Quick color check to qc

docs/quick_color_check.md

@@ -5,7 +5,7 @@ be better off excluded from analysis . A quick way to examine this is by plottin
 masked in the color card.
 
 
-**plantcv.transform.quick_color_check**(*source_matrix, target_matrix, num_chips*)
+**plantcv.qc.quick_color_check**(*source_matrix, target_matrix, num_chips*)
 
 **returns** Altair chart
 
@@ -23,9 +23,9 @@ masked in the color card.
 
 from plantcv import plantcv as pcv
 
-chart = pcv.transform.quick_color_check(source_matrix=s_matrix,
-                                        target_matrix=t_matrix,
-                                        num_chips=24)
+chart = pcv.qc.quick_color_check(source_matrix=s_matrix,
+                                 target_matrix=t_matrix,
+                                 num_chips=24)
 
 ```
 **Perfect Color Correlation**
@@ -36,4 +36,4 @@ chart = pcv.transform.quick_color_check(source_matrix=s_matrix,
 
 ![Screenshot](img/documentation_images/quick_color_check/quick_color_plot2.png)
 
-**Source Code:** [Here](https://github.com/danforthcenter/plantcv/blob/main/plantcv/plantcv/transform/color_correction.py)
+**Source Code:** [Here](https://github.com/danforthcenter/plantcv/blob/main/plantcv/plantcv/qc/quick_color_check.py)

docs/updating.md

@@ -994,6 +994,11 @@ pages for more details on the input and output variable types.
 * pre v4.3.1: NA
 * post v4.3.1: chart = **plantcv.qc.exposure**(*rgb_img, warning_threshold=0.05*)
 
+#### plantcv.qc.quick_color_check
+
+* pre v5.0: NA, see `plantcv.transform.quick_color_check`
+* post v5.0: chart = **plantcv.transform.quick_color_check**(*target_matrix, source_matrix, num_chips*)
+
 #### plantcv.readbayer
 
 * pre v3.0: NA
@@ -1497,6 +1502,7 @@ pages for more details on the input and output variable types.
 * pre v3.0: NA
 * post v3.0: **plantcv.transform.quick_color_check**(*target_matrix, source_matrix, num_chips*)
 * post v4.0: chart = **plantcv.transform.quick_color_check**(*target_matrix, source_matrix, num_chips*)
+* post v5.0: NA, moved to `plantcv.qc.quick_color_check`
 
 #### plantcv.transform.save_matrix
 

mkdocs.yml

@@ -145,6 +145,7 @@ nav:
       - 'Plot Image': plot_image.md
       - "Quality Control Tools":
         - "Exposure": qc_exposure.md
+        - "Quick Color Check": quick_color_check.md
       - 'Read Image': read_image.md
       - 'Read Bayer Raw Image': read_bayer.md
       - 'Report Size Marker': report_size_marker.md
@@ -187,7 +188,6 @@ nav:
           - 'Create Color Card Mask': create_color_card_mask.md
           - 'Convert Color Card to Matrix': get_color_matrix.md
           - 'Color Correction Workflow': transform_correct_color.md
-          - 'Quick Color Check': quick_color_check.md
           - 'Affine Color Correction': transform_affine_color_correction.md
           - 'Standard Color Matrix': std_color_matrix.md
           - 'Gamma Correction': transform_gamma_correct.md

plantcv/plantcv/qc/__init__.py

@@ -1,3 +1,5 @@
 from plantcv.plantcv.qc.exposure import exposure
+from plantcv.plantcv.qc.quick_color_check import quick_color_check
 
-__all__ = ["exposure"]
+
+__all__ = ["exposure", "quick_color_check"]

plantcv/plantcv/qc/quick_color_check.py

@@ -0,0 +1,77 @@
+# Plot the color values of a target and source color matrix
+import os
+import numpy as np
+import pandas as pd
+import altair as alt
+from plantcv.plantcv._debug import _debug
+from plantcv.plantcv._globals import params
+
+
+def quick_color_check(target_matrix, source_matrix, num_chips):
+    """Plot the color values of a target and source color card matrix.
+
+    Quickly plot target matrix values against source matrix values to determine
+    over saturated color chips or other issues.
+
+    Inputs:
+    source_matrix      = an nrowsXncols matrix containing the avg red, green, and blue values for each color chip
+                            of the source image
+    target_matrix      = an nrowsXncols matrix containing the avg red, green, and blue values for each color chip
+                            of the target image
+    num_chips          = number of color card chips included in th        # Test data directory
+        self.datadir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", "..", "testdata")e matrices (integer)
+
+    Returns:
+    p1                 = an altair plot of the target and source color values
+
+    :param source_matrix: numpy.ndarray
+    :param target_matrix: numpy.ndarray
+    :param num_chips: int
+    :return p1: altair.vegalite.v5.api.Chart
+    """
+    # Scale matrices to 0-255
+    target_matrix = 255*target_matrix
