diff --git a/src/napari_segment/_widget.py b/src/napari_segment/_widget.py
index 09c6f131533fc9d2b8d85330674388e6d98d412b..155a2532f84d94f4646a2024821d57356c2b6e12 100644
--- a/src/napari_segment/_widget.py
+++ b/src/napari_segment/_widget.py
@@ -9,6 +9,7 @@ Replace code below according to your needs.
from enum import Enum
import os
from functools import partial
+from tempfile import TemporaryFile
import dask
import magicgui.widgets as w
@@ -28,11 +29,14 @@ from scipy.ndimage import (
from functools import reduce
from skimage.measure import regionprops
-from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
+from matplotlib.backends.backend_qt5agg import (FigureCanvasQTAgg as FigureCanvas)
+from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as NavigationToolbar
from matplotlib.figure import Figure
+import matplotlib
from threading import Thread
import logging
from importlib.metadata import PackageNotFoundError, version
+import pandas as pd
try:
__version__ = version("napari-segment")
@@ -41,9 +45,9 @@ except PackageNotFoundError:
__version__ = "Unknown"
logging.basicConfig(
- level=logging.DEBUG, format="%(asctime)s %(levelname)s : %(message)s"
+ level=logging.WARNING, format="%(asctime)s %(levelname)s : %(message)s"
)
-logger = logging.getLogger("napari_segment.widget")
+logger = logging.getLogger("napari_segment._widget")
formatter = logging.Formatter(
"%(asctime)s - %(name)s - %(levelname)s : %(message)s"
@@ -117,20 +121,26 @@ class ExampleQWidget(q.QWidget):
value=.9
)
- self.btn = q.QPushButton("Save!")
+ self.btn = q.QPushButton("Save params!")
+ self.btn_save_csv = q.QPushButton("Save csv!")
+
+ self.check_auto_plot = w.CheckBox(label="Update Plots")
+ self.check_auto_plot.changed.connect(self.plot_stats)
self.canvas = FigureCanvas(Figure(figsize=(5,5)))
- self.ax = self.canvas.figure.subplots(nrows=3, sharex=True)
+ self.ax = self.canvas.figure.subplots(nrows=3, sharex=False)
self.ax[0].set_title("Number of detections")
self.ax[1].set_title(diams_title := "Diameters")
self.diams_title = diams_title
self.ax[2].set_title("Eccentricities")
+ self.canvas.figure.tight_layout()
- self._count, = self.ax[0].plot(range(10), [0]*10)
- self._diams, = self.ax[1].plot(range(10), [0]*10)
- self._eccs, = self.ax[2].plot(range(10), [0]*10)
+ self._count, = self.ax[0].plot(range(10), [0]*10, "o", picker=True, pickradius=5)
+ self._diams, = self.ax[1].plot(range(10), [0]*10, "o", picker=True, pickradius=5)
+ self._eccs, = self.ax[2].plot(range(10), [0]*10, "o", picker=True, pickradius=5)
self.container = w.Container(
+ label="Container",
widgets=[
self.input,
w.Label(label="Prepocessing"),
@@ -144,6 +154,7 @@ class ExampleQWidget(q.QWidget):
self.min_diam,
self.max_diam,
self.max_ecc,
+ self.check_auto_plot
]
)
@@ -151,27 +162,46 @@ class ExampleQWidget(q.QWidget):
self.layout().addWidget(self.container.native)
self.layout().addWidget(self.btn)
self.layout().addWidget(self.canvas)
+ self.layout().addWidget(NavigationToolbar(self.canvas, self))
+ self.layout().addWidget(self.btn_save_csv)
+
self.layout().addStretch()
self.viewer.layers.events.inserted.connect(self.reset_choices)
self.viewer.layers.events.removed.connect(self.reset_choices)
self.input.changed.connect(self.restore_params)
self.input.changed.connect(self.preprocess)
- self.binning_widget.changed.connect(self.preprocess)
- self.thr.changed.connect(self.threshold)
- self.erode.changed.connect(self.threshold)
- self.use.changed.connect(self.preprocess)
- self.smooth.changed.connect(self.preprocess)
- self.min_diam.changed.connect(self.update_out)
- self.max_diam.changed.connect(self.update_out)
- self.max_ecc.changed.connect(self.update_out)
- self.btn.clicked.connect(self.save_params)
+
+ self.canvas.mpl_connect('button_press_event', self.onfigclick)
+ self.canvas.mpl_connect('pick_event', self.on_pick)
+
logger.debug("Initialization finished.")
