deploy: phasorpy/phasorpy@7ea1582

main/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: cdee86f95429db0157b438fbe50abede
+config: 6a1d0a9c1312d1a5df376d628fa2dfc5
 tags: 645f666f9bcd5a90fca523b33c5a78b7

main/_downloads/bf9341a139a683d2ea1e508551acdd49/phasorpy_components.py

@@ -9,10 +9,15 @@
 # %%
 # Import required modules, functions, and classes:
 
+import matplotlib.animation as animation
 import matplotlib.pyplot as plt
 import numpy
 
-from phasorpy.components import two_fractions_from_phasor
+from phasorpy._utils import line_from_components, mask_segment
+from phasorpy.components import (
+    graphical_component_analysis,
+    two_fractions_from_phasor,
+)
 from phasorpy.phasor import phasor_from_lifetime
 from phasorpy.plot import PhasorPlot
 
@@ -61,7 +66,7 @@
 # phasor coordinates:
 
 real, imag = numpy.random.multivariate_normal(
-    (0.6, 0.35), [[8e-3, 1e-3], [1e-3, 1e-3]], (100, 100)
+    (0.5, 0.33), [[5e-3, 1e-3], [1e-3, 1e-3]], (100, 100)
 ).T
 plot = PhasorPlot(
     frequency=frequency,
@@ -102,5 +107,122 @@
 plt.tight_layout()
 plt.show()
 
+# %%
+# Graphical solution for the contribution of multiple components
+# --------------------------------------------------------------
+#
+# The :py:func:`graphical_component_analysis` function performs the graphical
+# analysis for two or three components and returns the number of phasors
+# for each fraction of the components (with respect to other components):
+components_real, components_imag = phasor_from_lifetime(
+    frequency, [1.0, 4.0, 15.0]
+)
+counts, fractions = graphical_component_analysis(
+    real, imag, components_real, components_imag
+)
+fig, ax = plt.subplots()
+plot = PhasorPlot(
+    frequency=frequency,
+    title='Phasor with contribution of three known components',
+    ax=ax,
+)
+plot.hist2d(real, imag, cmap='plasma')
+plot.plot(components_real, components_imag, 'o-', color='blue')
+plot.plot(
+    components_real[[0, -1]], components_imag[[0, -1]], fmt='-', color='blue'
+)
+ax.annotate('A', xy=(0.8, 0.45), fontsize=16, fontweight='bold', color='blue')
+ax.annotate('B', xy=(0.13, 0.43), fontsize=16, fontweight='bold', color='blue')
+ax.annotate(
+    'C', xy=(-0.04, 0.12), fontsize=16, fontweight='bold', color='blue'
+)
+plt.show()
+
+# %%
+# The results can be plotted as histograms for each component pair:
+
+fig, ax = plt.subplots()
+ax.plot(fractions, counts[0], linestyle='-', label='Component A vs B')
+ax.plot(fractions, counts[1], linestyle='-', label='Component A vs C')
+ax.plot(fractions, counts[2], linestyle='-', label='Component B vs C')
+ax.set_xlabel('Fraction of component')
+ax.set_ylabel('Counts')
+ax.set_title('Contribution of multiple components')
+ax.legend()
+plt.show()
+
+# %%
+# The graphical method for resolving the contribution of two or
+# three components (pairwise) to a phasor coordinate is based on
+# the quantification of moving circular cursors along the line
+# between the components, demonstrated in the following animation
+# which is repeated for the other combinations of components:
+
+grid_x = numpy.linspace(-0.2, 1, int((1 + 0.2) / 0.001) + 1)
+grid_y = numpy.linspace(-0.2, 0.6, int((0.6 + 0.2) / 0.001) + 1)
+grid_x, grid_y = numpy.meshgrid(grid_x, grid_y)
+cursor_diameter = 0.05
+number_of_steps = 30
+fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(5, 8))
+real_a, imag_a = [components_real[0], components_imag[0]]
+real_b, imag_b = [components_real[1], components_imag[1]]
+real_c, imag_c = [components_real[2], components_imag[2]]
+component_counts = []
+fractions = numpy.asarray(numpy.linspace(0, 1, number_of_steps + 1))
+unit_vector, distance = line_from_components(
+    [real_b, real_a], [imag_b, imag_a]
+)
+cursor_real, cursor_imag = real_b, imag_b
+step_size = distance / number_of_steps
+plot = PhasorPlot(frequency=frequency, ax=ax1)
+plot.hist2d(real, imag, cmap='plasma')
+plot.plot([real_a, real_b], [imag_a, imag_b], fmt='o-', color='blue')
+plot.plot(real_c, imag_c, fmt='o', color='blue')
+plots = []
+for step in range(number_of_steps + 1):
+    mask_shape = mask_segment(
+        grid_x,
+        grid_y,
+        cursor_real,
+        cursor_imag,
+        real_c,
+        imag_c,
+        cursor_diameter / 2,
+    )
+    plot.plot(grid_x[mask_shape], grid_y[mask_shape], color='red', alpha=0.01)
+    mask_phasors = mask_segment(
+        real,
+        imag,
+        cursor_real,
+        cursor_imag,
+        real_c,
+        imag_c,
+        cursor_diameter / 2,
+    )
+    fraction_counts = numpy.sum(mask_phasors)
+    component_counts.append(fraction_counts)
+    hist_artists = plt.plot(
+        fractions[: step + 1], component_counts, linestyle='-', color='blue'
+    )
+    plots.append(plot._lines + hist_artists)
+    cursor_real += step_size * unit_vector[0]
+    cursor_imag += step_size * unit_vector[1]
+moving_cursor_animation = animation.ArtistAnimation(
+    fig, plots, interval=100, blit=True
+)
+ax2.set_xlim(0, 1)
+ax2.set_title('Fraction of component A (respect to B)')
+ax2.set_xlabel('Fraction of A')
+ax2.set_ylabel('Counts')
+ax1.annotate('A', xy=(0.8, 0.45), fontsize=14, fontweight='bold', color='blue')
+ax1.annotate(
+    'B', xy=(0.13, 0.43), fontsize=14, fontweight='bold', color='blue'
+)
+ax1.annotate(
+    'C', xy=(-0.04, 0.12), fontsize=14, fontweight='bold', color='blue'
+)
+plt.tight_layout()
+plt.show()
+
 # %%
 # sphinx_gallery_thumbnail_number = 2

