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Refactor Stripe class #25

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merged 11 commits into from
Nov 22, 2024
Merged

Refactor Stripe class #25

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fd430bc
Refactor Stripe class
robomics Nov 8, 2024
52d740a
Add note about unused code
robomics Nov 8, 2024
d4fa5ea
Remove debug code
robomics Nov 8, 2024
00ac85c
Add notes regarding validaiton steps that are temporarily disabled
robomics Nov 8, 2024
f49948e
Minor style changes
robomics Nov 8, 2024
03590d6
Improve error checking
robomics Nov 8, 2024
444d37a
Run pre-commit
robomics Nov 8, 2024
c8338cc
Refactor bound setters
robomics Nov 8, 2024
1b29ae9
Merge branch 'main' into refactoring/stripe
robomics Nov 22, 2024
e60b4fb
Document the new Stripe class
robomics Nov 22, 2024
159517e
Minor adjustment in docstrings
rea1991 Nov 22, 2024
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52 changes: 24 additions & 28 deletions src/stripepy/stripepy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,6 @@
import h5py
import matplotlib.pyplot as plt
import numpy as np
import numpy.typing as npt
import pandas as pd
import scipy.sparse as ss
import seaborn as sns
Expand Down Expand Up @@ -334,15 +333,16 @@ def step_2(L, U, resolution, thresh_pers_type, thresh_pers_value, hf, Iproc_RoI=
UT_MPs, UT_pers_of_MPs = _sort_extrema_by_coordinate(UT_ps_MPs, pers_of_UT_ps_MPs)

print("2.3) Storing into a list of Stripe objects...")
candidate_stripes = dict()
candidate_stripes["lower"] = [
stripe.Stripe(seed=LT_MP, top_pers=LT_pers_of_MP, where="lower_triangular")
for LT_MP, LT_pers_of_MP in zip(LT_MPs, LT_pers_of_MPs)
]
candidate_stripes["upper"] = [
stripe.Stripe(seed=UT_MP, top_pers=UT_pers_of_MP, where="upper_triangular")
for UT_MP, UT_pers_of_MP in zip(UT_MPs, UT_pers_of_MPs)
]
candidate_stripes = {
"lower": [
stripe.Stripe(seed=LT_MP, top_pers=LT_pers_of_MP, where="lower_triangular")
for LT_MP, LT_pers_of_MP in zip(LT_MPs, LT_pers_of_MPs)
],
"upper": [
stripe.Stripe(seed=UT_MP, top_pers=UT_pers_of_MP, where="upper_triangular")
for UT_MP, UT_pers_of_MP in zip(UT_MPs, UT_pers_of_MPs)
],
}

# Dictionary containing everything that should be returned
pseudo_distributions = {
Expand Down Expand Up @@ -516,11 +516,9 @@ def step_3(

print("3.1.2) Updating list of Stripe objects with HIoIs...")
for num_cand_stripe, (LT_L_bound, LT_R_bound) in enumerate(zip(LT_L_bounds, LT_R_bounds)):
candidate_stripes["lower"][num_cand_stripe].L_bound = LT_L_bound
candidate_stripes["lower"][num_cand_stripe].R_bound = LT_R_bound
candidate_stripes["lower"][num_cand_stripe].set_horizontal_bounds(LT_L_bound, LT_R_bound)
for num_cand_stripe, (UT_L_bound, UT_R_bound) in enumerate(zip(UT_L_bounds, UT_R_bounds)):
candidate_stripes["upper"][num_cand_stripe].L_bound = UT_L_bound
candidate_stripes["upper"][num_cand_stripe].R_bound = UT_R_bound
candidate_stripes["upper"][num_cand_stripe].set_horizontal_bounds(UT_L_bound, UT_R_bound)

if all([param is not None for param in [RoI, output_folder]]):

Expand Down Expand Up @@ -696,11 +694,9 @@ def step_3(

print("3.2.2) Updating list of Stripe objects with VIoIs...")
for num_cand_stripe, (LT_U_bound, LT_D_bound) in enumerate(zip(LT_U_bounds, LT_D_bounds)):
candidate_stripes["lower"][num_cand_stripe].U_bound = LT_U_bound
candidate_stripes["lower"][num_cand_stripe].D_bound = LT_D_bound
candidate_stripes["lower"][num_cand_stripe].set_vertical_bounds(LT_U_bound, LT_D_bound)
for num_cand_stripe, (UT_U_bound, UT_D_bound) in enumerate(zip(UT_U_bounds, UT_D_bounds)):
candidate_stripes["upper"][num_cand_stripe].U_bound = UT_U_bound
candidate_stripes["upper"][num_cand_stripe].D_bound = UT_D_bound
candidate_stripes["upper"][num_cand_stripe].set_vertical_bounds(UT_U_bound, UT_D_bound)

print(f"Execution time: {time.time() - start_time} seconds ---")