- if (choice := self.input.current_choice):
+ if self.input.current_choice:
self.restore_params()
self.preprocess()
+ def move_step(self, slice):
+ cur_ = self.viewer.dims.current_step
+ new_ = list(cur_)
+ new_[0] = slice
+ self.viewer.dims.current_step = tuple(new_)
+
+
+ def onfigclick(self, event):
+ print('%s click: button=%d, x=%d, y=%d, xdata=%f, ydata=%f' %
+ ('double' if event.dblclick else 'single', event.button,
+ event.x, event.y, event.xdata, event.ydata))
+ self.move_step(np.round(event.xdata, 0).astype(int))
+
+ def on_pick(self, event):
+ line = event.artist
+ xdata, ydata = line.get_data()
+ ind = event.ind
+ print(f'on pick line: {np.array([xdata[ind], ydata[ind]]).T}')
+
+ self.move_step(xdata[ind])
+
def _invert(self, data2D):
return 1 - norm01(gaussian_filter(data2D, self.smooth.value))
@@ -185,7 +215,17 @@ class ExampleQWidget(q.QWidget):
)
def preprocess(self):
+ if not self.input.current_choice:
+ return
logger.debug(f"start preprocessing {self.input.current_choice}")
+
+ try:
+ self.path = self.viewer.layers[self.input.current_choice].metadata[
+ "path"
+ ]
+ except KeyError:
+ self.path = ""
+
self.binning = self.binning_widget.value
try:
self.data = self.viewer.layers[self.input.current_choice].data[
@@ -197,7 +237,8 @@ class ExampleQWidget(q.QWidget):
return
try:
- self.pixel_size = self.viewer.layers[self.input.current_choice].metadata["pixel_size_um"]
+ self.pixel_size = self.viewer.layers[self.input.current_choice]\
+ .metadata["pixel_size_um"]
self.unit = "um"
except KeyError:
@@ -258,18 +299,21 @@ class ExampleQWidget(q.QWidget):
**{"name": name, "scale": self.scale},
)
else:
- logger.debug(f'Updating Preprocessing layer with {self.smooth_gradient}')
+ logger.debug(f'Updating Preprocessing layer with \
+ {self.smooth_gradient}')
self.viewer.layers[name].data = self.smooth_gradient
self.viewer.layers[name].scale = self.scale
- logger.debug(f'Preprocessing finished, sending {self.smooth_gradient} to thresholding')
+ logger.debug(f'Preprocessing finished, \
+ sending {self.smooth_gradient} to thresholding')
self.threshold()
def threshold(self):
logger.debug('Start thresholding step')
if not self.input.current_choice:
return
- logger.debug(f'Thresholding with the thr={self.thr.value} and erode={self.erode.value}')
+ logger.debug(f'Thresholding with the thr={self.thr.value} \
+ and erode={self.erode.value}')
self.labels = self.smooth_gradient.map_blocks(
partial(
threshold_gradient, thr=self.thr.value, erode=self.erode.value
@@ -283,13 +327,15 @@ class ExampleQWidget(q.QWidget):
opacity=0.3,
**{"name": name, "scale": self.scale},
)
+ self.viewer.layers[name].contour = 8 // self.binning
+
else:
logger.debug(f'Updating Detections layer with {self.labels}')
self.viewer.layers[name].data = self.labels
self.viewer.layers[name].scale = self.scale
- self.viewer.layers[name].contour = 8 / self.binning
- logger.debug(f'Thresholding succesful. Sending labels {self.labels} to filtering')
+ logger.debug(f'Thresholding succesful. \
+ Sending labels {self.labels} to filtering')
self.update_out()
def update_out(self):
@@ -298,8 +344,9 @@ class ExampleQWidget(q.QWidget):
return
logger.debug(f'Start filtering')
try:
- logger.debug(f"""Filtering labels by ({self.min_diam.value / self.binning}