main/_downloads/ccecd4264e0158187b962766cb9fbe11/phasorpy_components.ipynb

@@ -22,7 +22,7 @@
       },
       "outputs": [],
       "source": [
-        "import matplotlib.pyplot as plt\nimport numpy\n\nfrom phasorpy.components import two_fractions_from_phasor\nfrom phasorpy.phasor import phasor_from_lifetime\nfrom phasorpy.plot import PhasorPlot\n\nnumpy.random.seed(42)"
+        "import matplotlib.animation as animation\nimport matplotlib.pyplot as plt\nimport numpy\n\nfrom phasorpy._utils import line_from_components, mask_segment\nfrom phasorpy.components import (\n    graphical_component_analysis,\n    two_fractions_from_phasor,\n)\nfrom phasorpy.phasor import phasor_from_lifetime\nfrom phasorpy.plot import PhasorPlot\n\nnumpy.random.seed(42)"
       ]
     },
     {
@@ -76,7 +76,7 @@
       },
       "outputs": [],
       "source": [
-        "real, imag = numpy.random.multivariate_normal(\n    (0.6, 0.35), [[8e-3, 1e-3], [1e-3, 1e-3]], (100, 100)\n).T\nplot = PhasorPlot(\n    frequency=frequency,\n    title='Phasor with contribution of two known components',\n)\nplot.hist2d(real, imag, cmap='plasma')\nplot.plot(*phasor_from_lifetime(frequency, components_lifetimes), fmt='o-')\nplot.show()"
+        "real, imag = numpy.random.multivariate_normal(\n    (0.5, 0.33), [[5e-3, 1e-3], [1e-3, 1e-3]], (100, 100)\n).T\nplot = PhasorPlot(\n    frequency=frequency,\n    title='Phasor with contribution of two known components',\n)\nplot.hist2d(real, imag, cmap='plasma')\nplot.plot(*phasor_from_lifetime(frequency, components_lifetimes), fmt='o-')\nplot.show()"
       ]
     },
     {
@@ -97,6 +97,60 @@
         "(\n    fraction_from_first_component,\n    fraction_from_second_component,\n) = two_fractions_from_phasor(real, imag, components_real, components_imag)\nfig, ax = plt.subplots()\nax.hist(\n    fraction_from_first_component.flatten(),\n    range=(0, 1),\n    bins=100,\n    alpha=0.75,\n    label='First',\n)\nax.hist(\n    fraction_from_second_component.flatten(),\n    range=(0, 1),\n    bins=100,\n    alpha=0.75,\n    label='Second',\n)\nax.set_title('Histograms of fractions of first and second component')\nax.set_xlabel('Fraction')\nax.set_ylabel('Counts')\nax.legend()\nplt.tight_layout()\nplt.show()"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Graphical solution for the contribution of multiple components\n\nThe :py:func:`graphical_component_analysis` function performs the graphical\nanalysis for two or three components and returns the number of phasors\nfor each fraction of the components (with respect to other components):\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "components_real, components_imag = phasor_from_lifetime(\n    frequency, [1.0, 4.0, 15.0]\n)\ncounts, fractions = graphical_component_analysis(\n    real, imag, components_real, components_imag\n)\nfig, ax = plt.subplots()\nplot = PhasorPlot(\n    frequency=frequency,\n    title='Phasor with contribution of three known components',\n    ax=ax,\n)\nplot.hist2d(real, imag, cmap='plasma')\nplot.plot(components_real, components_imag, 'o-', color='blue')\nplot.plot(\n    components_real[[0, -1]], components_imag[[0, -1]], fmt='-', color='blue'\n)\nax.annotate('A', xy=(0.8, 0.45), fontsize=16, fontweight='bold', color='blue')\nax.annotate('B', xy=(0.13, 0.43), fontsize=16, fontweight='bold', color='blue')\nax.annotate(\n    'C', xy=(-0.04, 0.12), fontsize=16, fontweight='bold', color='blue'\n)\nplt.