
Arguments
-----------
t_query: :class:`TileQuery`
Only the file path is needed
Returns
--------
dict
* :data:`OUTPUT.INFO`.``TYPE.NAME`` -- \
numpy datatype of any given tile
* :data:`RUNTIME.IMAGE`.``BLOCK.NAME`` -- \
numpy 3x1 array of any given tile shape
* :data:`OUTPUT.INFO`.``SIZE.NAME`` -- \
numpy 3x1 array of full volume shape
"""
common = Datasource.preload_source(t_query)
return common
def classify_2C_5L_Spiral():
#Load Dataset
P, T, Ptest, Ttest = dts.loadDataset_Espiral_2Class_N_Loops()
input_shape = (P.shape[1], )
output_shape = T.shape[1] # Number of Dense neurons at output layer
### Build Model
dendral_neurons = 250
lr = 0.2
activation = 'tanh'
batch_size = 512
model = bm.build_HybridModel_MLNN(dendral_neurons, activation, input_shape,
output_shape)
[hist, train_time] = bm.train_HybridModel_MLNN(model,
lr,
P,
T,
Ptest,
Ttest,
batch_size=batch_size,
nb_epoch=1000,
v_verbose=False)
print("\n\t Dataset 2 class 5 Loops spiral : ")
print("\n\t Classificacion: " + str(hist.history['val_acc'][-1]))
plt_util.my_plot_train_loss(hist)
plt_util.plot_decision_boundary_2_class(P,
model,
batch_size,
h=0.05,
half_dataset=True,
expand=0.5,
x_lim=45,
y_lim=45)
def preload_source(t_query):
"""load info from example tile (image)
Calls :meth:`valid_path` to get filename and \
inner dataset path for the full h5 image volume.
Then gets three needed values from the given \
path from the :class:`TileQuery` t_query
Arguments
-----------
t_query: :class:`TileQuery`
Only the file path is needed
Returns
--------
dict
Will be empty if :meth:`valid_path` finds\
this filname to not give a valid h5 volume.
* :class:`RUNTIME` ``.IMAGE.BLOCK.NAME``
(numpy.ndarray) -- 3x1 for any give tile shape
* :class:`OUTPUT` ``.INFO.TYPE.NAME``
(str) -- numpy dtype of any given tile
* :class:`OUTPUT` ``.INFO.SIZE.NAME``
(numpy.ndarray) -- 3x1 for full volume shape
"""
# Keyword names
output = t_query.OUTPUT.INFO
runtime = t_query.RUNTIME.IMAGE
k_h5 = runtime.SOURCE.HDF5.NAME
# Get the max block size in bytes for a single tile
max_bytes = t_query.RUNTIME.CACHE.MAX_BLOCK.VALUE
max_bytes = int(max_bytes/64)
# Check if path is valid
keywords = HDF5.valid_path(t_query)
if not keywords:
return {}
# Validate highest in z file name and dataset
filename = keywords[k_h5][-1][0]
dataset = keywords[k_h5][-1][1]
offset = keywords[k_h5][-1][2]
# Load properties from H5 dataset
with h5py.File(filename,'r') as fd:
# Get the volume
vol = fd[dataset]
# Get a shape for all the files
shape = np.uint32(vol.shape)
shape[0] += offset
####
# Get a blockshape as a flat section
####
# Get the bytes for a full slice
voxel_bytes = np.uint32(vol.dtype.itemsize)
slice_bytes = voxel_bytes * np.prod(shape[1:])
# Get the nearest tile size under cache limit
square_overage = np.ceil(slice_bytes / max_bytes)
side_scalar = np.ceil(np.sqrt(square_overage))
# Set the actual blocksize to be under the cache limit
plane_shape = np.ceil(shape[1:] / side_scalar)
max_block = np.r_[[64], plane_shape]
####
# Get max blocksizes for different resolutions
####
lo_res = 1
# Get all block sizes by halving the max block size
all_blocks = [shape/(2**res) for res in range(lo_res)]
block_array = np.clip(np.ceil(all_blocks), 1, max_block)
# return named keywords
keywords.update({
runtime.BLOCK.NAME: np.uint32(block_array),
output.SIZE.NAME: np.uint32(shape),
output.TYPE.NAME: str(HDF5.dtype(vol)),
})
# Combine results with parent method
common = Datasource.preload_source(t_query)
return dict(common, **keywords)
def preload_source(t_query):
"""load info from example tile (image)
Arguments
-----------
t_query: :class:`TileQuery`
Only the file path is needed
Returns
--------
dict
Will be empty if filename does not give \
a valid mojo directory.
