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Commit 2ec6ee84 authored by Valerio Mariani's avatar Valerio Mariani
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Code cleanup. Instroduced underscore notation for private functions, methods and attributes

parent 9675f57c
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...@@ -33,6 +33,7 @@ import numpy ...@@ -33,6 +33,7 @@ import numpy
_CXISimpleEntry = namedtuple('SimpleEntry', ['path', 'data', 'overwrite']) _CXISimpleEntry = namedtuple('SimpleEntry', ['path', 'data', 'overwrite'])
class _Stack: class _Stack:
def __init__(self, path, data, axes): def __init__(self, path, data, axes):
...@@ -47,6 +48,13 @@ class _Stack: ...@@ -47,6 +48,13 @@ class _Stack:
self._path = path self._path = path
self._axes = axes self._axes = axes
def is_there_data_to_write(self):
if self._data_to_write is not None:
return True
else:
return False
def write_initial_slice(self, file_handle, max_num_slices): def write_initial_slice(self, file_handle, max_num_slices):
file_handle.create_dataset(self._path, shape=(max_num_slices,) + self._data_shape, file_handle.create_dataset(self._path, shape=(max_num_slices,) + self._data_shape,
...@@ -337,7 +345,7 @@ class CXIWriter: ...@@ -337,7 +345,7 @@ class CXIWriter:
raise RuntimeError('The file already holds the maximum allowed number of slices, and should be closed') raise RuntimeError('The file already holds the maximum allowed number of slices, and should be closed')
for entry in self._cxi_stacks.values(): for entry in self._cxi_stacks.values():
if entry._data_to_write is None: if entry.is_there_data_to_write is False:
raise RuntimeError('The slice is incomplete and will not be written. The following stack is not ' raise RuntimeError('The slice is incomplete and will not be written. The following stack is not '
'present in the current slice:', entry.path) 'present in the current slice:', entry.path)
...@@ -376,4 +384,4 @@ class CXIWriter: ...@@ -376,4 +384,4 @@ class CXIWriter:
self._fh.close() self._fh.close()
self._file_is_open = False self._file_is_open = False
\ No newline at end of file
...@@ -64,8 +64,8 @@ def read_cbf_from_stream(stream): ...@@ -64,8 +64,8 @@ def read_cbf_from_stream(stream):
if len(cbf_obj.cif[cbf_obj.CIF_BINARY_BLOCK_KEY]) > int( if len(cbf_obj.cif[cbf_obj.CIF_BINARY_BLOCK_KEY]) > int(
cbf_obj.header["X-Binary-Size"]) + cbf_obj.start_binary + len(cbf_obj.STARTER): cbf_obj.header["X-Binary-Size"]) + cbf_obj.start_binary + len(cbf_obj.STARTER):
cbf_obj.cbs = cbf_obj.cif[cbf_obj.CIF_BINARY_BLOCK_KEY][:int(cbf_obj.header["X-Binary-Size"]) + cbf_obj.cbs = cbf_obj.cif[cbf_obj.CIF_BINARY_BLOCK_KEY][:int(cbf_obj.header["X-Binary-Size"]) +
cbf_obj.start_binary + cbf_obj.start_binary +
len(cbf_obj.STARTER)] len(cbf_obj.STARTER)]
else: else:
cbf_obj.cbs = cbf_obj.cif[cbf_obj.CIF_BINARY_BLOCK_KEY] cbf_obj.cbs = cbf_obj.cif[cbf_obj.CIF_BINARY_BLOCK_KEY]
binary_data = cbf_obj.cbs[cbf_obj.start_binary + len(cbf_obj.STARTER):] binary_data = cbf_obj.cbs[cbf_obj.start_binary + len(cbf_obj.STARTER):]
......
...@@ -460,8 +460,12 @@ def scatterplot_3d(data, color=None, point_size=None, cmap="jet", point_shape=No ...@@ -460,8 +460,12 @@ def scatterplot_3d(data, color=None, point_size=None, cmap="jet", point_shape=No
color (Optional[numpy.ndimage]): 1D Array of floating points with same length as the data array. color (Optional[numpy.ndimage]): 1D Array of floating points with same length as the data array.
These numbers give the color of each point. These numbers give the color of each point.
point_size (Optional[float]): The size of each points. Behaves differently depending on the point_shape. point_size (Optional[float]): The size of each points. Behaves differently depending on the point_shape.
If shape is spheres the size is relative to the scene and if squares the size is relative to the window. If shape is spheres the size is relative to the scene and if squares the size is relative to the window.
cmap (Optional[str]): Color map
point_shape (Optional["spheres" or "squares"]): "spheres" plots each point as a sphere, recommended for point_shape (Optional["spheres" or "squares"]): "spheres" plots each point as a sphere, recommended for
small data sets. "squares" plot each point as a square without any 3D structure, recommended for small data sets. "squares" plot each point as a square without any 3D structure, recommended for
large data sets. large data sets.
......
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