keyword stringclasses 7 values | repo_name stringlengths 8 98 | file_path stringlengths 4 244 | file_extension stringclasses 29 values | file_size int64 0 84.1M | line_count int64 0 1.6M | content stringlengths 1 84.1M ⌀ | language stringclasses 14 values |
|---|---|---|---|---|---|---|---|
3D | mpes-kit/fuller | figures/extra/E03_Band_path.ipynb | .ipynb | 4,605 | 155 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Slice the band mapping or band structure data along certain high-symmetry lines\n",
"The following demo relates to the software package [mpes](https://github.com/mpes-kit/mpes/), which contains the functionality for making band path figures"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import warnings as wn\n",
"wn.filterwarnings(\"ignore\")\n",
"\n",
"import numpy as np\n",
"import fuller\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib as mpl\n",
"from mpes import analysis as aly, fprocessing as fp\n",
"from matplotlib.ticker import MultipleLocator, FormatStrFormatter\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mpl.rcParams['font.family'] = 'sans-serif'\n",
"mpl.rcParams['font.sans-serif'] = 'Arial'\n",
"mpl.rcParams['axes.linewidth'] = 2\n",
"mpl.rcParams['pdf.fonttype'] = 42\n",
"mpl.rcParams['ps.fonttype'] = 42"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Load photoemission data files\n",
"fdir = r'../../data/pes'\n",
"files = fuller.utils.findFiles(fdir, fstring='/*', ftype='h5')\n",
"fdata = fp.readBinnedhdf5(files[1])\n",
"mc = aly.MomentumCorrector(fdata['V'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mc.selectSlice2D(selector=slice(30, 32), axis=2)\n",
"mc.featureExtract(mc.slice, method='daofind', sigma=6, fwhm=20, symscores=False)\n",
"\n",
"# False detection filter, if needed\n",
"try:\n",
" mc.pouter_ord = mc.pouter_ord[[0,1,3,5,6,9],:]\n",
"except:\n",
" pass"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mc.view(image=mc.slice, annotated=True, points=mc.features)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Define high-symmetry points\n",
"G = mc.pcent # Gamma point\n",
"K = mc.pouter_ord[0,:] # K point\n",
"K1 = mc.pouter_ord[1,:] # K' point\n",
"M = (K + K1) / 2 # M point\n",
"\n",
"# Define cutting path\n",
"pathPoints = np.asarray([G, M, K, G])\n",
"nGM, nMK, nKG = 70, 39, 79\n",
"segPoints = [nGM, nMK, nKG]\n",
"rowInds, colInds, pathInds = aly.points2path(pathPoints[:,0], pathPoints[:,1], npoints=segPoints)\n",
"nSegPoints = len(rowInds)\n",
"\n",
"# Normalize data\n",
"imNorm = fdata['V'] / fdata['V'].max()\n",
"\n",
"# Sample the data along high-symmetry lines (k-path) connecting the corresponding high-symmetry points\n",
"pathDiagram = aly.bandpath_map(imNorm, pathr=rowInds, pathc=colInds, eaxis=2)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"Evals = fdata['E']\n",
"ehi, elo = Evals[0], Evals[469]\n",
"\n",
"f, ax = plt.subplots(figsize=(10, 6))\n",
"plt.imshow(pathDiagram[:470, :], cmap='Blues', aspect=10.9, extent=[0, nSegPoints, elo, ehi], vmin=0, vmax=0.5)\n",
"ax.set_xticks(pathInds)\n",
"ax.set_xticklabels(['$\\overline{\\Gamma}$', '$\\overline{\\mathrm{M}}$',\n",
" '$\\overline{\\mathrm{K}}$', '$\\overline{\\Gamma}$'], fontsize=15)\n",
"for p in pathInds[:-1]:\n",
" ax.axvline(x=p, c='r', ls='--', lw=2, dashes=[4, 2])\n",
"# ax.axhline(y=0, ls='--', color='r', lw=2)\n",
"ax.yaxis.set_major_locator(MultipleLocator(2))\n",
"ax.yaxis.set_minor_locator(MultipleLocator(1))\n",
"ax.yaxis.set_label_position(\"right\")\n",
"ax.yaxis.tick_right()\n",
"ax.set_ylabel('Energy (eV)', fontsize=15, rotation=-90, labelpad=20)\n",
"ax.tick_params(axis='x', length=0, pad=6)\n",
"ax.tick_params(which='both', axis='y', length=8, width=2, labelsize=15)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
| Unknown |
3D | mpes-kit/fuller | figures/extra/E02_Brillouin_zoning.ipynb | .ipynb | 4,761 | 223 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Cutting band structure or band mapping data to the first Brillouin zone"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import warnings as wn\n",
"wn.filterwarnings(\"ignore\")\n",
"\n",
"import numpy as np\n",
"import fuller\n",
"import scipy.io as sio\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1. Load data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bs_hse = sio.loadmat(r'../../data/theory/WSe2_HSE06_bands.mat')\n",
"bshse = np.moveaxis(bs_hse['evb'][::2,...], 1, 2)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"bs_hse['kxxsc'].shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 2. Determine Brillouin zone boundary using landmarks"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn = fuller.generator.BrillouinZoner(bands=bshse, axis=0)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.select_slice(selector=slice(0, 1))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.findlandmarks(image=bzn.slice, method='daofind', sigma=25, fwhm=40, sigma_radius=4, image_ofs=[25,25,0,0])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.visualize(bzn.slice, annotated=True, points=dict(pts=bzn.pouter_ord))\n",
"# plt.scatter(bzn.pcent[1], bzn.pcent[0], s=100, c='r')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 3. Calculate geometric parameters for creating data mask"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"imr, imc = bzn.slice.shape\n",
"hexside = np.linalg.norm(bzn.pouter_ord[1,:] - bzn.pouter_ord[2,:])\n",
"hexdiag = np.linalg.norm(bzn.pouter_ord[1,:] - bzn.pouter_ord[4,:])\n",
"imside = min(bzn.slice.shape)\n",
"ptop = (imr - hexdiag) / 2\n",
"# Calculate the distance of twice of the apothem (apo diameter)\n",
"apod = np.abs(np.sqrt(3)*hexside)\n",
"pleft = (imc - hexdiag) / 2"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.maskgen(hexdiag=int(hexdiag), imside=imside, image=None, padded=True,\n",
" pad_top=int(ptop), pad_left=int(pleft), ret='all')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.visualize(bzn.mask*bzn.slice, annotated=True, points=dict(pts=bzn.pouter_ord))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.bandcutter(selector=slice(0, None))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Energy band data sliced to the first Brillouin zone now bears the name `bandcuts`"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.bandcuts.shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 4. Save sliced data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Summarize the content of the class (remove the semiconlon to see output)\n",
"bzn.summary();"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# bzn.save_data(form='h5', save_addr=r'./wse2_hse_bandcuts.h5')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.imshow(bzn.bandcuts[0,...])"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
| Unknown |
3D | mpes-kit/fuller | figures/extra/E01_Hexagonal_tiling.ipynb | .ipynb | 2,209 | 106 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Construct large patches of the Brillouin zones (from DFT calculations) using symmetry operations"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import warnings as wn\n",
"wn.filterwarnings(\"ignore\")\n",
"\n",
"import numpy as np\n",
"import fuller\n",
"from mpes import visualization as vis\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Download data \n",
"pbedata = fuller.utils.load_calculation(r'../../data/theory/patch/band_all_paths_cart.out.pbe')\n",
"pbedata.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.imshow(pbedata[..., 285])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Perform symmetry operations to fill a larger patch of Brillouin zones\n",
"pbe_vb, pbe_cb = fuller.generator.bandstack(pbedata[:50,:,:], nvb=80, ncb=40, gap_id=286, cvd=103.9)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pbe_vb.shape, pbe_cb.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.imshow(pbe_vb[0,...])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"axs = vis.sliceview3d(pbe_cb, axis=0, ncol=8, colormap='Spectral_r');"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
| Unknown |
3D | mpes-kit/fuller | figures/recon/R02_Example_reconstruction_synthetic_multiband_3D_data.ipynb | .ipynb | 5,729 | 199 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Reconstruction of synthetic 3D multiband photoemission data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import warnings as wn\n",
"wn.filterwarnings(\"ignore\")\n",
"\n",
"import os\n",
"import numpy as np\n",
"import fuller\n",
"from fuller.mrfRec import MrfRec\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib as mpl\n",
"from tqdm import tqdm_notebook as tqdm\n",
"%matplotlib inline\n",
"\n",
"mpl.rcParams['font.family'] = 'sans-serif'\n",
"mpl.rcParams['font.sans-serif'] = 'Arial'\n",
"mpl.rcParams['axes.linewidth'] = 2\n",
"mpl.rcParams['pdf.fonttype'] = 42\n",
"mpl.rcParams['ps.fonttype'] = 42"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Import synthetic data and axes values\n",
"fdir = r'../../data/synthetic'\n",
"data = fuller.utils.loadHDF(fdir + r'/synth_data_WSe2_LDA_top8.h5', hierarchy='nested')\n",
"E0 = data['params']['E']\n",
"kx = data['params']['kx']\n",
"ky = data['params']['ky']\n",
"I = np.moveaxis(np.nan_to_num(data['data']['mpes_padded']), 0, -1)\n",
"I.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Import initial conditions\n",
"datab = fuller.utils.loadHDF(r'../../data/theory/bands_padded/wse2_hse_bands_padded.h5')\n",
"datab['bands_padded'].shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Compare ground truth with coefficient-tuned band structure\n",
"for i in range(6):\n",
" if i < 5:\n",
" plt.plot(ky, data['data']['bands_padded'][i, :, 150], c='k')\n",
" plt.plot(ky, datab['bands_padded'][i, :, 128].T, ls='--', c='b')\n",
" elif i == 5:\n",
" plt.plot(ky, data['data']['bands_padded'][i, :, 150], c='k', label='ground truth (LDA)')\n",
" plt.plot(ky, datab['bands_padded'][i, :, 128].T, ls='--', c='b', label='initialization (PBE)')\n",
"\n",
"plt.tick_params(axis='both', length=10, labelsize=15)\n",
"plt.ylabel('Energy (eV)', fontsize=15)\n",
"plt.legend(bbox_to_anchor=(1,0.2,0.2,0.3), fontsize=15, frameon=False);"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Create MRF model\n",
"mrf = MrfRec(E=E0, kx=kx, ky=ky, I=I, eta=.12)\n",
"mrf.I_normalized = False"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mrf.normalizeI(kernel_size=(20, 20, 20), clip_limit=0.01)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# These hyperparameters are already tuned\n",
"etas = [0.08, 0.1, 0.08, 0.1, 0.1, 0.14, 0.08, 0.08]\n",
"ofs = [0.3, 0.1, 0.26, 0.14, 0.3, 0.24, 0.34, 0.14]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Demonstration for reconstructing one band\n",
"mrf.eta = etas[1]\n",
"offset = ofs[1]\n",
"mrf.initializeBand(kx, ky, datab['bands_padded'][1,...], offset=offset, kScale=1., flipKAxes=False)\n",
"mrf.iter_para(100, use_gpu=True, disable_tqdm=False, graph_reset=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"# Illustration of outcome (black line = initialization, red line = reconstruction)\n",
"mrf.plotBands()\n",
"mrf.plotI(ky=0, plotBand=True, plotBandInit=True, plotSliceInBand=False, cmapName='coolwarm')\n",
"mrf.plotI(ky=0.4, plotBand=True, plotBandInit=True, plotSliceInBand=False, cmapName='coolwarm')\n",
"mrf.plotI(kx=0, plotBand=True, plotBandInit=True, plotSliceInBand=False, cmapName='coolwarm')\n",
"mrf.plotI(kx=0.4, plotBand=True, plotBandInit=True, plotSliceInBand=False, cmapName='coolwarm')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Reconstruct all bands and save the results"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"if not os.path.exists(r'../../results/hse_lda'):\n",
" os.mkdir(r'../../results/hse_lda')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Reconstruct band by band\n",
"for idx, (eta, offset) in enumerate(zip(tqdm(etas), ofs)):\n",
"\n",
" mrf.eta = eta\n",
" iband = idx + 1\n",
" mrf.initializeBand(kx, ky, datab['bands_padded'][idx,...], offset=offset, kScale=1., flipKAxes=False)\n",
" mrf.iter_para(100, use_gpu=True, disable_tqdm=True, graph_reset=True)\n",
" mrf.saveBand(r'../../results/hse_lda/mrf_rec_band='+str(iband).zfill(2)+'_ofs='+str(offset)+'_eta='+str(eta)+'.h5',\n",
" index=iband)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
| Unknown |
3D | mpes-kit/fuller | figures/recon/R01_Example_reconstruction_wse2_3D_data.ipynb | .ipynb | 5,592 | 172 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Reconstruction of photoemission band structure using Markov Random Field model\n",
"### Model setup"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import warnings as wn\n",
"wn.filterwarnings(\"ignore\")\n",
"\n",
"import os\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib as mpl\n",
"import fuller\n",
"from fuller.mrfRec import MrfRec\n",
"from tqdm import tnrange\n",
"\n",
"%matplotlib inline\n",
"mpl.rcParams['axes.linewidth'] = 2\n",
"mpl.rcParams['pdf.fonttype'] = 42\n",
"mpl.rcParams['ps.fonttype'] = 42"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Load preprocessed data\n",
"data_path = '../../data/pes/3_smooth.h5'\n",
"data = fuller.utils.loadHDF(data_path)\n",
"\n",
"E = data['E'][:470]\n",
"kx = data['kx']\n",
"ky = data['ky']\n",
"I = data['V'][...,:470]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Create MRF model\n",
"mrf = MrfRec(E=E, kx=kx, ky=ky, I=I, eta=.12)\n",
"mrf.I_normalized = True"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Reconstruction"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Initialize parameters for loop\n",
"path_dft = ['../../data/theory/WSe2_LDA_bands.mat',\n",
" '../../data/theory/WSe2_PBE_bands.mat',\n",
" '../../data/theory/WSe2_PBEsol_bands.mat',\n",
" '../../data/theory/WSe2_HSE06_bands.mat']\n",
"path_hyperparam = ['../../data/hyperparameter/LDA.csv',\n",
" '../../data/hyperparameter/PBE.csv',\n",
" '../../data/hyperparameter/PBEsol.csv',\n",
" '../../data/hyperparameter/HSE06.csv']\n",
"num_dft = 1 # Number of DFTs to consider, can be up to 4 here, but set to 1 to save computation\n",
"recon = np.zeros((num_dft, 14, len(kx), len(ky)))\n",
"\n",
"for ind_dft in tnrange(num_dft, desc='Initialization'):\n",
" # Load hyperparameter and DFT\n",
" hyperparam = np.loadtxt(path_hyperparam[ind_dft], delimiter=',', skiprows=1)\n",
" kx_dft, ky_dft, E_dft = mrf.loadBandsMat(path_dft[ind_dft])\n",
" \n",
" for ind_band in tnrange(14, desc='Band'):\n",
" # Set eta and initialization\n",
" mrf.eta = hyperparam[ind_band, 1]\n",
" mrf.initializeBand(kx=kx_dft, ky=ky_dft, Eb=E_dft[2 * ind_band,...], kScale=hyperparam[ind_band, 3],\n",
" offset=hyperparam[ind_band, 2] + 0.65, flipKAxes=True)\n",
" \n",
" # Perform optimization\n",
" mrf.iter_para(150, disable_tqdm=True)\n",
" \n",
" # Store result\n",
" recon[ind_dft, ind_band, ...] = mrf.getEb()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Results"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Plot slices ky slice\n",
"dft_name = ['LDA', 'PBE', 'PBEsol', 'HSE06']\n",
"\n",
"# Mask to only plot Brillouin zone\n",
"mask = np.load('../../data/processed/WSe2_Brillouin_Zone_Mask.npy')\n",
"mrf.I = mrf.I * mask[:, :, None]\n",
"ky_val = 0\n",
"ind_ky = np.argmin(np.abs(mrf.ky - ky_val))\n",
"\n",
"# Loop over initializations and bands\n",
"for ind_dft in range(num_dft):\n",
" mrf.plotI(ky=ky_val, cmapName='coolwarm')\n",
" plt.title(dft_name[ind_dft], fontsize=26)\n",
" plt.xlim((-1.35, 1.3))\n",
" kx_dft, ky_dft, E_dft = mrf.loadBandsMat(path_dft[ind_dft])\n",
" for ind_band in range(14):\n",
" #mrf.initializeBand(kx=kx_dft, ky=ky_dft, Eb=E_dft[2 * ind_band,...], kScale=1,\n",
" # offset=0.65, flipKAxes=True)\n",
" #E0 = mrf.E[mrf.indE0[:, ind_ky]]\n",
" #plt.plot(mrf.kx, E0 * mask[:, ind_ky], 'k', linewidth=2.0, \n",
" # label='DFT' if ind_band==0 else None, zorder=3)\n",
" mrf.initializeBand(kx=kx_dft, ky=ky_dft, Eb=E_dft[2 * ind_band,...], kScale=hyperparam[ind_band, 3],\n",
" offset=hyperparam[ind_band, 2] + 0.65, flipKAxes=True)\n",
" E0 = mrf.E[mrf.indE0[:, ind_ky]]\n",
" plt.plot(mrf.kx, E0 * mask[:, ind_ky], 'c--', linewidth=2.0, \n",
" label='Initialization' if ind_band==0 else None, zorder=2)\n",
" plt.plot(mrf.kx, recon[ind_dft, ind_band, :, ind_ky] * mask[:, ind_ky], 'r', linewidth=2.0,\n",
" label='Reconstruction' if ind_band==0 else None, zorder=1)\n",
" plt.legend(loc=4, prop={'size': 14}, framealpha=1)\n",
" "
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
| Unknown |
3D | mpes-kit/fuller | examples/synthetic_mpes_data_generation_I (from calculation).ipynb | .ipynb | 4,958 | 242 | {
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import fuller\n",
"from fuller import generator\n",
"import scipy.io as sio\n",
"from mpes import analysis as aly\n",
"from symmetrize import pointops as po\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from imp import reload\n",
"reload(fuller)\n",
"reload(fuller.utils)\n",
"reload(fuller.generator)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"fth = r'../theory'"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bsth = sio.loadmat(fth + r'/WSe2_DFT_BandStructure.mat')\n",
"bsth.keys()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.pcolormesh(bsth['kxx'], bsth['kyy'], bsth['evb'][0,...])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"nr, nc = bsth['kxx'].shape\n",
"kxvals = bsth['kxx'][:,0]\n",
"kyvals = bsth['kyy'][0,:]\n",
"xlen, ylen = 256, int(256/(nr/nc))\n",
"ofs = (xlen - ylen) // 2"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bandaug, _, [kxx, kyy] = fuller.utils.interpolate2d(kxvals, kyvals, bsth['evb'][0,...], xlen, ylen, ret='all')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"plt.pcolormesh(kxx, kyy, bandaug)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Detect landmarks"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mc = aly.MomentumCorrector(image=bandaug)\n",
"mc.slice = mc.image\n",
"mc.featureExtract(image=mc.image, direction='ccw', method='daofind', sigma=15, fwhm=30)\n",
"mc.view(mc.image, points=mc.features, annotated=True, cmap='viridis')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mc.pouter_ord[0,:] - mc.pouter_ord[3,:]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Synthesize artificial MPES data within the first Brillouin zone"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"hm, margins = fuller.generator.hexmask(hexside=170, imside=256, padded=True, pad_left=43, pad_top=43, ret='all')\n",
"plt.imshow(hm[:,ofs:-ofs]*bandaug)\n",
"plt.scatter(mc.pouter_ord[:,1], mc.pouter_ord[:,0])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bandcut = cut_margins(bandaug, margins, offsetx=ofs)\n",
"hmcut = cut_margins(hm, margins)\n",
"bandhm = bandcut*hmcut\n",
"plt.imshow(bandhm)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bandhm_dmean = np.nan_to_num(bandhm - np.nanmean(bandhm))\n",
"bcf = fuller.generator.decomposition_hex2d(bandhm_dmean, nterms=400)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.plot(bcf)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dg = fuller.generator.MPESDataGenerator()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Simulate DFT error in initial estimates"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
| Unknown |
3D | mpes-kit/fuller | examples/05_synthetic_data_and_initial_conditions.ipynb | .ipynb | 11,861 | 398 | {
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import fuller\n",
"from mpes import analysis as aly\n",
"import matplotlib.pyplot as plt\n",
"from tqdm import tqdm_notebook as tqdm\n",
"import tifffile as ti\n",
"import matplotlib as mpl\n",
"from scipy import interpolate"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from imp import reload\n",
"reload(fuller)\n",
"reload(fuller.utils)\n",
"reload(fuller.generator)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ncfs = 400\n",
"bases = fuller.generator.ppz.hexike_basis(nterms=ncfs, npix=208, vertical=True, outside=0)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Compute the polynomial decomposition coefficients\n",
"bandout = np.nan_to_num(fuller.utils.loadHDF(r'.\\wse2_lda_bandcuts.h5')['bands'])\n",
"bcfs = []\n",
"for i in tqdm(range(14)):\n",
" bcfs.append(fuller.generator.decomposition_hex2d(bandout[i,...] + 0.86813, bases=bases, baxis=0, ret='coeffs'))\n",
"bcfs = np.array(bcfs)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.imshow(bandout[0,...])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Generate Brillouin zone mask\n",
"bzmsk = fuller.generator.hexmask(hexdiag=208, imside=208, padded=False, margins=[1, 1, 1, 1])\n",
"bzmsk_tight = fuller.generator.hexmask(hexdiag=202, imside=208, padded=True, margins=[3, 3, 3, 3])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"nbands = 8"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Generate photoemission data without padding\n",
"bshape = (208, 208)\n",
"amps = np.ones(bshape)\n",
"xs = np.linspace(-4.5, 0.5, 280, endpoint=True)\n",
"syndat = np.zeros((280, 208, 208))\n",
"gamss = []\n",
"for i in tqdm(range(nbands)):\n",
" gams = 0.05\n",
" syndat += aly.voigt(feval=True, vardict={'amp':amps, 'xvar':xs[:,None,None], 'ctr':(bandout[i,...] + 0.86813),\n",
" 'sig':0.1, 'gam':gams})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Generate edge-padded bands\n",
"synfbands = []\n",
"padsize = ((24, 24), (24, 24))\n",
"for i in tqdm(range(nbands)): \n",
" impad = fuller.generator.hexpad(bandout[i,...] + 0.86813, cvd=104, mask=bzmsk, edgepad=padsize)\n",
" synfbands.append(fuller.generator.restore(impad, method='cubic'))\n",
"synfbands = np.asarray(synfbands)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Generate edge-padded photoemission data\n",
"bshape = (256, 256)\n",
"amps = np.ones(bshape)\n",
"xs = np.linspace(-4.5, 0.5, 280, endpoint=True)\n",
"synfdat = np.zeros((280, 256, 256))\n",
"gamss = []\n",
"for i in tqdm(range(nbands)):\n",
"# btemp = np.nan_to_num(synbands[i,...])\n",
"# gams = np.abs(synfbands[i,...] - np.nanmean(synfbands[i,...]))/3\n",
" gams = 0.05\n",
"# gamss.append(gams)\n",
" synfdat += aly.voigt(feval=True, vardict={'amp':amps, 'xvar':xs[:,None,None], 'ctr':(synfbands[i,...]),\n",
" 'sig':0.1, 'gam':gams})\n",
"# gamss = np.asarray(gamss)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"xss = np.linspace(-4.5, 0.5, 280, endpoint=True)\n",
"xss[1] - xss[0], xss.size"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.imshow(synfdat[:,80,:], aspect=0.5, origin='lower', cmap='terrain_r')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Generate mask for large coefficients\n",
"cfmask = bcfs.copy()\n",
"cfmask[np.abs(cfmask) >= 1e-2] = 1.\n",
"cfmask[np.abs(cfmask) < 1e-2] = 0\n",
"cfmask[:, 0] = 0 # No rigid shift modulation"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Generate coefficient-scaled data\n",
"synfscaled = {}\n",
"errs = np.around(np.arange(0.3, 2.01, 0.05), 2)\n",
"bscmod = bcfs.copy()\n",
"\n",
"for err in tqdm(errs):\n",
" \n",
" synbands = []\n",
" for i in range(nbands):\n",
" \n",
" bscmod[i, 1:] = err*bcfs[i, 1:] # Scale only the dispersion terms (leave out the first offset term)\n",
" bandmod = fuller.generator.reconstruction_hex2d(bscmod[i, :], bases=bases)\n",
" \n",
" # Sixfold rotational symmetrization\n",
" symmed = fuller.generator.rotosymmetrize(bandmod, center=(104, 104), rotsym=6)[0]\n",
" symmed = fuller.generator.reflectosymmetrize(symmed, center=(104, 104), refangles=[0, 90])\n",
" padded = fuller.generator.hexpad(symmed, cvd=104, mask=bzmsk_tight, edgepad=padsize)\n",
" synbands.append(fuller.generator.restore(padded, method='nearest'))\n",
" \n",
" synfscaled[str(err)] = np.asarray(synbands)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.figure(figsize=(8, 8))\n",
"plt.imshow(synbands[0])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Generate coefficient-perturbed data\n",
"synfperturbed = {}\n",
"noizamp = 0.02\n",
"# noizamps = np.asarray([5e-3, 1e-2, 2.5e-2, 5e-2, 7.5e-2, 1e-1, 2.5e-1, 5e-1])\n",
"bscmod = bcfs.copy()\n",
"\n",
"for si in tqdm(range(nbands)):\n",
" \n",
" # Generate random perturbation to the coefficients\n",
" np.random.seed(si)\n",
" noiz = fuller.utils.coeffgen((nbands, 400), amp=noizamp, distribution='uniform', modulation='exp',\n",
" mask=cfmask[:nbands,:], low=-1, high=1)\n",
" bscmod[:nbands, 1:] += noiz[:, 1:]\n",
" \n",
" synbands = []\n",
" for i in range(nbands):\n",
" bandmod = fuller.generator.reconstruction_hex2d(noiz[i, :], bases=bases)*bzmsk\n",
" bandmod += bandout[i,...]\n",
" \n",
" # Sixfold rotational symmetrization\n",
" symmed = fuller.generator.rotosymmetrize(bandmod, center=(104, 104), rotsym=6)[0]\n",
" symmed = fuller.generator.reflectosymmetrize(symmed, center=(104, 104), refangles=[0, 90])*bzmsk_tight\n",
" padded = fuller.generator.hexpad(symmed, cvd=104, mask=bzmsk_tight, edgepad=padsize)\n",
" synbands.append(fuller.generator.restore(padded, method='nearest'))\n",
" \n",
" synfperturbed[str(si).zfill(2)] = np.asarray(synbands)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.figure(figsize=(8, 8))\n",
"plt.imshow(synbands[0])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Generate coefficient-perturbed data\n",
"synfperturbed2 = {}\n",
"noizamp = 0.05\n",
"# noizamps = np.asarray([5e-3, 1e-2, 2.5e-2, 5e-2, 7.5e-2, 1e-1, 2.5e-1, 5e-1])\n",
"bscmod = bcfs.copy()\n",
"\n",
"for si in tqdm(range(nbands)):\n",
" \n",
" # Generate random perturbation to the coefficients\n",
" np.random.seed(si)\n",
" noiz = fuller.utils.coeffgen((nbands, 400), amp=noizamp, distribution='uniform', modulation='exp',\n",
" mask=cfmask[:nbands,:], low=-1, high=1)\n",
" bscmod[:nbands, 1:] += noiz[:, 1:]\n",
" \n",
" synbands = []\n",
" for i in range(nbands):\n",
" bandmod = fuller.generator.reconstruction_hex2d(noiz[i, :], bases=bases)*bzmsk\n",
" bandmod += bandout[i,...]\n",
" \n",
" # Sixfold rotational symmetrization\n",
