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@@ -9,7 +9,7 @@ conda install h5py numpy matplotlib tqdm
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pip3 install -U 'mrestimator[full]'
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```
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-The outline is the following:
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+## Outline
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1. create a realization of a branching process of certain length, timescale and number of trials. This is done in `run/triallength.py`
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2. calculate the correlation coefficients. This is done in `run/triallength.py`.
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@@ -17,3 +17,5 @@ The outline is the following:
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* The `run/triallength.py` script takes an integer argument (think thread or job id) because we ran this on the cluster. Every id creates it's own hdf5 output file.
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* Merge the individual files with `run/merge_hdf5.py` to obtain data files similar to the ones provided here.
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3. fit the exponentials. This is done with `plt/plot_merged.py`.
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+
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+Note that the realizations for long trials (large `targettau` and `targetlength` in `run/triallength.py`) will take on the order of days computation and multiple gigabytes of ram. Adjust as needed.
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