Locstable

examples/article_figures/fig1_hiv_examples.py

@@ -0,0 +1,186 @@
+from vlab4mic import experiments
+import matplotlib.pyplot as plt
+import os
+seed = 1
+
+
+images, noisless, my_experiment = experiments.image_vsample(
+    structure="3J3Y",
+    probe_template="anti-p24_primary_antibody_HIV",
+    probe_DoL=3,
+    structural_integrity_small_cluster=20,
+    structural_integrity_large_cluster=100,
+    sample_dimensions=[1000,1000,100],
+    random_orientations=True,
+    structural_integrity=1,
+    clear_experiment=True,
+    number_of_particles=30,
+    multimodal=["Widefield", "Confocal", "AiryScan", "STED", "SMLM", "Reference"],
+    random_seed=seed,
+    run_simulation=False,
+)
+my_experiment.set_virtualsample_params(minimal_distance=110)
+my_experiment.build(modules=["coordinate_field"])
+my_experiment.update_modality(modality_name="SMLM",
+                              pixelsize_nm=2,
+                              psf_voxel_nm=2,
+                              depth_of_field_nm=1000,
+                              lateral_resolution_nm=5,
+                              simulate_localistations=True,
+                              lateral_precision=5,
+                              axial_precision=5,
+                              nlocalisations=20)
+my_experiment.update_modality(modality_name="STED", depth_of_field_nm=1000, lateral_resolution_nm=30)
+my_experiment.set_modality_acq(modality_name="STED", exp_time=0.001)
+my_experiment.update_modality(modality_name="Reference",
+                              pixelsize_nm=2,
+                              psf_voxel_nm=2,
+                              depth_of_field_nm=1000,
+                              lateral_resolution_nm=2,
+                              simulate_localistations=True,
+                              lateral_precision=0.001,
+                              axial_precision=0.001,
+                              nlocalisations=30)
+my_experiment.set_modality_acq(modality_name="Reference", exp_time=1)
+my_experiment.build(modules=["imager"])
+images, noiseless = my_experiment.run_simulation()
+modalities = list(images.keys())
+n_modalities = len(modalities)
+fig = plt.figure(figsize=[40,10])
+
+for i, name in enumerate(modalities):
+    ax = fig.add_subplot(1, n_modalities, i+1)
+    ax.imshow(images[name]["ch0"][0], cmap="grey")
+    ax.set_axis_off()
+
+filename = my_experiment.date_as_string + 'vlab4mic_hiv_modalities.png'
+filename2 = os.path.join(my_experiment.output_directory, filename)
+fig.savefig(filename2,dpi=300, bbox_inches='tight')
+plt.close()
+
+
+target_colour="#01579D"
+fig = plt.figure(figsize=[20,10])
+ax = fig.add_subplot(1, 2, 1, projection="3d")
+total = my_experiment.structure.num_assembly_atoms
+fraction = 100000/total
+my_experiment.structure.show_target_labels(
+    with_assembly_atoms=True, 
+    axis_object=ax, 
+    show_axis=False, 
+    assembly_fraction = fraction,
+    view_init=[20,0,0],
+    target_size = 0,
+    atoms_size = 10,
+    atoms_alpha = 0.01,
+    reference_point = False,
+    target_plotcolour=target_colour
+    )
+ax = fig.add_subplot(1, 2, 2, projection="3d")
+total = my_experiment.structure.num_assembly_atoms
+fraction = 100000/total
+my_experiment.structure.show_target_labels(
+    with_assembly_atoms=True, 
+    axis_object=ax, 
+    show_axis=False, 
+    assembly_fraction = fraction,
+    view_init=[20,0,0],
+    target_size = 15,
+    atoms_size = 10,
+    atoms_alpha = 0.01,
+    reference_point = False,
+    target_plotcolour=target_colour
+    )
+probe_template = list(my_experiment.probe_parameters.keys())[0]
+title = "Structure: 3J3Y \n Probe: " + probe_template
+title = title + "\n" + "Sequence: " + my_experiment.probe_parameters[probe_template]["target"]["value"]
+ax.set_title(title)
+filename = my_experiment.date_as_string + 'vlab4mic_hiv_structure_epitopes.png'
+filename2 = os.path.join(my_experiment.output_directory, filename)
+fig.savefig(filename2,dpi=300, bbox_inches='tight')
+plt.close()
+
+
+fig = plt.figure(figsize=[5,5])
+ax = fig.add_subplot(1, 1, 1, projection="3d")
+my_experiment.particle.show_probe(
+    plotcolour="#984ea3", axesoff=True,
+    with_structural_atoms=True,
+    emitter_plotsize=70,
+    atoms_plotalpha=0.05,
+    atoms_plotsize=10,
+    atoms_fraction=0.3,
+    view_init=[0,40,100],
+    central_axis=False,
+    use_dol=True,
+    axis_object = ax,
+    )
+
+filename = my_experiment.date_as_string + 'vlab4mic_hiv_antibody.png'
+filename2 = os.path.join(my_experiment.output_directory, filename)
+fig.savefig(filename2,dpi=300, bbox_inches='tight')
+plt.close()
+
+
+target_colour="#01579D"
+plotmarker="o"
+emitter_plotmarker = "o"
+hiv_antibody=dict(
+        source_plotsize=3,
+        emitter_plotsize=50,
+        source_plotcolour=target_colour,
+        source_plotalpha=1,
+        source_plotmarker=plotmarker,
+        emitter_plotmarker=emitter_plotmarker
+    )
+fig = plt.figure(figsize=[10,10])
+ax = fig.add_subplot(1, 1, 1, projection="3d")
+my_experiment.particle.gen_axis_plot(
+        reference_point=False,
+        view_init=[20, 0, 0],
+        axesoff=True,
+        show_axis=False,
+        with_sources=True,
+        axis_object=ax,
+        with_normals=False,
+        **hiv_antibody)
+filename = my_experiment.date_as_string + 'vlab4mic_hiv_labelled_particle.png'
+filename2 = os.path.join(my_experiment.output_directory, filename)
+fig.savefig(filename2,dpi=300, bbox_inches='tight')
+plt.close()
+
+n_examples = 8
+fig = plt.figure(figsize=[20, 10])
+row=2
+my_experiment.set_structural_integrity(
+            structural_integrity=1,
+            structural_integrity_small_cluster=20,
+            structural_integrity_large_cluster=100,
+        )
+my_experiment.build(modules=["particle",])
+for i in range(n_examples):
+    ax = fig.add_subplot(row, int(n_examples/2), i+1, projection="3d")
+    if i == 4:
+        my_experiment.set_structural_integrity(
+            structural_integrity=0.5
+        )
+        my_experiment.build(modules=["particle",])
+
+    my_experiment.particle.generate_instance()
+    my_experiment.particle.gen_axis_plot(
+        reference_point=False,
+        view_init=[20, 0, 0],
+        axesoff=True,
+        show_axis=False,
+        with_sources=True,
+        axis_object=ax,
+        with_normals=False,
+        source_plotsize=1,
+        source_plotalpha=0.4,
+        emitter_plotsize=5,
+        )
+
+filename = my_experiment.date_as_string + 'vlab4mic_hiv_labelled_particle_examples.png'
+filename2 = os.path.join(my_experiment.output_directory, filename)
+fig.savefig(filename2,dpi=300, bbox_inches='tight')
+plt.close()

examples/article_figures/fig2_EF.py

@@ -5,9 +5,9 @@
 import os
 import numpy as np
 from vlab4mic.analysis.metrics import zoom_img
-from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar 
-np.random.seed(44)
+from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar
 
+random_seed = 24
 modalities = ["STED", "SMLM",]
 target_colour="#01579D"
 
@@ -18,8 +18,10 @@
     probe_template = "GFP_w_nanobody",
     probe_target_type = "Sequence",
     probe_target_value = "ELAVGSL",
+    probe_DoL = 2,
     multimodal=modalities,
-    clear_experiment=True
+    clear_experiment=True,
+    random_seed=random_seed
 )
 ############  T4 capsid head
 image_outputs2, image_outputs_noiseless2, experiment2 = image_vsample(
@@ -29,14 +31,19 @@
     multimodal=modalities,
     random_orientations=True,
     yz_orientations=[90,],
-    clear_experiment=True
+    clear_experiment=True,
+    random_seed=random_seed
 )
 ############  HIV-capsid
 image_outputs3, image_outputs_noiseless3, experiment3 = image_vsample(
     structure = "3J3Y",
-    probe_template = "anti-p24_primary_antibody_HIV",
+    probe_template = "Antibody",
+    probe_target_type = "Sequence",
+    probe_target_value = "SPRTLNA",
+    probe_DoL = 6,
     multimodal=modalities,
-    clear_experiment=True
+    clear_experiment=True,
+    random_seed=random_seed
 )
 ############ Clathrin coated pit, primary and secodnary labelling
 
@@ -50,15 +57,17 @@
     probe_template = "Antibody",
     probe_name="Secondary-clathrin",
     probe_target_type = "Primary",
-    probe_target_value = "Primary-clathrin"
+    probe_target_value = "Primary-clathrin",
+    probe_DoL = 1.5
 )
 image_outputs4, image_outputs_noiseless4, experiment4 = image_vsample(
     structure = "1XI5",
     primary_probe = primary,
     secondary_probe = secondary,
     multimodal=modalities,
     clear_experiment=True,
-    run_simulation=True
+    run_simulation=True,
+    random_seed=random_seed
 )
 