* :class:`RUNTIME` ``.IMAGE.BLOCK.NAME``
(numpy.ndarray) -- 3x1 for any give tile shape
* :class:`OUTPUT` ``.INFO.TYPE.NAME``
(str) -- numpy dtype of any given tile
* :class:`OUTPUT` ``.INFO.SIZE.NAME``
(numpy.ndarray) -- 3x1 for full volume shape
"""
# Keyword names
output = t_query.OUTPUT.INFO
runtime = t_query.RUNTIME.IMAGE
k_format = runtime.SOURCE.MOJO.FORMAT.NAME
# Get the name and ending of the target folder
path_name = t_query.OUTPUT.INFO.PATH.VALUE
meta_file = os.path.join(path_name, Mojo._meta)
# Return if no meta file for mojo
if not os.path.exists(meta_file):
return {}
# Load the meta info
meta_info = ET.parse(meta_file).getroot().attrib
# Estimate the data type
n_bytes = int(meta_info['numBytesPerVoxel'])
dtype = 'uint{}'.format(8 * n_bytes)
# Get the data file exension
file_ext = meta_info['fileExtension']
# Get the block shape and full size
block_z = meta_info['numVoxelsPerTileZ']
block_y = meta_info['numVoxelsPerTileY']
block_x = meta_info['numVoxelsPerTileX']
full_z = meta_info['numVoxelsZ']
full_y = meta_info['numVoxelsY']
full_x = meta_info['numVoxelsX']
####
# Get max blocksizes for different resolutions
####
lo_res = int(meta_info['numTilesW'])
block_size = [block_z, block_y, block_x]
# Specify block_size for all resolutions
block_array = [block_size for res in range(lo_res)]
# Combine results with parent method
common = Datasource.preload_source(t_query)
return dict(common, **{
runtime.BLOCK.NAME: np.uint32(block_array),
output.SIZE.NAME: np.uint32([full_z, full_y, full_x]),
output.TYPE.NAME: dtype,
k_format: file_ext,
})
def preload_source(t_query):
"""load info from example tile (image)
Then gets three needed values from the given \
path from the :class:`TileQuery` t_query
Arguments
-----------
t_query: :class:`TileQuery`
Only the file path is needed
Returns
--------
dict
Will be empty if filename does not give \
a valid json file pointing to the tiff grid.
* :class:`RUNTIME` ``.IMAGE.BLOCK.NAME``
(numpy.ndarray) -- 3x1 for any give tile shape
* :class:`OUTPUT` ``.INFO.TYPE.NAME``
(str) -- numpy dtype of any given tile
* :class:`OUTPUT` ``.INFO.SIZE.NAME``
(numpy.ndarray) -- 3x1 for full volume shape
"""
# Keyword names
output = t_query.OUTPUT.INFO
runtime = t_query.RUNTIME.IMAGE
boss_field = runtime.SOURCE.BOSS
info_field = boss_field.INFO
block_field = info_field.BLOCK
full_field = info_field.EXTENT
start_field = info_field.START
# Get the name and ending of the target file
filename = t_query.OUTPUT.INFO.PATH.VALUE
ending = os.path.splitext(filename)[1]
# Return if the ending is not json
if ending not in BossGrid._meta_files:
return {}
# Return if the path does not exist
if not os.path.exists(filename):
return {}
# Get function to read the metainfo file
order = BossGrid._meta_files.index(ending)
reader = BossGrid._read[order]
# Get information from json file
with open(filename, 'r') as jd:
# Get all the filenames
all_info = reader(jd)
boss = all_info.get(boss_field.ALL, [])
info = all_info.get(info_field.NAME, {})
# Return if no metadata
if not len(info):
return {}
# All the paths
path_dict = {}
any_path = None
# Origin of first tile
start_info = info.get(start_field.NAME, {})
start_list = map(start_info.get, start_field.ZYX)
# Set default first tile origin
if any([s is None for s in start_list]):
start_list = start_field.VALUE
# Extract offset of first tile
tile_start = np.uint64(start_list)
any_y, any_x = tile_start[1:]
# Shape of one tile
block_info = info.get(block_field.NAME, {})
block_list = map(block_info.get, block_field.ZYX)
# Return if no block shape
if not all(block_list):
return {}