" symmed = fuller.generator.rotosymmetrize(bandmod, (104, 104), rotsym=6)[0]\n",
" symmed = fuller.generator.reflectosymmetrize(symmed, center=(104, 104), refangles=[0, 90])*bzmsk_tight\n",
" padded = fuller.generator.hexpad(symmed, cvd=104, mask=bzmsk_tight, edgepad=padsize)\n",
" synbands.append(fuller.generator.restore(padded, method='nearest'))\n",
" \n",
" synfperturbed2[str(si).zfill(2)] = np.asarray(synbands)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"fuller.utils.saveHDF(*[['data', {'bands':bandout[:8,...], 'bands_padded':synfbands, 'mpes':syndat, 'mpes_padded':synfdat}],\n",
" ['estimates_amp_tuning_padded', synfscaled], \n",
" ['estimates_amp=0.02', synfperturbed], ['estimates_amp=0.05', synfperturbed2],\n",
" ['params', {'coeffs':bcfs, 'basis':bases, 'E':xs, 'amps':amps, 'sig':0.1, 'gam':gams,\n",
" 'kx':axes['axes'][0], 'ky':axes['axes'][1], 'mask':bzmsk, 'mask_tight':bzmsk_tight}]],\n",
" save_addr=r'./synth_data_test_004_WSe2_LDA_top8.h5')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Calibrate momentum axes\n",
"mc = aly.MomentumCorrector(np.asarray(synbands))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mc.selectSlice2D(selector=slice(0,1), axis=0)\n",
"mc.view(mc.slice)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mc.featureExtract(mc.slice, method='daofind', fwhm=30, sigma=20)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mc.view(mc.slice, annotated=True, points=mc.features)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Calculate distances\n",
"dg = 1.64/np.cos(np.radians(30))\n",
"dg"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"axes = mc.calibrate(mc.slice, mc.pouter_ord[0,:], mc.pcent, dist=dg, equiscale=True, ret='axes')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"axes['axes'][0][0], axes['axes'][0][-1]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": ".pyenv38",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.12"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
| Unknown |
3D | mpes-kit/fuller | examples/01_Hexagonal_tiling.ipynb | .ipynb | 2,556 | 122 | {
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"from mpes import visualization as vis\n",
"import fuller\n",
"import matplotlib.pyplot as plt\n",
"import os"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"data_path = '../' # Put in Path to a storage of at least 20 Gbyte free space.\n",
"if not os.path.exists(data_path + \"/data.zip\"):\n",
" os.system(f\"curl -L --output {data_path}/data.zip https://zenodo.org/records/7314278/files/data.zip\")\n",
"if not os.path.isdir(data_path + \"/data\"):\n",
" os.system(f\"unzip -d {data_path} -o {data_path}/data\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pbedata = fuller.utils.load_calculation('../data/theory/patch/band_all_paths_cart.out.pbe')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pbedata.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.imshow(pbedata[..., 285])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pbe_vb, pbe_cb = fuller.generator.bandstack(pbedata[:50,:,:], nvb=80, ncb=40, gap_id=286, cvd=103.9)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pbe_vb.shape, pbe_cb.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.imshow(pbe_vb[0,...])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"axs = vis.sliceview3d(pbe_cb, axis=0, ncol=8, colormap='rainbow');"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": ".pyenv38",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.12"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
| Unknown |
3D | mpes-kit/fuller | examples/02_Brillouin_zoning.ipynb | .ipynb | 6,441 | 300 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Cutting band structure or band mapping data to the first Brillouin zone"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import fuller\n",
"import scipy.io as sio\n",
"import matplotlib.pyplot as plt\n",
"import os"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"data_path = '../' # Put in Path to a storage of at least 20 Gbyte free space.\n",
"if not os.path.exists(data_path + \"/data.zip\"):\n",
" os.system(f\"curl -L --output {data_path}/data.zip https://zenodo.org/records/7314278/files/data.zip\")\n",
"if not os.path.isdir(data_path + \"/data\"):\n",
" os.system(f\"unzip -d {data_path} -o {data_path}/data\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1. Load data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bs_hse = sio.loadmat('../data/theory/WSe2_HSE06_bands.mat')\n",
"bshse = np.moveaxis(bs_hse['evb'][::2,...], 1, 2)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"bs_hse['kxxsc'].shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 2. Determine Brillouin zone boundary using landmarks"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn = fuller.generator.BrillouinZoner(bands=bshse, axis=0)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.select_slice(selector=slice(0, 1))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.findlandmarks(image=bzn.slice, method='daofind', sigma=25, fwhm=40, sigma_radius=4, image_ofs=[25,25,0,0])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.visualize(bzn.slice, annotated=True, points=dict(pts=bzn.pouter_ord))\n",
"# plt.scatter(bzn.pcent[1], bzn.pcent[0], s=100, c='r')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 3. Calculate geometric parameters for creating data mask"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"imr, imc = bzn.slice.shape\n",
"hexside = np.linalg.norm(bzn.pouter_ord[1,:] - bzn.pouter_ord[2,:])\n",
"hexdiag = np.linalg.norm(bzn.pouter_ord[1,:] - bzn.pouter_ord[4,:])\n",
"imside = min(bzn.slice.shape)\n",
"ptop = (imr - hexdiag) / 2\n",
"# Calculate the distance of twice of the apothem (apo diameter)\n",
"apod = np.abs(np.sqrt(3)*hexside)\n",
"pleft = (imc - hexdiag) / 2"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.maskgen(hexdiag=int(hexdiag), imside=imside, image=None, padded=True,\n",
" pad_top=int(ptop), pad_left=int(pleft), ret='all')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.visualize(bzn.mask*bzn.slice, annotated=True, points=dict(pts=bzn.pouter_ord))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.bandcutter(selector=slice(0, None))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Energy band data sliced to the first Brillouin zone now bears the name `bandcuts`"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.bandcuts.shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 4. Save sliced data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.summary();"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.save_data(form='h5', save_addr=r'./wse2_hse_bandcuts.h5')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.imshow(bzn.bandcuts[0,...])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.visualize(bzn.bandcuts[12,...])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Load data using external function\n",
"Demonstration here using ``fuller.utils.load_multiple_bands()``"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"fdir = '../data/theory/bands_1BZ/'"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn = fuller.generator.BrillouinZoner(folder=fdir)\n",
"bzn.load_data('', loadfunc=fuller.utils.load_multiple_bands, ret=False, ename='bands/Eb', kname='axes')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.select_slice(selector=slice(0, 1))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bzn.visualize(bzn.slice, annotated=False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": ".pyenv38",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.12"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
| Unknown |
3D | mpes-kit/fuller | examples/04_mpes_reconstruction_mrf.ipynb | .ipynb | 4,360 | 186 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Reconstruction of band using Markov Random Field Model"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Model setup"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Import packages\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"from fuller.mrfRec import MrfRec\n",
"from fuller.utils import loadHDF\n",
"\n",
"import os"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"data_path = '../' # Put in Path to a storage of at least 20 Gbyte free space.\n",
"if not os.path.exists(data_path + \"/data.zip\"):\n",
" os.system(f\"curl -L --output {data_path}/data.zip https://zenodo.org/records/7314278/files/data.zip\")\n",
"if not os.path.isdir(data_path + \"/data\"):\n",
" os.system(f\"unzip -d {data_path} -o {data_path}/data\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Load preprocessed data\n",
"data = loadHDF('../data/pes/1_sym.h5')\n",
"E = data['E']\n",
"kx = data['kx']\n",
"ky = data['ky']\n",
"I = data['V']"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Create MRF model\n",
"mrf = MrfRec(E=E, kx=kx, ky=ky, I=I, eta=.12)\n",
"mrf.I_normalized = True"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Initialization"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Initialize mrf model with band structure approximation from DFT\n",
"path_dft = '../data/theory/WSe2_PBEsol_bands.mat'\n",
"\n",
"band_index = 4\n",
"offset = .5\n",
"k_scale = 1.1\n",
"\n",
"kx_dft, ky_dft, E_dft = mrf.loadBandsMat(path_dft)\n",
"mrf.initializeBand(kx=kx_dft, ky=ky_dft, Eb=E_dft[band_index,...], offset=offset, kScale=k_scale, flipKAxes=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Plot slices with initialiation to check offset and scale\n",
"mrf.plotI(ky=0, plotBandInit=True, cmapName='coolwarm')\n",
"mrf.plotI(kx=0, plotBandInit=True, cmapName='coolwarm')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Reconstruction"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"# Run optimization to perform reconstruction\n",
"eta = .1\n",
"n_epochs = 150\n",
"\n",
"mrf.eta = eta\n",
"mrf.iter_para(n_epochs)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"# Plot results\n",
"mrf.plotBands()\n",
"mrf.plotI(ky=0, plotBand=True, plotBandInit=True, plotSliceInBand=False, cmapName='coolwarm')\n",
"mrf.plotI(ky=0.5, plotBand=True, plotBandInit=True, plotSliceInBand=False, cmapName='coolwarm')\n",
"mrf.plotI(kx=0, plotBand=True, plotBandInit=True, plotSliceInBand=False, cmapName='coolwarm')\n",
"mrf.plotI(kx=0.5, plotBand=True, plotBandInit=True, plotSliceInBand=False, cmapName='coolwarm')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Save results\n",
"path_save = 'reconstructed_bands'\n",
"mrf.saveBand(path_save + 'mrf_rec_%02i.h5' % band_index, index=band_index)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": ".pyenv38",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.12"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
| Unknown |
3D | mpes-kit/fuller | examples/interpolation_cutter.ipynb | .ipynb | 4,555 | 203 | {
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import fuller\n",
"import scipy.io as sio\n",
"from mpes import fprocessing as fp, analysis as aly\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from imp import reload\n",
"reload(aly)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bm = fp.readBinnedhdf5('..\\data\\WSe2_256x256x1024_fullrange_rotsym.h5')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bm['V'].shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"emax, emin = -bm['E'][::-1][0], -bm['E'][::-1][499]\n",
"emax, emin"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mc = aly.MomentumCorrector(bm['V'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mc.selectSlice2D(slice(30, 38), axis=2)\n",
"mc.view(mci.slice)\n",
"plt.axvline(x=129)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mc.featureExtract(mc.slice, method='daofind', sigma=4, fwhm=7, sigma_radius=2)\n",
"mc.view(mc.slice, annotated=True, points=mc.features)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"G = mc.pcent\n",
"K = mc.pouter_ord[0,:]\n",
"M = mc.pouter_ord[:2,:].mean(axis=0)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"rpts = np.asarray([G[0], M[0], K[0], G[0]])\n",
"cpts = np.asarray([G[1], M[1], K[1], G[1]])\n",
"rr, cc, ids = aly.points2path(rpts, cpts, npoints=[40, 32, 50])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"paths = np.concatenate((rr, cc, np.ones((120, 1))), axis=1)\n",
"bc = aly.bandpath_map(bm['V'][:,:,:500], pathr=rr, pathc=cc, eaxis=2)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plt.figure(figsize=(10,8))\n",
"plt.imshow(bc, cmap='terrain_r', aspect=10, extent=[0, 119, emin, emax])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from skimage.exposure import equalize_adapthist"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bceq = equalize_adapthist(bc/100, kernel_size=(20, 12), clip_limit=0.015)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"f, ax = plt.subplots(figsize=(10,8))\n",
"plt.imshow(bceq, cmap='terrain_r', aspect=9, extent=[0, 119, emin, emax])\n",
"for j in range(len(ids)):\n",
" plt.axvline(ids[j], ls='--', dashes=(5, 5), color='r', lw=2)\n",
"# plt.xticks([])\n",
"plt.tick_params(labelsize=15)\n",
"plt.xlim([ids[0], ids[-1]-1])\n",
"plt.ylabel('Binding energy (eV)', fontsize=15)\n",
"ax.set_xticks([ 0, 39, 70, 119])\n",
"ax.set_xticklabels(['$\\Gamma$', 'M', 'K', '$\\Gamma$']);\n",
"# plt.savefig('WSe2_Comparison_ExperimentSym_TheoryLDA_Ramp.pdf', bbox_inches='tight', dpi=300)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dicta = [['data', {'cut':bc, 'cut_clahe':bceq}]]\n",
"fuller.utils.saveHDF(*dicta, save_addr=r'.\\WSe2_BZSymLineCut.h5')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
| Unknown |
3D | mpes-kit/fuller | examples/03_preprocessing.ipynb | .ipynb | 5,321 | 242 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"# Illustration of the preprocessing steps"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Import packages\n",
"import numpy as np\n",
"import tensorflow as tf\n",
"import matplotlib.pyplot as plt\n",
"\n",
"from fuller.mrfRec import MrfRec\n",
"from fuller.generator import rotosymmetrize\n",
"from fuller.utils import saveHDF\n",
"\n",
"from fuller.utils import loadHDF\n",
"\n",
"import os"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"data_path = '../' # Put in Path to a storage of at least 20 Gbyte free space.\n",
"if not os.path.exists(data_path + \"/data.zip\"):\n",
" os.system(f\"curl -L --output {data_path}/data.zip https://zenodo.org/records/7314278/files/data.zip\")\n",
"if not os.path.isdir(data_path + \"/data\"):\n",
" os.system(f\"unzip -d {data_path} -o {data_path}/data\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Load data\n",
"data = loadHDF('../data/pes/0_binned.h5')\n",
"I = data['V']\n",
"E = data['E']\n",
"kx = data['kx']\n",
"ky = data['ky']\n",
"\n",
"# Create reconstruction object from data file\n",
"mrf = MrfRec(E=E, kx=kx, ky=ky, I=I)\n",
"I_raw = I.copy()\n",
"\n",
"# Set plot folder\n",
"plot_dir = 'plots'"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Create function for plotting\n",
"def plot_slices(mrf, plot_dir, prefix):\n",
" # ky sice\n",
" mrf.plotI(ky=0., cmapName=\"coolwarm\")\n",
" plt.xlim((-1.65, 1.65))\n",
" plt.ylim((-8.5, 0.5))\n",
" plt.savefig(plot_dir + '/' + prefix + '_ky_slice.png', dpi=300)\n",
"\n",
" # kx sice\n",
" mrf.plotI(kx=0., cmapName=\"coolwarm\")\n",
" plt.xlim((-1.65, 1.65))\n",
" plt.ylim((-8.5, 0.5))\n",
" plt.savefig(plot_dir + '/' + prefix + '_kx_slice.png', dpi=300)\n",
"\n",
" # ky sice\n",
" mrf.plotI(E=-1.2, cmapName=\"coolwarm\", equal_axes=True, figsize=(9, 7.5))\n",
" plt.xlim((-1.65, 1.65))\n",
" plt.ylim((-1.65, 1.65))\n",
" plt.tight_layout()\n",
" plt.savefig(plot_dir + '/' + prefix + '_E_slice.png', dpi=300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plot raw data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"plot_slices(mrf, plot_dir, 'raw')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Rotational symmetrization"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mrf.symmetrizeI(mirror=False)\n",
"plot_slices(mrf, plot_dir, 'sym_rot')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Mirror symetrization"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mrf.symmetrizeI(rotational=False)\n",
"plot_slices(mrf, plot_dir, 'sym_mir')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Normalization using clahe"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"mrf.normalizeI(kernel_size=(30, 30, 40), n_bins=256, clip_limit=0.1, use_gpu=True)\n",
"plot_slices(mrf, plot_dir, 'clahe')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Smoothing using Gaussian filter"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mrf.smoothenI(sigma=(.8, .8, 1.))\n",
"plot_slices(mrf, plot_dir, 'smooth')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Save preprocessed dataset"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"data_save = [['axes', {'E': mrf.E, 'kx': mrf.kx, 'ky': mrf.ky}], ['binned', {'V': mrf.I}]]\n",
"saveHDF(*data_save, save_addr='./WSe2_preprocessed.h5')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": ".pyenv38",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.12"
},
"pycharm": {
"stem_cell": {
"cell_type": "raw",
"metadata": {
"collapsed": false
},
"source": []
}
}
},
"nbformat": 4,
"nbformat_minor": 1
}
| Unknown |
3D | mpes-kit/fuller | docs/conf.py | .py | 8,956 | 276 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
#
import sys
import os
# import sphinx_rtd_theme
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
sys.path.insert(0, os.path.abspath('..'))
sys.path.append(os.path.abspath('../..'))
#sys.path.append(os.path.abspath('..'))
import fuller
import sphinx_theme
# -- General configuration ------------------------------------------------
# If your documentation needs a minimal Sphinx version, state it here.
#needs_sphinx = '1.0'
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = [
'sphinx.ext.autodoc',
'sphinx.ext.intersphinx',
'sphinx.ext.mathjax',
'sphinx.ext.ifconfig',
'sphinx.ext.todo',
'sphinx.ext.githubpages',
]
# Add any paths that contain templates here, relative to this directory.
templates_path = ['_templates']
# The suffix of source filenames.
source_suffix = '.rst'
# The encoding of source files.
#source_encoding = 'utf-8-sig'
# The master toctree document.
master_doc = 'index'
# -- Project information -----------------------------------------------------
project = 'fuller'
copyright = '2018-2020, Vincent Stimper, R. Patrick Xian'
author = 'Vincent Stimper, R. Patrick Xian'
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
#
# The short X.Y version.
version = fuller.__version__
# The full version, including alpha/beta/rc tags.
release = fuller.__version__
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
#language = None
# There are two options for replacing |today|: either, you set today to some
# non-false value, then it is used:
#today = ''
# Else, today_fmt is used as the format for a strftime call.
#today_fmt = '%B %d, %Y'
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
exclude_patterns = ['_build']
# The reST default role (used for this markup: `text`) to use for all
# documents.
#default_role = None
# If true, '()' will be appended to :func: etc. cross-reference text.
#add_function_parentheses = True
# If true, the current module name will be prepended to all description
# unit titles (such as .. function::).
#add_module_names = True
# If true, sectionauthor and moduleauthor directives will be shown in the
# output. They are ignored by default.
#show_authors = False
# The name of the Pygments (syntax highlighting) style to use.
pygments_style = 'sphinx'
# A list of ignored prefixes for module index sorting.
#modindex_common_prefix = []
# If true, keep warnings as "system message" paragraphs in the built documents.
#keep_warnings = False
# -- Options for HTML output ----------------------------------------------
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
html_theme = "stanford_theme"
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
#html_theme_options = {}
# Add any paths that contain custom themes here, relative to this directory.
html_theme_path = [sphinx_theme.get_html_theme_path('stanford-theme')]
# The name for this set of Sphinx documents. If None, it defaults to
# "<project> v<release> documentation".
#html_title = None
# A shorter title for the navigation bar. Default is the same as html_title.
#html_short_title = None
# The name of an image file (relative to this directory) to place at the top
# of the sidebar.
#html_logo = None
# The name of an image file (within the static path) to use as favicon of the
# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
# pixels large.
#html_favicon = None
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
# html_static_path = ['_static']
# Add any extra paths that contain custom files (such as robots.txt or
# .htaccess) here, relative to this directory. These files are copied
# directly to the root of the documentation.
#html_extra_path = []
# If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
# using the given strftime format.
#html_last_updated_fmt = '%b %d, %Y'
# If true, SmartyPants will be used to convert quotes and dashes to
# typographically correct entities.
#html_use_smartypants = True
# Custom sidebar templates, maps document names to template names.
#html_sidebars = {}
# Additional templates that should be rendered to pages, maps page names to
# template names.
#html_additional_pages = {}
# If false, no module index is generated.
#html_domain_indices = True
# If false, no index is generated.
#html_use_index = True
# If true, the index is split into individual pages for each letter.
#html_split_index = False
# If true, links to the reST sources are added to the pages.
#html_show_sourcelink = True
# If true, "Created using Sphinx" is shown in the HTML footer. Default is True.
#html_show_sphinx = True
# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True.
#html_show_copyright = True
# If true, an OpenSearch description file will be output, and all pages will
# contain a <link> tag referring to it. The value of this option must be the
# base URL from which the finished HTML is served.
#html_use_opensearch = ''
# This is the file name suffix for HTML files (e.g. ".xhtml").
#html_file_suffix = None
# Output file base name for HTML help builder.
htmlhelp_basename = 'fullerdoc'
# -- Options for LaTeX output ---------------------------------------------
latex_elements = {
# The paper size ('letterpaper' or 'a4paper').
#'papersize': 'letterpaper',
# The font size ('10pt', '11pt' or '12pt').
#'pointsize': '10pt',
# Additional stuff for the LaTeX preamble.
#'preamble': '',
}
# Grouping the document tree into LaTeX files. List of tuples
# (source start file, target name, title,
# author, documentclass [howto, manual, or own class]).
latex_documents = [
('index', 'fuller.tex', u'fuller Documentation',
u'Vincent Stimper, R. Patrick Xian', 'manual'),
]
# The name of an image file (relative to this directory) to place at the top of
# the title page.
#latex_logo = None
# For "manual" documents, if this is true, then toplevel headings are parts,
# not chapters.
#latex_use_parts = False
# If true, show page references after internal links.
#latex_show_pagerefs = False
# If true, show URL addresses after external links.
#latex_show_urls = False
# Documents to append as an appendix to all manuals.
#latex_appendices = []
# If false, no module index is generated.
#latex_domain_indices = True
# -- Options for manual page output ---------------------------------------
# One entry per manual page. List of tuples
# (source start file, name, description, authors, manual section).
man_pages = [
('index', 'fuller', u'fuller Documentation',
[u'Vincent Stimper, R. Patrick Xian'], 1)
]
# If true, show URL addresses after external links.
#man_show_urls = False
# -- Options for Texinfo output -------------------------------------------
# Grouping the document tree into Texinfo files. List of tuples
# (source start file, target name, title, author,
# dir menu entry, description, category)
texinfo_documents = [
('index', 'fuller', u'fuller Documentation',
u'Vincent Stimper, R. Patrick Xian', 'fuller', 'One line description of project.',
'Miscellaneous'),
]
# Documents to append as an appendix to all manuals.
#texinfo_appendices = []
# If false, no module index is generated.
#texinfo_domain_indices = True
# How to display URL addresses: 'footnote', 'no', or 'inline'.
#texinfo_show_urls = 'footnote'
# If true, do not generate a @detailmenu in the "Top" node's menu.
#texinfo_no_detailmenu = False
# Example configuration for intersphinx: refer to the Python standard library.
intersphinx_mapping = {'http://docs.python.org/': None}
| Python |
3D | Autodesk/molecular-design-toolkit | setup.py | .py | 3,184 | 94 | # Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import sys
from os.path import relpath, join
from setuptools import find_packages, setup
from setuptools.command.install import install
import versioneer
PACKAGE_NAME = 'moldesign'
CLASSIFIERS = """\
Development Status :: 4 - Beta
Intended Audience :: Science/Research
Intended Audience :: Developers
Intended Audience :: Education
License :: OSI Approved :: Apache Software License
Programming Language :: Python :: 2
Programming Language :: Python :: 2.7
Programming Language :: Python :: 3
Programming Language :: Python :: 3.5
Programming Language :: Python :: 3.6
Topic :: Scientific/Engineering :: Chemistry
Topic :: Scientific/Engineering :: Physics
Operating System :: POSIX
Operating System :: Unix
Operating System :: MacOS
"""
HOME = os.path.expanduser('~')
CONFIG_DIR = os.path.join(HOME, '.moldesign')
PYEXT = set('.py .pyc .pyo'.split())
with open('requirements.txt', 'r') as reqfile:
requirements = [x.strip() for x in reqfile if x.strip()]
def find_package_data(pkgdir):
""" Just include all files that won't be included as package modules.
