kaplan_meier

Calculate the state survival function using the Kaplan-Meier estimator.

Given that a state transition occurred at time \(t_0\), calculate the probability that a compound is still in the new state at time \(t_0 + \Delta t\).

Options

-f: Name of the file containing the discrete trajectory. The discrete trajectory must be stored as numpy.ndarray either in a binary NumPy .npy file or in a (compressed) NumPy .npz archive. See mdtools.file_handler.load_dtrj() for more information about the requirements for the input file.
-o: Output filename.
-b: First frame to read from the discrete trajectory. Frame numbering starts at zero. Default: 0.
-e: Last frame to read from the discrete trajectory. This is exclusive, i.e. the last frame read is actually END - 1. A value of -1 means to read the very last frame. Default: -1.
--every: Read every n-th frame from the discrete trajectory. Default: 1.
--intermittency: Maximum number of frames a compound is allowed to leave its state whilst still being considered to be in this state provided that it returns to this state after the given number of frames. In other words, a compound is only considered to have left its state if it has left it for at least the given number of frames.
--discard-neg-start: If provided, discard state leavings starting from negative states. Transitions from positive to negative states are regarded as proper state leaving.
--discard-all-neg: If provided, discard all state leavings starting from or ending in a negative state. This is different to --discard-neg-start in the sense that transitions from positive to negative states are treated as censored.