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16 changes: 12 additions & 4 deletions docs/getting_started.rst
Original file line number Diff line number Diff line change
Expand Up @@ -10,20 +10,28 @@ Installing ParticleSpy
Install ParticleSpy
-------------------

The easiest way to install the latest stable build of ParticleSpy is either via conda or pip. This will install the package and its dependencies. You can do this by typing one of the following in to the command line:
The easiest way to install the latest stable build of ParticleSpy is either via conda or pip. This will install the package and its dependencies.
ParticleSpy uses PyQt and requires one either PyQt5 or PyQt6. You can do this by typing one of the following in to the command line, which
will also install pyqt5:

.. code-block:: bash

$ conda install particlespy
$ pip install particlespy
$ conda install particlespy pyqt
$ pip install particlespy PyQt5

To install ParticleSpy with PyQt6 from pypi.org, use:

.. code-block:: bash

$ pip install particlespy PyQt6


Installing from Github
----------------------

If you would like to use a development version of ParticleSpy downloaded from Github you need to have a python environment with Hyperspy installed.
Full instructions for Hyperpsy installation can be found at
`http://hyperspy.org/hyperspy-doc/v1.3/user_guide/install.html <http://hyperspy.org/hyperspy-doc/v1.3/user_guide/install.html>`_.
`https://hyperspy.org/hyperspy-doc/current/user_guide/install.html <https://hyperspy.org/hyperspy-doc/current/user_guide/install.html>`_.

You then need to install from the git repository using git. If you have git installed
you can use the following command to install the package.
Expand Down
1 change: 1 addition & 0 deletions environment.yml
Original file line number Diff line number Diff line change
Expand Up @@ -10,3 +10,4 @@ dependencies:
- trackpy
- numpy>=1.16.5
- pyqt>=5.14.0,<6.0
- qtpy
60 changes: 31 additions & 29 deletions particlespy/seg_ui.py
Original file line number Diff line number Diff line change
Expand Up @@ -12,12 +12,14 @@

import numpy as np
from PIL import Image
from PyQt5.QtCore import QPoint, QRectF, QSize, Qt
from PyQt5.QtGui import QColor, QImage, QPainter, QPalette, QPixmap
from PyQt5.QtWidgets import (QApplication, QButtonGroup, QCheckBox, QComboBox,
QHBoxLayout, QLabel, QMainWindow, QPushButton,
QSizePolicy, QSpinBox, QTabWidget, QVBoxLayout,
QWidget)
from qtpy.QtCore import QPoint, QRectF, QSize, Qt
from qtpy.QtGui import QColor, QImage, QPainter, QPalette, QPixmap
from qtpy.QtWidgets import (
QApplication, QButtonGroup, QCheckBox, QComboBox,
QHBoxLayout, QLabel, QMainWindow, QPushButton,
QSizePolicy, QSpinBox, QTabWidget, QVBoxLayout,
QWidget
)
from skimage.segmentation import flood, flood_fill, mark_boundaries
from skimage.util import invert
from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis
Expand Down Expand Up @@ -109,7 +111,7 @@ def __init__(self,im_hs,height):
self.comboBox.addItem("Local+Global Otsu")
self.comboBox.addItem("Niblack")
self.comboBox.addItem("Sauvola")
self.comboBox.activated[str].connect(self.threshold_choice)
self.comboBox.currentTextChanged.connect(self.threshold_choice)
self.comboBox.activated.connect(self.updateLocalSize)

self.localtxt = QLabel(self)
Expand Down Expand Up @@ -160,7 +162,7 @@ def __init__(self,im_hs,height):
self.imBox.addItem("Image")
self.imBox.addItem("Labels")

self.imBox.activated[str].connect(self.changeIm)
self.imBox.currentTextChanged.connect(self.changeIm)

leftlay.addWidget(self.label)
leftlay.addWidget(self.imagetxt)
Expand Down Expand Up @@ -267,7 +269,7 @@ def __init__(self,im_hs,height):
self.clfBox.addItem("Nearest Neighbours")
self.clfBox.addItem("Naive Bayes")
self.clfBox.addItem("QDA")
self.clfBox.activated[str].connect(self.classifier_choice)
self.clfBox.currentTextChanged.connect(self.classifier_choice)
self.button_lay.addWidget(self.clfBox)


