The MD Histogram Workspace[MDHistoWorkspace] is a simple multi-dimensional workspace. In contrast to the MDWorkspace, which contains points in space, the MDHistoWorkspace consists of a signal and error spread around space on a regular grid.
In a way, the MDHistoWorkspace is to a MDWorkspace is what the Workspace2D is to the EventWorkspace.
MDHistoWorkspaces typically have 3 or 4 dimensions, although they can be created in up to 9 dimensions.
The following algorithms allow you to perform simple arithmetic on the values:
These arithmetic operations propagate errors as described here. The formulas used are described in each algorithm’s wiki page.
The basic arithmetic operators are available from python. For example:
# Get two workspaces
A = mtd['workspaceA']
B = mtd['workspaceB']
# Creating a new workspace
C = A + B
C = A - B
C = A * B
C = A / B
# Modifying a workspace in-place
C += A
C -= A
C *= A
C /= A
# Operators with doubles
C = A * 12.3
C *= 3.45
Compound arithmetic expressions can be made, e.g:
E = (A - B) / (C - D)
The MDHistoWorkspace can be treated as a boolean workspace. In this case, 0.0 is “false” and 1.0 is “true”.
The following operations can create a boolean MDHistoWorkspace:
These operations can combine/modify boolean MDHistoWorkspaces:
These boolean operators are available from python. Make sure you use the bitwise operators: & | ^ ~ , not the “word” operators (and, or, not). For example:
# Create boolean workspaces by comparisons
C = A > B
D = B < 12.34
# Combine boolean workspaces using not, or, and, xor:
not_C = ~C
C_or_D = C | D
C_and_D = C & D
C_xor_D = C ^ D
C |= D
C &= D
C ^= D
# Compound expressions can be used:
D = (A > 123) & (A > B) & (A < 456)
The SetMDUsingMask algorithm allows you to modify the values in a MDHistoWorkspace using a mask created using the boolean operations above. See the algorithm wiki page for more details.
Category: Concepts