Mercurial > repos > bimib > marea_2
changeset 270:4617f8a3ab28 draft
Uploaded
author | luca_milaz |
---|---|
date | Sun, 04 Aug 2024 16:36:03 +0000 |
parents | 3671d7cb4eaf |
children | d879c594013d |
files | marea_2/flux_to_map.py |
diffstat | 1 files changed, 15 insertions(+), 13 deletions(-) [+] |
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--- a/marea_2/flux_to_map.py Sun Aug 04 16:02:16 2024 +0000 +++ b/marea_2/flux_to_map.py Sun Aug 04 16:36:03 2024 +0000 @@ -818,20 +818,22 @@ """Convert an RGBA color to HEX format.""" return '#{:02x}{:02x}{:02x}'.format(int(rgba[0] * 255), int(rgba[1] * 255), int(rgba[2] * 255)) -def reds_cmap(value): - """Map a normalized value to RGB color using the Reds colormap.""" - # Assumi che 'value' sia scalare e tra 0 e 1 - r = value - g = 0 - b = 0 +def gray_to_red_cmap(value): + """Map a normalized value to RGB color transitioning from gray to red.""" + # Ensure value is in the range [0, 1] + value = abs(value) + r = value + 0.5 + g = 0.5 - 0.5 * value + b = 0.5 - 0.5 * value + return (r, g, b) -def computeEnrichmentMedoids(metabMap :ET.ElementTree, class_pat :Dict[str, List[List[float]]], ids :List[str]) -> None: +def computeEnrichmentMeanMedian(metabMap :ET.ElementTree, class_pat :Dict[str, List[List[float]]], ids :List[str]) -> None: metabMap_mean = copy.deepcopy(metabMap) metabMap_median = copy.deepcopy(metabMap) - medians = {} # dict , for each class an array (the median) + medians = {} # dict, for each class an array (the median) means = {} for key, value in class_pat.items(): values = np.array(class_pat[key]) @@ -854,27 +856,27 @@ colors_median={} i=0 for rxn_id in ids: - colors_median[rxn_id] = rgba_to_hex(reds_cmap(medians[key][i])) + colors_median[rxn_id] = rgba_to_hex(gray_to_red_cmap(medians[key][i])) i+=1 colors_mean={} i=0 for rxn_id in ids: - colors_mean[rxn_id] = rgba_to_hex(reds_cmap(means[key][i])) + colors_mean[rxn_id] = rgba_to_hex(gray_to_red_cmap(means[key][i])) i+=1 for rxn_id in ids: arrow = Arrow(width=5, col=colors_median[rxn_id]) arrow.applyTo(arrow.getMapReactionId(rxn_id, mindReactionDir=False), metabMap_median, arrow.toStyleStr()) # Now we style the arrow head(s): - idOpt1, idOpt2 = getArrowHeadElementId(arrow.getMapReactionId(rxn_id, mindReactionDir=False)) + idOpt1, idOpt2 = getArrowHeadElementId(arrow.getMapReactionId(rxn_id, mindReactionDir=True)) arrow.applyTo(idOpt1, metabMap_median, arrow.toStyleStr(downSizedForTips = True)) if idOpt2: arrow.applyTo(idOpt2, metabMap_median, arrow.toStyleStr(downSizedForTips = True)) arrow = Arrow(width=5, col=colors_mean[rxn_id]) arrow.applyTo(arrow.getMapReactionId(rxn_id, mindReactionDir=False), metabMap_mean, arrow.toStyleStr()) # Now we style the arrow head(s): - idOpt1, idOpt2 = getArrowHeadElementId(arrow.getMapReactionId(rxn_id, mindReactionDir=False)) + idOpt1, idOpt2 = getArrowHeadElementId(arrow.getMapReactionId(rxn_id, mindReactionDir=True)) arrow.applyTo(idOpt1, metabMap_mean, arrow.toStyleStr(downSizedForTips = True)) if idOpt2: arrow.applyTo(idOpt2, metabMap_mean, arrow.toStyleStr(downSizedForTips = True)) @@ -911,7 +913,7 @@ ids, class_pat = getClassesAndIdsFromDatasets(ARGS.input_datas_fluxes, ARGS.input_data_fluxes, ARGS.input_class_fluxes, ARGS.names_fluxes) - computeEnrichmentMedoids(core_map, class_pat, ids) + computeEnrichmentMeanMedian(core_map, class_pat, ids) computeEnrichment(core_map, class_pat, ids)