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JNB: Blacken notebooks #180

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merged 5 commits into from Jun 18, 2021
Merged

JNB: Blacken notebooks #180

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c61dcc7
DEV: nbstripout needs to be before large file check
scottclowe Jun 16, 2021
75f4d8f
DEV: Add black_nbconvert to pre-commit
scottclowe Jun 16, 2021
6e5afcf
JNB:STY: Blacken notebooks
scottclowe Jun 16, 2021
58a2f6f
JNB:STY: Blacken code in comments
scottclowe Jun 15, 2021
cf17610
JNB:STY: Fix formatting after cell magic, not caught by black
scottclowe Jun 16, 2021
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15 changes: 10 additions & 5 deletions .pre-commit-config.yaml
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Expand Up @@ -10,6 +10,16 @@ repos:
- id: rst-inline-touching-normal
types: [text]

- repo: https://github.com/kynan/nbstripout
rev: 0.4.0
hooks:
- id: nbstripout

- repo: https://github.com/dfm/black_nbconvert
rev: dcd7789
hooks:
- id: black_nbconvert

- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v3.3.0
hooks:
Expand All @@ -30,8 +40,3 @@ repos:
- id: trailing-whitespace
args: [--markdown-linebreak-ext=md]
exclude: \.(html|svg)$

- repo: https://github.com/kynan/nbstripout
rev: 0.4.0
hooks:
- id: nbstripout
53 changes: 31 additions & 22 deletions examples/Basic usage.ipynb
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Expand Up @@ -39,8 +39,9 @@
"source": [
"# Import our plotting toolbox, and enable options for embedded notebook figures\n",
"import holoviews as hv\n",
"\n",
"%load_ext holoviews.ipython\n",
"%output widgets='embed'"
"%output widgets=\"embed\""
]
},
{
Expand All @@ -58,7 +59,7 @@
"\n",
"Images can be defined as a folder with tiff stacks:\n",
"```python\n",
"images = 'folder'\n",
"images = \"folder\"\n",
"```\n",
"Where each tiff stack in the folder is a trial with several frames.\n",
"\n",
Expand All @@ -71,8 +72,8 @@
"\n",
"If the ROIs were defined using ImageJ use ImageJ's export function to save them in a zip. Then, indicate the locations as a list:\n",
"```python\n",
"rois = 'rois.zip' # for a single set of rois across images\n",
"rois = ['rois1.zip', 'rois2.zip', ...] # for a roiset for each image\n",
"rois = \"rois.zip\" # for a single set of rois across images\n",
"rois = [\"rois1.zip\", \"rois2.zip\", ...] # for a roiset for each image\n",
"```\n",
"Defining a different roiset per image can be useful if you need to adjust for motion drift for example.\n",
"\n",
Expand All @@ -86,15 +87,15 @@
"outputs": [],
"source": [
"# Define image and ROI locations\n",
"images_location = 'exampleData/20150529'\n",
"rois_location = 'exampleData/20150429.zip'\n",
"images_location = \"exampleData/20150529\"\n",
"rois_location = \"exampleData/20150429.zip\"\n",
"\n",
"# Define the folder where FISSA's outputs will be stored, so they can be\n",
"# quickly reloaded in the future without having to recompute them.\n",
"# Make sure to use a different folder for each experiment.\n",
"# This argument is optional; if it is not provided, FISSA will not save its\n",
"# results for later use.\n",
"output_folder = 'fissa_example'\n",
"output_folder = \"fissa_example\"\n",
"\n",
