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Switch print function to logging #40

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3 changes: 2 additions & 1 deletion python/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,8 @@ pc_fix = PointCloud(X_fix, columns=["x", "y", "z"])
pc_mov = PointCloud(X_mov, columns=["x", "y", "z"])

# Create simpleICP object, add point clouds, and run algorithm!
icp = SimpleICP()
# Set verbose to get information on stdout
icp = SimpleICP(verbose=True)
icp.add_point_clouds(pc_fix, pc_mov)
H, X_mov_transformed, rigid_body_transformation_params, distance_residuals = icp.run(max_overlap_distance=1)
```
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56 changes: 35 additions & 21 deletions python/simpleicp/simpleicp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,23 +11,37 @@
from dataclasses import fields
from pathlib import Path
from typing import Optional, Tuple
import logging

import numpy as np

from . import corrpts, mathutils, optimization, pointcloud

# TODO Rename rbp (rigid-body parameters) to rbtp (rigid-body transformation parameters)

_log = logging.getLogger(__name__)


class SimpleICP:
"""Class for setting up and run simpleICP."""

def __init__(self) -> None:
"""Constructor method."""
def __init__(self, verbose: bool = False) -> None:
"""
Constructor method.

Args:
verbose (bool): print information about the ICP run to stdout
"""

self.pc1 = None
self.pc2 = None

if verbose:
_log.setLevel(logging.INFO)
handler = logging.StreamHandler()
handler.setFormatter(logging.Formatter('%(message)s'))
_log.addHandler(handler)

def add_point_clouds(
self,
pc_fix: pointcloud.PointCloud,
Expand Down Expand Up @@ -112,7 +126,7 @@ def run(
start_time = time.time()

if debug_dirpath:
print(f'Write debug files to directory "{debug_dirpath}"')
_log.info(f'Write debug files to directory "{debug_dirpath}"')
Path(debug_dirpath).mkdir(parents=True, exist_ok=True)

# Convert angle valus from degree -> radian
Expand All @@ -130,7 +144,7 @@ def run(

if np.isfinite(max_overlap_distance):

print("Consider partial overlap of point clouds ...")
_log.info("Consider partial overlap of point clouds ...")
self.pc2.transform_by_H(H) # temporarily transform pc2
self.pc1.select_in_range(self.pc2.X, max_range=max_overlap_distance)
self.pc2.transform_by_H(np.linalg.inv(H)) # undo transformation
Expand All @@ -142,17 +156,17 @@ def run(
"max_overlap_distance."
)

print("Select points for correspondences in fixed point cloud ...")
_log.info("Select points for correspondences in fixed point cloud ...")
self.pc1.select_n_points(correspondences)
selected_orig = self.pc1["selected"]

if not {"nx", "ny", "nz", "planarity"}.issubset(self.pc1.columns):
print("Estimate normals of selected points ...")
_log.info("Estimate normals of selected points ...")
self.pc1.estimate_normals(neighbors)

distance_residuals = []

print("Start iterations ...")
_log.info("Start iterations ...")
for it in range(0, max_iterations):

cp = corrpts.CorrPts(self.pc1, self.pc2)
Expand Down Expand Up @@ -227,55 +241,55 @@ def run(
distance_residuals[it], distance_residuals[it - 1], min_change
):
optim.estimate_parameter_uncertainties()
print("Convergence criteria fulfilled -> stop iteration!")
_log.info("Convergence criteria fulfilled -> stop iteration!")
break

if it == 0:
print(
_log.info(
f"{'iteration':>9s} | "
f"{'correspondences':>15s} | "
f"{'mean(residuals)':>15s} | "
f"{'std(residuals)':>15s}"
)
print(
_log.info(
f"{'orig:0':>9s} | "
f"{len(initial_distances):15d} | "
f"{np.mean(initial_distances):15.4f} | "
f"{np.std(initial_distances):15.4f}"
)
print(
_log.info(
f"{it+1:9d} | "
f"{len(distance_residuals[it]):15d} | "
f"{np.mean(distance_residuals[it]):15.4f} | "
f"{np.std(distance_residuals[it]):15.4f}"
)

print("Estimated transformation matrix H:")
print(f"[{H[0, 0]:12.6f} {H[0, 1]:12.6f} {H[0, 2]:12.6f} {H[0, 3]:12.6f}]")
print(f"[{H[1, 0]:12.6f} {H[1, 1]:12.6f} {H[1, 2]:12.6f} {H[1, 3]:12.6f}]")
print(f"[{H[2, 0]:12.6f} {H[2, 1]:12.6f} {H[2, 2]:12.6f} {H[2, 3]:12.6f}]")
print(f"[{H[3, 0]:12.6f} {H[3, 1]:12.6f} {H[3, 2]:12.6f} {H[3, 3]:12.6f}]")
_log.info("Estimated transformation matrix H:")
_log.info(f"[{H[0, 0]:12.6f} {H[0, 1]:12.6f} {H[0, 2]:12.6f} {H[0, 3]:12.6f}]")
_log.info(f"[{H[1, 0]:12.6f} {H[1, 1]:12.6f} {H[1, 2]:12.6f} {H[1, 3]:12.6f}]")
_log.info(f"[{H[2, 0]:12.6f} {H[2, 1]:12.6f} {H[2, 2]:12.6f} {H[2, 3]:12.6f}]")
_log.info(f"[{H[3, 0]:12.6f} {H[3, 1]:12.6f} {H[3, 2]:12.6f} {H[3, 3]:12.6f}]")

print(
_log.info(
"... which corresponds to the following rigid-body transformation parameters:"
)
print(
_log.info(
f"{'parameter':>9s} | "
f"{'est.value':>15s} | "
f"{'est.uncertainty':>15s} | "
f"{'obs.value':>15s} | "
f"{'obs.weight':>15s}"
)
for parameter in fields(rbp):
print(
_log.info(
f"{parameter.name:>9s} | "
f"{getattr(rbp, parameter.name).estimated_value_scaled:15.6f} | "
f"{getattr(rbp, parameter.name).estimated_uncertainty_scaled:15.6f} | "
f"{getattr(rbp, parameter.name).observed_value_scaled:15.6f} | "
f"{getattr(rbp, parameter.name).observation_weight:15.3e}"
)

print(
_log.info(
"(Unit of est.value, est.uncertainty, and obs.value for alpha1/2/3 is degree)"
)

Expand All @@ -286,7 +300,7 @@ def run(
Path(debug_dirpath).joinpath(f"iteration{it:03d}_postoptim_pcmov.xyz")
)

print(f"Finished in {time.time() - start_time:.3f} seconds!")
_log.info(f"Finished in {time.time() - start_time:.3f} seconds!")

return H, self.pc2.X, rbp, distance_residuals[it]

Expand Down