"""
files = []
for root, dirnames, filenames in os.walk(pkgdir):
not_a_package = '__init__.py' not in filenames
for fn in filenames:
basename, fext = os.path.splitext(fn)
if not_a_package or (fext not in PYEXT) or ('static' in fn):
files.append(relpath(join(root, fn), pkgdir))
return files
class PostInstall(install):
def run(self):
install.run(self)
self.prompt_intro()
def prompt_intro(self): # this doesn't actually display - print statements don't work?
print('Thank you for installing the Molecular Design Toolkit!!!')
print('For help, documentation, and any questions, visit us at ')
print(' http://moldesign.bionano.autodesk.com/')
print("\nFor visualization functionality inside python notebooks, please also install")
print("the `mdtwidgets` package.")
cmdclass = versioneer.get_cmdclass()
cmdclass['install'] = PostInstall
setup(
name=PACKAGE_NAME,
version=versioneer.get_version(),
classifiers=CLASSIFIERS.splitlines(),
packages=find_packages(),
package_data={PACKAGE_NAME: find_package_data(PACKAGE_NAME)},
install_requires=requirements,
url='http://moldesign.bionano.autodesk.com',
cmdclass=cmdclass,
license='Apache 2.0',
author='Aaron Virshup, Autodesk Life Sciences',
author_email='moleculardesigntoolkit@autodesk.com',
description='A single, intuitive interface to a huge range of molecular modeling software')
| Python |
3D | Autodesk/molecular-design-toolkit | versioneer.py | .py | 68,587 | 1,818 |
# Version: 0.17
"""The Versioneer - like a rocketeer, but for versions.
The Versioneer
==============
* like a rocketeer, but for versions!
* https://github.com/warner/python-versioneer
* Brian Warner
* License: Public Domain
* Compatible With: python2.6, 2.7, 3.2, 3.3, 3.4, 3.5, and pypy
* [![Latest Version]
(https://pypip.in/version/versioneer/badge.svg?style=flat)
](https://pypi.python.org/pypi/versioneer/)
* [![Build Status]
(https://travis-ci.org/warner/python-versioneer.png?branch=master)
](https://travis-ci.org/warner/python-versioneer)
This is a tool for managing a recorded version number in distutils-based
python projects. The goal is to remove the tedious and error-prone "update
the embedded version string" step from your release process. Making a new
release should be as easy as recording a new tag in your version-control
system, and maybe making new tarballs.
## Quick Install
* `pip install versioneer` to somewhere to your $PATH
* add a `[versioneer]` section to your setup.cfg (see below)
* run `versioneer install` in your source tree, commit the results
## Version Identifiers
Source trees come from a variety of places:
* a version-control system checkout (mostly used by developers)
* a nightly tarball, produced by build automation
* a snapshot tarball, produced by a web-based VCS browser, like github's
"tarball from tag" feature
* a release tarball, produced by "setup.py sdist", distributed through PyPI
Within each source tree, the version identifier (either a string or a number,
this tool is format-agnostic) can come from a variety of places:
* ask the VCS tool itself, e.g. "git describe" (for checkouts), which knows
about recent "tags" and an absolute revision-id
* the name of the directory into which the tarball was unpacked
* an expanded VCS keyword ($Id$, etc)
* a `_version.py` created by some earlier build step
For released software, the version identifier is closely related to a VCS
tag. Some projects use tag names that include more than just the version
string (e.g. "myproject-1.2" instead of just "1.2"), in which case the tool
needs to strip the tag prefix to extract the version identifier. For
unreleased software (between tags), the version identifier should provide
enough information to help developers recreate the same tree, while also
giving them an idea of roughly how old the tree is (after version 1.2, before
version 1.3). Many VCS systems can report a description that captures this,
for example `git describe --tags --dirty --always` reports things like
"0.7-1-g574ab98-dirty" to indicate that the checkout is one revision past the
0.7 tag, has a unique revision id of "574ab98", and is "dirty" (it has
uncommitted changes.
The version identifier is used for multiple purposes:
* to allow the module to self-identify its version: `myproject.__version__`
* to choose a name and prefix for a 'setup.py sdist' tarball
## Theory of Operation
Versioneer works by adding a special `_version.py` file into your source
tree, where your `__init__.py` can import it. This `_version.py` knows how to
dynamically ask the VCS tool for version information at import time.
`_version.py` also contains `$Revision$` markers, and the installation
process marks `_version.py` to have this marker rewritten with a tag name
during the `git archive` command. As a result, generated tarballs will
contain enough information to get the proper version.
To allow `setup.py` to compute a version too, a `versioneer.py` is added to
the top level of your source tree, next to `setup.py` and the `setup.cfg`
that configures it. This overrides several distutils/setuptools commands to
compute the version when invoked, and changes `setup.py build` and `setup.py
sdist` to replace `_version.py` with a small static file that contains just
the generated version data.
## Installation
See [INSTALL.md](./INSTALL.md) for detailed installation instructions.
## Version-String Flavors
Code which uses Versioneer can learn about its version string at runtime by
importing `_version` from your main `__init__.py` file and running the
`get_versions()` function. From the "outside" (e.g. in `setup.py`), you can
import the top-level `versioneer.py` and run `get_versions()`.
Both functions return a dictionary with different flavors of version
information:
* `['version']`: A condensed version string, rendered using the selected
style. This is the most commonly used value for the project's version
string. The default "pep440" style yields strings like `0.11`,
`0.11+2.g1076c97`, or `0.11+2.g1076c97.dirty`. See the "Styles" section
below for alternative styles.
* `['full-revisionid']`: detailed revision identifier. For Git, this is the
full SHA1 commit id, e.g. "1076c978a8d3cfc70f408fe5974aa6c092c949ac".
* `['date']`: Date and time of the latest `HEAD` commit. For Git, it is the
commit date in ISO 8601 format. This will be None if the date is not
available.
* `['dirty']`: a boolean, True if the tree has uncommitted changes. Note that
this is only accurate if run in a VCS checkout, otherwise it is likely to
be False or None
* `['error']`: if the version string could not be computed, this will be set
to a string describing the problem, otherwise it will be None. It may be
useful to throw an exception in setup.py if this is set, to avoid e.g.
creating tarballs with a version string of "unknown".
Some variants are more useful than others. Including `full-revisionid` in a
bug report should allow developers to reconstruct the exact code being tested
(or indicate the presence of local changes that should be shared with the
developers). `version` is suitable for display in an "about" box or a CLI
`--version` output: it can be easily compared against release notes and lists
of bugs fixed in various releases.
The installer adds the following text to your `__init__.py` to place a basic
version in `YOURPROJECT.__version__`:
from ._version import get_versions
__version__ = get_versions()['version']
del get_versions
## Styles
The setup.cfg `style=` configuration controls how the VCS information is
rendered into a version string.
The default style, "pep440", produces a PEP440-compliant string, equal to the
un-prefixed tag name for actual releases, and containing an additional "local
version" section with more detail for in-between builds. For Git, this is
TAG[+DISTANCE.gHEX[.dirty]] , using information from `git describe --tags
--dirty --always`. For example "0.11+2.g1076c97.dirty" indicates that the
tree is like the "1076c97" commit but has uncommitted changes (".dirty"), and
that this commit is two revisions ("+2") beyond the "0.11" tag. For released
software (exactly equal to a known tag), the identifier will only contain the
stripped tag, e.g. "0.11".
Other styles are available. See details.md in the Versioneer source tree for
descriptions.
## Debugging
Versioneer tries to avoid fatal errors: if something goes wrong, it will tend
to return a version of "0+unknown". To investigate the problem, run `setup.py
version`, which will run the version-lookup code in a verbose mode, and will
display the full contents of `get_versions()` (including the `error` string,
which may help identify what went wrong).
## Known Limitations
Some situations are known to cause problems for Versioneer. This details the
most significant ones. More can be found on Github
[issues page](https://github.com/warner/python-versioneer/issues).
### Subprojects
Versioneer has limited support for source trees in which `setup.py` is not in
the root directory (e.g. `setup.py` and `.git/` are *not* siblings). The are
two common reasons why `setup.py` might not be in the root:
* Source trees which contain multiple subprojects, such as
[Buildbot](https://github.com/buildbot/buildbot), which contains both
"master" and "slave" subprojects, each with their own `setup.py`,
`setup.cfg`, and `tox.ini`. Projects like these produce multiple PyPI
distributions (and upload multiple independently-installable tarballs).
* Source trees whose main purpose is to contain a C library, but which also
provide bindings to Python (and perhaps other langauges) in subdirectories.
Versioneer will look for `.git` in parent directories, and most operations
should get the right version string. However `pip` and `setuptools` have bugs
and implementation details which frequently cause `pip install .` from a
subproject directory to fail to find a correct version string (so it usually
defaults to `0+unknown`).
`pip install --editable .` should work correctly. `setup.py install` might
work too.
Pip-8.1.1 is known to have this problem, but hopefully it will get fixed in
some later version.
[Bug #38](https://github.com/warner/python-versioneer/issues/38) is tracking
this issue. The discussion in
[PR #61](https://github.com/warner/python-versioneer/pull/61) describes the
issue from the Versioneer side in more detail.
[pip PR#3176](https://github.com/pypa/pip/pull/3176) and
[pip PR#3615](https://github.com/pypa/pip/pull/3615) contain work to improve
pip to let Versioneer work correctly.
Versioneer-0.16 and earlier only looked for a `.git` directory next to the
`setup.cfg`, so subprojects were completely unsupported with those releases.
### Editable installs with setuptools <= 18.5
`setup.py develop` and `pip install --editable .` allow you to install a
project into a virtualenv once, then continue editing the source code (and
test) without re-installing after every change.
"Entry-point scripts" (`setup(entry_points={"console_scripts": ..})`) are a
convenient way to specify executable scripts that should be installed along
with the python package.
These both work as expected when using modern setuptools. When using
setuptools-18.5 or earlier, however, certain operations will cause
`pkg_resources.DistributionNotFound` errors when running the entrypoint
script, which must be resolved by re-installing the package. This happens
when the install happens with one version, then the egg_info data is
regenerated while a different version is checked out. Many setup.py commands
cause egg_info to be rebuilt (including `sdist`, `wheel`, and installing into
a different virtualenv), so this can be surprising.
[Bug #83](https://github.com/warner/python-versioneer/issues/83) describes
this one, but upgrading to a newer version of setuptools should probably
resolve it.
### Unicode version strings
While Versioneer works (and is continually tested) with both Python 2 and
Python 3, it is not entirely consistent with bytes-vs-unicode distinctions.
Newer releases probably generate unicode version strings on py2. It's not
clear that this is wrong, but it may be surprising for applications when then
write these strings to a network connection or include them in bytes-oriented
APIs like cryptographic checksums.
[Bug #71](https://github.com/warner/python-versioneer/issues/71) investigates
this question.
## Updating Versioneer
To upgrade your project to a new release of Versioneer, do the following:
* install the new Versioneer (`pip install -U versioneer` or equivalent)
* edit `setup.cfg`, if necessary, to include any new configuration settings
indicated by the release notes. See [UPGRADING](./UPGRADING.md) for details.
* re-run `versioneer install` in your source tree, to replace
`SRC/_version.py`
* commit any changed files
## Future Directions
This tool is designed to make it easily extended to other version-control
systems: all VCS-specific components are in separate directories like
src/git/ . The top-level `versioneer.py` script is assembled from these
components by running make-versioneer.py . In the future, make-versioneer.py
will take a VCS name as an argument, and will construct a version of
`versioneer.py` that is specific to the given VCS. It might also take the
configuration arguments that are currently provided manually during
installation by editing setup.py . Alternatively, it might go the other
direction and include code from all supported VCS systems, reducing the
number of intermediate scripts.
## License
To make Versioneer easier to embed, all its code is dedicated to the public
domain. The `_version.py` that it creates is also in the public domain.
Specifically, both are released under the Creative Commons "Public Domain
Dedication" license (CC0-1.0), as described in
https://creativecommons.org/publicdomain/zero/1.0/ .
"""
from __future__ import print_function
try:
import configparser
except ImportError:
import ConfigParser as configparser
import errno
import json
import os
import re
import subprocess
import sys
class VersioneerConfig:
"""Container for Versioneer configuration parameters."""
def get_root():
"""Get the project root directory.
We require that all commands are run from the project root, i.e. the
directory that contains setup.py, setup.cfg, and versioneer.py .
"""
root = os.path.realpath(os.path.abspath(os.getcwd()))
setup_py = os.path.join(root, "setup.py")
versioneer_py = os.path.join(root, "versioneer.py")
if not (os.path.exists(setup_py) or os.path.exists(versioneer_py)):
# allow 'python path/to/setup.py COMMAND'
root = os.path.dirname(os.path.realpath(os.path.abspath(sys.argv[0])))
setup_py = os.path.join(root, "setup.py")
versioneer_py = os.path.join(root, "versioneer.py")
if not (os.path.exists(setup_py) or os.path.exists(versioneer_py)):
err = ("Versioneer was unable to run the project root directory. "
"Versioneer requires setup.py to be executed from "
"its immediate directory (like 'python setup.py COMMAND'), "
"or in a way that lets it use sys.argv[0] to find the root "
"(like 'python path/to/setup.py COMMAND').")
raise VersioneerBadRootError(err)
try:
# Certain runtime workflows (setup.py install/develop in a setuptools
# tree) execute all dependencies in a single python process, so
# "versioneer" may be imported multiple times, and python's shared
# module-import table will cache the first one. So we can't use
# os.path.dirname(__file__), as that will find whichever
# versioneer.py was first imported, even in later projects.
me = os.path.realpath(os.path.abspath(__file__))
me_dir = os.path.normcase(os.path.splitext(me)[0])
vsr_dir = os.path.normcase(os.path.splitext(versioneer_py)[0])
if me_dir != vsr_dir:
print("Warning: build in %s is using versioneer.py from %s"
% (os.path.dirname(me), versioneer_py))
except NameError:
pass
return root
def get_config_from_root(root):
"""Read the project setup.cfg file to determine Versioneer config."""
# This might raise EnvironmentError (if setup.cfg is missing), or
# configparser.NoSectionError (if it lacks a [versioneer] section), or
# configparser.NoOptionError (if it lacks "VCS="). See the docstring at
# the top of versioneer.py for instructions on writing your setup.cfg .
setup_cfg = os.path.join(root, "setup.cfg")
parser = configparser.SafeConfigParser()
with open(setup_cfg, "r") as f:
parser.readfp(f)
VCS = parser.get("versioneer", "VCS") # mandatory
def get(parser, name):
if parser.has_option("versioneer", name):
return parser.get("versioneer", name)
return None
cfg = VersioneerConfig()
cfg.VCS = VCS
cfg.style = get(parser, "style") or ""
cfg.versionfile_source = get(parser, "versionfile_source")
cfg.versionfile_build = get(parser, "versionfile_build")
cfg.tag_prefix = get(parser, "tag_prefix")
if cfg.tag_prefix in ("''", '""'):
cfg.tag_prefix = ""
cfg.parentdir_prefix = get(parser, "parentdir_prefix")
cfg.verbose = get(parser, "verbose")
return cfg
class NotThisMethod(Exception):
"""Exception raised if a method is not valid for the current scenario."""
# these dictionaries contain VCS-specific tools
LONG_VERSION_PY = {}
HANDLERS = {}
def register_vcs_handler(vcs, method): # decorator
"""Decorator to mark a method as the handler for a particular VCS."""
def decorate(f):
"""Store f in HANDLERS[vcs][method]."""
if vcs not in HANDLERS:
HANDLERS[vcs] = {}
HANDLERS[vcs][method] = f
return f
return decorate
def run_command(commands, args, cwd=None, verbose=False, hide_stderr=False,
env=None):
"""Call the given command(s)."""
assert isinstance(commands, list)
p = None
for c in commands:
try:
dispcmd = str([c] + args)
# remember shell=False, so use git.cmd on windows, not just git
p = subprocess.Popen([c] + args, cwd=cwd, env=env,
stdout=subprocess.PIPE,
stderr=(subprocess.PIPE if hide_stderr
else None))
break
except EnvironmentError:
e = sys.exc_info()[1]
if e.errno == errno.ENOENT:
continue
if verbose:
print("unable to run %s" % dispcmd)
print(e)
return None, None
else:
if verbose:
print("unable to find command, tried %s" % (commands,))
return None, None
stdout = p.communicate()[0].strip()
if sys.version_info[0] >= 3:
stdout = stdout.decode()
if p.returncode != 0:
if verbose:
print("unable to run %s (error)" % dispcmd)
print("stdout was %s" % stdout)
return None, p.returncode
return stdout, p.returncode
LONG_VERSION_PY['git'] = '''
# This file helps to compute a version number in source trees obtained from
# git-archive tarball (such as those provided by githubs download-from-tag
# feature). Distribution tarballs (built by setup.py sdist) and build
# directories (produced by setup.py build) will contain a much shorter file
# that just contains the computed version number.
# This file is released into the public domain. Generated by
# versioneer-0.17 (https://github.com/warner/python-versioneer)
"""Git implementation of _version.py."""
import errno
import os
import re
import subprocess
import sys
def get_keywords():
"""Get the keywords needed to look up the version information."""
# these strings will be replaced by git during git-archive.
# setup.py/versioneer.py will grep for the variable names, so they must
# each be defined on a line of their own. _version.py will just call
# get_keywords().
git_refnames = "%(DOLLAR)sFormat:%%d%(DOLLAR)s"
git_full = "%(DOLLAR)sFormat:%%H%(DOLLAR)s"
git_date = "%(DOLLAR)sFormat:%%ci%(DOLLAR)s"
keywords = {"refnames": git_refnames, "full": git_full, "date": git_date}
return keywords
class VersioneerConfig:
"""Container for Versioneer configuration parameters."""
def get_config():
"""Create, populate and return the VersioneerConfig() object."""
# these strings are filled in when 'setup.py versioneer' creates
# _version.py
cfg = VersioneerConfig()
cfg.VCS = "git"
cfg.style = "%(STYLE)s"
cfg.tag_prefix = "%(TAG_PREFIX)s"
cfg.parentdir_prefix = "%(PARENTDIR_PREFIX)s"
cfg.versionfile_source = "%(VERSIONFILE_SOURCE)s"
cfg.verbose = False
return cfg
class NotThisMethod(Exception):
"""Exception raised if a method is not valid for the current scenario."""
LONG_VERSION_PY = {}
HANDLERS = {}
def register_vcs_handler(vcs, method): # decorator
"""Decorator to mark a method as the handler for a particular VCS."""
def decorate(f):
"""Store f in HANDLERS[vcs][method]."""
if vcs not in HANDLERS:
HANDLERS[vcs] = {}
HANDLERS[vcs][method] = f
return f
return decorate
def run_command(commands, args, cwd=None, verbose=False, hide_stderr=False,
env=None):
"""Call the given command(s)."""
assert isinstance(commands, list)
p = None
for c in commands:
try:
dispcmd = str([c] + args)
# remember shell=False, so use git.cmd on windows, not just git
p = subprocess.Popen([c] + args, cwd=cwd, env=env,
stdout=subprocess.PIPE,
stderr=(subprocess.PIPE if hide_stderr
else None))
break
except EnvironmentError:
e = sys.exc_info()[1]
if e.errno == errno.ENOENT:
continue
if verbose:
print("unable to run %%s" %% dispcmd)
print(e)
return None, None
else:
if verbose:
print("unable to find command, tried %%s" %% (commands,))
return None, None
stdout = p.communicate()[0].strip()
if sys.version_info[0] >= 3:
stdout = stdout.decode()
if p.returncode != 0:
if verbose:
print("unable to run %%s (error)" %% dispcmd)
print("stdout was %%s" %% stdout)
return None, p.returncode
return stdout, p.returncode
def versions_from_parentdir(parentdir_prefix, root, verbose):
"""Try to determine the version from the parent directory name.
Source tarballs conventionally unpack into a directory that includes both
the project name and a version string. We will also support searching up
two directory levels for an appropriately named parent directory
"""
rootdirs = []
for i in range(3):
dirname = os.path.basename(root)
if dirname.startswith(parentdir_prefix):
return {"version": dirname[len(parentdir_prefix):],
"full-revisionid": None,
"dirty": False, "error": None, "date": None}
else:
rootdirs.append(root)
root = os.path.dirname(root) # up a level
if verbose:
print("Tried directories %%s but none started with prefix %%s" %%
(str(rootdirs), parentdir_prefix))
raise NotThisMethod("rootdir doesn't start with parentdir_prefix")
@register_vcs_handler("git", "get_keywords")
def git_get_keywords(versionfile_abs):
"""Extract version information from the given file."""
# the code embedded in _version.py can just fetch the value of these
# keywords. When used from setup.py, we don't want to import _version.py,
# so we do it with a regexp instead. This function is not used from
# _version.py.
keywords = {}
try:
f = open(versionfile_abs, "r")
for line in f.readlines():
if line.strip().startswith("git_refnames ="):
mo = re.search(r'=\s*"(.*)"', line)
if mo:
keywords["refnames"] = mo.group(1)
if line.strip().startswith("git_full ="):
mo = re.search(r'=\s*"(.*)"', line)
if mo:
keywords["full"] = mo.group(1)
if line.strip().startswith("git_date ="):
mo = re.search(r'=\s*"(.*)"', line)
if mo:
keywords["date"] = mo.group(1)
f.close()
except EnvironmentError:
pass
return keywords
@register_vcs_handler("git", "keywords")
def git_versions_from_keywords(keywords, tag_prefix, verbose):
"""Get version information from git keywords."""
if not keywords:
raise NotThisMethod("no keywords at all, weird")
date = keywords.get("date")
if date is not None:
# git-2.2.0 added "%%cI", which expands to an ISO-8601 -compliant
# datestamp. However we prefer "%%ci" (which expands to an "ISO-8601
# -like" string, which we must then edit to make compliant), because
# it's been around since git-1.5.3, and it's too difficult to
# discover which version we're using, or to work around using an
# older one.
date = date.strip().replace(" ", "T", 1).replace(" ", "", 1)
refnames = keywords["refnames"].strip()
if refnames.startswith("$Format"):
if verbose:
print("keywords are unexpanded, not using")
raise NotThisMethod("unexpanded keywords, not a git-archive tarball")
refs = set([r.strip() for r in refnames.strip("()").split(",")])
# starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of
# just "foo-1.0". If we see a "tag: " prefix, prefer those.
TAG = "tag: "
tags = set([r[len(TAG):] for r in refs if r.startswith(TAG)])
if not tags:
# Either we're using git < 1.8.3, or there really are no tags. We use
# a heuristic: assume all version tags have a digit. The old git %%d
# expansion behaves like git log --decorate=short and strips out the
# refs/heads/ and refs/tags/ prefixes that would let us distinguish
# between branches and tags. By ignoring refnames without digits, we
# filter out many common branch names like "release" and
# "stabilization", as well as "HEAD" and "master".
tags = set([r for r in refs if re.search(r'\d', r)])
if verbose:
print("discarding '%%s', no digits" %% ",".join(refs - tags))
if verbose:
print("likely tags: %%s" %% ",".join(sorted(tags)))
for ref in sorted(tags):
# sorting will prefer e.g. "2.0" over "2.0rc1"
if ref.startswith(tag_prefix):
r = ref[len(tag_prefix):]
if verbose:
print("picking %%s" %% r)
return {"version": r,
"full-revisionid": keywords["full"].strip(),
"dirty": False, "error": None,
"date": date}
# no suitable tags, so version is "0+unknown", but full hex is still there
if verbose:
print("no suitable tags, using unknown + full revision id")
return {"version": "0+unknown",
"full-revisionid": keywords["full"].strip(),
"dirty": False, "error": "no suitable tags", "date": None}
@register_vcs_handler("git", "pieces_from_vcs")
def git_pieces_from_vcs(tag_prefix, root, verbose, run_command=run_command):
"""Get version from 'git describe' in the root of the source tree.
This only gets called if the git-archive 'subst' keywords were *not*
expanded, and _version.py hasn't already been rewritten with a short
version string, meaning we're inside a checked out source tree.
"""
GITS = ["git"]
if sys.platform == "win32":
GITS = ["git.cmd", "git.exe"]
out, rc = run_command(GITS, ["rev-parse", "--git-dir"], cwd=root,
hide_stderr=True)
if rc != 0:
if verbose:
print("Directory %%s not under git control" %% root)
raise NotThisMethod("'git rev-parse --git-dir' returned error")
# if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty]
# if there isn't one, this yields HEX[-dirty] (no NUM)
describe_out, rc = run_command(GITS, ["describe", "--tags", "--dirty",
"--always", "--long",
"--match", "%%s*" %% tag_prefix],
cwd=root)
# --long was added in git-1.5.5
if describe_out is None:
raise NotThisMethod("'git describe' failed")
describe_out = describe_out.strip()
full_out, rc = run_command(GITS, ["rev-parse", "HEAD"], cwd=root)
if full_out is None:
raise NotThisMethod("'git rev-parse' failed")
full_out = full_out.strip()
pieces = {}
pieces["long"] = full_out
pieces["short"] = full_out[:7] # maybe improved later
pieces["error"] = None
# parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty]
# TAG might have hyphens.
git_describe = describe_out
# look for -dirty suffix
dirty = git_describe.endswith("-dirty")
pieces["dirty"] = dirty
if dirty:
git_describe = git_describe[:git_describe.rindex("-dirty")]
# now we have TAG-NUM-gHEX or HEX
if "-" in git_describe:
# TAG-NUM-gHEX
mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe)
if not mo:
# unparseable. Maybe git-describe is misbehaving?
pieces["error"] = ("unable to parse git-describe output: '%%s'"
%% describe_out)
return pieces
# tag
full_tag = mo.group(1)
if not full_tag.startswith(tag_prefix):
if verbose:
fmt = "tag '%%s' doesn't start with prefix '%%s'"
print(fmt %% (full_tag, tag_prefix))
pieces["error"] = ("tag '%%s' doesn't start with prefix '%%s'"
%% (full_tag, tag_prefix))
return pieces
pieces["closest-tag"] = full_tag[len(tag_prefix):]
# distance: number of commits since tag
pieces["distance"] = int(mo.group(2))
# commit: short hex revision ID
pieces["short"] = mo.group(3)
else:
# HEX: no tags
pieces["closest-tag"] = None
count_out, rc = run_command(GITS, ["rev-list", "HEAD", "--count"],
cwd=root)
pieces["distance"] = int(count_out) # total number of commits
# commit date: see ISO-8601 comment in git_versions_from_keywords()
date = run_command(GITS, ["show", "-s", "--format=%%ci", "HEAD"],
cwd=root)[0].strip()
pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1)
return pieces
def plus_or_dot(pieces):
"""Return a + if we don't already have one, else return a ."""
if "+" in pieces.get("closest-tag", ""):
return "."
return "+"
def render_pep440(pieces):
"""Build up version string, with post-release "local version identifier".
Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you
get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty
Exceptions:
1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty]
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"] or pieces["dirty"]:
rendered += plus_or_dot(pieces)
rendered += "%%d.g%%s" %% (pieces["distance"], pieces["short"])
if pieces["dirty"]:
rendered += ".dirty"
else:
# exception #1
rendered = "0+untagged.%%d.g%%s" %% (pieces["distance"],
pieces["short"])
if pieces["dirty"]:
rendered += ".dirty"
return rendered
def render_pep440_pre(pieces):
"""TAG[.post.devDISTANCE] -- No -dirty.
Exceptions:
1: no tags. 0.post.devDISTANCE
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"]:
rendered += ".post.dev%%d" %% pieces["distance"]
else:
# exception #1
rendered = "0.post.dev%%d" %% pieces["distance"]
return rendered
def render_pep440_post(pieces):
"""TAG[.postDISTANCE[.dev0]+gHEX] .
The ".dev0" means dirty. Note that .dev0 sorts backwards
(a dirty tree will appear "older" than the corresponding clean one),
but you shouldn't be releasing software with -dirty anyways.
Exceptions:
1: no tags. 0.postDISTANCE[.dev0]
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"] or pieces["dirty"]:
rendered += ".post%%d" %% pieces["distance"]
if pieces["dirty"]:
rendered += ".dev0"
rendered += plus_or_dot(pieces)
rendered += "g%%s" %% pieces["short"]
else:
# exception #1
rendered = "0.post%%d" %% pieces["distance"]
if pieces["dirty"]:
rendered += ".dev0"
rendered += "+g%%s" %% pieces["short"]
return rendered
def render_pep440_old(pieces):
"""TAG[.postDISTANCE[.dev0]] .
The ".dev0" means dirty.
Eexceptions:
1: no tags. 0.postDISTANCE[.dev0]
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"] or pieces["dirty"]:
rendered += ".post%%d" %% pieces["distance"]
if pieces["dirty"]:
rendered += ".dev0"
else:
# exception #1
rendered = "0.post%%d" %% pieces["distance"]
if pieces["dirty"]:
rendered += ".dev0"
return rendered
def render_git_describe(pieces):
"""TAG[-DISTANCE-gHEX][-dirty].
Like 'git describe --tags --dirty --always'.
Exceptions:
1: no tags. HEX[-dirty] (note: no 'g' prefix)
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"]:
rendered += "-%%d-g%%s" %% (pieces["distance"], pieces["short"])
else:
# exception #1
rendered = pieces["short"]
if pieces["dirty"]:
rendered += "-dirty"
return rendered
def render_git_describe_long(pieces):
"""TAG-DISTANCE-gHEX[-dirty].
Like 'git describe --tags --dirty --always -long'.
The distance/hash is unconditional.
Exceptions:
1: no tags. HEX[-dirty] (note: no 'g' prefix)
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
rendered += "-%%d-g%%s" %% (pieces["distance"], pieces["short"])
else:
# exception #1
rendered = pieces["short"]
if pieces["dirty"]:
rendered += "-dirty"
return rendered
def render(pieces, style):
"""Render the given version pieces into the requested style."""
if pieces["error"]:
return {"version": "unknown",
"full-revisionid": pieces.get("long"),
"dirty": None,
"error": pieces["error"],
"date": None}
if not style or style == "default":
style = "pep440" # the default
if style == "pep440":
rendered = render_pep440(pieces)
elif style == "pep440-pre":
rendered = render_pep440_pre(pieces)
elif style == "pep440-post":
rendered = render_pep440_post(pieces)
elif style == "pep440-old":
rendered = render_pep440_old(pieces)
elif style == "git-describe":
rendered = render_git_describe(pieces)
elif style == "git-describe-long":
rendered = render_git_describe_long(pieces)
else:
raise ValueError("unknown style '%%s'" %% style)
return {"version": rendered, "full-revisionid": pieces["long"],
"dirty": pieces["dirty"], "error": None,
"date": pieces.get("date")}
def get_versions():
"""Get version information or return default if unable to do so."""
# I am in _version.py, which lives at ROOT/VERSIONFILE_SOURCE. If we have
# __file__, we can work backwards from there to the root. Some
# py2exe/bbfreeze/non-CPython implementations don't do __file__, in which
# case we can only use expanded keywords.
cfg = get_config()
verbose = cfg.verbose
try:
return git_versions_from_keywords(get_keywords(), cfg.tag_prefix,
verbose)
except NotThisMethod:
pass
try:
root = os.path.realpath(__file__)
# versionfile_source is the relative path from the top of the source
# tree (where the .git directory might live) to this file. Invert
# this to find the root from __file__.
for i in cfg.versionfile_source.split('/'):
root = os.path.dirname(root)
except NameError:
return {"version": "0+unknown", "full-revisionid": None,
"dirty": None,
"error": "unable to find root of source tree",
"date": None}
try:
pieces = git_pieces_from_vcs(cfg.tag_prefix, root, verbose)
return render(pieces, cfg.style)
except NotThisMethod:
pass
try:
if cfg.parentdir_prefix:
return versions_from_parentdir(cfg.parentdir_prefix, root, verbose)
except NotThisMethod:
pass
return {"version": "0+unknown", "full-revisionid": None,
"dirty": None,
"error": "unable to compute version", "date": None}
'''
@register_vcs_handler("git", "get_keywords")
def git_get_keywords(versionfile_abs):
"""Extract version information from the given file."""
# the code embedded in _version.py can just fetch the value of these
# keywords. When used from setup.py, we don't want to import _version.py,
# so we do it with a regexp instead. This function is not used from
# _version.py.
keywords = {}
try:
f = open(versionfile_abs, "r")
for line in f.readlines():
if line.strip().startswith("git_refnames ="):
mo = re.search(r'=\s*"(.*)"', line)
if mo:
keywords["refnames"] = mo.group(1)
if line.strip().startswith("git_full ="):
mo = re.search(r'=\s*"(.*)"', line)
if mo:
keywords["full"] = mo.group(1)
if line.strip().startswith("git_date ="):
mo = re.search(r'=\s*"(.*)"', line)
if mo:
keywords["date"] = mo.group(1)
f.close()
except EnvironmentError:
pass
return keywords
@register_vcs_handler("git", "keywords")
def git_versions_from_keywords(keywords, tag_prefix, verbose):
"""Get version information from git keywords."""
if not keywords:
raise NotThisMethod("no keywords at all, weird")
date = keywords.get("date")
if date is not None:
# git-2.2.0 added "%cI", which expands to an ISO-8601 -compliant
# datestamp. However we prefer "%ci" (which expands to an "ISO-8601
# -like" string, which we must then edit to make compliant), because
# it's been around since git-1.5.3, and it's too difficult to
# discover which version we're using, or to work around using an
# older one.
date = date.strip().replace(" ", "T", 1).replace(" ", "", 1)
refnames = keywords["refnames"].strip()
if refnames.startswith("$Format"):
if verbose:
print("keywords are unexpanded, not using")
raise NotThisMethod("unexpanded keywords, not a git-archive tarball")
refs = set([r.strip() for r in refnames.strip("()").split(",")])
# starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of
# just "foo-1.0". If we see a "tag: " prefix, prefer those.
TAG = "tag: "
tags = set([r[len(TAG):] for r in refs if r.startswith(TAG)])
if not tags:
# Either we're using git < 1.8.3, or there really are no tags. We use
# a heuristic: assume all version tags have a digit. The old git %d
# expansion behaves like git log --decorate=short and strips out the
# refs/heads/ and refs/tags/ prefixes that would let us distinguish
# between branches and tags. By ignoring refnames without digits, we
# filter out many common branch names like "release" and
# "stabilization", as well as "HEAD" and "master".
tags = set([r for r in refs if re.search(r'\d', r)])
if verbose:
print("discarding '%s', no digits" % ",".join(refs - tags))
if verbose:
print("likely tags: %s" % ",".join(sorted(tags)))
for ref in sorted(tags):
# sorting will prefer e.g. "2.0" over "2.0rc1"
if ref.startswith(tag_prefix):
r = ref[len(tag_prefix):]
if verbose:
print("picking %s" % r)
return {"version": r,
"full-revisionid": keywords["full"].strip(),
"dirty": False, "error": None,
"date": date}
# no suitable tags, so version is "0+unknown", but full hex is still there
if verbose:
print("no suitable tags, using unknown + full revision id")
return {"version": "0+unknown",
"full-revisionid": keywords["full"].strip(),
"dirty": False, "error": "no suitable tags", "date": None}
@register_vcs_handler("git", "pieces_from_vcs")
def git_pieces_from_vcs(tag_prefix, root, verbose, run_command=run_command):
"""Get version from 'git describe' in the root of the source tree.
This only gets called if the git-archive 'subst' keywords were *not*
expanded, and _version.py hasn't already been rewritten with a short
version string, meaning we're inside a checked out source tree.
"""
GITS = ["git"]
if sys.platform == "win32":
GITS = ["git.cmd", "git.exe"]
out, rc = run_command(GITS, ["rev-parse", "--git-dir"], cwd=root,
hide_stderr=True)
if rc != 0:
if verbose:
print("Directory %s not under git control" % root)
raise NotThisMethod("'git rev-parse --git-dir' returned error")
# if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty]
# if there isn't one, this yields HEX[-dirty] (no NUM)
describe_out, rc = run_command(GITS, ["describe", "--tags", "--dirty",
"--always", "--long",
"--match", "%s*" % tag_prefix],
cwd=root)
# --long was added in git-1.5.5
if describe_out is None:
raise NotThisMethod("'git describe' failed")
describe_out = describe_out.strip()
full_out, rc = run_command(GITS, ["rev-parse", "HEAD"], cwd=root)
if full_out is None:
raise NotThisMethod("'git rev-parse' failed")
full_out = full_out.strip()
pieces = {}
pieces["long"] = full_out
pieces["short"] = full_out[:7] # maybe improved later
pieces["error"] = None
# parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty]
# TAG might have hyphens.
git_describe = describe_out
# look for -dirty suffix
dirty = git_describe.endswith("-dirty")
pieces["dirty"] = dirty
if dirty:
git_describe = git_describe[:git_describe.rindex("-dirty")]
# now we have TAG-NUM-gHEX or HEX
if "-" in git_describe:
# TAG-NUM-gHEX
mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe)
if not mo:
# unparseable. Maybe git-describe is misbehaving?
pieces["error"] = ("unable to parse git-describe output: '%s'"
% describe_out)
return pieces
# tag
full_tag = mo.group(1)
if not full_tag.startswith(tag_prefix):
if verbose:
fmt = "tag '%s' doesn't start with prefix '%s'"
print(fmt % (full_tag, tag_prefix))
pieces["error"] = ("tag '%s' doesn't start with prefix '%s'"
% (full_tag, tag_prefix))
return pieces
pieces["closest-tag"] = full_tag[len(tag_prefix):]
# distance: number of commits since tag
pieces["distance"] = int(mo.group(2))
# commit: short hex revision ID
pieces["short"] = mo.group(3)
else:
# HEX: no tags
pieces["closest-tag"] = None
count_out, rc = run_command(GITS, ["rev-list", "HEAD", "--count"],
cwd=root)
pieces["distance"] = int(count_out) # total number of commits
# commit date: see ISO-8601 comment in git_versions_from_keywords()
date = run_command(GITS, ["show", "-s", "--format=%ci", "HEAD"],
cwd=root)[0].strip()
pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1)
return pieces
def do_vcs_install(manifest_in, versionfile_source, ipy):
"""Git-specific installation logic for Versioneer.
For Git, this means creating/changing .gitattributes to mark _version.py
for export-subst keyword substitution.
"""
GITS = ["git"]
if sys.platform == "win32":
GITS = ["git.cmd", "git.exe"]
files = [manifest_in, versionfile_source]
if ipy:
files.append(ipy)
try:
me = __file__
if me.endswith(".pyc") or me.endswith(".pyo"):
me = os.path.splitext(me)[0] + ".py"
versioneer_file = os.path.relpath(me)
except NameError:
versioneer_file = "versioneer.py"
files.append(versioneer_file)
present = False
try:
f = open(".gitattributes", "r")
for line in f.readlines():
if line.strip().startswith(versionfile_source):
if "export-subst" in line.strip().split()[1:]:
present = True
f.close()
except EnvironmentError:
pass
if not present:
f = open(".gitattributes", "a+")
f.write("%s export-subst\n" % versionfile_source)
f.close()
files.append(".gitattributes")
run_command(GITS, ["add", "--"] + files)
def versions_from_parentdir(parentdir_prefix, root, verbose):
"""Try to determine the version from the parent directory name.
Source tarballs conventionally unpack into a directory that includes both
the project name and a version string. We will also support searching up
two directory levels for an appropriately named parent directory
"""
rootdirs = []
for i in range(3):
dirname = os.path.basename(root)
if dirname.startswith(parentdir_prefix):
return {"version": dirname[len(parentdir_prefix):],
"full-revisionid": None,
"dirty": False, "error": None, "date": None}
else:
rootdirs.append(root)
root = os.path.dirname(root) # up a level
if verbose:
print("Tried directories %s but none started with prefix %s" %
(str(rootdirs), parentdir_prefix))
raise NotThisMethod("rootdir doesn't start with parentdir_prefix")
SHORT_VERSION_PY = """
# This file was generated by 'versioneer.py' (0.17) from
# revision-control system data, or from the parent directory name of an
# unpacked source archive. Distribution tarballs contain a pre-generated copy
# of this file.
import json
version_json = '''
%s
''' # END VERSION_JSON
def get_versions():
return json.loads(version_json)
"""
def versions_from_file(filename):
"""Try to determine the version from _version.py if present."""
try:
with open(filename) as f:
contents = f.read()
except EnvironmentError:
raise NotThisMethod("unable to read _version.py")
mo = re.search(r"version_json = '''\n(.*)''' # END VERSION_JSON",
contents, re.M | re.S)
if not mo:
mo = re.search(r"version_json = '''\r\n(.*)''' # END VERSION_JSON",
contents, re.M | re.S)
if not mo:
raise NotThisMethod("no version_json in _version.py")
return json.loads(mo.group(1))
def write_to_version_file(filename, versions):
"""Write the given version number to the given _version.py file."""
os.unlink(filename)
contents = json.dumps(versions, sort_keys=True,
indent=1, separators=(",", ": "))
with open(filename, "w") as f:
f.write(SHORT_VERSION_PY % contents)
print("set %s to '%s'" % (filename, versions["version"]))
def plus_or_dot(pieces):
"""Return a + if we don't already have one, else return a ."""
if "+" in pieces.get("closest-tag", ""):
return "."
return "+"
def render_pep440(pieces):
"""Build up version string, with post-release "local version identifier".
Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you
get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty
Exceptions:
1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty]
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"] or pieces["dirty"]:
rendered += plus_or_dot(pieces)
rendered += "%d.g%s" % (pieces["distance"], pieces["short"])
if pieces["dirty"]:
rendered += ".dirty"
else:
# exception #1
rendered = "0+untagged.%d.g%s" % (pieces["distance"],
pieces["short"])
if pieces["dirty"]:
rendered += ".dirty"
return rendered
def render_pep440_pre(pieces):
"""TAG[.post.devDISTANCE] -- No -dirty.
Exceptions:
1: no tags. 0.post.devDISTANCE
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"]:
rendered += ".post.dev%d" % pieces["distance"]
else:
# exception #1
rendered = "0.post.dev%d" % pieces["distance"]
return rendered
def render_pep440_post(pieces):
"""TAG[.postDISTANCE[.dev0]+gHEX] .
The ".dev0" means dirty. Note that .dev0 sorts backwards
(a dirty tree will appear "older" than the corresponding clean one),
but you shouldn't be releasing software with -dirty anyways.
Exceptions:
1: no tags. 0.postDISTANCE[.dev0]
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"] or pieces["dirty"]:
rendered += ".post%d" % pieces["distance"]
if pieces["dirty"]:
rendered += ".dev0"
rendered += plus_or_dot(pieces)
rendered += "g%s" % pieces["short"]
else:
# exception #1
rendered = "0.post%d" % pieces["distance"]
if pieces["dirty"]:
rendered += ".dev0"
rendered += "+g%s" % pieces["short"]
return rendered
def render_pep440_old(pieces):
"""TAG[.postDISTANCE[.dev0]] .
The ".dev0" means dirty.
Eexceptions:
1: no tags. 0.postDISTANCE[.dev0]
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"] or pieces["dirty"]:
rendered += ".post%d" % pieces["distance"]
if pieces["dirty"]:
rendered += ".dev0"
else:
# exception #1
rendered = "0.post%d" % pieces["distance"]
if pieces["dirty"]:
rendered += ".dev0"
return rendered
def render_git_describe(pieces):
"""TAG[-DISTANCE-gHEX][-dirty].
Like 'git describe --tags --dirty --always'.
Exceptions:
1: no tags. HEX[-dirty] (note: no 'g' prefix)
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"]:
rendered += "-%d-g%s" % (pieces["distance"], pieces["short"])
else:
# exception #1
rendered = pieces["short"]
if pieces["dirty"]:
rendered += "-dirty"
return rendered
def render_git_describe_long(pieces):
"""TAG-DISTANCE-gHEX[-dirty].
Like 'git describe --tags --dirty --always -long'.
The distance/hash is unconditional.
Exceptions:
1: no tags. HEX[-dirty] (note: no 'g' prefix)
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
rendered += "-%d-g%s" % (pieces["distance"], pieces["short"])
else:
# exception #1
rendered = pieces["short"]
if pieces["dirty"]:
rendered += "-dirty"
return rendered
def render(pieces, style):
"""Render the given version pieces into the requested style."""
if pieces["error"]:
return {"version": "unknown",
"full-revisionid": pieces.get("long"),
"dirty": None,
"error": pieces["error"],
"date": None}
if not style or style == "default":
style = "pep440" # the default
if style == "pep440":
rendered = render_pep440(pieces)
elif style == "pep440-pre":
rendered = render_pep440_pre(pieces)
elif style == "pep440-post":
rendered = render_pep440_post(pieces)
elif style == "pep440-old":
rendered = render_pep440_old(pieces)
elif style == "git-describe":
rendered = render_git_describe(pieces)
elif style == "git-describe-long":
rendered = render_git_describe_long(pieces)
else:
raise ValueError("unknown style '%s'" % style)
return {"version": rendered, "full-revisionid": pieces["long"],
"dirty": pieces["dirty"], "error": None,
"date": pieces.get("date")}
class VersioneerBadRootError(Exception):
"""The project root directory is unknown or missing key files."""
def get_versions(verbose=False):
"""Get the project version from whatever source is available.
Returns dict with two keys: 'version' and 'full'.
"""
if "versioneer" in sys.modules:
# see the discussion in cmdclass.py:get_cmdclass()
del sys.modules["versioneer"]
root = get_root()
cfg = get_config_from_root(root)
assert cfg.VCS is not None, "please set [versioneer]VCS= in setup.cfg"
handlers = HANDLERS.get(cfg.VCS)
assert handlers, "unrecognized VCS '%s'" % cfg.VCS
verbose = verbose or cfg.verbose
assert cfg.versionfile_source is not None, \
"please set versioneer.versionfile_source"
assert cfg.tag_prefix is not None, "please set versioneer.tag_prefix"
versionfile_abs = os.path.join(root, cfg.versionfile_source)
# extract version from first of: _version.py, VCS command (e.g. 'git
# describe'), parentdir. This is meant to work for developers using a
# source checkout, for users of a tarball created by 'setup.py sdist',
# and for users of a tarball/zipball created by 'git archive' or github's
# download-from-tag feature or the equivalent in other VCSes.
get_keywords_f = handlers.get("get_keywords")
from_keywords_f = handlers.get("keywords")
if get_keywords_f and from_keywords_f:
try:
keywords = get_keywords_f(versionfile_abs)
ver = from_keywords_f(keywords, cfg.tag_prefix, verbose)
if verbose:
print("got version from expanded keyword %s" % ver)
return ver
except NotThisMethod:
pass
try:
ver = versions_from_file(versionfile_abs)
if verbose:
print("got version from file %s %s" % (versionfile_abs, ver))
return ver
except NotThisMethod:
pass
from_vcs_f = handlers.get("pieces_from_vcs")
if from_vcs_f:
try:
pieces = from_vcs_f(cfg.tag_prefix, root, verbose)
ver = render(pieces, cfg.style)
if verbose:
print("got version from VCS %s" % ver)
return ver
except NotThisMethod:
pass
try:
if cfg.parentdir_prefix:
ver = versions_from_parentdir(cfg.parentdir_prefix, root, verbose)
if verbose:
print("got version from parentdir %s" % ver)
return ver
except NotThisMethod:
pass
if verbose:
print("unable to compute version")
return {"version": "0+unknown", "full-revisionid": None,
"dirty": None, "error": "unable to compute version",
"date": None}
def get_version():
"""Get the short version string for this project."""
return get_versions()["version"]
def get_cmdclass():
"""Get the custom setuptools/distutils subclasses used by Versioneer."""
if "versioneer" in sys.modules:
del sys.modules["versioneer"]
# this fixes the "python setup.py develop" case (also 'install' and
# 'easy_install .'), in which subdependencies of the main project are
# built (using setup.py bdist_egg) in the same python process. Assume
# a main project A and a dependency B, which use different versions
# of Versioneer. A's setup.py imports A's Versioneer, leaving it in
# sys.modules by the time B's setup.py is executed, causing B to run
# with the wrong versioneer. Setuptools wraps the sub-dep builds in a
# sandbox that restores sys.modules to it's pre-build state, so the
# parent is protected against the child's "import versioneer". By
# removing ourselves from sys.modules here, before the child build
# happens, we protect the child from the parent's versioneer too.
# Also see https://github.com/warner/python-versioneer/issues/52
cmds = {}
# we add "version" to both distutils and setuptools
from distutils.core import Command
class cmd_version(Command):
description = "report generated version string"
user_options = []
boolean_options = []
def initialize_options(self):
pass
def finalize_options(self):
pass
def run(self):
vers = get_versions(verbose=True)
print("Version: %s" % vers["version"])
print(" full-revisionid: %s" % vers.get("full-revisionid"))
print(" dirty: %s" % vers.get("dirty"))
print(" date: %s" % vers.get("date"))
if vers["error"]:
print(" error: %s" % vers["error"])
cmds["version"] = cmd_version
# we override "build_py" in both distutils and setuptools
#
# most invocation pathways end up running build_py:
# distutils/build -> build_py
# distutils/install -> distutils/build ->..
# setuptools/bdist_wheel -> distutils/install ->..
# setuptools/bdist_egg -> distutils/install_lib -> build_py
# setuptools/install -> bdist_egg ->..
# setuptools/develop -> ?
# pip install:
# copies source tree to a tempdir before running egg_info/etc
# if .git isn't copied too, 'git describe' will fail
# then does setup.py bdist_wheel, or sometimes setup.py install
# setup.py egg_info -> ?
# we override different "build_py" commands for both environments
if "setuptools" in sys.modules:
from setuptools.command.build_py import build_py as _build_py
else:
from distutils.command.build_py import build_py as _build_py
class cmd_build_py(_build_py):
def run(self):
root = get_root()
cfg = get_config_from_root(root)
versions = get_versions()
_build_py.run(self)
# now locate _version.py in the new build/ directory and replace
# it with an updated value
if cfg.versionfile_build:
target_versionfile = os.path.join(self.build_lib,
cfg.versionfile_build)
print("UPDATING %s" % target_versionfile)
write_to_version_file(target_versionfile, versions)
cmds["build_py"] = cmd_build_py
if "cx_Freeze" in sys.modules: # cx_freeze enabled?
from cx_Freeze.dist import build_exe as _build_exe
# nczeczulin reports that py2exe won't like the pep440-style string
# as FILEVERSION, but it can be used for PRODUCTVERSION, e.g.
# setup(console=[{
# "version": versioneer.get_version().split("+", 1)[0], # FILEVERSION
# "product_version": versioneer.get_version(),
# ...
class cmd_build_exe(_build_exe):
def run(self):
root = get_root()
cfg = get_config_from_root(root)
versions = get_versions()
target_versionfile = cfg.versionfile_source
print("UPDATING %s" % target_versionfile)
write_to_version_file(target_versionfile, versions)
_build_exe.run(self)
os.unlink(target_versionfile)
with open(cfg.versionfile_source, "w") as f:
LONG = LONG_VERSION_PY[cfg.VCS]
f.write(LONG %
{"DOLLAR": "$",
"STYLE": cfg.style,
"TAG_PREFIX": cfg.tag_prefix,
"PARENTDIR_PREFIX": cfg.parentdir_prefix,
"VERSIONFILE_SOURCE": cfg.versionfile_source,
})
cmds["build_exe"] = cmd_build_exe
del cmds["build_py"]
if 'py2exe' in sys.modules: # py2exe enabled?
try:
from py2exe.distutils_buildexe import py2exe as _py2exe # py3
except ImportError:
from py2exe.build_exe import py2exe as _py2exe # py2
class cmd_py2exe(_py2exe):
def run(self):
root = get_root()
cfg = get_config_from_root(root)
versions = get_versions()
target_versionfile = cfg.versionfile_source
print("UPDATING %s" % target_versionfile)
write_to_version_file(target_versionfile, versions)
_py2exe.run(self)
os.unlink(target_versionfile)
with open(cfg.versionfile_source, "w") as f:
LONG = LONG_VERSION_PY[cfg.VCS]
f.write(LONG %
{"DOLLAR": "$",
"STYLE": cfg.style,
"TAG_PREFIX": cfg.tag_prefix,
"PARENTDIR_PREFIX": cfg.parentdir_prefix,
"VERSIONFILE_SOURCE": cfg.versionfile_source,
})
cmds["py2exe"] = cmd_py2exe
# we override different "sdist" commands for both environments
if "setuptools" in sys.modules:
from setuptools.command.sdist import sdist as _sdist
else:
from distutils.command.sdist import sdist as _sdist
class cmd_sdist(_sdist):
def run(self):
versions = get_versions()
self._versioneer_generated_versions = versions
# unless we update this, the command will keep using the old
# version
self.distribution.metadata.version = versions["version"]
return _sdist.run(self)
def make_release_tree(self, base_dir, files):
root = get_root()
cfg = get_config_from_root(root)
_sdist.make_release_tree(self, base_dir, files)
# now locate _version.py in the new base_dir directory
# (remembering that it may be a hardlink) and replace it with an
# updated value
target_versionfile = os.path.join(base_dir, cfg.versionfile_source)
print("UPDATING %s" % target_versionfile)
write_to_version_file(target_versionfile,
self._versioneer_generated_versions)
cmds["sdist"] = cmd_sdist
return cmds
CONFIG_ERROR = """
setup.cfg is missing the necessary Versioneer configuration. You need
a section like:
[versioneer]
VCS = git
style = pep440
versionfile_source = src/myproject/_version.py
versionfile_build = myproject/_version.py
tag_prefix =
parentdir_prefix = myproject-
You will also need to edit your setup.py to use the results:
import versioneer
setup(version=versioneer.get_version(),
cmdclass=versioneer.get_cmdclass(), ...)