- < size[px] < {self.max_diam.value / self.binning})
+ logger.debug(f"""Filtering labels by \
+ ({self.min_diam.value / self.binning} \
+ < size[px] < {self.max_diam.value / self.binning}) \
and eccentricity > {self.max_ecc.value}""")
selected_labels = dask.array.map_blocks(
@@ -310,6 +357,8 @@ class ExampleQWidget(q.QWidget):
self.max_ecc.value,
dtype=np.int32,
)
+ self.selected_labels = selected_labels
+
if not (name := "selected labels") in self.viewer.layers:
logger.debug(f'No selected labels layer found, adding one')
@@ -320,7 +369,7 @@ class ExampleQWidget(q.QWidget):
**{"name": name, "scale": self.scale},
)
else:
- logger.debug(f'Updating selected labels layer with {selected_labels}')
+ logger.debug(f'Updating labels layer with {selected_labels}')
self.viewer.layers[name].scale = self.scale
self.viewer.layers[name].data = selected_labels
@@ -331,40 +380,75 @@ class ExampleQWidget(q.QWidget):
show_error(f"Relax filter! {e}")
try:
-
- self.plot_stats(selected_labels)
+ self.plot_stats()
except Exception as e:
show_error(f"Plot failed: {e}")
-
- def plot_stats(self, data):
- props = [regionprops(label_image=img) for img in data.compute()]
+
+ def plot_stats(self, ignore_check_auto_plot=False):
+ if not self.check_auto_plot.value:
+ if not ignore_check_auto_plot:
+ return
+ props = [regionprops(label_image=img) for img in self.selected_labels.compute()]
num_regions_per_frame = [len(p) for p in props]
- diams_ = [
+ area_ = [
[
- (i, prop.major_axis_length * self.binning * self.pixel_size) \
+ (i, prop.area * (self.binning * self.pixel_size)**2) \
for prop in props_per_frame
] for i,props_per_frame in enumerate(props)
]
- diams = reduce(lambda a,b: a+b, diams_[:])
+ area = reduce(lambda a,b: a+b, area_[:])
+
+ self.props_df = \
+ pd.DataFrame(
+ data=area,
+ columns=["frame", (area_col := f"area [{self.unit}$^2$]")]
+ )
+ self.props_df.loc[:, (diam_col := f"diameter [{self.unit}]")] = \
+ np.sqrt(self.props_df[area_col]) * 2 / np.pi
+
eccs_ = [
[
- (i, prop.eccentricity) for prop in props_per_frame
+ (prop.eccentricity) for prop in props_per_frame
] for i,props_per_frame in enumerate(props)
]
eccs = reduce(lambda a,b: a+b, eccs_)
+ self.props_df.loc[:, (ecc_col := "eccentricity")] = eccs
+
+ data=self.props_df
self._count.set_data(*zip(*enumerate(num_regions_per_frame)))
- self._diams.set_data(*zip(*diams))
- self._eccs.set_data(*zip(*eccs))
- [a.set_xlim(len(num_regions_per_frame)) for a in self.ax]
- self.ax[0].set_ylim(min(num_regions_per_frame), max(num_regions_per_frame))
- self.ax[1].set_ylim(min(r := [d[1] for d in diams]), max(r))
+ self._diams.set_data(data["frame"], data[diam_col])
+ self._eccs.set_data(data["frame"], data[ecc_col])
+ [a.set_xlim(0, len(num_regions_per_frame)) for a in self.ax]
+ self.ax[0].set_ylim(0, max(num_regions_per_frame) + 1)
+ self.ax[1].set_ylim(
+ self.props_df[diam_col].min(),
+ self.props_df[diam_col].max()
+ )
self.ax[2].set_ylim(0,1)
self.canvas.draw_idle()
+ def save_csv(self):
+ self.plot_stats(ignore_check_auto_plot=True)
+ try:
+ len(self.props_df)
+ except Exception as e:
+ logger.error(f"Unable to find the data to save: {e}")
+ show_error(f"Unable to find the data to save: {e}")
+ return
+ path = self.path + ".table.csv"
+ try:
+ self.props_df.to_csv(path)
+ logger.info(f"Saved csv {path}")