Expand Down Expand Up @@ -944,19 +940,19 @@ def step_4(

LT_biological_descriptors = pd.DataFrame(
{
"inner mean": [c_s.inner_descriptors["mean"] for c_s in candidate_stripes["lower"]],
"outer mean": [c_s.outer_descriptors["mean"] for c_s in candidate_stripes["lower"]],
"inner mean": [c_s.inner_mean for c_s in candidate_stripes["lower"]],
"outer mean": [c_s.outer_mean for c_s in candidate_stripes["lower"]],
"relative change": [c_s.rel_change for c_s in candidate_stripes["lower"]],
"standard deviation": [c_s.inner_descriptors["std"] for c_s in candidate_stripes["lower"]],
"standard deviation": [c_s.inner_std for c_s in candidate_stripes["lower"]],
}
)

UT_biological_descriptors = pd.DataFrame(
{
"inner mean": [c_s.inner_descriptors["mean"] for c_s in candidate_stripes["upper"]],
"outer mean": [c_s.outer_descriptors["mean"] for c_s in candidate_stripes["upper"]],
"inner mean": [c_s.inner_mean for c_s in candidate_stripes["upper"]],
"outer mean": [c_s.outer_mean for c_s in candidate_stripes["upper"]],
"relative change": [c_s.rel_change for c_s in candidate_stripes["upper"]],
"standard deviation": [c_s.inner_descriptors["std"] for c_s in candidate_stripes["upper"]],
"standard deviation": [c_s.inner_std for c_s in candidate_stripes["upper"]],
}
)

Expand All @@ -973,10 +969,10 @@ def step_4(
# Retrieve data:
LT_MPs = [c_s.seed for c_s in candidate_stripes["lower"]]
UT_MPs = [c_s.seed for c_s in candidate_stripes["upper"]]
LT_HIoIs = [[c_s.L_bound, c_s.R_bound] for c_s in candidate_stripes["lower"]]
LT_VIoIs = [[c_s.U_bound, c_s.D_bound] for c_s in candidate_stripes["lower"]]
UT_HIoIs = [[c_s.L_bound, c_s.R_bound] for c_s in candidate_stripes["upper"]]
UT_VIoIs = [[c_s.U_bound, c_s.D_bound] for c_s in candidate_stripes["upper"]]
LT_HIoIs = [[c_s.left_bound, c_s.right_bound] for c_s in candidate_stripes["lower"]]
LT_VIoIs = [[c_s.top_bound, c_s.bottom_bound] for c_s in candidate_stripes["lower"]]
UT_HIoIs = [[c_s.left_bound, c_s.right_bound] for c_s in candidate_stripes["upper"]]
UT_VIoIs = [[c_s.top_bound, c_s.bottom_bound] for c_s in candidate_stripes["upper"]]

for threshold in thresholds_relative_change:

Expand Down
5 changes: 4 additions & 1 deletion src/stripepy/utils/postprocessing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,9 @@

from . import stripe

# TODO All functions defined in this file appear to be unused.
# Review!


def filter_stripes(candida_stripes, threshold):
rel_changes = np.array([candida_stripe.rel_change for candida_stripe in candida_stripes])
Expand Down Expand Up @@ -122,7 +125,7 @@ def filter_U_stripes(I, sites, HIoIs, VIoIs, threshold, output_folder=None):
for num_cand, (site, HIoI, VIoI) in enumerate(zip(sites, HIoIs, VIoIs)):

# Update list of candidate stripes:
candida_stripe = stripe.Stripe(site, HIoI[0], HIoI[1], VIoI[0], VIoI[1])
candida_stripe = stripe.Stripe(HIoI[0], HIoI[1], VIoI[0], VIoI[1], seed=site)

# Restricting Iproc1 to the rectangular domain defined by current HIoI and VIoI:
convex_comb = int(round(0.01 * VIoI[0] + 0.99 * VIoI[1]))
Expand Down
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