Please read the docstring in ./versioneer.py for configuration instructions,
edit setup.cfg, and re-run the installer or 'python versioneer.py setup'.
"""
SAMPLE_CONFIG = """
# See the docstring in versioneer.py for instructions. Note that you must
# re-run 'versioneer.py setup' after changing this section, and commit the
# resulting files.
[versioneer]
#VCS = git
#style = pep440
#versionfile_source =
#versionfile_build =
#tag_prefix =
#parentdir_prefix =
"""
INIT_PY_SNIPPET = """
from ._version import get_versions
__version__ = get_versions()['version']
del get_versions
"""
def do_setup():
"""Main VCS-independent setup function for installing Versioneer."""
root = get_root()
try:
cfg = get_config_from_root(root)
except (EnvironmentError, configparser.NoSectionError,
configparser.NoOptionError) as e:
if isinstance(e, (EnvironmentError, configparser.NoSectionError)):
print("Adding sample versioneer config to setup.cfg",
file=sys.stderr)
with open(os.path.join(root, "setup.cfg"), "a") as f:
f.write(SAMPLE_CONFIG)
print(CONFIG_ERROR, file=sys.stderr)
return 1
print(" creating %s" % cfg.versionfile_source)
with open(cfg.versionfile_source, "w") as f:
LONG = LONG_VERSION_PY[cfg.VCS]
f.write(LONG % {"DOLLAR": "$",
"STYLE": cfg.style,
"TAG_PREFIX": cfg.tag_prefix,
"PARENTDIR_PREFIX": cfg.parentdir_prefix,
"VERSIONFILE_SOURCE": cfg.versionfile_source,
})
ipy = os.path.join(os.path.dirname(cfg.versionfile_source),
"__init__.py")
if os.path.exists(ipy):
try:
with open(ipy, "r") as f:
old = f.read()
except EnvironmentError:
old = ""
if INIT_PY_SNIPPET not in old:
print(" appending to %s" % ipy)
with open(ipy, "a") as f:
f.write(INIT_PY_SNIPPET)
else:
print(" %s unmodified" % ipy)
else:
print(" %s doesn't exist, ok" % ipy)
ipy = None
# Make sure both the top-level "versioneer.py" and versionfile_source
# (PKG/_version.py, used by runtime code) are in MANIFEST.in, so
# they'll be copied into source distributions. Pip won't be able to
# install the package without this.
manifest_in = os.path.join(root, "MANIFEST.in")
simple_includes = set()
try:
with open(manifest_in, "r") as f:
for line in f:
if line.startswith("include "):
for include in line.split()[1:]:
simple_includes.add(include)
except EnvironmentError:
pass
# That doesn't cover everything MANIFEST.in can do
# (http://docs.python.org/2/distutils/sourcedist.html#commands), so
# it might give some false negatives. Appending redundant 'include'
# lines is safe, though.
if "versioneer.py" not in simple_includes:
print(" appending 'versioneer.py' to MANIFEST.in")
with open(manifest_in, "a") as f:
f.write("include versioneer.py\n")
else:
print(" 'versioneer.py' already in MANIFEST.in")
if cfg.versionfile_source not in simple_includes:
print(" appending versionfile_source ('%s') to MANIFEST.in" %
cfg.versionfile_source)
with open(manifest_in, "a") as f:
f.write("include %s\n" % cfg.versionfile_source)
else:
print(" versionfile_source already in MANIFEST.in")
# Make VCS-specific changes. For git, this means creating/changing
# .gitattributes to mark _version.py for export-subst keyword
# substitution.
do_vcs_install(manifest_in, cfg.versionfile_source, ipy)
return 0
def scan_setup_py():
"""Validate the contents of setup.py against Versioneer's expectations."""
found = set()
setters = False
errors = 0
with open("setup.py", "r") as f:
for line in f.readlines():
if "import versioneer" in line:
found.add("import")
if "versioneer.get_cmdclass()" in line:
found.add("cmdclass")
if "versioneer.get_version()" in line:
found.add("get_version")
if "versioneer.VCS" in line:
setters = True
if "versioneer.versionfile_source" in line:
setters = True
if len(found) != 3:
print("")
print("Your setup.py appears to be missing some important items")
print("(but I might be wrong). Please make sure it has something")
print("roughly like the following:")
print("")
print(" import versioneer")
print(" setup( version=versioneer.get_version(),")
print(" cmdclass=versioneer.get_cmdclass(), ...)")
print("")
errors += 1
if setters:
print("You should remove lines like 'versioneer.VCS = ' and")
print("'versioneer.versionfile_source = ' . This configuration")
print("now lives in setup.cfg, and should be removed from setup.py")
print("")
errors += 1
return errors
if __name__ == "__main__":
cmd = sys.argv[1]
if cmd == "setup":
errors = do_setup()
errors += scan_setup_py()
if errors:
sys.exit(1)
| Python |
3D | Autodesk/molecular-design-toolkit | nb-output-filter.sh | .sh | 137 | 6 | #!/bin/bash
git config filter.notebooks.clean moldesign/_notebooks/nbscripts/strip_nb_output.py
git config filter.notebooks.smudge cat
| Shell |
3D | Autodesk/molecular-design-toolkit | DEVELOPMENT.md | .md | 6,110 | 113 | # DEVELOPING MDT
### Setting up a dev environment
(still under construction)
### Install prequisites (first time only)
You need to install docker, and an environment manager for Python 3 (Miniconda 3). Here's one way to do that:
1. Install docker: [link]
2. Install pyenv and pyenv-venv: [link]
3. Install miniconda3 by running: `pyenv install miniconda3-latest`
4. Switch to miniconda environment by running: `pyenv shell miniconda3-latest`
### Set up your environment (first time only)
1. Get MDT: `git clone http://github.com/Autodesk/molecular-design-toolkit`
1. `cd molecular-design-toolkit`
1. Create conda environment (optional but recommended) by running: [command to create conda env]
2. Activate the environment: `pyenv activate [environment name???]`
1. Install dev dependencies: `pip install -r requirements.txt DockerMakefiles/requirements.txt deployment/requirements.txt`
2. Set up for local dev mode (this tells MDT to use your local docker containers):
```bash
mkdir ~/.moldesign
echo "devmode: true" > ~/.moldesign/moldesign.yml
```
8. Install MDT in "development mode":
```
pip install -e molecular-design-toolkit
```
### To activate environment (in any new shell)
1. Run `pyenv activate [environment name???]`
### To rebuild docker images (first time and after changes that affect dockerized code)
5. Build development versions of all docker images:
```bash
cd DockerMakefiles
docker-make --all --tag dev
```
### To run tests
```bash
cd molecular-design-toolkit/moldesign/_tests
py.test -n [number of concurrent tests]
```
See [the testing README](moldesign/_tests/README.md) for more details.
### Code style
1. Functions and variables should be `lowercase_with_underscores`. Class names and constructors should be `CapitalizedCamelCase`.
1. The user-exposed API should be clean, [PEP 8](https://www.python.org/dev/peps/pep-0008/) code.
1. Internally, readability and functionality are more important than consistency - that said, [Google's style guide](https://google.github.io/styleguide/pyguide.html), along with [PEP 8](https://www.python.org/dev/peps/pep-0008/), is strongly encouraged.
# Contributing
### Who should contribute?
Anyone with a molecular modeling workflow that they want to enable or share. Experience and research-level knowledge of the field is an important asset! In contrast, limited programming experience *is definitely not* barrier to contributing - we can help you with that! Please ask for help getting started in our forums [link].
### Scope: What goes into MDT?
Established techniques and general simulation tools that will be useful for **3-dimensional biomolecular modeling**. MDT aims to enable scientists to easily build new simulation techniques and workflows, but new, immature techniques, or those with limited applicability outside of a particular system should be implemented as separate projects that *use* MDT, not *part of* MDT.
###### Could (and should!) be implemented in MDT:
* Physical simulation and modelilng: Lambda dynamics; homology modelling; surface hopping; RPMD; metadynamics; markov state models; a library of common 3D structures (such as amino acids, carbon nanotubes, small molecules, etc.)
* Visualization and UI: transitions between different views; interactive structure building and editing; ray-traced rendering; movie exports
###### Should implemented as a separate project:
* Computational techniques: fluid dynamics solver (not useful at the atomic level), biological network models (no clear connection to 3D structures); machine-learning based quantum chemistry (immature, untested)
* Visualization and UI: visualizations for specific systems (not generally applicable);
# Development guidelines
### Whenever commiting changes anywhere
Make SURE that you've run `nb-output-filter.sh` at the project base. You only need to do this once (per copy of the repository). This will make sure that you don't accidentally commit any `ipynb` output fields into the repository. You can check to make sure the filters are working by running `git diff` on any notebook file that has output in it: all `output` and `metadata` fields should remain blank.
### Maintainers: Accepting a PR
Work can be merged into `master` or a feature branch, as appropriate. Don't merge broken code
into master, but it doesn't need to be totally production-ready either: only releases (below)
are considered "stable".
1. Review the code.
1. Make sure that there's appropriate functional tests.
1. Check that the travis build is at least running all the way to the end. The tests don't *necessarily* need to pass, but you need to undertand why what's passing and what's not.
### Releases
1. Decide on the new version number (see below). For our purposes here, we'll pretend it's `0.9.3`.
1. Tag the relevant commit (the build must be passing) with a release candidate version number, e.g., `0.9.3rc1`.
1. Codeship will automatically deploy the updated release to PyPI and DockerHub
1. Manually test the example notebooks against this pre-release version.
1. If succesful, tag the relevant commit with the official release version `0.9.3`
### Versioning
For now, we're using a subset [PEP 440](https://www.python.org/dev/peps/pep-0440/):
1. Every release should be of the form MAJOR.MINOR.PATCH, e.g. `0.1.2`
2. Pre-releases should be numbered consecutively, and may be alpha, beta, or "release candidate", e.g. `1.0.1rc3` or `0.5.3a1`
3. Our deployment infrastructure uses this regular expression to accept version strings:
`^(0|[1-9]\d*)\.(0|[1-9]\d*)\.(0|[1-9]\d*)((a|rc|b)(0|[1-9]\d*))?$`
### Maintainers: updating the documentation
Documentation is NOT coupled to the package releases; docs tend to get updated continuously.
1. In the `master` branch, update the version numbers in `docs/conf.py`
1. Run `cd docs; make clean; make html`.
1. In a separate directory, check out a fresh copy of the repo and run `git checkout gh-pages`
1. Copy the contents of `[master branch]/docs/_build/html` into the root of the `gh-pages` branch.
1. Commit your changes to the `gh-pages` branch and push them back to GitHub.
| Markdown |
3D | Autodesk/molecular-design-toolkit | CONTRIBUTING.md | .md | 6,484 | 119 | # Contributing to Molecular Design Toolkit
<!-- START doctoc generated TOC please keep comment here to allow auto update -->
<!-- DON'T EDIT THIS SECTION, INSTEAD RE-RUN doctoc TO UPDATE -->
**Table of Contents** *generated with [DocToc](https://github.com/thlorenz/doctoc)*
- [Contributing to Molecular Design Toolkit](#contributing-to-molecular-design-toolkit)
- [Tips and guidelines](#tips-and-guidelines)
- [What can I contribute?](#what-can-i-contribute)
- [Pull requests are always welcome](#pull-requests-are-always-welcome)
- [Design and cleanup proposals](#design-and-cleanup-proposals)
- [Submission Guidelines](#submission-guidelines)
- [Project Roles](#project-roles)
- [Timing](#timing)
- [Issues](#issues)
- [Pull Requests](#pull-requests)
<!-- END doctoc generated TOC please keep comment here to allow auto update -->
<!-- to generate: npm install doctoc: doctoc --gitlab --maxlevel 3 CONTRIBUTING.md-->
## Tips and guidelines
### What can I contribute?
Contributions to this project are encouraged! Email the maintainers at `moldesign_maintainers@autodesk.com` to become a contributor.
If you're interested in getting started, here are some general contributions that are always welcome. We also maintain a [wishlist of specific ideas on the wiki](https://github.com/Autodesk/molecular-design-toolkit/wiki/Contribution-ideas).
**Tests**: This is one of the easiest ways to get started - see also `moldesign/tests/README.md`
* **Contribute unit tests** - test that MDT's functions work correctly in a variety of situations, and that they report errors when appropriate
* **Validate methods** - methods need to be tested against known results for accuracy; for instance, we need to check that a Hartree-Fock calculation gives the same results as Gaussian, GAMESS, and MolDesign
**Examples**: See also `moldesign/notebooks`
* **Best practices** - put together template notebooks that will help users get started with a particular workflow, from modeling proteins from crystal structures to exploring electronic structure
* **Interesting use cases** - Contribute a notebook that shows off a cool bit of science or design.
**Bug fixes:** Found a typo in the code? Found that a function fails under certain conditions? Know how to fix it? Great! Go for it. Please do [open an issue](https://github.com/autodesk/molecular-design-toolkit/issues) so that we know you're working on it, and submit a pull request when you're ready.
**Features:** The chemical modeling universe is vast, and we want toolkit users to have access to a lot of it. Whether you want free energy perturbation, or Boyes' localization, or 3D structural alignment - we want it too! As always, please [open an issue](https://github.com/autodesk/molecular-design-toolkit/issues) so that we know what you're working on.
**Whatever:** There's ALWAYS something to do, whether supporting other languages (e.g., Spanish or Bahasa Indonesia, not Fortran or C++); improving 3D viewer performance; improving documentation; adding Python 3.X support; or integrating with other IDE technologies.
### Pull requests are always welcome
All PRs should be documented as [GitHub issues](https://github.com/autodesk/molecular-design-toolkit/issues), ideally BEFORE you start working on them.
### Design and cleanup proposals
Good API design is at the heart of this project, and you don't need to do any programming to help with this! For example:
* You could describe how a user will run a Hamiltonian replica exchange calculation (should it be a class or a function? What are the method names? How does the user specify the temperatures?).
* You can also propose redesigns for existing features - maybe you think `mdt.add_hydrogens(mol)` should be renamed to `mol.add_hydrogens()`, or you want to propose a better way to access trajectory data.
To get started, as always: [open an issue](https://github.com/autodesk/molecular-design-toolkit/issues). For information on making these types of
contributions, see [the development guide](DEVELOPMENT.md).
## Submission Guidelines
### Maintainers
Maintainers are responsible for responding to pull requests and issues, as well as guiding the direction of the project.
Aaron Virshup - Lead developer and maintainer<br>
Dion Amago - Maintainer<br>
Malte Tinnus - Maintainer
If you've established yourself as an impactful contributor for the project, and are willing take on the extra work, we'd love to have your help maintaining it! Email the maintainers list at `moldesign_maintainers@autodesk.com` for details.
### Timing
We will attempt to address all issues and pull requests within one week. It may a bit longer before pull requests are actually merged, as they must be inspected and tested.
### Issues
If MDT isn't working like you expect, please open a new issue! We appreciate any effort you can make to avoid reporting duplicate issues, but please err on the side of reporting the bug if you're not sure.
Providing the following information will increase the chances of your issue being dealt with quickly:
* **Overview of the Issue** - Please describe the issue, and include any relevant exception messages or screenshots.
* **Environment** - Include the relevant output of `pip freeze` as well as your system and python version info.
* **Help us reproduce the issue** - Please include code that will help us reproduce the issue. For complex situations, attach a notebook file.
* **Related Issues** - Please link to other issues in this project (or even other projects) that appear to be related
### Pull Requests
Before you submit your pull request consider the following guidelines:
* Search GitHub for an open or closed Pull Request that relates to your submission. You don't want to duplicate effort.
* Make your changes in a new git branch:
```shell
git checkout -b my-fix-branch [working-branch-name]
```
* Create your patch.
* Commit your changes using a descriptive commit message.
```shell
git commit -a
```
Note: the optional commit `-a` command line option will automatically "add" and "rm" edited files.
* Push your branch to GitHub:
```shell
git push origin my-fix-branch
```
* In GitHub, send a pull request to `molecular-design-toolkit:dev`
* Before any request is merged, you'll need to agree to the contribution boilerplate. Email us at `moldesign_maintainers@autodesk.com` for details.
| Markdown |
3D | Autodesk/molecular-design-toolkit | DockerMakefiles/buildfiles/notebook/run_notebook.sh | .sh | 84 | 4 | #!/bin/bash
jupyter notebook --ip=0.0.0.0 --no-browser --port=8888 --allow-root $@
| Shell |
3D | Autodesk/molecular-design-toolkit | DockerMakefiles/buildfiles/ambertools/runsander.py | .py | 7,026 | 255 | #!/usr/bin/env python
"""
This script drives an NWChem calculation given a generic QM specification
"""
import json
import os
import pint
ureg = pint.UnitRegistry()
ureg.define('bohr = a0 = hbar/(m_e * c * fine_structure_constant')
"""
&cntrl
ntb=1, ! use PBC
imin=1, ! run minimization
ntmin=5 ! run steepest descent
maxcyc=10, ! minimize for 10 steps
ncyc=0, ! no switch to congugate gradient
cut=8.0, ! MM cutoff
ntc=2, ntf=2, ! SHAKE
ioutfmt=1 ! netcdf output
/
"""
FILENAME_DEFAULTS = {x+"_file":x for x in "inpcrd mdcrd prmtop mdvel".split()}
def run_calculation(parameters):
""" Drive the calculation, based on passed parameters
Args:
parameters (dict): dictionary describing this run (see
https://github.com/Autodesk/molecular-design-toolkit/wiki/Generic-parameter-names )
"""
for key, val in FILENAME_DEFAULTS:
parameters.setdefault(key, val)
if parameters.get('num_processors', 1) > 1:
cmd = 'mpirun -n %d sander.MPI' % parameters['num_processors']
else:
cmd = ('sander -i {inpcrd_file} -o {mdcrd_file} -p {prmtop_file} '
'-v {mdvel_file} ').format(**parameters)
os.system(cmd)
def write_inputs(parameters):
""" Write input files using passed parameters
Args:
parameters (dict): dictionary describing this run (see
https://github.com/Autodesk/molecular-design-toolkit/wiki/Generic-parameter-names )
"""
# check that coordinates were passed
assert os.path.isfile('input.xyz'), 'Expecting input coordinates at input.xyz'
os.mkdir('./perm')
inputs = _make_input_files(parameters)
for filename, contents in inputs.iteritems():
with open(filename, 'w') as inputfile:
inputfile.write(contents)
def convert(q, units):
"""
Convert a javascript quantity description into a floating point number in the desired units
Args:
q (dict): Quantity to convert (of form ``{value: <float>, units: <str>}`` )
units (str): name of the units
Returns:
float: value of the quantity in the passed unit system
Raises:
pint.DimensionalityError: If the units are incompatible with the desired quantity
Examples:
>>> q = {'value':1.0, 'units':'nm'}
>>> convert(q, 'angstrom')
10.0
"""
quantity = q['value'] * ureg(q['units'])
return quantity.value_in(units)
##### helper routines below ######
def _make_input_files(calc):
nwin = [_header(calc),
_geom_block(calc),
_basisblock(calc),
_chargeblock(calc),
_theoryblock(calc),
_otherblocks(calc),
_taskblock(calc)]
return {'nw.in': '\n'.join(nwin)}
def _header(calc):
return '\nstart mol\n\npermanent_dir ./perm\n'
def _geom_block(calc):
lines = ['geometry units angstrom noautoz noautosym nocenter',
' load format xyz input.xyz',
'end']
return '\n'.join(lines)
def _basisblock(calc):
return 'basis\n * library %s\nend' % calc['basis'] # TODO: translate names
def _theoryblock(calc):
lines = [_taskname(calc),
_multiplicityline(calc),
_theorylines(calc),
'end'
]
return '\n'.join(lines)
def _otherblocks(calc):
lines = []
if calc['runType'] == 'minimization':
lines.append('driver\n xyz opt\n print high\n')
if 'minimization_steps' in calc:
lines.append('maxiter %d' % calc['minimization_steps'])
lines.append('end')
return '\n'.join(lines)
TASKNAMES = {'rhf': 'scf',
'uhf': 'scf',
'rks': 'dft',
'uks': 'dft'}
def _taskname(calc):
return TASKNAMES[calc['theory']]
SCFNAMES = {'rhf': 'rhf',
'uhf': 'uhf',
'rks': 'rhf',
'uks': 'uhf'}
def _scfname(calc):
return SCFNAMES[calc['theory']]
def _taskblock(calc):
if calc['runType'] == 'minimization':
tasktype = 'optimize'
elif 'forces' in calc['properties']:
tasktype = 'gradient'
else:
tasktype = 'energy'
return 'task %s %s' % (_taskname(calc), tasktype)
STATENAMES = {1: "SINGLET",
2: "DOUBLET",
3: "TRIPLET",
4: "QUARTET",
5: "QUINTET",
6: "SEXTET",
7: "SEPTET",
8: "OCTET"}
def _multiplicityline(calc):
if calc['theory'] in ('rks', 'uks'):
return 'mult %s' % calc.get('multiplicity', 1)
else:
return STATENAMES[calc.get('multiplicity', 1)]
def _constraintblock(calc):
"""
Constraints / restraints are specified in JSON objects at calc.constraints and calc.restraints.
"Constraints" describe a specific degree of freedom and its value. This value is expected to be
rigorously conserved by any dynamics or optimization algorithms.
A "restraint", in constrast, is a harmonic restoring force applied to a degree of freedom.
Restraint forces should be added to the nuclear hamiltonian. A restraint's "value" is the
spring's equilibrium position.
The list at calc['constraints'] has the form:
[{type: <str>,
restraint: <bool>,
value: {value: <float>, units: <str>}
atomIdx0: <int>...} ...]
For example, fixes atom constraints have the form:
{type: 'atomPosition',
restraint: False,
atomIdx: <int>}
Restraints are described similary, but include a spring constant (of the appropriate units):
{type: 'bond',
restraint: True,
atomIdx1: <int>,
atomIdx2: <int>,
springConstant: {value: <float>, units: <str>},
value: {value: <float>, units: <str>}}
"""
clist = calc.get('constraints', None)
if clist is None: return
lines = ['constraints']
for constraint in clist:
if constraint['type'] == 'position':
lines.append(' fix atom %d' % constraint['atomIdx'])
elif constraint['type'] == 'distance' and constraint['restraint']:
k = convert(constraint['springConstant'], 'hartree/(a0*a0)')
d0 = convert(constraint('value', 'a0'))
lines.append(' spring bond %d %d %20.10f %20.10f' %
(constraint['atomIdx1']+1, constraint['atomIdx2']+1, k, d0))
else:
raise NotImplementedError('Constraint type %s (as restraint: %b) not implemented' %
(constraint['type'], constraint['restraint']))
lines.append('end')
return '\n'.join(lines)
def _chargeblock(calc):
return '\ncharge %s\n' % calc.get('charge', 0)
def _theorylines(calc):
lines = ['direct']
if _taskname(calc) == 'dft':
lines.append('XC %s' % calc['functional'])
return '\n'.join(lines)
if __name__ == '__main__':
with open('params.json','r') as pjson:
parameters = json.load(pjson)
write_inputs(parameters)
run_calculation(parameters)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/parameters.py | .py | 9,802 | 238 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
This module stores definitions of common parameters for common techniques.
These are used to standardize our interfaces to other codes, and automatically generate interactive
notebook interfaces to configure various techniques.
"""
import operator as op
import copy
from . import units as u
from . import utils
from .utils import named_dict
def isin(a, b): return a in b
class WhenParam(object):
def __init__(self, parameter, operator, checkval):
self.operator = operator
self.parameter = parameter
self.checkval = checkval
def __call__(self, paramset):
"""
Args:
paramset (dict):
Returns:
bool: True if the parameter is releveant, false otherwise
"""
#TODO: anything relevant to an irrelevant parameter is also irrelevant
return self.operator(paramset[self.parameter], self.checkval)
class Parameter(object):
""" A generic parameter for a computational method
Args:
name (str): the arguments name (this is also its key in the method's ``params`` dictionary)
short_description (str): A more readable description of about 100 characters
type: The type of the param, including units if applicable.
This may be a type (``int``, ``str``, etc.); if the quantity has physical units, you may
also pass an example of this quantity (e.g., ``1.0 * units.angstrom``)
default: the default value, or None if the user is required to set this parameter manually
choices (list): A list of allowable values for the parameter
help_url (str): URL for detailed help (not currently implemented)
relevance (WhenParam): specifies when a given parameter will affect the dynamics
Examples:
>>> Parameter('timestep', 'Dynamics timestep', type=1.0*u.fs, default=2.0*u.fs)
<Parameter "timestep", type: float, units: fs>
>>> Parameter('functional', 'DFT XC functional', choices=['b3lyp', 'pbe0'],
>>> relevance=WhenParam('theory', op.eq, 'rks'))
<Parameter "functional", type: str>
"""
def __init__(self, name,
short_description=None,
type=None,
default=None,
choices=None,
help_url=None,
relevance=None,
help=None):
self.name = name
self.displayname = utils.if_not_none(short_description, name)
self.value = None
self.default = default
self.choices = utils.if_not_none(choices, [])
self.type = type
self.help_url = help_url
self.help = help
if isinstance(type, u.MdtQuantity):
type = type.units
if isinstance(type, u.MdtUnit):
self.type = float
self.units = type
else:
self.units = None
self.relevance = relevance
def __str__(self):
s = '%s "%s", type: %s' % (type(self).__name__, self.name, self.type.__name__)
if self.units is not None:
s += ', units: %s' % self.units
return s
def __repr__(self):
try:
return '<%s>' % self
except (KeyError, AttributeError):
return '<%s at %x - exception in __repr__>' % (type(self), id(self))
def copy(self):
""" Make a copy of this parameter (usually to modify it for a given method)
Returns:
Parameter: a copy of this parameter type
"""
return copy.deepcopy(self)
mm_model_parameters = named_dict([
Parameter('cutoff', 'Cutoff for nonbonded interactions',
default=1.0 * u.nm, type=u.nm,
relevance=WhenParam('nonbonded', op.ne, 'nocutoff')),
Parameter('nonbonded', 'Nonbonded interaction method', default='cutoff', type=str,
choices=['cutoff', 'pme', 'ewald', 'nocutoff']),
Parameter('implicit_solvent',
'Implicit solvent method',
type=str,
choices=['gbsa', 'obc', 'pbsa', None]),
Parameter('solute_dielectric', 'Solute dielectric constant',
default=1.0, type=float),
Parameter('solvent_dielectric', 'Solvent dielectric constant',
default=78.5, type=float),
Parameter('ewald_error', 'Ewald error tolerance', default=0.0005, type=float),
Parameter('periodic', 'Periodicity', default=False, choices=[False, 'box'])
])
QMTHEORIES = ['rhf', 'rks', 'mp2', 'casscf', 'casci', 'fci']
BASISSETS = ['3-21g', '4-31g', '6-31g', '6-31g*', '6-31g**',
'6-311g', '6-311g*', '6-311g+', '6-311g*+',
'sto-3g', 'sto-6g', 'minao', 'weigend',
'dz' 'dzp', 'dtz', 'dqz',
'aug-cc-pvdz', 'aug-cc-pvtz', 'aug-cc-pvqz']
FUNCTIONALS = ['b3lyp', 'blyp', 'pbe0', 'x3lyp', 'mpw3lyp5']
# This is a VERY limited set to start with; all hybrid functionals for now
# Need to think more about interface and what to offer by default
# PySCF xcs are at https://github.com/sunqm/pyscf/blob/master/dft/libxc.py for now
qm_model_parameters = named_dict([
Parameter('theory', 'QM theory', choices=QMTHEORIES),
Parameter('functional', 'DFT Functional', default='b3lyp',
choices=FUNCTIONALS, # TODO: allow separate x and c functionals
relevance=WhenParam('theory', isin, 'dft rks ks uks'.split())),
Parameter('active_electrons', 'Active electrons', type=int, default=2,
relevance=WhenParam('theory', isin, ['casscf', 'mcscf', 'casci'])),
Parameter('active_orbitals', 'Active orbitals', type=int, default=2,
relevance=WhenParam('theory', isin, ['casscf', 'mcscf', 'casci'])),
Parameter('state_average', 'States to average for SCF', type=int, default=1,
relevance=WhenParam('theory', isin, ['casscf', 'mcscf'])),
Parameter('basis', 'Basis set', choices=BASISSETS),
Parameter('wfn_guess', 'Starting guess method', default='huckel',
choices=['huckel', 'minao', 'stored']),
Parameter('store_orb_guesses', 'Automatically use orbitals for next initial guess',
default=True, type=bool),
Parameter('multiplicity', 'Spin multiplicity', default=1, type=int),
Parameter('symmetry', 'Symmetry detection',
default=None, choices=[None, 'Auto', 'Loose']),
Parameter('initial_guess', 'Wfn for initial guess',
relevance=WhenParam('wfn_guess', op.eq, 'stored'))
])
integrator_parameters = named_dict([
Parameter('timestep', 'Dynamics timestep', default=1.0*u.fs, type=u.default.time),
Parameter('frame_interval', 'Time between frames', default=1.0*u.ps, type=u.fs)
])
md_parameters = named_dict([
Parameter('remove_translation', 'Remove global translations', default=True,
type=bool),
Parameter('constrain_hbonds', 'Constrain covalent hydrogen bonds',
default=True, type=bool),
Parameter('constrain_water', 'Constrain water geometries',
default=True, type=bool),
Parameter('remove_rotation', 'Remove global rotations', default=False, type=bool),
])
constant_temp_parameters = named_dict([
Parameter('temperature', 'Thermostat temperature', default=298 * u.kelvin,
type=u.default.temperature)])
langevin_parameters = named_dict([
Parameter('collision_rate', 'Thermal collision rate', default=1.0/u.ps, type=1/u.ps)
])
num_cpus = Parameter('num_cpus', 'Number of CPUs (0=unlimited)', default=0, type=int)
ground_state_properties = ['potential_energy',
'forces',
'dipole_moment',
'quadrupole_moment',
'octupole_moment',
'mulliken_charges',
'esp_charges',
'orbitals',
'orbital_energies',
'ci_vector',
'hessian',
'am1_bcc_charges']
"""If you're just calculating these, then just pass the
requested quantities as a list of keywords to the calculate method"""
excited_state_properties = ['state_energies',
'state_forces',
'state_ci_vector']
"""
When requesting these quantities, requests need to be passed to mol.calculate
as a dict with a list of states for each quantity, e.g.
>>> mol.calculate(requests={'state_energies':[1,2],'forces':[1,2]})
to get state_energies and forces for states 1 and 2.
Adiabatic states are indexed starting at 0, so state 0 is
the ground state, 1 is the first excited state, etc.
E.g.. state_energies[0] == potential_energy
"""
multistate_properties = ['transition_dipole',
'nacv',
'oscillator_strength']
"""
When requesting these quantities, requests need to be passed to mol.calculate
as a dict with a list of *pairs* of states for each quantity, e.g.
>>> mol.calculate(requests={'esp_charges':None, 'nacv':[(0,1),(0,2),(1,2)]})
"""
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/HISTORY.md | .md | 6,854 | 116 | ## Changelog
### 0.8.0 - September 9, 2017
MDT 0.8 represents a substantial refinement of the core MDT code, offering Python 2/3 support
and increased stability and robustness.
##### NEW MODELING FEATURES
- Initial **NWChem** integration and pre-compiled docker image ([\#120](https://github.com/autodesk/molecular-design-toolkit/issues/120))
- **ParmEd integration** - assigned forcefield parameters are now stored as ParmEd objects, and
MDT `Molecule` objects can be interconverted with ParmEd `Structures` via
`mdt.interfaces.parmed_to_mdt` and `mdt.interfaces.mdt_to_parmed` ([\#116](https://github.com/autodesk/molecular-design-toolkit/issues/116))
- **Orbital and basis function** descriptions are now mathematically complete, allowing
operations such as gaussian multiplication, overlap calculations, and real-space amplitude
evaluation ([\#167](https://github.com/autodesk/molecular-design-toolkit/issues/167))
- Overhauled **forcefield handling** ([\#149](https://github.com/autodesk/molecular-design-toolkit/issues/149)):
1. `mdt.assign_forcefield` has been replaced with flexible `ForceField` objects, which offer
`Forcefield.assign` and `Forcefield.create_prepped_molecule`
2. Forcefield parameters are stored in ParmEd objects instead of text files
3. atom- and bond-specific terms can be retrieved through the `Atom.ff` and `Bond.ff` attributes
4. Replaced `mdt.parameterize` with `mdt.create_ff_parameters`, which creates a Forcefield
object with parameters for a passed molecule.
- Molecular **alignments** using principal moments of inertia and bond-bond alignment
- Better **constraint handling**, making it easier to add, remove, and clear geometric constraints
- **Drug discovery energy models** - mmff94, mmff94s, and Ghemical - available through the `OpenBabelPotential` model ([\#111](https://github.com/autodesk/molecular-design-toolkit/issues/111))
##### INFRASTRUCTURE CHANGES
- Simultaneous Python 2/3 support ([\#150](https://github.com/autodesk/molecular-design-toolkit/issues/150))
- `moldesign` no longer requires `nbmolviz`, making for a much lighter-weight installation
([\#140](https://github.com/autodesk/molecular-design-toolkit/issues/140))
- Users will be prompted to install the correct version of `nbmolviz` if necessary; that
package now automatically installs itself in more cases
- MDT can be configured to run external packages locally, if you'd prefer not to use docker
- More robust molecular data structures make it harder (albeit still not THAT hard) to create
an inconsistent topological state
- More automation, runtime checks and notebook UI options to make sure sure that
everything is installed correctly
- "CCC" demo server removed. To automatically download and run dependencies like OpenBabel and
NWChem, docker must be installed locally
- Centralized handling of external software interactions via the `moldesign.compute.packages`
module
##### BUGS
Test coverage has gone from <40% in the last release to 88% in the current one;
the test and deploy pipeline is now fully automated; and tests have been added for a variety
of corner cases. All this testing exposed a veritable cornucopia of bugs, a panoply of
off-by-one-errors, typos, race conditions and more. These have all been fixed, leaving the
code on a much more stable footing moving forward.
### 0.7.3 - October 17, 2016
##### NEW MODELING FEATURES
- [\#33](https://github.com/autodesk/molecular-design-toolkit/issues/33) - Add DFT w/ gradients; MP2, CASSCF, CASCI w/out gradients
- Constrained minimizations w/ SHAKE and scipy's SLQSP
- Transition dipoles and oscillator strengths
- GAFF parameterizer for small molecules -- `params = mdt.parameterize(mol)`
- AM1-BCC and Gasteiger partial charge calculators: `mdt.calc_am1_bcc_charges` and
`mdt.calc_gasteiger_charges`
- Add PDB database and biomolecular assembly support for mmCIF files
- [\#72](https://github.com/autodesk/molecular-design-toolkit/issues/72) - Add `moldesign.guess_formal_charges` and `moldesign.add_missing_data`
- Excited and multi-state property calculations with CAS methods
- Rename `build_bdna` to `build_dna_helix` and give access to all NAB helix types
##### OTHER ENHANCEMENTS
- [\#78](https://github.com/autodesk/molecular-design-toolkit/issues/78) - `moldesign` now imports much more quickly
- Add `GAFF` energy model to automate small molecule parameterization
- Change Example 2 to show an absorption spectrum calculation
- Add Example 4 on protein MD with a small ligand
- Add Example 5: on constrained minimization and enthalpic barriers
- Add Tutorial 3: QM data analysis
- Show changelog and version check in the `mdt.about()` (aka `mdt.configure`) widget
- Change moldesign.tools and moldesign.helpers modules into more rationally organized subpackages
- `mdt.set_dihedral` can be called with two atoms in the same way as `mdt.dihedral`
- Explicit parameter created to store wavefunction guesses
- Better access to density matrix in wavefunction objects
- Improved parsing support for PDB and mmCIF files
##### BUGFIXES
- [\#61](https://github.com/autodesk/molecular-design-toolkit/issues/61) - fixed a KeyError when parsing PDBs with metal centers or ions
- [\#74](https://github.com/autodesk/molecular-design-toolkit/issues/74) - Add function to create PDB files with correct TER records (used for TLeap input)
- Better handling of chains with non-standard residues
- `mdt.add_hydrogens` no longer creates structures with separated residues
- Fix sign of dihedral gradient
- Charge quantities now mostly have the correct units
### 0.7.2 - July 26, 2016
##### NEW MODELING FEATURES
- Add trajectory geometry analysis functions (`traj.dihedral`, `traj.angle`, etc.)
- Can now calculate angles, dists, and dihedrals by name within a residue
(`residue.distance('CA','CG')`)
- Calculate dihedral angles using only two atoms defining the central bond (MDT will infer
infer the other two in a consistent way)
##### CHANGES
- Completed tutorials
##### BUGFIXES
- [\#28](https://github.com/autodesk/molecular-design-toolkit/issues/28): Fixed a rounding error and logging problems with OpenMM trajectory snapshots
- [\#21](https://github.com/autodesk/molecular-design-toolkit/issues/21): Better bond orders to structures in Amber files, which don't store them
- [\#20](https://github.com/autodesk/molecular-design-toolkit/issues/20): Store OpenMM force vector correctly
### 0.7.1 - July 20, 2016
##### BUGFIXES
- [\#4](https://github.com/autodesk/molecular-design-toolkit/issues/4): Use public demo CCC server by default
- [\#3](https://github.com/autodesk/molecular-design-toolkit/issues/3): Fix `python -m moldesign intro`
#### 0.7.0 - July 15, 2016
- Initial public release
| Markdown |
3D | Autodesk/molecular-design-toolkit | moldesign/fileio.py | .py | 16,197 | 501 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from past.builtins import basestring
from future.utils import PY2
import bz2
import pickle as pkl # TODO: if cpickle fails, retry with regular pickle to get a better traceback
import io
import functools
import gzip
import os
import moldesign as mdt
from . import utils
from .interfaces import biopython_interface
from .interfaces import openbabel as openbabel_interface
from .interfaces.parmed_interface import write_pdb, write_mmcif
from .helpers import pdb
from .external import pathlib
# imported names
read_amber = mdt.interfaces.openmm.amber_to_mol
from_smiles = mdt.interfaces.openbabel.from_smiles
from_inchi = mdt.interfaces.openbabel.from_inchi
utils.exports_names('from_smiles', 'read_amber', 'from_inchi')
@utils.exports
def read(f, format=None):
"""Read in a molecule from a file, file-like object, or string.
Will also depickle a pickled object.
Note:
Files with ``.bz2`` or ``.gz`` suffixes will be automatically decompressed.
Currently does not support files with more than one record - only returns the first record
Args:
f (str or file-like or pathlib.Path): Either a path to a file, OR a string with the
file's contents, OR a file-like object
format (str): molecule format (pdb, xyz, sdf, etc.) or pickle format
(recognizes p, pkl, or pickle); guessed from filename if not passed
Returns:
moldesign.Molecule or object: molecule parsed from the file (or python object, for
pickle files)
Raises:
ValueError: if ``f`` isn't recognized as a string, file path, or file-like object
"""
filename = None
closehandle = False
streamtype = io.StringIO
readmode = 'r'
if PY2:
f = pathlib._backport_pathlib_fixup(f)
try: # Gets a file-like object, depending on exactly what was passed:
# it's a path to a file
if _ispath(f):
path = pathlib.Path(f).expanduser()
format, compression, modesuffix = _get_format(path.name, format)
fileobj = COMPRESSION[compression](str(path), mode='r' + modesuffix)
closehandle = True
# it can create a file-like object
elif hasattr(f, 'open'):
if format in PICKLE_EXTENSIONS:
readmode = 'rb'
fileobj = f.open(readmode)
closehandle = True
# it's already file-like
elif hasattr(f, 'read'):
fileobj = f
# It's a string with a file's content
elif isinstance(f, basestring):
if format is None:
raise IOError(('No file named "%s"; ' % f[:50]) +
'please set the `format` argument if you want to parse the string')
elif format in PICKLE_EXTENSIONS or isinstance(f, bytes):
streamtype = io.BytesIO
fileobj = streamtype(f)
else:
raise ValueError('Parameter to moldesign.read (%s) not ' % str(f) +
'recognized as string, file path, or file-like object')
if format in READERS:
mol = READERS[format](fileobj)
else: # default to openbabel if there's not an explicit reader for this format
mol = openbabel_interface.read_stream(fileobj, format)
finally:
if closehandle:
fileobj.close()
if filename is not None and mol.name not in (None, 'untitled'):
mol.name = filename
if isinstance(mol, mdt.Molecule):
mdt.helpers.atom_name_check(mol)
return mol
def _ispath(f):
if not f:
return False
elif isinstance(f, basestring) and _isfile(f):
return True
elif isinstance(f, pathlib.Path):
return True
elif PY2 and pathlib._backportpathlib and isinstance(f, pathlib._backportpathlib.Path):
return True
else:
return False
def _isfile(f):
try:
return os.path.isfile(f)
except (TypeError, ValueError):
return False
@utils.exports
def write(obj, filename=None, format=None):
""" Write a molecule to a file or string.
Will also pickle arbitrary python objects.
Notes:
Files with ``.bz2`` or ``.gz`` suffixes will be automatically compressed.
Users will usually call this by way of ``Molecule.write``.
Args:
obj (moldesign.Molecule or object): the molecule to be written
(or python object to be pickled)
filename (str or pathlib.Path or file-like): path or buffer to write to (if not passed),
string is returned
format (str): molecule format (pdb, xyz, sdf, etc.) or a pickle file extension
('pkl' and 'mdt' are both accepted)
Returns:
str: if filename is none, return the output file as a string (otherwise returns ``None``)
"""
close_handle = False
if hasattr(filename, 'write'): # it's a stream
fileobj = filename
return_string = False
if format is None and getattr(fileobj, 'name', None):
format, compression, mode = _get_format(fileobj.name, format)
if format is None:
raise ValueError("Could not determine format to write - please the 'format' argument")
else:
if ( format is None
and filename is not None
and not isinstance(filename, pathlib.Path)
and len(str(filename)) < 5
and '.' not in filename):
# lets users call mdt.write(obj, 'pdb') and get a string (without needing the "format" keyword
path, format = None, filename
elif filename is None:
path = None
elif isinstance(filename, str):
path = pathlib.Path(filename).expanduser()
else:
path = filename
filename = str(path)
writemode = 'w'
format, compression, mode = _get_format(filename, format)
if mode == 'b':
streamtype = io.BytesIO
else:
streamtype = io.StringIO
# First, create an object to write to (either file handle or file-like buffer)
if path:
return_string = False
fileobj = COMPRESSION[compression](str(path), mode=writemode + mode)
close_handle = True
else:
return_string = True
fileobj = streamtype()
# Now, write to the object
if format in WRITERS:
WRITERS[format](obj, fileobj)
else:
fileobj.write(openbabel_interface.write_string(obj, format))
# Return a string if necessary
if return_string:
return fileobj.getvalue()
elif close_handle:
fileobj.close()
@utils.exports
def write_trajectory(traj, filename=None, format=None, overwrite=True):
""" Write trajectory a file (if filename provided) or file-like buffer
Args:
traj (moldesign.molecules.Trajectory): trajectory to write
filename (str): name of file (return a file-like object if not passed)
format (str): file format (guessed from filename if None)
overwrite (bool): overwrite filename if it exists
Returns:
StringIO: file-like object (only if filename not passed)
"""
format, compression, modesuffix = _get_format(filename, format)
# If user is requesting a pickle, just dump the whole thing now and return
if format.lower() in PICKLE_EXTENSIONS:
write(traj, filename=filename, format=format)
# for traditional molecular file formats, write the frames one after another
else:
if filename and (not overwrite) and _isfile(filename):
raise IOError('%s exists' % filename)
if not filename:
fileobj = io.StringIO()
else:
fileobj = open(filename, 'w' + modesuffix)
for frame in traj.frames:
fileobj.write(frame.write(format=format))
if filename is None:
fileobj.seek(0)
return fileobj
else:
fileobj.close()
def read_pdb(f, assign_ccd_bonds=True):
""" Read a PDB file and return a molecule.
This uses ParmEd's parser to get the molecular structure, with additional functionality
to assign Chemical Component Dictionary bonds, detect missing residues, and find
biomolecular assembly information.
Note:
Users won't typically use this routine; instead, they'll use ``moldesign.read``, which will
delegate to this routine when appropriate.
Args:
f (filelike): filelike object giving access to the PDB file (must implement readline+seek)
assign_ccd_bonds (bool): Use the PDB Chemical Component Dictionary (CCD) to create bond
topology (note that bonds from CONECT records will always be created as well)
Returns:
moldesign.Molecule: the parsed molecule
"""
assemblies = pdb.get_pdb_assemblies(f)
f.seek(0)
mol = mdt.interfaces.parmed_interface.read_pdb(f)
mol.properties.bioassemblies = assemblies
f.seek(0)
mol.metadata.missing_residues = mdt.helpers.get_pdb_missing_residues(f)
# Assign bonds from residue templates
if assign_ccd_bonds:
pdb.assign_biopolymer_bonds(mol)
if assemblies:
pdb.warn_assemblies(mol, assemblies)
return mol
def read_mmcif(f):
""" Read an mmCIF file and return a molecule.
This uses OpenBabel's basic structure parser along with biopython's mmCIF bioassembly parser
Note:
Users won't typically use this routine; instead, they'll use ``moldesign.read``, which will
delegate to this routine when appropriate.
Args:
f (filelike): file-like object that accesses the mmCIF file (must implement seek)
Returns:
moldesign.Molecule: the parsed molecular structure
"""
mol = mdt.interfaces.parmed_interface.read_mmcif(f)
f.seek(0)
assemblies = biopython_interface.get_mmcif_assemblies(f)
if assemblies:
pdb.warn_assemblies(mol, assemblies)
mol.properties.bioassemblies = assemblies
return mol
def read_xyz(f):
tempmol = openbabel_interface.read_stream(f, 'xyz')
for atom in tempmol.atoms:
atom.residue = None
return mdt.Molecule(tempmol.atoms)
def read_smiles_file(f):
return _get_mol_from_identifier_file(f, from_smiles)
def read_inchi_file(f):
return _get_mol_from_identifier_file(f, from_inchi)
def read_iupac_file(f):
return _get_mol_from_identifier_file(f, from_name)
def _get_mol_from_identifier_file(fileobj, mol_constructor):
for line in fileobj:
if line.strip()[0] == '#':
continue
else:
return mol_constructor(line.strip())
else:
raise IOError("Didn't find any chemical identifiers in the passed file.")
def write_xyz(mol, fileobj):
fileobj.write(u" %d\n%s\n" % (mol.num_atoms, mol.name))
for atom in mol.atoms:
x, y, z = atom.position.value_in(mdt.units.angstrom)
fileobj.write(u"%s %24.14f %24.14f %24.14f\n" % (atom.element, x, y, z))
@utils.exports
def from_pdb(pdbcode, usecif=False):
""" Import the given molecular geometry from PDB.org
By default, this will use the structure from the PDB-formatted data; however, it will fall back
to using the mmCIF data for this pdbcode if the PDB file is not present.
See Also:
http://pdb101.rcsb.org/learn/guide-to-understanding-pdb-data/introduction
Args:
pdbcode (str): 4-character PDB code (e.g. 3AID, 1BNA, etc.)
usecif (bool): If False (the default), use the PDB-formatted file (default).
If True, use the mmCIF-format file from RCSB.org.
Returns:
moldesign.Molecule: molecule object
"""
import requests
assert len(pdbcode) == 4, "%s is not a valid PDB ID." % pdbcode
fileext = 'cif' if usecif else 'pdb'
url = 'https://www.rcsb.org/pdb/files/%s.%s' % (pdbcode, fileext)
request = requests.get(url)
if request.status_code == 404 and not usecif: # if not found, try the cif-format version
print('WARNING: %s.pdb not found in rcsb.org database. Trying %s.cif...' % (
pdbcode, pdbcode), end=' ')
retval = from_pdb(pdbcode, usecif=True)
print('success.')
return retval
elif request.status_code != 200:
raise ValueError('Failed to download %s.%s from rcsb.org: %s %s' % (
pdbcode, fileext, request.status_code, request.reason))
filestring = request.text
mol = read(filestring, format=fileext)
mol.name = pdbcode
mol.metadata.sourceurl = url
mol.metadata.structureurl = 'https://www.rcsb.org/pdb/explore.do?structureId=%s' % pdbcode
mol.metadata.pdbid = pdbcode
if usecif:
mol.metadata.sourceformat = 'mmcif'
else:
mol.metadata.sourceformat = 'pdb'
return mol
@utils.exports
def from_name(name):
"""Attempt to convert an IUPAC or common name to a molecular geometry.
