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check_chain_propagation This function confirms the propagation of a detected chain from the current to the subsequent timeframe, returning the propagation’s details if found.

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Function Parameters

ParameterTypeRequiredDescription
current_dfobjectTrueA DataFrame representing the current timeframe, which holds the detected chain that the function checks for propagation into the next_df.
next_dfobjectTrueA DataFrame representing the subsequent timeframe being monitored to confirm the propagation of the detected change.

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Data Columns

Both dataframes must contain the following columns:
  • datetime (string): A timestamp for each data point.
  • chain_detected (float): The detected chain value for the interval.

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Python Code Example

from sumtyme import EIPClient

# Initialise the EIPClient with the provided API key
client = EIPClient(apikey='your-api-key-here')

current_timeframe_df = 1min_outputs  # Example: DataFrame for the 1 minute api outputs
next_timeframe_df = 2min_outputs    # Example: DataFrame for the 2 minute api outputs

result = client.check_chain_propagation(
    current_tf=current_timeframe_df,
    next_tf=next_timeframe_df
)

# Returns a tuple: (propagation confirmed [bool], propagation timestamp [datetime or None], chain value [int or None])
has_propagated, propagation_datetime, chain_value = result

if has_propagated:
    print(f"Chain value {chain_value} successfully propagated at {propagation_datetime}.")
else:
    print("No propagation detected between the timeframes.")
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