Source code for wheatsheaf

import numba as nb
import numpy as np

from oasislmf.pytools.lec.utils import get_sample_idx_data, get_wheatsheaf_items_idx


@nb.njit(cache=True, error_model="numpy")
[docs] def fill_wheatsheaf_items( items, items_start_end, row_used_indices, outloss_vals, period_weights, max_summary_id, num_sidxs, ): # Track number of entries per summary_id summary_sidx_counts = np.zeros(max_summary_id * num_sidxs, dtype=np.int32) # First pass to count how many times each summary_id appears for idx in row_used_indices: summary_id, sidx, period_no = get_sample_idx_data(idx, max_summary_id, num_sidxs) summary_sidx_idx = get_wheatsheaf_items_idx(summary_id, sidx, num_sidxs) summary_sidx_counts[summary_sidx_idx] += 1 # Compute cumulative start indices pos = 0 for idx in range(max_summary_id * num_sidxs): if summary_sidx_counts[idx] > 0: items_start_end[idx][0] = pos # Start index pos += summary_sidx_counts[idx] items_start_end[idx][1] = pos # End index # Reset summary counts for inserting data summary_sidx_counts[:] = 0 # Track which period_no are used if period_weights exists is_weighted = len(period_weights) > 0 used_period_no = np.zeros(len(period_weights), dtype=np.bool_) # Second pass to populate the data array for idx in row_used_indices: summary_id, sidx, period_no = get_sample_idx_data(idx, max_summary_id, num_sidxs) summary_sidx_idx = get_wheatsheaf_items_idx(summary_id, sidx, num_sidxs) # Compute position in the flat array insert_idx = items_start_end[summary_sidx_idx][0] + summary_sidx_counts[summary_sidx_idx] # Store values items[insert_idx]["summary_id"] = summary_id items[insert_idx]["sidx"] = sidx items[insert_idx]["value"] = outloss_vals[idx] if is_weighted: # Fast lookup period_weights as they are numbered 1 to no_of_periods items[insert_idx]["period_weighting"] = period_weights[period_no - 1]["weighting"] items[insert_idx]["period_no"] = period_no used_period_no[period_no - 1] = True summary_sidx_counts[summary_sidx_idx] += 1 return is_weighted, used_period_no