Args:
name (str): molecular name (generally IUPAC - some common names are also recognized)
Returns:
moldesign.Molecule: molecule object
"""
from moldesign.interfaces.opsin_interface import name_to_smiles
# TODO: fallback to http://cactus.nci.nih.gov/chemical/structure
smi = name_to_smiles(name)
mol = from_smiles(smi, name)
return mol
def _get_format(filename, format):
""" Determine the requested file format and optional compression library
Args:
filename (str or None): requested filename, if present
format (str or None): requested format, if present
Returns:
(str, str, str): (file format, compression format or ``None`` for no compression)
Examples:
>>> _get_format('mymol.pdb', None)
('pdb', None)
>>> _get_format('smallmol.xyz.bz2', None)
('xyz','bz2')
>>> _get_format('mymol.t.gz', 'sdf')
('sdf','gz')
"""
compressor = None
if filename is None and format is None:
raise ValueError('No filename or file format specified')
elif filename is not None:
fname, extn = os.path.splitext(filename)
suffix = extn[1:].lower()
compressor = None
if suffix in COMPRESSION:
compressor = suffix
suffix = os.path.splitext(fname)[1][1:].lower()
if format is None:
format = suffix
if format in PICKLE_EXTENSIONS:
mode = 'b'
elif (compressor == 'bz2' and not PY2) or compressor == 'gz':
mode = 't'
else:
mode = ''
return format, compressor, mode
####################################
# FILE EXTENSION HANDLERS #
####################################
# All extensions MUST be lower case
READERS = {'pdb': read_pdb,
'cif': read_mmcif,
'mmcif': read_mmcif,
'smi': read_smiles_file,
'smiles': read_smiles_file,
'inchi': read_inchi_file,
'iupac': read_iupac_file,
'xyz': read_xyz}
WRITERS = {'pdb': write_pdb,
'mmcif': write_mmcif,
'xyz': write_xyz}
if PY2:
bzopener = bz2.BZ2File
else:
bzopener = bz2.open
PICKLE_EXTENSIONS = set("p pkl pickle mdt".split())
COMPRESSION = {'gz': gzip.open,
'gzip': gzip.open,
'bz2': bzopener,
'bzip2': bzopener,
None: open}
for ext in PICKLE_EXTENSIONS:
READERS[ext] = pkl.load
WRITERS[ext] = functools.partial(pkl.dump, protocol=2)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/__init__.py | .py | 2,506 | 89 | # Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import print_function, absolute_import, division
import os as _os
_NBMOLVIZ_EXPECTED_VERSION = "0.7.0"
_building_docs = bool(_os.environ.get('SPHINX_IS_BUILDING_DOCS', ""))
from . import data
PACKAGEPATH = data.PACKAGEPATH
# Base subpackages - import these first
from . import utils
from . import units
# Functional subpackages
from . import compute
from . import fileio
from . import exceptions
from . import external
from . import forcefields
from . import geom
from . import helpers
from . import integrators
from . import interfaces
from . import parameters
from . import mathutils
from . import min
from . import models
from . import method
from . import orbitals
from . import molecules
from . import tools
from . import widgets
from .widgets import configure, about
# Populate the top-level namespace (imports everything from each <submodule>.__all__ variable)
from .exceptions import *
from .fileio import *
from .forcefields import *
from .geom import *
from .min import *
from .orbitals import *
from .molecules import *
from .tools import *
# Initialize confiugration
compute.init_config()
# package metadata
from . import _version
__version__ = _version.get_versions()['version']
__copyright__ = "Copyright 2017 Autodesk Inc."
__license__ = "Apache 2.0"
# Set warnings appropriately
# TODO: don't clobber user's settings!!!
import numpy as _np
import warnings as _warnings
_np.seterr(all='raise')
_warnings.simplefilter('error', _np.ComplexWarning)
# We keep a list of weak of references to every RPC job that's run
import weakref as _weakref
_lastjobs = _weakref.WeakValueDictionary()
_njobs = 0
# For documentation purposes only - make sphinx document the toplevel namespace
if _building_docs:
__all__ = fileio.__all__ + \
geom.__all__ + \
min.__all__ + \
orbitals.__all__ + \
molecules.__all__ + \
tools.__all__
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/widgets.py | .py | 2,933 | 90 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import sys
import functools
from .utils import exports, exports_names
from . import _NBMOLVIZ_EXPECTED_VERSION
__all__ = 'BondSelector GeometryBuilder ResidueSelector Symmetrizer AtomSelector'.split()
INSTALL_CMD = """Install `nbmolviz` by running these commands at the terminal:
$ pip install "nbmolviz==%s"
$ python -m nbmolviz activate
Afterwards, restart python and reload any running notebooks."""%_NBMOLVIZ_EXPECTED_VERSION
_warnings = []
try:
import nbmolviz.widget_utils
from nbmolviz import __version__ as nbv_version
except ImportError:
nbmolviz_enabled = False
nbmolviz_installed = False
else:
nbmolviz_installed = True
nbmolviz_enabled = nbmolviz.widget_utils.can_use_widgets()
def notebook_only_method(*args, **kwargs):
assert not nbmolviz_enabled
if nbmolviz_installed:
raise ImportError("This function is only available in a Jupyter notebook!")
else:
raise ImportError(
"The `nbmolviz` library must be installed to use this function!\n"
+ INSTALL_CMD)
if nbmolviz_enabled:
# TODO: Make these into lazy imports
from nbmolviz.widgets import (BondSelector, GeometryBuilder, ResidueSelector, Symmetrizer,
AtomSelector)
from nbmolviz.mdtconfig.compute import configure
about = configure
nbmolviz.widget_utils.print_extension_warnings(stream=sys.stderr)
else:
BondSelector = GeometryBuilder = ResidueSelector = AtomSelector = Symmetrizer = configure \
= about = notebook_only_method
def _get_nbmethod(name):
# don't import nbmolviz methods until a method is actually called
from nbmolviz import methods as nbmethods
module = nbmethods
for item in name.split('.'):
module = getattr(module, item)
return module
@exports
class WidgetMethod(object):
def __init__(self, name):
self.name = name
self.method = None
def __get__(self, instance, owner):
if not nbmolviz_enabled:
return notebook_only_method
elif self.method is None:
self.method = _get_nbmethod(self.name)
return functools.partial(self.method, instance)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/exceptions.py | .py | 1,736 | 57 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
class NotSupportedError(Exception):
""" Raised when a given method can't support the requested calculation
"""
class ConvergenceFailure(Exception):
""" Raised when an iterative calculation fails to converge """
pass
class NotCalculatedError(Exception):
""" Raised when a molecular property is requested that hasn't been calculated """
pass
class UnhandledValenceError(Exception):
def __init__(self, atom):
self.message = 'Atom %s has unhandled valence: %d' % (atom, atom.valence)
class QMConvergenceError(Exception):
""" Raised when an iterative QM calculation (typically SCF) fails to converge
"""
pass
class DockerError(Exception):
pass
class ForcefieldAssignmentError(Exception):
""" Class that define displays for common errors in assigning a forcefield
"""
def __init__(self, msg, errors, mol=None, job=None):
self.args = [msg]
self.errors = errors
self.mol = mol
self.job = job
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/_version.py | .py | 18,450 | 521 |
# This file helps to compute a version number in source trees obtained from
# git-archive tarball (such as those provided by githubs download-from-tag
# feature). Distribution tarballs (built by setup.py sdist) and build
# directories (produced by setup.py build) will contain a much shorter file
# that just contains the computed version number.
# This file is released into the public domain. Generated by
# versioneer-0.17 (https://github.com/warner/python-versioneer)
"""Git implementation of _version.py."""
import errno
import os
import re
import subprocess
import sys
def get_keywords():
"""Get the keywords needed to look up the version information."""
# these strings will be replaced by git during git-archive.
# setup.py/versioneer.py will grep for the variable names, so they must
# each be defined on a line of their own. _version.py will just call
# get_keywords().
git_refnames = "$Format:%d$"
git_full = "$Format:%H$"
git_date = "$Format:%ci$"
keywords = {"refnames": git_refnames, "full": git_full, "date": git_date}
return keywords
class VersioneerConfig:
"""Container for Versioneer configuration parameters."""
def get_config():
"""Create, populate and return the VersioneerConfig() object."""
# these strings are filled in when 'setup.py versioneer' creates
# _version.py
cfg = VersioneerConfig()
cfg.VCS = "git"
cfg.style = "pep440"
cfg.tag_prefix = ""
cfg.parentdir_prefix = "None"
cfg.versionfile_source = "moldesign/_version.py"
cfg.verbose = False
return cfg
class NotThisMethod(Exception):
"""Exception raised if a method is not valid for the current scenario."""
LONG_VERSION_PY = {}
HANDLERS = {}
def register_vcs_handler(vcs, method): # decorator
"""Decorator to mark a method as the handler for a particular VCS."""
def decorate(f):
"""Store f in HANDLERS[vcs][method]."""
if vcs not in HANDLERS:
HANDLERS[vcs] = {}
HANDLERS[vcs][method] = f
return f
return decorate
def run_command(commands, args, cwd=None, verbose=False, hide_stderr=False,
env=None):
"""Call the given command(s)."""
assert isinstance(commands, list)
p = None
for c in commands:
try:
dispcmd = str([c] + args)
# remember shell=False, so use git.cmd on windows, not just git
p = subprocess.Popen([c] + args, cwd=cwd, env=env,
stdout=subprocess.PIPE,
stderr=(subprocess.PIPE if hide_stderr
else None))
break
except EnvironmentError:
e = sys.exc_info()[1]
if e.errno == errno.ENOENT:
continue
if verbose:
print("unable to run %s" % dispcmd)
print(e)
return None, None
else:
if verbose:
print("unable to find command, tried %s" % (commands,))
return None, None
stdout = p.communicate()[0].strip()
if sys.version_info[0] >= 3:
stdout = stdout.decode()
if p.returncode != 0:
if verbose:
print("unable to run %s (error)" % dispcmd)
print("stdout was %s" % stdout)
return None, p.returncode
return stdout, p.returncode
def versions_from_parentdir(parentdir_prefix, root, verbose):
"""Try to determine the version from the parent directory name.
Source tarballs conventionally unpack into a directory that includes both
the project name and a version string. We will also support searching up
two directory levels for an appropriately named parent directory
"""
rootdirs = []
for i in range(3):
dirname = os.path.basename(root)
if dirname.startswith(parentdir_prefix):
return {"version": dirname[len(parentdir_prefix):],
"full-revisionid": None,
"dirty": False, "error": None, "date": None}
else:
rootdirs.append(root)
root = os.path.dirname(root) # up a level
if verbose:
print("Tried directories %s but none started with prefix %s" %
(str(rootdirs), parentdir_prefix))
raise NotThisMethod("rootdir doesn't start with parentdir_prefix")
@register_vcs_handler("git", "get_keywords")
def git_get_keywords(versionfile_abs):
"""Extract version information from the given file."""
# the code embedded in _version.py can just fetch the value of these
# keywords. When used from setup.py, we don't want to import _version.py,
# so we do it with a regexp instead. This function is not used from
# _version.py.
keywords = {}
try:
f = open(versionfile_abs, "r")
for line in f.readlines():
if line.strip().startswith("git_refnames ="):
mo = re.search(r'=\s*"(.*)"', line)
if mo:
keywords["refnames"] = mo.group(1)
if line.strip().startswith("git_full ="):
mo = re.search(r'=\s*"(.*)"', line)
if mo:
keywords["full"] = mo.group(1)
if line.strip().startswith("git_date ="):
mo = re.search(r'=\s*"(.*)"', line)
if mo:
keywords["date"] = mo.group(1)
f.close()
except EnvironmentError:
pass
return keywords
@register_vcs_handler("git", "keywords")
def git_versions_from_keywords(keywords, tag_prefix, verbose):
"""Get version information from git keywords."""
if not keywords:
raise NotThisMethod("no keywords at all, weird")
date = keywords.get("date")
if date is not None:
# git-2.2.0 added "%cI", which expands to an ISO-8601 -compliant
# datestamp. However we prefer "%ci" (which expands to an "ISO-8601
# -like" string, which we must then edit to make compliant), because
# it's been around since git-1.5.3, and it's too difficult to
# discover which version we're using, or to work around using an
# older one.
date = date.strip().replace(" ", "T", 1).replace(" ", "", 1)
refnames = keywords["refnames"].strip()
if refnames.startswith("$Format"):
if verbose:
print("keywords are unexpanded, not using")
raise NotThisMethod("unexpanded keywords, not a git-archive tarball")
refs = set([r.strip() for r in refnames.strip("()").split(",")])
# starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of
# just "foo-1.0". If we see a "tag: " prefix, prefer those.
TAG = "tag: "
tags = set([r[len(TAG):] for r in refs if r.startswith(TAG)])
if not tags:
# Either we're using git < 1.8.3, or there really are no tags. We use
# a heuristic: assume all version tags have a digit. The old git %d
# expansion behaves like git log --decorate=short and strips out the
# refs/heads/ and refs/tags/ prefixes that would let us distinguish
# between branches and tags. By ignoring refnames without digits, we
# filter out many common branch names like "release" and
# "stabilization", as well as "HEAD" and "master".
tags = set([r for r in refs if re.search(r'\d', r)])
if verbose:
print("discarding '%s', no digits" % ",".join(refs - tags))
if verbose:
print("likely tags: %s" % ",".join(sorted(tags)))
for ref in sorted(tags):
# sorting will prefer e.g. "2.0" over "2.0rc1"
if ref.startswith(tag_prefix):
r = ref[len(tag_prefix):]
if verbose:
print("picking %s" % r)
return {"version": r,
"full-revisionid": keywords["full"].strip(),
"dirty": False, "error": None,
"date": date}
# no suitable tags, so version is "0+unknown", but full hex is still there
if verbose:
print("no suitable tags, using unknown + full revision id")
return {"version": "0+unknown",
"full-revisionid": keywords["full"].strip(),
"dirty": False, "error": "no suitable tags", "date": None}
@register_vcs_handler("git", "pieces_from_vcs")
def git_pieces_from_vcs(tag_prefix, root, verbose, run_command=run_command):
"""Get version from 'git describe' in the root of the source tree.
This only gets called if the git-archive 'subst' keywords were *not*
expanded, and _version.py hasn't already been rewritten with a short
version string, meaning we're inside a checked out source tree.
"""
GITS = ["git"]
if sys.platform == "win32":
GITS = ["git.cmd", "git.exe"]
out, rc = run_command(GITS, ["rev-parse", "--git-dir"], cwd=root,
hide_stderr=True)
if rc != 0:
if verbose:
print("Directory %s not under git control" % root)
raise NotThisMethod("'git rev-parse --git-dir' returned error")
# if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty]
# if there isn't one, this yields HEX[-dirty] (no NUM)
describe_out, rc = run_command(GITS, ["describe", "--tags", "--dirty",
"--always", "--long",
"--match", "%s*" % tag_prefix],
cwd=root)
# --long was added in git-1.5.5
if describe_out is None:
raise NotThisMethod("'git describe' failed")
describe_out = describe_out.strip()
full_out, rc = run_command(GITS, ["rev-parse", "HEAD"], cwd=root)
if full_out is None:
raise NotThisMethod("'git rev-parse' failed")
full_out = full_out.strip()
pieces = {}
pieces["long"] = full_out
pieces["short"] = full_out[:7] # maybe improved later
pieces["error"] = None
# parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty]
# TAG might have hyphens.
git_describe = describe_out
# look for -dirty suffix
dirty = git_describe.endswith("-dirty")
pieces["dirty"] = dirty
if dirty:
git_describe = git_describe[:git_describe.rindex("-dirty")]
# now we have TAG-NUM-gHEX or HEX
if "-" in git_describe:
# TAG-NUM-gHEX
mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe)
if not mo:
# unparseable. Maybe git-describe is misbehaving?
pieces["error"] = ("unable to parse git-describe output: '%s'"
% describe_out)
return pieces
# tag
full_tag = mo.group(1)
if not full_tag.startswith(tag_prefix):
if verbose:
fmt = "tag '%s' doesn't start with prefix '%s'"
print(fmt % (full_tag, tag_prefix))
pieces["error"] = ("tag '%s' doesn't start with prefix '%s'"
% (full_tag, tag_prefix))
return pieces
pieces["closest-tag"] = full_tag[len(tag_prefix):]
# distance: number of commits since tag
pieces["distance"] = int(mo.group(2))
# commit: short hex revision ID
pieces["short"] = mo.group(3)
else:
# HEX: no tags
pieces["closest-tag"] = None
count_out, rc = run_command(GITS, ["rev-list", "HEAD", "--count"],
cwd=root)
pieces["distance"] = int(count_out) # total number of commits
# commit date: see ISO-8601 comment in git_versions_from_keywords()
date = run_command(GITS, ["show", "-s", "--format=%ci", "HEAD"],
cwd=root)[0].strip()
pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1)
return pieces
def plus_or_dot(pieces):
"""Return a + if we don't already have one, else return a ."""
if "+" in pieces.get("closest-tag", ""):
return "."
return "+"
def render_pep440(pieces):
"""Build up version string, with post-release "local version identifier".
Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you
get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty
Exceptions:
1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty]
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"] or pieces["dirty"]:
rendered += plus_or_dot(pieces)
rendered += "%d.g%s" % (pieces["distance"], pieces["short"])
if pieces["dirty"]:
rendered += ".dirty"
else:
# exception #1
rendered = "0+untagged.%d.g%s" % (pieces["distance"],
pieces["short"])
if pieces["dirty"]:
rendered += ".dirty"
return rendered
def render_pep440_pre(pieces):
"""TAG[.post.devDISTANCE] -- No -dirty.
Exceptions:
1: no tags. 0.post.devDISTANCE
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"]:
rendered += ".post.dev%d" % pieces["distance"]
else:
# exception #1
rendered = "0.post.dev%d" % pieces["distance"]
return rendered
def render_pep440_post(pieces):
"""TAG[.postDISTANCE[.dev0]+gHEX] .
The ".dev0" means dirty. Note that .dev0 sorts backwards
(a dirty tree will appear "older" than the corresponding clean one),
but you shouldn't be releasing software with -dirty anyways.
Exceptions:
1: no tags. 0.postDISTANCE[.dev0]
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"] or pieces["dirty"]:
rendered += ".post%d" % pieces["distance"]
if pieces["dirty"]:
rendered += ".dev0"
rendered += plus_or_dot(pieces)
rendered += "g%s" % pieces["short"]
else:
# exception #1
rendered = "0.post%d" % pieces["distance"]
if pieces["dirty"]:
rendered += ".dev0"
rendered += "+g%s" % pieces["short"]
return rendered
def render_pep440_old(pieces):
"""TAG[.postDISTANCE[.dev0]] .
The ".dev0" means dirty.
Eexceptions:
1: no tags. 0.postDISTANCE[.dev0]
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"] or pieces["dirty"]:
rendered += ".post%d" % pieces["distance"]
if pieces["dirty"]:
rendered += ".dev0"
else:
# exception #1
rendered = "0.post%d" % pieces["distance"]
if pieces["dirty"]:
rendered += ".dev0"
return rendered
def render_git_describe(pieces):
"""TAG[-DISTANCE-gHEX][-dirty].
Like 'git describe --tags --dirty --always'.
Exceptions:
1: no tags. HEX[-dirty] (note: no 'g' prefix)
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
if pieces["distance"]:
rendered += "-%d-g%s" % (pieces["distance"], pieces["short"])
else:
# exception #1
rendered = pieces["short"]
if pieces["dirty"]:
rendered += "-dirty"
return rendered
def render_git_describe_long(pieces):
"""TAG-DISTANCE-gHEX[-dirty].
Like 'git describe --tags --dirty --always -long'.
The distance/hash is unconditional.
Exceptions:
1: no tags. HEX[-dirty] (note: no 'g' prefix)
"""
if pieces["closest-tag"]:
rendered = pieces["closest-tag"]
rendered += "-%d-g%s" % (pieces["distance"], pieces["short"])
else:
# exception #1
rendered = pieces["short"]
if pieces["dirty"]:
rendered += "-dirty"
return rendered
def render(pieces, style):
"""Render the given version pieces into the requested style."""
if pieces["error"]:
return {"version": "unknown",
"full-revisionid": pieces.get("long"),
"dirty": None,
"error": pieces["error"],
"date": None}
if not style or style == "default":
style = "pep440" # the default
if style == "pep440":
rendered = render_pep440(pieces)
elif style == "pep440-pre":
rendered = render_pep440_pre(pieces)
elif style == "pep440-post":
rendered = render_pep440_post(pieces)
elif style == "pep440-old":
rendered = render_pep440_old(pieces)
elif style == "git-describe":
rendered = render_git_describe(pieces)
elif style == "git-describe-long":
rendered = render_git_describe_long(pieces)
else:
raise ValueError("unknown style '%s'" % style)
return {"version": rendered, "full-revisionid": pieces["long"],
"dirty": pieces["dirty"], "error": None,
"date": pieces.get("date")}
def get_versions():
"""Get version information or return default if unable to do so."""
# I am in _version.py, which lives at ROOT/VERSIONFILE_SOURCE. If we have
# __file__, we can work backwards from there to the root. Some
# py2exe/bbfreeze/non-CPython implementations don't do __file__, in which
# case we can only use expanded keywords.
cfg = get_config()
verbose = cfg.verbose
try:
return git_versions_from_keywords(get_keywords(), cfg.tag_prefix,
verbose)
except NotThisMethod:
pass
try:
root = os.path.realpath(__file__)
# versionfile_source is the relative path from the top of the source
# tree (where the .git directory might live) to this file. Invert
# this to find the root from __file__.
for i in cfg.versionfile_source.split('/'):
root = os.path.dirname(root)
except NameError:
return {"version": "0+unknown", "full-revisionid": None,
"dirty": None,
"error": "unable to find root of source tree",
"date": None}
try:
pieces = git_pieces_from_vcs(cfg.tag_prefix, root, verbose)
return render(pieces, cfg.style)
except NotThisMethod:
pass
try:
if cfg.parentdir_prefix:
return versions_from_parentdir(cfg.parentdir_prefix, root, verbose)
except NotThisMethod:
pass
return {"version": "0+unknown", "full-revisionid": None,
"dirty": None,
"error": "unable to compute version", "date": None}
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/__main__.py | .py | 10,065 | 303 | """
This file collects the various command line tasks accessed via
``python -m moldesign [command]``
The functions here are intended help users set up their environment.
Note that MDT routines will NOT be importable from this module when it runs as a script -- you
won't be working with molecules or atoms in this module.