# Shape of full volume
full_info = info.get(full_field.NAME)
full_extent = map(full_info.get, full_field.ZYX)
# Return if no full extent shape
if not all(full_extent):
return {}
# Block shape as a numpy array
block_shape = np.uint64(block_list)
if block_shape.shape != (3,):
return {}
# Finally, list all the mip levels
block_shapes = block_shape[np.newaxis]
# Full shape as a numpy array
full_bounds = np.uint64(full_extent)
if full_bounds.shape != (3,2):
return {}
# Finally, get the full shape from extent
full_shape = np.diff(full_bounds).T[0]
# All paths in dictionary
for d in boss:
path = d.get(boss_field.PATH, '')
# Update the maximum value
z,y,x = map(d.get, boss_field.ZYX)
z_format = x is None or y is None
# Set any path
if not any_path:
any_path = path
if z_format:
any_path = path.format(column=any_x, row=any_y)
if not os.path.exists(any_path):
any_path = None
# Allow for simple section formats
if z_format:
path_dict[z] = path
continue
# Allow for specific paths per tile
if z not in path_dict:
path_dict[z] = {
y: {
x: path
}
}
continue
# Add column to dictionary
if y not in path_dict[z]:
path_dict[z][y] = {
x: path
}
continue
# Add row to dictionary
path_dict[z][y][x] = path
# Return if no paths
if not any_path:
return {}
# Get the tile size from a tile
any_tile = BossGrid.imread(any_path)
any_dtype = str(any_tile.dtype)
# All keys to follow API
keywords = {
start_field.NAME: tile_start,
boss_field.PATHS.NAME: path_dict,
runtime.BLOCK.NAME: block_shapes,
output.SIZE.NAME: full_shape,
output.TYPE.NAME: any_dtype,
}
# Combine results with parent method
common = Datasource.preload_source(t_query)
return dict(common, **keywords)
def preload_source(t_query):
"""load info from example tile (image)
Arguments
-----------
t_query: :class:`TileQuery`
Only the file path is needed
Returns
--------
dict
Will be empty if filename does not give \
a valid mojo directory.
* :class:`RUNTIME` ``.IMAGE.BLOCK.NAME``
(numpy.ndarray) -- 3x1 for any give tile shape
* :class:`OUTPUT` ``.INFO.TYPE.NAME``
(str) -- numpy dtype of any given tile
* :class:`OUTPUT` ``.INFO.SIZE.NAME``
(numpy.ndarray) -- 3x1 for full volume shape
"""
# Keyword names
output = t_query.OUTPUT.INFO
runtime = t_query.RUNTIME.IMAGE
k_format = runtime.SOURCE.MOJO.FORMAT.NAME
# Get the name and ending of the target folder
path_name = t_query.OUTPUT.INFO.PATH.VALUE
meta_file = os.path.join(path_name, Mojo._meta)
# Return if no meta file for mojo
if not os.path.exists(meta_file):
return {}
# Load the meta info
meta_info = ET.parse(meta_file).getroot().attrib
# Estimate the data type
n_bytes = int(meta_info['numBytesPerVoxel'])
dtype = 'uint{}'.format(8 * n_bytes)
# Get the data file exension
file_ext = meta_info['fileExtension']
# Get the block shape and full size
block_z = meta_info['numVoxelsPerTileZ']
block_y = meta_info['numVoxelsPerTileY']
block_x = meta_info['numVoxelsPerTileX']
full_z = meta_info['numVoxelsZ']
full_y = meta_info['numVoxelsY']
full_x = meta_info['numVoxelsX']
####
# Get max blocksizes for different resolutions
####
lo_res = int(meta_info['numTilesW'])
block_size = [block_z, block_y, block_x]
# Specify block_size for all resolutions
block_array = [block_size for res in range(lo_res)]
# Combine results with parent method
common = Datasource.preload_source(t_query)
return dict(
common, **{
runtime.BLOCK.NAME: np.uint32(block_array),
output.SIZE.NAME: np.uint32([full_z, full_y, full_x]),
output.TYPE.NAME: dtype,
k_format: file_ext,
})
def load_tile(t_query):
"""load a single tile (image)
Gets the image path from the \
:data:`TileQuery.RUNTIME`. ``IMAGE`` attribute.