"experiment = fissa.Experiment(images_location, rois_location, output_folder)"
]
Expand Down Expand Up @@ -212,8 +213,9 @@
"c = 2\n",
"t = 1\n",
"\n",
"(hv.Curve(experiment.raw[c][t][0, :], label='Raw')\n",
" * hv.Curve(experiment.result[c, t][0, :], label='Decontaminated')\n",
"(\n",
" hv.Curve(experiment.raw[c][t][0, :], label=\"Raw\")\n",
" * hv.Curve(experiment.result[c, t][0, :], label=\"Decontaminated\")\n",
")"
]
},
Expand Down Expand Up @@ -249,8 +251,9 @@
"c = 2\n",
"t = 1\n",
"\n",
"(hv.Curve(experiment.deltaf_raw[c][t], label='Raw', vdims=['df/f0']) *\n",
" hv.Curve(experiment.deltaf_result[c, t][0, :], label='Decontaminated')\n",
"(\n",
" hv.Curve(experiment.deltaf_raw[c][t], label=\"Raw\", vdims=[\"df/f0\"])\n",
" * hv.Curve(experiment.deltaf_result[c, t][0, :], label=\"Decontaminated\")\n",
")"
]
},
Expand Down Expand Up @@ -285,10 +288,10 @@
"```octave\n",
"ROIs.cell0.trial0{1} % polygon for the ROI\n",
"ROIs.cell0.trial0{2} % polygon for first neuropil subregion\n",
"result.cell0.trial0(1,:) % final extracted cell signal\n",
"result.cell0.trial0(2,:) % contaminating signal\n",
"raw.cell0.trial0(1,:) % raw measured celll signal\n",
"raw.cell0.trial0(2,:) % raw signal from first neuropil subregion\n",
"result.cell0.trial0(1, :) % final extracted cell signal\n",
"result.cell0.trial0(2, :) % contaminating signal\n",
"raw.cell0.trial0(1, :) % raw measured celll signal\n",
"raw.cell0.trial0(2, :) % raw signal from first neuropil subregion\n",
"```"
]
},
Expand Down Expand Up @@ -382,12 +385,12 @@
"\n",
"t = trial_of_interest\n",
"\n",
"plt.imshow(experiment.means[t], cmap='gray')\n",
"plt.imshow(experiment.means[t], cmap=\"gray\")\n",
"for roi_poly in experiment.roi_polys:\n",
" # Plot border around cells\n",
" # plt.plot(roi_poly[t][0][0][:, 1], roi_poly[t][0][0][:, 0], ':c')\n",
" # plt.plot(roi_poly[t][0][0][:, 1], roi_poly[t][0][0][:, 0], \":c\")\n",
" # Fill cells with partially-transparent shaded area\n",
" plt.fill(roi_poly[t][0][0][:, 1], roi_poly[t][0][0][:, 0], ':r', alpha=0.2)\n",
" plt.fill(roi_poly[t][0][0][:, 1], roi_poly[t][0][0][:, 0], \":r\", alpha=0.2)\n",
"plt.show()"
]
},
Expand Down Expand Up @@ -436,7 +439,8 @@
" rois_location,\n",
" output_folder,\n",
" nRegions=nRegions,\n",
" expansion=expansion,alpha=alpha,\n",
" expansion=expansion,\n",
" alpha=alpha,\n",
" ncores_preparation=ncores_preparation,\n",
" ncores_separation=ncores_separation,\n",
")\n",
Expand Down Expand Up @@ -469,8 +473,9 @@
"c = 2\n",
"t = 1\n",
"\n",
"(hv.Curve(experiment.raw[c][t][0, :], label='Raw')\n",
" * hv.Curve(experiment.result[c, t][0, :], label='Decontaminated')\n",
"(\n",
" hv.Curve(experiment.raw[c][t][0, :], label=\"Raw\")\n",
" * hv.Curve(experiment.result[c, t][0, :], label=\"Decontaminated\")\n",
")"
]
},
Expand Down Expand Up @@ -509,7 +514,9 @@
"metadata": {},
"outputs": [],
"source": [
"experiment = fissa.Experiment(images_location, rois_location, output_folder, lowmemory_mode=True)\n",
"experiment = fissa.Experiment(\n",
" images_location, rois_location, output_folder, lowmemory_mode=True\n",
")\n",
"experiment.separate(redo_prep=True)"
]
},
Expand Down Expand Up @@ -550,6 +557,7 @@
"# appropriately. In this case, we only need to overwrite the\n",
"# `image2array` method to work with our custom data format.\n",
