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Merged
daavid00 merged 1 commit into from
Dec 2, 2025
Merged

Support for porespy version 3.0.0 #14

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2 changes: 1 addition & 1 deletion CITATION.cff
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@ authors:
orcid: "https://orcid.org/0000-0002-3343-1005"
title: "py-micp: An Open-Source Simulation Workflow for Field-Scale Application of
Microbially Induced Calcite Precipitation Technology for Leakage Remediation"
version: 2025.10
version: "2025.10"
year: 2025
doi: 10.5281/zenodo.8430988
url: "https://github.com/cssr-tools/pymm"
25 changes: 17 additions & 8 deletions src/pymm/core/pymm.py
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@@ -1,6 +1,6 @@
# SPDX-FileCopyrightText: 2022-2025 NORCE Research AS
# SPDX-License-Identifier: GPL-3.0
# pylint: disable=R0912,R0915,E1102
# pylint: disable=R0912,R0915,E1102,E1123

"""Main script for pymm"""

Expand Down Expand Up @@ -173,16 +173,25 @@ def process_image(dic, in_image):
axis.set_yticks([])
fig.savefig(f"{dic['fol']}/binary_image.png", dpi=600)
# Extract the contour of the grains on the image border and interior
dic["border"] = ps.filters.trim_small_clusters(
dic["im"], size=(dic["imH"] + 2 * dic["imL"]) * dic["ad_bord"]
)
if int(ps.__version__.split(".", maxsplit=1)[0]) > 2:
dic["border"] = ps.filters.trim_small_clusters(
dic["im"], min_size=(dic["imH"] + 2 * dic["imL"]) * dic["ad_bord"]
)
grains = ps.filters.trim_small_clusters(
np.logical_and(np.bitwise_not(dic["border"]), dic["im"]),
min_size=dic["grainsSize"],
)
else:
dic["border"] = ps.filters.trim_small_clusters(
dic["im"], size=(dic["imH"] + 2 * dic["imL"]) * dic["ad_bord"]
)
grains = ps.filters.trim_small_clusters(
np.logical_and(np.bitwise_not(dic["border"]), dic["im"]),
size=dic["grainsSize"],
)
dic["cn_border"] = measure.find_contours(
dic["border"], 0.5, fully_connected="high", positive_orientation="high"
)
grains = ps.filters.trim_small_clusters(
np.logical_and(np.bitwise_not(dic["border"]), dic["im"]),
size=dic["grainsSize"],
)
grains = grains[dic["ad_bord"] : -dic["ad_bord"], dic["ad_bord"] : -dic["ad_bord"]]
dic["cn_grains"] = measure.find_contours(
grains, 0.5, fully_connected="high", positive_orientation="high"
Expand Down