Gets the position of the image with the whole \
volume from :meth:`TileQuery.all_scales`, \
:meth:`TileQuery.tile_origin`, and \
:meth:`TileQuery.blocksize`.
Arguments
-----------
t_query: :class:`TileQuery`
With file path and image position
Returns
-----------
np.ndarray
An image array that may be as large \
as an entire full resolution slice of \
the whole hdf5 volume. Based on the value \
of :meth:`TileQuery.all_scales`, this array \
will likely be downsampled by to a small fraction \
of the full tile resolution.
"""
# call superclass
Datasource.load_tile(t_query)
# Load data for all the h5 files
h5_files = t_query.RUNTIME.IMAGE.SOURCE.HDF5.VALUE
# Get all the z indices and coordinates
z_stops = list(enumerate(zip(*h5_files)[-1]))
z_starts = z_stops[::-1]
# Find the region to crop
sk, sj, si = t_query.all_scales
[z0, y0, x0], [z1, y1, x1] = t_query.source_tile_bounds
# Get the scaled blocksize for the output array
zb, yb, xb = t_query.blocksize
# get the right h5 files for the current z index
start_z = next((i for i, z in z_starts if z <= z0), 0)
stop_z = next((i for i, z in z_stops if z >= z1), len(z_stops))
needed_files = [h5_files[zi] for zi in range(start_z, stop_z)]
####
# Load from all needed files
####
dtype = getattr(np, t_query.OUTPUT.INFO.TYPE.VALUE)
# Make the full volume for all needed file volumes
full_vol = np.zeros([zb, yb, xb], dtype=dtype)
# Get the first offset
offset_0 = needed_files[0][-1]
# Loop through all needed h5 files
for h5_file in needed_files:
# Offset for this file
z_offset = h5_file[-1]
# Get input and output start
iz0 = max(z0 - z_offset, 0)
# Scale output bounds by z-scale
oz0 = (z_offset - offset_0) // sk
# Load the image region from the h5 file
with h5py.File(h5_file[0]) as fd:
# read from one file
vol = fd[h5_file[1]]
# Get the input and output end-bounds
iz1 = min(z1 - z_offset, vol.shape[0])
# Scale the output bounds by the z-scale
dz = iz1 - iz0
oz1 = oz0 + dz // sk
# Get the volume from one file
file_vol = vol[iz0:iz1:sk, y0:y1:sj, x0:x1:si]
yf, xf = file_vol.shape[1:]
# Add the volume to the full volume
full_vol[oz0:oz1, :yf, :xf] = file_vol
# Combined from all files
return full_vol
def preload_source(t_query):
"""load info from example tile (image)
Calls :meth:`valid_path` to get filename and \
inner dataset path for the full h5 image volume.
Then gets three needed values from the given \
path from the :class:`TileQuery` t_query
Arguments
-----------
t_query: :class:`TileQuery`
Only the file path is needed
Returns
--------
dict
Will be empty if :meth:`valid_path` finds\
this filname to not give a valid h5 volume.