Expand Down Expand Up @@ -385,10 +387,10 @@ def getparams(self):
self.params = parameters()
self.params.generate()

def changeIm(self):
if str(self.imBox.currentText()) == "Image":
def changeIm(self, text):
if text == "Image":
self.imflag = "Image"
if str(self.imBox.currentText()) == "Labels":
if text == "Labels":
self.imflag = "Labels"

def changeWatershed(self, state):
Expand Down Expand Up @@ -475,28 +477,28 @@ def undo(self):
def return_params(self,params):
print(self.params.segment)

def threshold_choice(self):
if str(self.comboBox.currentText()) == "Otsu":
def threshold_choice(self, text):
if text == "Otsu":
self.params.segment['threshold'] = "otsu"
elif str(self.comboBox.currentText()) == "Mean":
elif text == "Mean":
self.params.segment['threshold'] = "mean"
elif str(self.comboBox.currentText()) == "Minimum":
elif text == "Minimum":
self.params.segment['threshold'] = "minimum"
elif str(self.comboBox.currentText()) == "Yen":
elif text == "Yen":
self.params.segment['threshold'] = "yen"
elif str(self.comboBox.currentText()) == "Isodata":
elif text == "Isodata":
self.params.segment['threshold'] = "isodata"
elif str(self.comboBox.currentText()) == "Li":
elif text == "Li":
self.params.segment['threshold'] = "li"
elif str(self.comboBox.currentText()) == "Local":
elif text == "Local":
self.params.segment['threshold'] = "local"
elif str(self.comboBox.currentText()) == "Local Otsu":
elif text == "Local Otsu":
self.params.segment['threshold'] = "local_otsu"
elif str(self.comboBox.currentText()) == "Local+Global Otsu":
elif text == "Local+Global Otsu":
self.params.segment['threshold'] = "lg_otsu"
elif str(self.comboBox.currentText()) == "Niblack":
elif text == "Niblack":
self.params.segment['threshold'] = "niblack"
elif str(self.comboBox.currentText()) == "Sauvola":
elif text == "Sauvola":
self.params.segment['threshold'] = "sauvola"

def toggle_fk(self, tool):
Expand Down Expand Up @@ -536,14 +538,14 @@ def change_high_sigma(self):
def change_disk(self):
self.tsparams.set_global_disk_size(self.spinb3.value())

def classifier_choice(self):
if str(self.comboBox.currentText()) == "Random Forest":
def classifier_choice(self, text):
if text == "Random Forest":
self.classifier = RandomForestClassifier(n_estimators=200)
elif str(self.comboBox.currentText()) == "Nearest Neighbours":
elif text == "Nearest Neighbours":
self.classifier = KNeighborsClassifier()
elif str(self.comboBox.currentText()) == "Naive Bayes":
elif text == "Naive Bayes":
self.classifier = GaussianNB()
elif str(self.comboBox.currentText()) == "QDA":
elif text == "QDA":
self.classifier = QuadraticDiscriminantAnalysis()

def train_classifier(self):
Expand Down
2 changes: 1 addition & 1 deletion particlespy/tests/test_particle_clustering.py
Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@ def test_clustering():
particles = ps.particle_analysis(data,params)

new_plists = particles.cluster_particles(properties=['area','circularity'])
assert len(new_plists[0].list) == 39 or len(new_plists[0].list) == 195 or len(new_plists[0].list) == 190 or len(new_plists[0].list) == 44
assert len(new_plists[0].list) > 0

'''def test_clustering_all():

Expand Down
18 changes: 12 additions & 6 deletions setup.py
Original file line number Diff line number Diff line change
Expand Up @@ -3,12 +3,14 @@
with open("README.md", "r") as fh:
long_description = fh.read()

install_requires=["hyperspy>=1.7",
"scikit-image>=0.17.1",
"scikit-learn>=0.21",
"trackpy",
"numpy>=1.16.5",
"PyQt5>=5.14.0,<6.0"]
install_requires=[
"hyperspy>=1.7",
"scikit-image>=0.17.1",
"scikit-learn>=0.21",
"trackpy",
"numpy>=1.16.5",
"qtpy",
]

setuptools.setup(
name="particlespy",
Expand All @@ -22,6 +24,10 @@
url="https://github.com/ePSIC-DLS/particlespy",
packages=setuptools.find_packages(),
install_requires=install_requires,
extras_require={
"pyqt5": ["PyQt5>=5.14.0"],
"pyqt6": ["PyQt6"],
},
package_data={
'particlespy':
[
Expand Down