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "The results can be plotted as histograms for each component pair:\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "fig, ax = plt.subplots()\nax.plot(fractions, counts[0], linestyle='-', label='Component A vs B')\nax.plot(fractions, counts[1], linestyle='-', label='Component A vs C')\nax.plot(fractions, counts[2], linestyle='-', label='Component B vs C')\nax.set_xlabel('Fraction of component')\nax.set_ylabel('Counts')\nax.set_title('Contribution of multiple components')\nax.legend()\nplt.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "The graphical method for resolving the contribution of two or\nthree components (pairwise) to a phasor coordinate is based on\nthe quantification of moving circular cursors along the line\nbetween the components, demonstrated in the following animation\nwhich is repeated for the other combinations of components:\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "grid_x = numpy.linspace(-0.2, 1, int((1 + 0.2) / 0.001) + 1)\ngrid_y = numpy.linspace(-0.2, 0.6, int((0.6 + 0.2) / 0.001) + 1)\ngrid_x, grid_y = numpy.meshgrid(grid_x, grid_y)\ncursor_diameter = 0.05\nnumber_of_steps = 30\nfig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(5, 8))\nreal_a, imag_a = [components_real[0], components_imag[0]]\nreal_b, imag_b = [components_real[1], components_imag[1]]\nreal_c, imag_c = [components_real[2], components_imag[2]]\ncomponent_counts = []\nfractions = numpy.asarray(numpy.linspace(0, 1, number_of_steps + 1))\nunit_vector, distance = line_from_components(\n    [real_b, real_a], [imag_b, imag_a]\n)\ncursor_real, cursor_imag = real_b, imag_b\nstep_size = distance / number_of_steps\nplot = PhasorPlot(frequency=frequency, ax=ax1)\nplot.hist2d(real, imag, cmap='plasma')\nplot.plot([real_a, real_b], [imag_a, imag_b], fmt='o-', color='blue')\nplot.plot(real_c, imag_c, fmt='o', color='blue')\nplots = []\nfor step in range(number_of_steps + 1):\n    mask_shape = mask_segment(\n        grid_x,\n        grid_y,\n        cursor_real,\n        cursor_imag,\n        real_c,\n        imag_c,\n        cursor_diameter / 2,\n    )\n    plot.plot(grid_x[mask_shape], grid_y[mask_shape], color='red', alpha=0.01)\n    mask_phasors = mask_segment(\n        real,\n        imag,\n        cursor_real,\n        cursor_imag,\n        real_c,\n        imag_c,\n        cursor_diameter / 2,\n    )\n    fraction_counts = numpy.sum(mask_phasors)\n    component_counts.append(fraction_counts)\n    hist_artists = plt.plot(\n        fractions[: step + 1], component_counts, linestyle='-', color='blue'\n    )\n    plots.append(plot._lines + hist_artists)\n    cursor_real += step_size * unit_vector[0]\n    cursor_imag += step_size * unit_vector[1]\nmoving_cursor_animation = animation.ArtistAnimation(\n    fig, plots, interval=100, blit=True\n)\nax2.set_xlim(0, 1)\nax2.set_title('Fraction of component A (respect to B)')\nax2.set_xlabel('Fraction of A')\nax2.set_ylabel('Counts')\nax1.annotate('A', xy=(0.8, 0.45), fontsize=14, fontweight='bold', color='blue')\nax1.annotate(\n    'B', xy=(0.13, 0.43), fontsize=14, fontweight='bold', color='blue'\n)\nax1.annotate(\n    'C', xy=(-0.04, 0.12), fontsize=14, fontweight='bold', color='blue'\n)\nplt.tight_layout()\nplt.show()"
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {},