diff --git a/Notebooks/Attribute Profiles Classifier.ipynb b/Notebooks/Attribute Profiles Classifier.ipynb index 7842e8a..7f1c066 100644 --- a/Notebooks/Attribute Profiles Classifier.ipynb +++ b/Notebooks/Attribute Profiles Classifier.ipynb @@ -332,6 +332,16 @@ "show(cv_labels)" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.imsave('../Res/labels.png', labels)\n", + "plt.imsave('../Res/prediction.png', cv_labels)" + ] + }, { "cell_type": "markdown", "metadata": {}, diff --git a/Notebooks/DFC2018 Ground truth split train and validation.ipynb b/Notebooks/DFC2018 Ground truth split train and validation.ipynb index 6f8be31..832fa7e 100644 --- a/Notebooks/DFC2018 Ground truth split train and validation.ipynb +++ b/Notebooks/DFC2018 Ground truth split train and validation.ipynb @@ -101,7 +101,7 @@ "metadata": {}, "outputs": [], "source": [ - "train_part = .7\n", + "train_part = .9\n", "\n", "split = np.zeros_like(gt)\n", "\n", @@ -118,6 +118,32 @@ "plt.show()" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import matplotlib.animation\n", + "import numpy as np\n", + "\n", + "t = np.linspace(0,2*np.pi)\n", + "x = np.sin(t)\n", + "\n", + "fig, ax = plt.subplots()\n", + "ax.axis([0,2*np.pi,-1,1])\n", + "l, = ax.plot([],[])\n", + "\n", + "def animate(i):\n", + " l.set_data(t[:i], x[:i])\n", + "\n", + "ani = matplotlib.animation.FuncAnimation(fig, animate, frames=len(t))\n", + "\n", + "from IPython.display import HTML\n", + "HTML(ani.to_jshtml())" + ] + }, { "cell_type": "markdown", "metadata": {}, diff --git a/Notebooks/Node Streaming Benchmark.ipynb b/Notebooks/Node Streaming Benchmark.ipynb index 3e43c08..b3d81a7 100644 --- a/Notebooks/Node Streaming Benchmark.ipynb +++ b/Notebooks/Node Streaming Benchmark.ipynb @@ -41,17 +41,32 @@ "metadata": {}, "outputs": [], "source": [ - "l = ld2dap.LoadTIFF(layers_files[5])\n", + "l = ld2dap.LoadTIFF(layers_files)\n", "t = ld2dap.Treshold(1e4)\n", - "a = ld2dap.AttributeProfiles(area = [1e3, 1e6])\n", + "a = ld2dap.SelfDualAttributeProfiles(area = [1e3, 1e6])\n", "f = ld2dap.Differential()\n", - "d = ld2dap.ShowFig('all', fname='../Res/aps.png', pad_inches=0, symb=True, vmax=255)\n", + "d_ap_3 = ld2dap.ShowFig(stack_id=3, fname='../Res/daps_3.png', pad_inches=0, symb=True, vmax=255, transparent=True)\n", + "d_dap_3 = ld2dap.ShowFig(stack_id=3, fname='../Res/aps_3.png', pad_inches=0, symb=True, vmax=255, transparent=True)\n", + "d_ap_6 = ld2dap.ShowFig(stack_id=6, fname='../Res/daps_6.png', pad_inches=0, symb=True, vmax=255, transparent=True)\n", + "d_dap_6 = ld2dap.ShowFig(stack_id=6, fname='../Res/aps_6.png', pad_inches=0, symb=True, vmax=255, transparent=True)\n", + "\n", + "\n", "\n", "t.input = l\n", "a.input = t\n", "f.input = a\n", - "d.input = f\n", - "d.run()" + "d_dap_3.input = f\n", + "d_dap_6.input = f\n", + "d_ap_3.input = a\n", + "d_ap_6.input = a\n", + "l.run()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "$\\rho^{area}_{1000}$" ] }, { diff --git a/ld2dap/SelfDualAttributeProfiles.py b/ld2dap/SelfDualAttributeProfiles.py index fd5f9c0..8a917ef 100644 --- a/ld2dap/SelfDualAttributeProfiles.py +++ b/ld2dap/SelfDualAttributeProfiles.py @@ -42,7 +42,7 @@ class SelfDualAttributeProfiles(Filter): if self.__getattribute__(att) is not None: att_symb[att].append(None) att_symb[att].extend( - ['\rho^{{{}}}_{{{}}}'.format(att, x) for x in self.__getattribute__(att)]) + ['\\rho^{{{}}}_{{{}}}'.format(att, x) for x in self.__getattribute__(att)]) return att_symb diff --git a/ld2dap/ShowFig.py b/ld2dap/ShowFig.py index c7bc272..0b7e464 100644 --- a/ld2dap/ShowFig.py +++ b/ld2dap/ShowFig.py @@ -13,7 +13,7 @@ from ld2dap.core import Output import matplotlib.pyplot as plt class ShowFig(Output): - def __init__(self, stack_id=0, symb=False, fname=None, bbox_inches='tight', pad_inches=1, vmax=None): + def __init__(self, stack_id=0, symb=False, fname=None, bbox_inches='tight', pad_inches=1, vmax=None, transparent=False): super().__init__(self.__class__.__name__) self.bbox_inches = bbox_inches self.pad_inches = pad_inches @@ -21,6 +21,7 @@ class ShowFig(Output): self.symb = symb self.fname = fname self.vmax = vmax + self.transparent = transparent def _process(self, data, metadata): if self.stack_id == 'all': @@ -49,6 +50,6 @@ class ShowFig(Output): f1.set_title(' > '.join(filter(None, stack.desc[i]))) if self.fname is not None: - fig.savefig(self.fname, bbox_inches=self.bbox_inches, pad_inches=self.pad_inches) + fig.savefig(self.fname, bbox_inches=self.bbox_inches, pad_inches=self.pad_inches, transparent=self.transparent) plt.show() plt.close(fig)