 
@@ -71,17 +80,17 @@
 #ax_general = fig.add_subplot(111, projection="3d")
 hide_axes=True
 experiment1.particle.transform_translate(np.array([0,0,0]))
-experiment1.particle.gen_axis_plot(axesoff=hide_axes, with_sources=True, axis_object=ax_general,target_colour=target_colour, source_plotsize=5, emitter_plotsize=5)
+experiment1.particle.gen_axis_plot(axesoff=hide_axes, with_sources=True, axis_object=ax_general,target_colour=target_colour, source_plotsize=5, emitter_plotsize=5, source_plotmarker="o")
 
 experiment4.particle.transform_translate(np.array([0,1400,0]))
-experiment4.particle.gen_axis_plot(axesoff=hide_axes,with_sources=True, axis_object=ax_general,target_colour=target_colour, source_plotsize=2, emitter_plotsize=0.5, source_plotalpha=1)
+experiment4.particle.gen_axis_plot(axesoff=hide_axes,with_sources=True, axis_object=ax_general,target_colour=target_colour, source_plotsize=2, emitter_plotsize=0.5, source_plotalpha=1, source_plotmarker="o")
 
 experiment2.particle.transform_translate(np.array([0,2600,0]))
 
-experiment2.particle.gen_axis_plot(axesoff=hide_axes, with_sources=True, axis_object=ax_general,target_colour=target_colour, source_plotsize=0.5, emitter_plotsize=10, source_plotalpha=0.05)
+experiment2.particle.gen_axis_plot(axesoff=hide_axes, with_sources=True, axis_object=ax_general,target_colour=target_colour, source_plotsize=0.5, emitter_plotsize=10, source_plotalpha=0.05, source_plotmarker="o")
 
 experiment3.particle.transform_translate(np.array([0,3800,0]))
-experiment3.particle.gen_axis_plot(axesoff=hide_axes, with_sources=True, axis_object=ax_general,target_colour=target_colour, source_plotsize=1, emitter_plotsize=0.5, source_plotalpha=1)
+experiment3.particle.gen_axis_plot(axesoff=hide_axes, with_sources=True, axis_object=ax_general,target_colour=target_colour, source_plotsize=1, emitter_plotsize=0.5, source_plotalpha=1, source_plotmarker="o")
 ax_general.set_zlim3d(bottom=-300, top=1000)
 ax_general.set_ylim3d(bottom=-500, top=4500)
 ax_general.set_xlim3d(left=0, right=1000)
@@ -98,10 +107,10 @@
 y0,y1 = figy*0.64, figy*0.82
 
 bbox = Bbox([[x0,y0],[x1,y1]])
-filename1 = os.path.join(experiment1.output_directory, 'vlab4mic_fig2_E.png')
-
-#bbox = bbox.transformed(ax_general.transData).transformed(fig.dpi_scale_trans.inverted())
+filename_ = experiment1.date_as_string + 'vlab4mic_fig2_E.png'
+filename1 = os.path.join(experiment1.output_directory, filename_)
 fig.savefig(filename1, dpi=300, bbox_inches=bbox)
+
 fig = plt.figure(figsize=[figy,figx])
 ax = fig.add_subplot(141)
 img_zoom = 0.6
@@ -142,5 +151,6 @@
 y0,y1 = figy*0.6, figy*0.89
 
 bbox = Bbox([[x0,y0],[x1,y1]])
-filename2 = os.path.join(experiment1.output_directory, 'vlab4mic_fig2_F.png')
+filename = experiment1.date_as_string + 'vlab4mic_fig2_F.png'
+filename2 = os.path.join(experiment1.output_directory, filename)
 fig.savefig(filename2,dpi=300, bbox_inches=bbox)

examples/article_figures/fig3F.py

@@ -316,7 +316,7 @@ def render_from_localisations(localisations, crop_size_nm = 3000, centerx = None
 axs[0,0].set_ylabel("Thevathasan, et al. 2019", fontsize=24)
 axs[1,0].set_ylabel("VLab4Mic simulation", fontsize=24)
 plt.tight_layout(h_pad=0, w_pad=3)
-
-filename = os.path.join(my_experiment.output_directory, 'vlab4mic_fig3F_url.png')
+name = my_experiment.date_as_string + 'vlab4mic_fig3F_url.png'
+filename = os.path.join(my_experiment.output_directory, name)
 fig.savefig(filename, dpi=300, bbox_inches='tight')
 plt.close()