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add option to follow redirects to curl call to fetch data from zenodo
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rettigl committed Oct 16, 2023
1 parent 02d2723 commit 572bd73
Showing 1 changed file with 5 additions and 5 deletions.
Original file line number Diff line number Diff line change
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"source": [
"data_path = '../../' # Put in Path to a storage of at least 20 Gbyte free space.\n",
"if not os.path.exists(data_path + \"/WSe2.zip\"):\n",
" os.system(f\"curl --output {data_path}/WSe2.zip https://zenodo.org/record/6369728/files/WSe2.zip\")\n",
" os.system(f\"curl -L --output {data_path}/WSe2.zip https://zenodo.org/record/6369728/files/WSe2.zip\")\n",
"if not os.path.isdir(data_path + \"/Scan049_1\") or not os.path.isdir(data_path + \"energycal_2019_01_08/\"):\n",
" os.system(f\"unzip -d {data_path} -o {data_path}/WSe2.zip\")"
]
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"metadata": {},
"outputs": [],
"source": [
"# Apply jittering to X, Y, t, ADC columns. \n",
"# Apply jittering to X, Y, t, ADC columns.\n",
"# Columns are defined in the config, or can be provided as list.\n",
"sp.add_jitter()"
]
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"# Manual selection: Use a GUI tool to select peaks:\n",
"#sp.define_features(rotation_symmetry=6, include_center=True)\n",
"#sp.generate_splinewarp(rotation_symmetry=6, include_center=True, fwhm=10, sigma=12, sigma_radius=4)\n",
"# Autodetect: Uses the DAOStarFinder routine to locate maxima. \n",
"# Parameters are: \n",
"# Autodetect: Uses the DAOStarFinder routine to locate maxima.\n",
"# Parameters are:\n",
"# fwhm: Full-width at half maximum of peaks.\n",
"# sigma: Number of standard deviations above the mean value of the image peaks must have.\n",
"# sigma_radius: number of standard deviations around a peak that peaks are fitted\n",
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"# sp.find_bias_peaks(ranges=rg, infer_others=False)\n",
"# Option 2 = specify the range for one curve and infer the others\n",
"# This will open an interactive tool to select the correct ranges for the curves.\n",
"# IMPORTANT: Don't choose the range too narrow about a peak, and choose a refid \n",
"# IMPORTANT: Don't choose the range too narrow about a peak, and choose a refid\n",
"# somewhere in the middle or towards larger biases!\n",
"rg = (66100, 67000)\n",
"sp.find_bias_peaks(ranges=rg, ref_id=5, infer_others=True, apply=True)"
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