* :class:`RUNTIME` ``.IMAGE.BLOCK.NAME``
(numpy.ndarray) -- 3x1 for any give tile shape
* :class:`OUTPUT` ``.INFO.TYPE.NAME``
(str) -- numpy dtype of any given tile
* :class:`OUTPUT` ``.INFO.SIZE.NAME``
(numpy.ndarray) -- 3x1 for full volume shape
"""
# Keyword names
output = t_query.OUTPUT.INFO
runtime = t_query.RUNTIME.IMAGE
k_h5 = runtime.SOURCE.HDF5.NAME
# Get the max block size in bytes for a single tile
max_bytes = t_query.RUNTIME.CACHE.MAX_BLOCK.VALUE
max_bytes = int(max_bytes / 64)
# Check if path is valid
keywords = HDF5.valid_path(t_query)
if not keywords:
return {}
# Validate highest in z file name and dataset
filename = keywords[k_h5][-1][0]
dataset = keywords[k_h5][-1][1]
offset = keywords[k_h5][-1][2]
# Load properties from H5 dataset
with h5py.File(filename, 'r') as fd:
# Get the volume
vol = fd[dataset]
# Get a shape for all the files
shape = np.uint32(vol.shape)
shape[0] += offset
####
# Get a blockshape as a flat section
####
# Get the bytes for a full slice
voxel_bytes = np.uint32(vol.dtype.itemsize)
slice_bytes = voxel_bytes * np.prod(shape[1:])
# Get the nearest tile size under cache limit
square_overage = np.ceil(slice_bytes / max_bytes)
side_scalar = np.ceil(np.sqrt(square_overage))
# Set the actual blocksize to be under the cache limit
plane_shape = np.ceil(shape[1:] / side_scalar)
max_block = np.r_[[64], plane_shape]
####
# Get max blocksizes for different resolutions
####
lo_res = 1
# Get all block sizes by halving the max block size
all_blocks = [shape / (2**res) for res in range(lo_res)]
block_array = np.clip(np.ceil(all_blocks), 1, max_block)
# return named keywords
keywords.update({
runtime.BLOCK.NAME: np.uint32(block_array),
output.SIZE.NAME: np.uint32(shape),
output.TYPE.NAME: str(HDF5.dtype(vol)),
})
# Combine results with parent method
common = Datasource.preload_source(t_query)
return dict(common, **keywords)
def OnInit(self):
self.res = xrc.XmlResource('gui.xrc')
self.init_frame()
self.d = Datasource()
self.d.token()
return True
def __init__(self, main_window): Thread.__init__(self) self._main_window = main_window self.d = Datasource() self.d.token() self.start()
def load_tile(t_query):
"""load a single tile (image)
Gets the image path from the \
:data:`TileQuery.RUNTIME`. ``IMAGE`` attribute.
Gets the position of the image with the whole \
volume from :meth:`TileQuery.all_scales`, \
:meth:`TileQuery.tile_origin`, and \
:meth:`TileQuery.blocksize`.
Arguments
-----------
t_query: :class:`TileQuery`
With file path and image position
Returns
-----------
np.ndarray
An image array that may be as large \
as an entire full resolution slice of \
the whole hdf5 volume. Based on the value \
of :meth:`TileQuery.all_scales`, this array \
will likely be downsampled by to a small fraction \
of the full tile resolution.
"""
# call superclass
Datasource.load_tile(t_query)
# Load data for all the h5 files
h5_files = t_query.RUNTIME.IMAGE.SOURCE.HDF5.VALUE
# Get all the z indices and coordinates
z_stops = list(enumerate(zip(*h5_files)[-1]))
z_starts = z_stops[::-1]
# Find the region to crop
sk,sj,si = t_query.all_scales
[z0,y0,x0],[z1,y1,x1] = t_query.source_tile_bounds
# Get the scaled blocksize for the output array
zb,yb,xb = t_query.blocksize
# get the right h5 files for the current z index
start_z = next((i for i, z in z_starts if z <= z0), 0)
stop_z = next((i for i, z in z_stops if z >= z1), len(z_stops))
needed_files = [h5_files[zi] for zi in range(start_z, stop_z)]
####
# Load from all needed files
####
dtype = getattr(np, t_query.OUTPUT.INFO.TYPE.VALUE)
# Make the full volume for all needed file volumes
full_vol = np.zeros([zb, yb, xb], dtype = dtype)
# Get the first offset
offset_0 = needed_files[0][-1]
# Loop through all needed h5 files
for h5_file in needed_files:
# Offset for this file
z_offset = h5_file[-1]
# Get input and output start
iz0 = max(z0 - z_offset, 0)
# Scale output bounds by z-scale
oz0 = (z_offset - offset_0) // sk
# Load the image region from the h5 file
with h5py.File(h5_file[0]) as fd:
# read from one file
vol = fd[h5_file[1]]
# Get the input and output end-bounds
iz1 = min(z1 - z_offset, vol.shape[0])
# Scale the output bounds by the z-scale
dz = iz1 - iz0
oz1 = oz0 + dz // sk
# Get the volume from one file
file_vol = vol[iz0:iz1:sk, y0:y1:sj, x0:x1:si]
yf, xf = file_vol.shape[1:]
# Add the volume to the full volume
full_vol[oz0:oz1,:yf,:xf] = file_vol
# Combined from all files
return full_vol
def preload_source(t_query):
"""load info from example tile (image)
Then gets three needed values from the given \
path from the :class:`TileQuery` t_query
Arguments
-----------
t_query: :class:`TileQuery`
Only the file path is needed
Returns
--------
dict
Will be empty if filename does not give \
a valid json file pointing to the tiff grid.