"\n",
"\n",
"class DataHandlerCustom(DataHandlerTifffile):\n",
" @staticmethod\n",
" def image2array(image):\n",
Expand All @@ -569,6 +577,7 @@
" # Some custom code\n",
" pass\n",
"\n",
"\n",
"# Then pass an instance of this class to fissa.Experiment when creating\n",
"# a new experiment.\n",
"datahandler = DataHandlerCustom()\n",
Expand Down
32 changes: 19 additions & 13 deletions examples/SIMA example.ipynb
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Expand Up @@ -38,8 +38,9 @@
"\n",
"# Plotting toolbox, with notebook embedding options\n",
"import holoviews as hv\n",
"\n",
"%load_ext holoviews.ipython\n",
"%output widgets='embed'"
"%output widgets=\"embed\""
]
},
{
Expand All @@ -63,20 +64,20 @@
"outputs": [],
"source": [
"# Define folder where tiffs are present\n",
"tiff_folder = 'exampleData/20150529/'\n",
"tiff_folder = \"exampleData/20150529/\"\n",
"\n",
"# Find tiffs in folder\n",
"tiffs = sorted(glob.glob(tiff_folder + '/*.tif*'))\n",
"tiffs = sorted(glob.glob(tiff_folder + \"/*.tif*\"))\n",
"\n",
"# define motion correction method\n",
"mc_approach = sima.motion.DiscreteFourier2D()\n",
"\n",
"# Define SIMA dataset\n",
"sequences = [sima.Sequence.create('TIFF', tiff) for tiff in tiffs[:1]]\n",
"sequences = [sima.Sequence.create(\"TIFF\", tiff) for tiff in tiffs[:1]]\n",
"try:\n",
" dataset = sima.ImagingDataset(sequences, 'example.sima')\n",
" dataset = sima.ImagingDataset(sequences, \"example.sima\")\n",
"except:\n",
" dataset = sima.ImagingDataset.load('example.sima')"
" dataset = sima.ImagingDataset.load(\"example.sima\")"
]
},
{
Expand All @@ -96,7 +97,7 @@
"stica_approach.append(sima.segment.SparseROIsFromMasks())\n",
"stica_approach.append(sima.segment.SmoothROIBoundaries())\n",
"stica_approach.append(sima.segment.MergeOverlapping(threshold=0.5))\n",
"rois = dataset.segment(stica_approach, 'auto_ROIs')"
"rois = dataset.segment(stica_approach, \"auto_ROIs\")"
]
},
{
Expand Down Expand Up @@ -173,7 +174,7 @@
"metadata": {},
"outputs": [],
"source": [
"output_folder = 'fissa_sima_example'\n",
"output_folder = \"fissa_sima_example\"\n",
"exp = fissa.Experiment(tiff_folder, [rois_fissa], output_folder)\n",
"exp.separate()"
]
Expand All @@ -195,9 +196,9 @@
"\n",
"\n",
"def plot_cell_regions(roi_polys, plot_neuropil=False):\n",
" '''\n",
" \"\"\"\n",
" Plot a single cell region, using holoviews.\n",
" '''\n",
" \"\"\"\n",
" out = hv.Overlay()\n",
"\n",
" if plot_neuropil:\n",
Expand Down Expand Up @@ -225,16 +226,21 @@
"\n",
"# Generate plots for raw extracts and neuropil removed\n",
"traces_plots = {\n",
" i_cell: hv.Curve(exp.raw[i_cell][i_trial][0, :], label='SIMA') *\n",
" hv.Curve(exp.result[i_cell][i_trial][0, :], label='FISSA')\n",
" i_cell: (\n",
" hv.Curve(exp.raw[i_cell][i_trial][0, :], label=\"SIMA\")\n",
" * hv.Curve(exp.result[i_cell][i_trial][0, :], label=\"FISSA\")\n",
" )\n",
" for i_cell in range(exp.nCell)\n",
"}\n",
"\n",
"# Get average image\n",
"avg_img = hv.Raster(exp.means[i_trial])\n",
"\n",
"# Render holoviews\n",
"avg_img * hv.HoloMap(region_plots,kdims=['Cell']) * fig + hv.HoloMap(traces_plots,kdims=['Cell'])"
"(\n",
" avg_img * hv.HoloMap(region_plots, kdims=[\"Cell\"]) * fig\n",
" + hv.HoloMap(traces_plots, kdims=[\"Cell\"])\n",
")"
]
},
{
Expand Down