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Added Balance Pool Group data for Cardano #145

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Added Balance Pool Group data for Cardano #145

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11 changes: 4 additions & 7 deletions consensus_decentralization/helper.py
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Original file line number Diff line number Diff line change
Expand Up @@ -78,7 +78,7 @@ def get_pool_identifiers(project_name):
or an empty dictionary if no information is available for the project (the relevant file does not exist)
"""
try:
with open(MAPPING_INFO_DIR / f'identifiers/{project_name}.json') as f:
with open(MAPPING_INFO_DIR / f'identifiers/{project_name}.json', encoding='utf-8') as f:
identifiers = json.load(f)
except FileNotFoundError:
return dict()
Expand Down Expand Up @@ -174,16 +174,13 @@ def write_blocks_per_entity_to_file(output_dir, blocks_per_entity, time_chunks,
:param time_chunks: a list of strings corresponding to the chunks of time that were analyzed
:param filename: the name to be given to the produced file.
"""
with open(output_dir / filename, 'w', newline='') as f:
with open(output_dir / filename, 'w', newline='', encoding='utf-8') as f:
csv_writer = csv.writer(f)
csv_writer.writerow(['Entity \\ Time period'] + time_chunks) # write header
for entity, blocks_per_chunk in blocks_per_entity.items():
entity_row = [entity]
for chunk in time_chunks:
try:
entity_row.append(blocks_per_chunk[chunk])
except KeyError:
entity_row.append(0)
entity_row.append(blocks_per_chunk.get(chunk, 0))
csv_writer.writerow(entity_row)


Expand All @@ -196,7 +193,7 @@ def get_blocks_per_entity_from_file(filepath):
dictionary with entities (keys) and a list of the number of blocks they produced during each time chunk (values)
"""
blocks_per_entity = defaultdict(dict)
with open(filepath, newline='') as f:
with open(filepath, newline='', encoding='utf-8') as f: # Specify encoding to prevent UnicodeDecodeError
csv_reader = csv.reader(f)
header = next(csv_reader, None)
time_chunks = header[1:]
Expand Down
9 changes: 8 additions & 1 deletion consensus_decentralization/metrics/gini.py
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Expand Up @@ -27,4 +27,11 @@ def gini(array):
array = np.sort(array)
index = np.arange(1, array.shape[0] + 1)
n = array.shape[0]
return (np.sum((2 * index - n - 1) * array)) / (n * np.sum(array))
# Normalize the array to prevent overflow
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I think these changes are fine, but there are two tests that fail because of floating point errors that are produced here. One option is to update the tests to use the new values, as they are not exactly wrong values. Another option would be to round the Gini coefficient (and perhaps all other metrics too) to some fixed number of decimals, e.g. 5, and then use the same number of digits when testing

sum_array = np.sum(array)
normalized_array = array / sum_array
# Calculate the Gini coefficient using the normalized array
gini_numerator = np.sum((2 * index - n - 1) * normalized_array)
# No need to multiply by sum_array as it would cancel out in the division
gini_coefficient = gini_numerator / n
return gini_coefficient
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