* :class:`RUNTIME` ``.IMAGE.BLOCK.NAME``
(numpy.ndarray) -- 3x1 for any give tile shape
* :class:`OUTPUT` ``.INFO.TYPE.NAME``
(str) -- numpy dtype of any given tile
* :class:`OUTPUT` ``.INFO.SIZE.NAME``
(numpy.ndarray) -- 3x1 for full volume shape
"""
# Keyword names
output = t_query.OUTPUT.INFO
runtime = t_query.RUNTIME.IMAGE
boss_field = runtime.SOURCE.BOSS
info_field = boss_field.INFO
block_field = info_field.BLOCK
full_field = info_field.EXTENT
start_field = info_field.START
# Get the name and ending of the target file
filename = t_query.OUTPUT.INFO.PATH.VALUE
ending = os.path.splitext(filename)[1]
# Return if the ending is not json
if ending not in BossGrid._meta_files:
return {}
# Return if the path does not exist
if not os.path.exists(filename):
return {}
# Get function to read the metainfo file
order = BossGrid._meta_files.index(ending)
reader = BossGrid._read[order]
# Get information from json file
with open(filename, 'r') as jd:
# Get all the filenames
all_info = reader(jd)
boss = all_info.get(boss_field.ALL, [])
info = all_info.get(info_field.NAME, {})
# Return if no metadata
if not len(info):
return {}
# All the paths
path_dict = {}
any_path = None
# Origin of first tile
start_info = info.get(start_field.NAME, {})
start_list = map(start_info.get, start_field.ZYX)
# Set default first tile origin
if any([s is None for s in start_list]):
start_list = start_field.VALUE
# Extract offset of first tile
tile_start = np.uint64(start_list)
any_y, any_x = tile_start[1:]
# Shape of one tile
block_info = info.get(block_field.NAME, {})
block_list = map(block_info.get, block_field.ZYX)
# Return if no block shape
if not all(block_list):
return {}
# Shape of full volume
full_info = info.get(full_field.NAME)
full_extent = map(full_info.get, full_field.ZYX)
# Return if no full extent shape
if not all(full_extent):
return {}
# Block shape as a numpy array
block_shape = np.uint64(block_list)
if block_shape.shape != (3, ):
return {}
# Finally, list all the mip levels
block_shapes = block_shape[np.newaxis]
# Full shape as a numpy array
full_bounds = np.uint64(full_extent)
if full_bounds.shape != (3, 2):
return {}
# Finally, get the full shape from extent
full_shape = np.diff(full_bounds).T[0]
# All paths in dictionary
for d in boss:
path = d.get(boss_field.PATH, '')
# Update the maximum value
z, y, x = map(d.get, boss_field.ZYX)
z_format = x is None or y is None
# Set any path
if not any_path:
any_path = path
if z_format:
any_path = path.format(column=any_x, row=any_y)
if not os.path.exists(any_path):
any_path = None
# Allow for simple section formats
if z_format:
path_dict[z] = path
continue
# Allow for specific paths per tile
if z not in path_dict:
path_dict[z] = {y: {x: path}}
continue
# Add column to dictionary
if y not in path_dict[z]:
path_dict[z][y] = {x: path}
continue
# Add row to dictionary
path_dict[z][y][x] = path
# Return if no paths
if not any_path:
return {}
# Get the tile size from a tile
any_tile = BossGrid.imread(any_path)
any_dtype = str(any_tile.dtype)
# All keys to follow API
keywords = {
start_field.NAME: tile_start,
boss_field.PATHS.NAME: path_dict,
runtime.BLOCK.NAME: block_shapes,
output.SIZE.NAME: full_shape,
output.TYPE.NAME: any_dtype,
}
# Combine results with parent method
common = Datasource.preload_source(t_query)
return dict(common, **keywords)
class BitcoinATM(wx.App):
def OnInit(self):
self.res = xrc.XmlResource('gui.xrc')
self.init_frame()
self.d = Datasource()
self.d.token()
return True
def init_frame(self):