+ show_info(f"Saved csv {path}")
+ except Exception as e:
+ logger.error(f"Error saving csv: {e}")
+ show_error(f"Error saving csv: {e}")
+
+
def save_params(self):
data = {
@@ -378,27 +462,33 @@ class ExampleQWidget(q.QWidget):
"max_ecc": self.max_ecc.value,
}
try:
- path = self.viewer.layers[self.input.current_choice].metadata[
- "path"
- ]
- dir = os.path.dirname(path)
- filename = os.path.basename(path)
+
+ dir = os.path.dirname(self.path)
+ filename = os.path.basename(self.path)
new_name = filename + ".params.yaml"
with open(os.path.join(dir, new_name), "w") as f:
yaml.safe_dump(data, f)
show_info(f"Parameters saves into {new_name}")
- except KeyError:
- show_error("Saving parameters failed")
+ logger.info(f"Parameters saves into {new_name}")
+ except Exception as e:
+ show_error(f"Saving parameters into {new_name} failed: {e}")
+ logger.error(f"Saving parameters into {new_name} failed: {e}")
with open((ff := ".latest.params.yaml"), "w") as f:
yaml.safe_dump(data, f)
- show_info(f"Parameters saves into {ff}")
+ logger.info(f"Parameters saves into {ff}")
def restore_params(self):
+ logger.debug(f'Start restoring parameters')
try:
- path = self.viewer.layers[self.input.current_choice].metadata[
+ self.path = self.viewer.layers[self.input.current_choice].metadata[
"path"
]
+ except KeyError:
+ self.path = ""
+
+ try:
+ path = self.path
dir = os.path.dirname(path)
filename = os.path.basename(path)
new_name = filename + ".params.yaml"
@@ -408,6 +498,7 @@ class ExampleQWidget(q.QWidget):
with open(ppp := os.path.join(dir, new_name)) as f:
data = yaml.safe_load(f)
show_info(f"restoring parameters from {new_name}")
+ logger.info(f"restoring parameters from {new_name}")
except (UnboundLocalError, UnicodeDecodeError, FileNotFoundError):
try:
@@ -416,7 +507,7 @@ class ExampleQWidget(q.QWidget):
show_info(f"restoring parameters from {ppp}")
except FileNotFoundError:
return
- print(data)
+ logger.debug(f'Loaded parameters: {data}')
try:
self.binning_widget.value = data["binning"]
self.use.value = data["use"]
@@ -428,16 +519,32 @@ class ExampleQWidget(q.QWidget):
self.max_ecc.value = data["max_ecc"]
except Exception as e:
show_error(f"Restore settings failed, {e}")
+ logger.error(f"Restore settings failed, {e}")
+
+ self.binning_widget.changed.connect(self.preprocess)
+ self.thr.changed.connect(self.threshold)
+ self.erode.changed.connect(self.threshold)
+ self.use.changed.connect(self.preprocess)
+ self.smooth.changed.connect(self.preprocess)
+ self.min_diam.changed.connect(self.update_out)
+ self.max_diam.changed.connect(self.update_out)
+ self.max_ecc.changed.connect(self.update_out)
+ self.btn.clicked.connect(self.save_params)
+ self.btn_save_csv.clicked.connect(self.save_csv)
+
def reset_choices(self, event=None):
- self.input.reset_choices(event)
- self.input.choices = [
+ logger.debug(f"New layer added. Reset choices. Event: {event}")
+ new_layers = [
layer.name
for layer in self.viewer.layers
if isinstance(layer, Image) and layer.name != "Preprocessing"
]
- # self.restore_params()
-
+ if self.input.choices != new_layers:
+ self.input.choices = new_layers
+ logger.debug(f'Updating layer list with {new_layers}')
+ else:
+ logger.debug('No new data layers, probably added pipeline layers triggered this reset')
def norm01(data):
d = data.copy()