## Usage

### Jupyter notebook workflow

Please see `notebooks/Delphi-Demo-Notebook.ipynb` for an example analysis
workflow using a Jupyter notebook.

You can also use the [Delphi binder](https://mybinder.org/v2/gh/ml4ai/delphi/master)
to try out the Jupyter notebook demo without having to install Delphi locally.

You can see a prerendered HTML version of the notebook 
[here.](http://vision.cs.arizona.edu/adarsh/Delphi-Demo-Notebook.html)


### Command line usage

The Delphi CLI app can be used to execute pickled AnalysisGraph models.

```
usage: delphi execute [-h] [--input_dressed_cag INPUT_DRESSED_CAG]
                      [--steps STEPS] [--samples SAMPLES]
                      [--output_sequences OUTPUT_SEQUENCES]
                      [--input_variables INPUT_VARIABLES]

optional arguments:
  -h, --help            show this help message and exit
  --input_dressed_cag INPUT_DRESSED_CAG
                        Path to the input dressed cag
  --steps STEPS         Number of time steps to take
  --samples SAMPLES     Number of sequences to sample
  --output_sequences OUTPUT_SEQUENCES
                        Output file containing sampled sequences
  --input_variables INPUT_VARIABLES
                        Path to the variables of the input dressed cag
```

The `input_variables` file for a model with rainfall influencing crop yield
might look like this:

```
rainfall,100.0
∂(rainfall)/∂t,1.0
crop yield,100.0
∂(crop yield)/∂t,1.0
```

Running `delphi execute` creates an output file `output_sequences.csv` (this
is the default output filename, but it can be changed with
the command line flag), that looks like this:

```
seq_no,time_slice,rainfall,crop yield
0,0,100.0,100.0
0,1,102.60446042864127,102.27252764173306
0,2,103.68597583717079,103.90533882812889
1,0,100.0,100.0
1,1,102.16123221277232,101.92000855752877
1,2,103.60428897964772,101.7157053024733
```

- `seq_no` specifies the sampled sequence
- `time_slice` denotes the time slice of the sequence
- The labels of the other columns denote the factors in the CAG. By collecting
    values from the same time slice over multiple sequences, one can create a
    histogram for the value of a quantity of interest at a particular time
    point. The spread of this histogram represents the uncertainty in our
    estimate.

To see all the command line options and the help message, do `delphi execute -h`.