self.frame = self.res.LoadFrame(None, 'mainFrame')
self.scanPanel = xrc.XRCCTRL(self.frame, 'scanPanel')
self.insertPanel = xrc.XRCCTRL(self.frame, 'insertPanel')
self.insertPanel.GetParent().GetSizer().Hide(self.insertPanel)
self.insertPanel.GetParent().GetSizer().Layout()
self.boughtPanel = xrc.XRCCTRL(self.frame, 'boughtPanel')
self.boughtPanel.GetParent().GetSizer().Hide(self.boughtPanel)
self.boughtPanel.GetParent().GetSizer().Layout()
self.next_btn = xrc.XRCCTRL(self.scanPanel, 'next');
self.buy_btn = xrc.XRCCTRL(self.insertPanel, 'buy');
self.again_btn = xrc.XRCCTRL(self.boughtPanel, 'again');
self.service_status_label = xrc.XRCCTRL(self.scanPanel, 'service_status_label');
self.alert_bar = xrc.XRCCTRL(self.insertPanel, 'alert_bar')
self.price_label = xrc.XRCCTRL(self.scanPanel, 'price_label')
self.identity_textbox = xrc.XRCCTRL(self.scanPanel, 'identity')
self.identity_textbox.SetFocus()
self.amount_inserted_label = xrc.XRCCTRL(self.insertPanel, 'amount_inserted_label')
self.qr_code_image = xrc.XRCCTRL(self.boughtPanel, 'qr_code_image')
self.frame.Bind(wx.EVT_BUTTON, self.OnScanned, id=xrc.XRCID('next') )
self.frame.Bind(wx.EVT_BUTTON, self.OnBuy, id=xrc.XRCID('buy') )
self.frame.Bind(wx.EVT_BUTTON, self.OnAgain, id=xrc.XRCID('again') )
self.Connect(-1, -1, GET_EXCHANGE_RATE_ID, self.GetExchangeRate)
self.Connect(-1, -1, GET_INSERTED_AMOUNT_ID, self.GetInsertedAmount)
self.Connect(-1, -1, GET_STATUS_ID, self.GetServiceStatus)
StatusWorker(self)
DataWorker(self)
self.frame.Show()
def OnScanned(self, event):
self.scanPanel.GetParent().GetSizer().Hide(self.scanPanel)
self.scanPanel.GetParent().GetSizer().Layout()
self.insertPanel.GetParent().GetSizer().Show(self.insertPanel)
self.insertPanel.GetParent().GetSizer().Layout()
try:
self.acceptor = Acceptor(self)
except IOError as e:
print e
except:
raise
def OnBuy(self, event):
try:
self.acceptor.abort()
except AttributeError as e:
print e
# send request to bitcoin api and get bitcoin private key
#
amount = self.amount_inserted_label.GetLabel()
result = self.d.action("exchange", {'amount': amount} )
if(result['meta']['code'] != 200):
self.alert_bar.SetLabel(result['meta']['status'])
self.alert_bar.SetForegroundColour("red");
else:
self.CreateQR(result['wif'])
self.insertPanel.GetParent().GetSizer().Hide(self.insertPanel)
self.insertPanel.GetParent().GetSizer().Layout()
self.boughtPanel.GetParent().GetSizer().Show(self.boughtPanel)
self.boughtPanel.GetParent().GetSizer().Layout()
self.amount_inserted_label.SetLabel("")
def OnAgain(self, event):
self.boughtPanel.GetParent().GetSizer().Hide(self.boughtPanel)
self.scanPanel.GetParent().GetSizer().Layout()
self.scanPanel.GetParent().GetSizer().Show(self.scanPanel)
self.boughtPanel.GetParent().GetSizer().Layout()
def CreateQR(self, string):
qr = QRCode(version=1, box_size=3, border=1)
qr.add_data(string)
qr.make(fit=True)
im = qr.make_image()
qrfile = os.path.join("tmp", str(time.time() ) + ".png")
image = open(qrfile, 'wb')
im.save(image, "PNG")
self.qr_code_image.SetBitmap(wx.BitmapFromImage(wx.Image(qrfile, wx.BITMAP_TYPE_ANY) ) )
def GetExchangeRate(self, event):
self.price_label.SetLabel(str(event.data['exchange_rate']) )
def GetInsertedAmount(self, event):
self.amount_inserted_label.SetLabel(str(event.data) )
def GetServiceStatus(self, event):
self.service_status_label.SetLabel("Status: " + str(event.data['meta']['status']) )
if(event.data['meta']['code'] != 200):
self.next_btn.Disable()
self.buy_btn.Disable()
self.again_btn.Disable()