+    source_matrix = 255*source_matrix
+
+    # Extract and organize matrix info
+    tr = target_matrix[:num_chips, 1:2]
+    tg = target_matrix[:num_chips, 2:3]
+    tb = target_matrix[:num_chips, 3:4]
+    sr = source_matrix[:num_chips, 1:2]
+    sg = source_matrix[:num_chips, 2:3]
+    sb = source_matrix[:num_chips, 3:4]
+
+    # Create columns of color labels
+    red = ["red"] * num_chips
+    blue = ["blue"] * num_chips
+    green = ["green"] * num_chips
+
+    # Make a column of chip numbers
+    chip = np.arange(0, num_chips).reshape((num_chips, 1))
+    chips = np.vstack((chip, chip, chip))
+
+    # Combine info
+    color_data_r = np.column_stack((sr, tr, red))
+    color_data_g = np.column_stack((sg, tg, green))
+    color_data_b = np.column_stack((sb, tb, blue))
+    all_color_data = np.vstack((color_data_b, color_data_g, color_data_r))
+
+    # Create a dataframe with headers
+    dataset = pd.DataFrame({'source': all_color_data[:, 0], 'target': all_color_data[:, 1],
+                            'color': all_color_data[:, 2]})
+
+    # Add chip numbers to the dataframe
+    dataset['chip'] = chips
+    dataset = dataset.astype({'color': str, 'chip': str, 'target': float, 'source': float})
+
+    # Make the plot
+    p1 = alt.Chart(dataset).mark_point(point=True).encode(
+        x="target",
+        y="source",
+        color=alt.Color("color").scale(range=["blue", "green", "red"]),
+        column="color"
+        )
+
+    _debug(visual=p1, filename=os.path.join(params.debug_outdir, 'color_quick_check.png'))
+
+    return p1.interactive()

plantcv/plantcv/transform/__init__.py

@@ -6,7 +6,6 @@
 from plantcv.plantcv.transform.color_correction import load_matrix
 from plantcv.plantcv.transform.color_correction import correct_color
 from plantcv.plantcv.transform.color_correction import create_color_card_mask
-from plantcv.plantcv.transform.color_correction import quick_color_check
 from plantcv.plantcv.transform.color_correction import std_color_matrix
 from plantcv.plantcv.transform.color_correction import astro_color_matrix
 from plantcv.plantcv.transform.color_correction import affine_color_correction
@@ -24,7 +23,7 @@
 from plantcv.plantcv.transform.auto_correct_color import auto_correct_color_nonlinear
 
 __all__ = ["get_color_matrix", "get_matrix_m", "calc_transformation_matrix", "apply_transformation_matrix",
-           "save_matrix", "load_matrix", "correct_color", "create_color_card_mask", "quick_color_check",
+           "save_matrix", "load_matrix", "correct_color", "create_color_card_mask",
            "std_color_matrix", "affine_color_correction", "rescale", "nonuniform_illumination", "resize",
            "resize_factor", "warp", "rotate", "warp", "warp_align", "gamma_correct", "detect_color_card", "checkerboard_calib",
            "calibrate_camera", "merge_images", "auto_correct_color", "mask_color_card", "auto_correct_color_nonlinear",

plantcv/plantcv/transform/color_correction.py

@@ -3,8 +3,6 @@
 import math
 import cv2
 import numpy as np
-import altair as alt
-import pandas as pd
 from plantcv.plantcv import params, fatal_error
 from plantcv.plantcv.roi import circle
 from plantcv.plantcv._debug import _debug
@@ -597,72 +595,3 @@ def create_color_card_mask(rgb_img, radius, start_coord, spacing, nrows, ncols,
     _debug(visual=canvas, filename=os.path.join(params.debug_outdir, str(params.device) + '_color_card_mask_rois.png'))
     _debug(visual=mask, filename=os.path.join(params.debug_outdir, str(params.device) + '_color_card_mask.png'))
     return mask
-
-
-def quick_color_check(target_matrix, source_matrix, num_chips):
-    """Plot the color values of a target and source color card matrix.
-
-    Quickly plot target matrix values against source matrix values to determine
-    over saturated color chips or other issues.
-
-    Inputs:
-    source_matrix      = an nrowsXncols matrix containing the avg red, green, and blue values for each color chip
-                            of the source image
-    target_matrix      = an nrowsXncols matrix containing the avg red, green, and blue values for each color chip
-                            of the target image
-    num_chips          = number of color card chips included in the matrices (integer)
-
-    Returns:
-    p1                 = an altair plot of the target and source color values
-
-    :param source_matrix: numpy.ndarray
-    :param target_matrix: numpy.ndarray
-    :param num_chips: int
-    :return p1: altair.vegalite.v5.api.Chart
-    """
-    # Scale matrices to 0-255
