PyGraf

Utility module to read SDDP hdr/bin result file pairs. Some examples to convert it to popular formats are available.

Installing

Install the latest version from PyPI

pip install psr-graf

Or download this repository contents.

Usage

Start by importing psr.graf module. It's possible to read data directly using open_bin and open_csv functions or load_as_dataframe function if pandas package is available.

The example below shows how to load data directly into a pandas.DataFrame and prints the first 5 lines of data.

import psr.graf

df = psr.graf.load_as_dataframe("sample_data/gerter.hdr")
print(df.head())

The output is:

                      Thermal 1  Thermal 2  Thermal 3
stage scenario block                                 
1     1        1       7.440000      0.744   0.368069
               2       6.437624      0.000   0.000000
               3       7.440000      0.744   0.576140
               4       7.440000      0.744   2.994997
               5       7.440000      0.744   0.916644

Alternatively, open_bin and open_csv functions can be used for direct data access as shown in the example next.

import psr.graf

with psr.graf.open_bin("sample_data/gerter.hdr") as graf_file:
    print("Stages:", graf_file.stages)
    print("Scenarios:", graf_file.scenarios)
    print("Agents:", graf_file.agents)
    print(f"Initial date: {graf_file.initial_year:04d}/{graf_file.initial_stage:02d}")
    print("Units:", graf_file.units)
    stage = 2
    print(f"Number of blocks at stage {stage}: {graf_file.blocks(stage)}")
    scenario = 10
    block = 1
    print(f"Data at stage {stage}, scenario {scenario}, block {block}:",
          graf_file.read(stage, scenario, block))

The output is:

Stages: 12
Scenarios: 50
Agents: ('Thermal 1', 'Thermal 2', 'Thermal 3')
Initial date: 2013/01
Units: GWh
Number of blocks at stage 2: 1
Data at stage 2, scenario 10, block 1: (7.440000057220459, 0.7440000176429749, 0.3680693209171295)

Requirements

• Python 2.7, 3.3 or newer.
• (Optional) pandas package to use load_as_dataframe function.

File Formats

• load_as_dataframe supports all of them and will determine which reader will be used based on the file extension.
• open_bin supports only .hdr/bin pairs or single-binary files.
• open_csv supports only CSV.

Both open_bin, open_csv, and load_as_dataframe functions accept encoding parameter to specify the encoding of the strings in file. The default is utf-8.

DataFrame options

MultiIndex or single index

load_as_dataframe accepts an optional keyword argument multi_index (default True) to specify if the returned pandas.DataFrame should use pandas.MultiIndex or not. If False, the returned pandas.DataFrame will have a single automatic index and the columns 'stage', 'scenario', 'block' will appear before the agents' data.

Example:

import psr.graf
df = psr.graf.load_as_dataframe("sample_data/gerter.hdr", multi_index=False)
print(df.head())
print("Column names:", df.columns.values)

The output is:

   stage  scenario  block  Thermal 1  Thermal 2  Thermal 3
0      1         1      1   7.440000      0.744   0.368069
1      1         2      1   6.437624      0.000   0.000000
2      1         3      1   7.440000      0.744   0.576140
3      1         4      1   7.440000      0.744   2.994997
4      1         5      1   7.440000      0.744   0.916644
Column names: ['stage' 'scenario' 'block' 'Thermal 1' 'Thermal 2' 'Thermal 3']

On the other hand,

import psr.graf
df = psr.graf.load_as_dataframe("sample_data/gerter.hdr", multi_index=True)
print(df.head())
print("Column names:", df.columns.values)

Will produce the following output:

                      Thermal 1  Thermal 2  Thermal 3
stage scenario block                                 
1     1        1       7.440000      0.744   0.368069
      2        1       6.437624      0.000   0.000000
      3        1       7.440000      0.744   0.576140
      4        1       7.440000      0.744   2.994997
      5        1       7.440000      0.744   0.916644
Column names: ['Thermal 1' 'Thermal 2' 'Thermal 3']

Index formats

The index_format specifies the format of index columns of the returned pandas.Dataframe. It accepts the following values:

• default creates a pandas.DataFrame with the columns as they are stored in the original file.
• period converts stage into year, month or week depending on the stage type of the file and the initial year and stage.

Filter by stage, scenario, block and/or agent

The load_as_dataframe function accepts the following optional keyword arguments to filter data:

An empty list or unspecified means all stages, blocks, scenarios or agents will be included.

Example:

import psr.graf
df = psr.graf.load_as_dataframe("sample_data/gerter.hdr", 
                                filter_stages=[8, ], 
                                filter_scenarios=[10, ],
                                filter_agents=["Thermal 3", "Thermal 2"])
print(df.head())

Outputs:

                      Thermal 3  Thermal 2
stage scenario block                      
10    8        1       9.127362        0.0

Usage Samples

dataframes_sample.py

Shows how to read data into pandas.DataFrames.

Requires pandas package installed.

matplotlib_sample.py

Shows how to read data and plot data from hdr/bin file pairs.

Requires matplotlib package installed.

csv_sample.py

Shows how to convert from hdr/bin file pairs to csv using psr.graf module.

This script can also be called from command line:

python csv_sample.py input_file.hdr output_file.csv

Where output_file.csv is optional.

parquet_sample.py

Shows how to convert from hdr/bin file pairs to Apache Parquet format.

Requires pyarrow package installed.

This script can also be called from command line:

python parquet_sample.py input_file.hdr output_file.parquet

Where output_file.parquet is optional.

Issues and Support

Check PyGraf's GitHub repository and issues page for support.