-    target_matrix = 255*target_matrix
-    source_matrix = 255*source_matrix
-
-    # Extract and organize matrix info
-    tr = target_matrix[:num_chips, 1:2]
-    tg = target_matrix[:num_chips, 2:3]
-    tb = target_matrix[:num_chips, 3:4]
-    sr = source_matrix[:num_chips, 1:2]
-    sg = source_matrix[:num_chips, 2:3]
-    sb = source_matrix[:num_chips, 3:4]
-
-    # Create columns of color labels
-    red = ["red"] * num_chips
-    blue = ["blue"] * num_chips
-    green = ["green"] * num_chips
-
-    # Make a column of chip numbers
-    chip = np.arange(0, num_chips).reshape((num_chips, 1))
-    chips = np.vstack((chip, chip, chip))
-
-    # Combine info
-    color_data_r = np.column_stack((sr, tr, red))
-    color_data_g = np.column_stack((sg, tg, green))
-    color_data_b = np.column_stack((sb, tb, blue))
-    all_color_data = np.vstack((color_data_b, color_data_g, color_data_r))
-
-    # Create a dataframe with headers
-    dataset = pd.DataFrame({'source': all_color_data[:, 0], 'target': all_color_data[:, 1],
-                            'color': all_color_data[:, 2]})
-
-    # Add chip numbers to the dataframe
-    dataset['chip'] = chips
-    dataset = dataset.astype({'color': str, 'chip': str, 'target': float, 'source': float})
-
-    # Make the plot
-    p1 = alt.Chart(dataset).mark_point(point=True).encode(
-        x="target",
-        y="source",
-        color=alt.Color("color").scale(range=["blue", "green", "red"]),
-        column="color"
-        )
-
-    _debug(visual=p1, filename=os.path.join(params.debug_outdir, 'color_quick_check.png'))
-
-    return p1.interactive()

tests/plantcv/qc/conftest.py

@@ -0,0 +1,29 @@
+import pytest
+import os
+import numpy as np
+import matplotlib
+
+# Disable plotting
+matplotlib.use("Template")
+
+
+class QCTestData:
+    def __init__(self):
+        """Initialize simple variables."""
+        # Test data directory
+        self.datadir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", "..", "testdata")
+        # Target matrix file
+        self.target_matrix_file = os.path.join(self.datadir, "target_matrix.npz")
+        # Source 1 matrix file
+        self.source1_matrix_file = os.path.join(self.datadir, "source1_matrix.npz")
+
+    @staticmethod
+    def load_npz(npz_file):
+        """Load data saved in a NumPy .npz file."""
+        data = np.load(npz_file, encoding="latin1")
+        return data['arr_0']
+
+@pytest.fixture(scope="session")
+def qc_test_data():
+    """Test data object for the PlantCV transform submodule."""
+    return QCTestData()

tests/plantcv/qc/test_quick_color_check.py

@@ -0,0 +1,11 @@
+from altair.vegalite.v5.api import Chart
+from plantcv.plantcv.qc.quick_color_check import quick_color_check
+
+
+def test_quick_color_check(qc_test_data):
+    """Test for PlantCV."""
+    # Load target image
+    target_matrix = qc_test_data.load_npz(qc_test_data.target_matrix_file)
+    source_matrix = qc_test_data.load_npz(qc_test_data.source1_matrix_file)
+    chart = quick_color_check(target_matrix, source_matrix, num_chips=22)
+    assert isinstance(chart, Chart)

tests/plantcv/transform/test_color_correction.py

@@ -3,10 +3,9 @@
 import os
 import cv2
 import numpy as np
-from altair.vegalite.v5.api import Chart
 from plantcv.plantcv.transform.color_correction import (get_color_matrix, get_matrix_m, calc_transformation_matrix,
                                                         apply_transformation_matrix, save_matrix, load_matrix, correct_color,
-                                                        create_color_card_mask, quick_color_check, std_color_matrix,
+                                                        create_color_card_mask, std_color_matrix,
                                                         astro_color_matrix, affine_color_correction)
 from plantcv.plantcv.transform.detect_color_card import detect_color_card
 
@@ -303,15 +302,6 @@ def test_create_color_card_mask(transform_test_data):
                                                                    220], dtype=np.uint8)))
 
 
-def test_quick_color_check(transform_test_data):
-    """Test for PlantCV."""
-    # Load target image
-    target_matrix = transform_test_data.load_npz(transform_test_data.target_matrix_file)
-    source_matrix = transform_test_data.load_npz(transform_test_data.source1_matrix_file)
-    chart = quick_color_check(target_matrix, source_matrix, num_chips=22)
-    assert isinstance(chart, Chart)
-
-
 def test_cameratrax_and_astro_consistent_color_calibration(transform_test_data):
     """Test for PlantCV."""
     # Load rgb image