"""
from __future__ import print_function, absolute_import, division
import atexit
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from future.utils import PY2
import argparse
import distutils.spawn
import errno
import os
import random
import shutil
import socket
import subprocess
import sys
import time
import yaml
URL_OPENERS = ['Open', 'xdg-open', 'sensible-browser', 'gnome-open', 'x-www-browser']
JUPYTERPORT = 8888
DOCKER_TOOLS = 'docker docker-machine docker-compose'.split()
DOCKER_REPOSITORY = 'docker-hub.autodesk.com/virshua/moldesign:'
HOME = os.path.expanduser('~')
CONFIG_DIR = os.path.join(HOME, '.moldesign')
EXAMPLE_DIR_TARGET = os.path.join(os.path.curdir, 'moldesign-examples')
MOLDESIGN_SRC = os.path.abspath(os.path.dirname(__file__))
EXAMPLE_DIR_SRC = unit_def_file = os.path.join(MOLDESIGN_SRC, '_notebooks')
MDTVERSION = subprocess.check_output(['python', '-c',
"import _version; print(_version.get_versions()['version'])"],
cwd=MOLDESIGN_SRC).splitlines()[-1].decode('ascii')
VERFILEPATH = os.path.join(EXAMPLE_DIR_TARGET, '.mdtversion')
CONFIG_PATH = os.path.join(CONFIG_DIR, 'moldesign.yml')
NO_NBMOLVIZ_ERR = 10
JUPYTER_ERR = 128
NO_EXAMPLE_OVERWRITE_ERR = 200
OUTDATED_EXAMPLES_ERR = 201
def main():
print('Molecular Design Toolkit v%s Launcher' % MDTVERSION)
global CONFIG_PATH
parser = argparse.ArgumentParser('python -m moldesign')
subparsers = parser.add_subparsers(title='command', dest='command')
subparsers.add_parser('intro', help='copy examples into current directory and launch a '
'notebook')
subparsers.add_parser('launch', help='launch a notebook and open it in a browser '
'(equivalent to running "jupyter notebook")')
subparsers.add_parser('pull', help='download docker containers that MDT requires ('
'only when a docker client is configured)')
subparsers.add_parser('config', help='print configuration and exit')
subparsers.add_parser('copyexamples', help='Copy example notebooks')
subparsers.add_parser('version', help='Write version string and exit')
subparsers.add_parser('dumpenv', help="Dump environment for bug reports")
parser.add_argument('-f', '--config-file', type=str,
help='Path to config file')
args = parser.parse_args()
if args.config_file:
CONFIG_PATH = args.config_file
if args.command == 'intro':
nbmolviz_check()
copy_example_dir(use_existing=True)
launch(cwd=EXAMPLE_DIR_TARGET,
path='notebooks/Getting%20Started.ipynb')
elif args.command == 'launch':
nbmolviz_check()
launch()
elif args.command == 'copyexamples':
copy_example_dir(use_existing=False)
elif args.command == 'version':
print(MDTVERSION)
elif args.command == 'dumpenv':
import moldesign as mdt
mdt.data.print_environment()
elif args.command == 'pull':
pull_images()
elif args.command == 'config':
print('Reading config file from: %s' % CONFIG_PATH)
print('----------------------------')
with open(CONFIG_PATH, 'r') as cfgfile:
for key, value in yaml.load(cfgfile).items():
print('%s: %s' % (key, value))
else:
raise ValueError("Unhandled CLI command '%s'" % args.command)
def pull_images():
from .compute import packages
imgs = [x.get_docker_image_path() for x in packages.packages + packages.executables]
print('\nPulling images:', ', '.join(imgs))
for i, img in enumerate(imgs):
print('\n------------- Pulling image %s/%s : %s' % (i+1, len(imgs), img))
subprocess.check_call(['docker', 'pull', img])
print('------------- Done with %s' % img)
def nbmolviz_check():
# Checks for the existence of nbmolviz before attempting to launch a notebook
from . import widgets
if not widgets.nbmolviz_installed:
print('ERROR: nbmolviz not found - notebooks not available. Install it by running\n'
' $ pip install nbmolviz`')
sys.exit(NO_NBMOLVIZ_ERR)
def launch(cwd=None, path=''):
server, portnum = launch_jupyter_server(cwd=cwd)
wait_net_service('localhost', portnum, server)
open_browser('http://localhost:%d/%s' % (portnum, path))
server.wait()
def copy_example_dir(use_existing=False):
print('Copying MDT examples to `%s` ...' % EXAMPLE_DIR_TARGET)
if os.path.exists(EXAMPLE_DIR_TARGET):
check_existing_examples(use_existing)
else:
shutil.copytree(EXAMPLE_DIR_SRC, EXAMPLE_DIR_TARGET)
with open(VERFILEPATH, 'w') as verfile:
print(MDTVERSION, file=verfile)
print('Done.')
def check_existing_examples(use_existing):
if os.path.exists(VERFILEPATH):
with open(VERFILEPATH, 'r') as vfile:
version = vfile.read().strip()
else:
version = 'pre-0.7.4'
if version != MDTVERSION:
print('WARNING - your example directory is out of date! It corresponds to MDT version '
'%s, but you are using version %s'%(version, MDTVERSION))
print('To update your examples, please rename or remove "%s"'
% EXAMPLE_DIR_TARGET)
sys.exit(OUTDATED_EXAMPLES_ERR)
if use_existing:
return
else:
print('\n'.join(
['FAILED: directory already exists. Please:'
' 1) Rename or remove the existing directory at %s,'%EXAMPLE_DIR_TARGET,
' 2) Run this command in a different location, or'
' 3) Run `python -m moldesign intro` to launch the example gallery.']))
sys.exit(NO_EXAMPLE_OVERWRITE_ERR)
def launch_jupyter_server(cwd=None): # pragma: no cover
for i in range(8888, 9999):
if localhost_port_available(i):
portnum = i
break
else:
print('WARNING: no available port found between 8888 and 9999. Will try a random port ... ')
portnum = random.randint(10001, 65535)
server = subprocess.Popen(('jupyter notebook --no-browser --port %d' % portnum).split(),
cwd=cwd)
atexit.register(server_shutdown, server)
return server, portnum
def server_shutdown(server): # pragma: no cover
print('Shutting down jupyter server...')
server.terminate()
server.wait()
print('Jupyter terminated.')
def open_browser(url): # pragma: no cover
for exe in URL_OPENERS:
if distutils.spawn.find_executable(exe) is not None:
try:
subprocess.check_call([exe, url])
except subprocess.CalledProcessError:
continue
else:
return
print('Point your browser to %s to get started.' % url) # fallback
def localhost_port_available(portnum): # pragma: no cover
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.settimeout(0.2)
try:
s.connect(("localhost", portnum))
except socket.error as err:
if err.errno == errno.ECONNREFUSED:
return True
else:
raise
else:
return False
def yaml_dumper(*args):
return yaml.dump(*args, default_flow_style=False)
def wait_net_service(server, port, process, timeout=None): # pragma: no cover
"""
Wait for network service to appear
FROM http://code.activestate.com/recipes/576655-wait-for-network-service-to-appear/
@param timeout: in seconds, if None or 0 wait forever
@return: True of False, if timeout is None may return only True or
throw unhandled network exception
"""
import socket
import errno
if timeout:
from time import time as now
# time module is needed to calc timeout shared between two exceptions
end = now() + timeout
while True:
if process.poll() is not None:
print('ERROR: Jupyter process exited prematurely')
sys.exit(JUPYTER_ERR)
s = socket.socket()
s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
try:
if timeout:
next_timeout = end - now()
if next_timeout < 0:
return False
else:
s.settimeout(next_timeout)
s.connect((server, port))
except socket.timeout as err:
print('x')
# this exception occurs only if timeout is set
if timeout: return False
except socket.error as err:
if type(err.args) != tuple or err.errno not in (errno.ETIMEDOUT, errno.ECONNREFUSED):
raise
else:
s.close()
return True
print('.', end=' ')
sys.stdout.flush()
time.sleep(0.1)
def check_path(exes):
return {c: distutils.spawn.find_executable(c) for c in exes}
is_mac = (check_path(['osascript'])['osascript'] is not None)
if __name__ == '__main__':
main()
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/method.py | .py | 4,182 | 135 | """
This module contains abstract base classes for potential models, integrators, and various
associated data types (force fields, orbitals, basis sets, etc.).
"""
from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from future.utils import with_metaclass
import funcsigs
import moldesign as mdt
from .widgets import WidgetMethod
from . import utils
class _InitKeywordMeta(type):
""" Constructs a custom call signature for __init__ based on cls.PARAMETERS.
"""
@property
def __signature__(self):
if hasattr(self, '__customsig'):
return self.__customsig
kwargs = []
for param in self.PARAMETERS:
kwargs.append(funcsigs.Parameter(param.name,
default=param.default,
kind=funcsigs.Parameter.POSITIONAL_OR_KEYWORD))
self.__customsig = funcsigs.Signature(kwargs, __validate_parameters__=True)
return self.__customsig
class Method(with_metaclass(_InitKeywordMeta, object)):
"""Abstract Base class for energy models, integrators, and "heavy duty" simulation objects
Args:
**kwargs (dict): list of parameters for the method.
Attributes:
mol (mdt.Molecule): the molecule this method is associated with
"""
PARAMETERS = []
""" list: list of Parameters that can be used to configure this method
"""
PARAM_SUPPORT = {}
""" Mapping(str, list): List of supported values for parameters (if a parameter is not found,
it's assumed that all possible values are supported)
"""
configure = WidgetMethod('method.configure')
def __reduce__(self):
return _make_method, (self.__class__, self.params, self.mol)
def __init__(self, **params):
"""
:param params:
:return:
"""
# TODO: better documentation for the expected keywords
self._prepped = False
self.status = None
self.mol = None
self.params = utils.DotDict(params)
# Set default parameter values
for param in self.PARAMETERS:
if param.name not in self.params:
self.params[param.name] = param.default
@classmethod
def supports_parameter(cls, paramname):
for parameter in cls.PARAMETERS:
if parameter.name == paramname:
return True
else:
return False
def __eq__(self, other):
return self.__class__ is other.__class__ and self.params == other.params
@classmethod
def get_parameters(cls):
"""
This doesn't do anything right now except provide guidelines for programmers
"""
return cls.PARAMETERS
def get_forcefield(self):
raise NotImplementedError()
@classmethod
def print_parameters(cls):
params = cls.PARAMETERS
lines = []
for obj in params:
description = ''
if obj.choices:
description = '%s' % obj.choices
if obj.types:
description += ' or '
if obj.types:
description += 'Type %s' % obj.types
doc = '%s: %s (DEFAULT: %s)' % (obj.name, description, obj.default)
lines.append(doc)
return '\n'.join(lines)
def _make_method(cls, params, mol):
"""
Helper for serialization - allows __reduce__ to use kwargs
"""
obj = cls(**params)
obj.mol = mol
return obj | Python |
3D | Autodesk/molecular-design-toolkit | moldesign/helpers/qmmm.py | .py | 3,277 | 93 | # Copyright 2016 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import moldesign as mdt
LINKBONDRATIO = 0.709 # fixed ratio of C-C to C-H bond length for link atoms
def create_link_atoms(mol, qmatoms):
""" Create hydrogen caps for bonds between QM and MM regions.
Each link atom will have ``metadata.mmatom``, ``metadata.mmpartner`` attributes to identify the
atom it replaces and the atom it's bonded to in the MM system.
Raises:
ValueError: if any MM/QM atom is bonded to more than one QM/MM atom, or the bond
order is not one
Returns:
List[mdt.Atom]: list of link atoms
"""
linkatoms = []
qmset = set(qmatoms)
for qmatom in qmatoms:
mmatom = _get_mm_nbr(mol, qmatom, qmset)
if mmatom is None:
continue
la = mdt.Atom(atnum=1, name='HL%d' % len(linkatoms),
metadata={'mmatom': mmatom, 'mmpartner': qmatom})
linkatoms.append(la)
set_link_atom_positions(linkatoms)
return linkatoms
def _get_mm_nbr(mol, qmatom, qmset):
mm_nbrs = [nbr for nbr in qmatom.bonded_atoms
if nbr not in qmset]
if len(mm_nbrs) == 0:
return None
# everything below is sanity checks
mmatom = mm_nbrs[0]
if len(mm_nbrs) != 1:
raise ValueError('QM atom %s is bonded to more than one MM atom' % qmatom)
if mol.bond_graph[qmatom][mmatom] != 1:
raise ValueError('Bond crossing QM/MM boundary (%s - %s) does not have order 1'
% (qmatom, mmatom))
if qmatom.atnum != 6 or mmatom.atnum != 6:
print ('WARNING: QM/MM bond involving non-carbon atoms: %s - %s' %
(qmatom, mmatom))
mm_qm_nbrs = [qmnbr for qmnbr in mmatom.bonded_atoms
if qmnbr in qmset]
if len(mm_qm_nbrs) != 1:
raise ValueError('MM atom %s is bonded to more than one QM atom'%mmatom)
return mmatom
def set_link_atom_positions(linkatoms):
"""
Set link atom positions using a fixed ratio of MM bond length to QM bond length
Warnings:
- This is only valid for
- Presumably, the most "correct" way to do this is to place the hydrogen in order to
match the force exterted on the QM atom by the MM atom. This is not currently supported.
Args:
linkatoms (List[mdt.Atom]): list of link atoms to set positions for
References:
http://www.nwchem-sw.org/index.php/Qmmm_link_atoms
"""
for atom in linkatoms:
nbr = atom.metadata.mmpartner
proxy = atom.metadata.mmatom
dist = LINKBONDRATIO * nbr.distance(proxy)
atom.position = (nbr.position +
dist * mdt.mathutils.normalized(proxy.position - nbr.position))
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/helpers/__init__.py | .py | 82 | 5 | from .helpers import *
from .pdb import *
from .qmmm import *
from .logs import *
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/helpers/helpers.py | .py | 4,375 | 133 | """
This module contains various helper functions used by MDT internally.
"""
from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import collections
def get_all_atoms(*objects):
""" Given Atoms, AtomContainers, lists of Atoms, and lists of AtomContainers,
return a flat list of all atoms contained therein.
A given atom is only returned once, even if it's found more than once.
Args:
*objects (moldesign.Atom OR moldesign.AtomContainer OR List[moldesign.Atom] OR
List[moldesign.AtomContainer]): objects to take atoms from
"""
from moldesign import molecules
atoms = collections.OrderedDict()
for obj in objects:
if isinstance(obj, molecules.Atom):
atoms[obj] = None
elif hasattr(obj, 'atoms'):
atoms.update((x,None) for x in obj.atoms)
else:
for item in obj:
if isinstance(item, molecules.Atom):
atoms[item] = None
elif hasattr(item, 'atoms'):
atoms.update((x, None) for x in item.atoms)
return molecules.AtomList(iter(atoms.keys()))
def kinetic_energy(momenta, masses):
""" Returns kinetic energy
This is just a helper for the KE formula, because the formula is used frequently but not
particularly recognizable or easy to read
Args:
momenta (Matrix[momentum, shape=(*,3)]): atomic momenta
dim_masses (Vector[mass]): atomic masses
Returns:
Scalar[energy]: kinetic energy of these atoms
"""
return 0.5 * (momenta*momenta/masses[:,None]).sum()
def kinetic_temperature(ke, dof):
from moldesign.units import k_b
t = (2.0*ke)/(k_b*dof)
return t.defunits()
def atom_name_check(mol, force=False):
""" Makes sure atom names are unique in each residue.
If atoms names aren't unqiue:
- if the names are just the names of the elements, rename them
- else print a warning
"""
badres = []
for residue in mol.residues:
names = set(atom.name for atom in residue.atoms)
if len(names) != residue.num_atoms:
# atom names aren't unique, check if we can change them
for atom in residue.atoms:
if atom.name.lower() != atom.symbol.lower():
badres.append(residue)
if not force:
break
else: # rename the atoms
atomnums = {}
for atom in residue.atoms:
atom.name = atom.symbol + str(atomnums.setdefault(atom.symbol, 0))
atomnums[atom.symbol] += 1
if badres:
print('WARNING: residues do not have uniquely named atoms: %s' % badres)
def restore_topology(mol, topo):
""" Restores chain IDs and residue indices (these are stripped by some methods)
Args:
mol (mdt.Molecule): molecule to restore topology to
topo (mdt.Molecule): reference topology
Returns:
mdt.Molecule: a copy of ``mol`` with a restored topology
"""
import moldesign as mdt
assert mol.num_residues == topo.num_residues
assert mol.num_chains == 1
chain_map = {}
for chain in topo.chains:
chain_map[chain] = mdt.Chain(name=chain.name)
for res, refres in zip(mol.residues, topo.residues):
if refres.resname != res.resname:
print(('INFO: Residue #{res.index} residue code changed from "{refres.resname}"'
' to "{res.resname}".').format(res=res, refres=refres))
res.pdbindex = refres.pdbindex
res.name = refres.name
res.chain = chain_map[refres.chain]
return mdt.Molecule(mol.atoms)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/helpers/pdb.py | .py | 10,837 | 323 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
""" PDB file parsing utilities
We don't yet (and hopefully will never need) an internal PDB parser or writer. For now,
routines in this module read and write data that's not necessarily parsed by other implementations.
"""
from past.builtins import basestring
import collections
from io import StringIO
import numpy as np
import moldesign as mdt
BioAssembly = collections.namedtuple('BioAssembly', 'desc chains transforms')
def get_conect_pairs(mol):
""" Returns a dicitonary of HETATM bonds for a PDB CONECT record
Note that this doesn't return the text records themselves, because they need
to reference a specific PDB sequence number
"""
conects = collections.OrderedDict()
for residue in mol.residues:
# intra-residue bonds
if not residue.is_standard_residue:
for bond in residue.bonds:
if bond.order <= 1:
order = 1
else:
order = bond.order
for i in range(order):
conects.setdefault(bond.a1, []).append(bond.a2)
# inter-residue bonds
try:
r2 = residue.next_residue
except (StopIteration, KeyError, NotImplementedError):
continue
if not (residue.is_standard_residue and r2.is_standard_residue):
for bond in residue.bonds_to(r2):
conects.setdefault(bond.a1, []).append(bond.a2)
return conects
def warn_assemblies(mol, assemblies):
""" Print a warning message if the PDB structure contains a biomolecular assembly
"""
# Don't warn if the only assembly is the asymmetric unit
if len(assemblies) > 1 or len(list(assemblies.values())[0].transforms) > 1:
print("WARNING: This PDB file contains the following biomolecular assemblies:")
for name, asm in assemblies.items():
print('WARNING: Assembly "%s": %d copies of chains %s'%(
name, len(asm.transforms), ', '.join(asm.chains)))
print('WARNING: Use ``mdt.build_assembly([molecule],[assembly_name])``' \
' to build one of the above assemblies')
class MissingResidue(object):
type = 'protein'
missing = True
def __init__(self, chain, resname, pdbindex):
self.chain = chain
self.resname = resname
self.pdbindex = pdbindex
@property
def code(self):
"""str: one-letter amino acid code or two letter nucleic acid code, or '?' otherwise"""
return mdt.data.RESIDUE_ONE_LETTER.get(self.resname, '?')
def get_pdb_missing_residues(fileobj):
""" Parses missing residues from a PDB file.
Args:
fileobj (filelike): file-like access to the PDB file
Returns:
dict: listing of the missing residues of the form
``{[chain_id]:{[residue_number]:[residue_name], ...}, ...}``
Examples:
>>> with open('2jaj.pdb') as pdbfile:
>>> res = get_pdb_missing_residues(pdbfile)
>>> res
'A': {-4: 'GLY',
-3: 'PRO',
[...]
284: 'SER'},
'B': {34: 'GLY',
35: 'GLU',
[...]
"""
lineiter = iter(fileobj)
while True:
try:
fields = next(lineiter).split()
except StopIteration:
missing = {} # no missing residues found in file
break
if fields == ['REMARK', '465', 'M', 'RES', 'C', 'SSSEQI']:
missing = _parse_missing_xtal(fileobj)
break
elif fields[:3] == ['REMARK', '465', 'MODELS']:
missing = _parse_missing_nmr(fileobj)
break
summary = {}
for m in missing:
summary.setdefault(m.chain, {})[m.pdbindex] = m.resname
return summary
def _parse_missing_xtal(fileobj):
missing = []
while True:
fields = next(fileobj).split()
if fields[:2] != ['REMARK', '465']:
break
if len(fields) == 6:
has_modelnum = 1
if fields[2] != 1: # only process the first model
continue
else:
has_modelnum = 0
missing.append(MissingResidue(chain=fields[3+has_modelnum],
resname=fields[2+has_modelnum],
pdbindex=int(fields[4+has_modelnum])))
return missing
def _parse_missing_nmr(fileobj):
header = next(fileobj).split()
assert header == ['REMARK', '465', 'RES', 'C', 'SSSEQI']
missing = []
while True:
fields = next(fileobj).split()
if fields[:2] != ['REMARK', '465']:
break
missing.append(MissingResidue(chain=fields[3],
resname=fields[2],
pdbindex=int(fields[4])))
return missing
def get_pdb_assemblies(fileobj):
"""Parse a PDB file, return biomolecular assembly specifications
Args:
fileobj (file-like): File-like object for the PDB file
(this object will be rewound before returning)
Returns:
Mapping[str, BioAssembly]: dict mapping assembly ids to BioAssembly instances
"""
assemblies = {}
lineiter = iter(fileobj)
while True: # first, search for assembly transformations
line = next(lineiter)
fields = line.split()
# Conditions that indicate we're past the "REMARK 350" section
if fields[0] in ('ATOM', 'HETATM', 'CONECT'):
break
if fields[0] == 'REMARK' and int(fields[1]) > 350:
break
# look for start of a assembly transformation, i.e. "REMARK 350 BIOMOLECULE: [name] "
if fields[:3] == 'REMARK 350 BIOMOLECULE:'.split():
assembly_name = fields[-1]
assemblies[assembly_name] = _read_pdb_assembly(lineiter)
return assemblies
def _read_pdb_assembly(lineiter):
"""Helper for get_pdb_assemblies
"""
# First, there's description lines: "REMARK 350 AUTHOR DETERMINED BIOLOGICAL UNIT: OCTAMERIC"
description_lines = []
line = next(lineiter)
fields = line.split()
while fields[:7] != 'REMARK 350 APPLY THE FOLLOWING TO CHAINS:'.split():
description_lines.append(line[len('REMARK 350 '):])
line = next(lineiter)
fields = line.split()
description = (''.join(description_lines)).strip()
# Next, we get the chains in this assembly: "REMARK 350 APPLY THE FOLLOWING TO CHAINS: C, D"
assert fields[:7] == 'REMARK 350 APPLY THE FOLLOWING TO CHAINS:'.split()
chain_names = [x.rstrip(',') for x in fields[7:]]
while fields[-1][-1] == ',': # deal with multi-line lists of chains
line = next(lineiter)
fields = line.split()
assert fields[2:4] == ['AND', 'CHAINS:']
chain_names.extend(x.rstrip(',') for x in fields[4:])
transforms = []
while True: # loop over each assembly transformation
# example: "REMARK 350 BIOMT1 1 1.000000 0.000000 0.000000 0.00000 "
t = np.zeros((4, 4))
t[3, 3] = 1.0
for idim in range(3):
line = next(lineiter)
fields = line.split()
if idim == 0 and len(fields) == 2:
return BioAssembly(description, chain_names, transforms)
assert int(fields[3]) == len(transforms)+1
assert fields[2] == ('BIOMT%d' % (idim+1))
t[idim, :] = list(map(float, fields[4:8]))
transforms.append(t)
def assign_biopolymer_bonds(mol):
""" Assign bonds to all standard residues using the PDB chemical component dictionary
Any unrecognized residues are ignored.
References:
http://www.wwpdb.org/data/ccd
"""
for chain in mol.chains:
try:
chain.assign_biopolymer_bonds()
except KeyError:
print(('WARNING: failed to assign backbone bonds for %s') % str(chain))
for residue in mol.residues:
try:
residue.assign_template_bonds()
except KeyError:
if residue.type not in ('ion', 'water'):
print(('WARNING: failed to assign bonds for %s; use '
'``residue.assign_distance.bonds`` to guess the topology') % str(residue))
def assign_unique_hydrogen_names(mol):
""" Assign unique names to all hydrogens, based on either:
1) information in the Chemical Component Database, or
2) newly generated, unique names
Args:
mol (moldesign.Molecule):
"""
for residue in mol.residues:
if residue.resname in mdt.data.RESIDUE_BONDS:
_assign_hydrogen_names_from_ccd(residue)
else:
_assign_unique_hydrogen_names_in_order(residue)
residue.rebuild()
def _assign_hydrogen_names_from_ccd(residue):
ccd_bonds = mdt.data.RESIDUE_BONDS[residue.resname]
taken = set(atom.name for atom in residue.atoms)
if 'H' not in taken:
return # nothing to do
if 'H' in ccd_bonds:
taken.remove('H') # someone will actually need to be named "H'
for atom in residue:
if atom.atnum != 1 or atom.name != 'H':
continue
assert atom.num_bonds == 1, 'Hydrogen has more than one bond'
bond = atom.bonds[0]
other = bond.partner(atom).name
for partner in ccd_bonds[other]:
if partner[0] == 'H' and partner not in taken:
assert ccd_bonds[other][partner] == 1, 'Hydrogen bond order is not 1'
atom.name = partner
taken.add(partner)
break
def _assign_unique_hydrogen_names_in_order(residue):
n_hydrogen = 1
namecounts = collections.Counter(x.name for x in residue.atoms)
if namecounts.get('H', 0) > 1:
used_names = set(atom.name for atom in residue.atoms)
for atom in residue.atoms:
if atom.name == 'H':
name = 'H%d' % n_hydrogen
while name in used_names:
n_hydrogen += 1
name = 'H%d' % n_hydrogen
atom.name = name
used_names.add(name)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/helpers/logs.py | .py | 3,405 | 93 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..utils import exports_names, exports
from ..widgets import nbmolviz_enabled
from .. import units as u
if nbmolviz_enabled:
from nbmolviz.uielements import Logger, display_log
exports_names('Logger', 'display_log')
else:
@exports
class Logger(object):
def __init__(self, title='log', **kwargs):
kwargs.setdefault('width', '75%')
kwargs.setdefault('height', '300px')
kwargs.setdefault('font_family', 'monospace')
self.title = title
self._is_widget = False
self.active = False
self.disabled = True # so user can't overwrite
def _write(self, string):
print(string.strip())
# temporary so that we can use this like a logging module later
error = warning = info = handled = debug = status = _write
@exports
def display_log(obj, title=None, show=False):
"""
Registers a new view. This is mostly so that we can
display all views from a cell in a LoggingTabs object.
:param obj: The object to display. If it has a "get_display_object" method, \
its return value is displayed
:param title: A name for the object (otherwise, str(obj) is used)
:return:
"""
print(obj)
@exports
class DynamicsLog(object):
ROW_FORMAT = ("{:<10.2f}") + 3*(" {:>15.4f}")
HEADER_FORMAT = ROW_FORMAT.replace('.4f','s').replace('.2f','s')
def __init__(self):
self._printed_header = False
def print_header(self):
timeheader = 'time /'
peheader = 'potential /'
keheader = 'kinetic /'
temperatureheader = 'T /'
print(self.HEADER_FORMAT.format(timeheader, peheader, keheader, temperatureheader))
timeunits = '{}'.format(u.default.time)
peunits = '{}'.format(u.default.energy)
keunits = '{}'.format(u.default.energy)
temperatureunits = '{}'.format(u.default.temperature)
print(self.HEADER_FORMAT.format(timeunits, peunits, keunits, temperatureunits))
self._printed_header = True
def print_step(self, mol, properties):
from . import kinetic_energy, kinetic_temperature
if not self._printed_header:
self.print_header()
ke = kinetic_energy(properties['momenta'], mol.masses)
t = kinetic_temperature(ke, mol.dynamic_dof)
print(self.ROW_FORMAT.format(properties['time'].defunits_value(),
properties['potential_energy'].defunits_value(),
ke.defunits_value(),
t.defunits_value()))
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/utils/descriptors.py | .py | 2,890 | 95 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
class Alias(object):
"""
Descriptor that delegates to a child's attribute or method.
e.g.
>>> class A(object):
>>> childkeys = Alias('child.keys')
>>> child = dict()
>>>
>>> a = A()
>>> a.child['key'] = 'value'
>>> a.childkeys() # calls a.child.keys(), returns ['key']
['key']
"""
def __init__(self, objattr):
objname, attrname = objattr.split('.')
self.objname = objname
self.attrname = attrname
def __get__(self, instance, owner):
if instance is None:
assert owner is not None
return _unbound_getter(self.objname, self.attrname)
else:
proxied = getattr(instance, self.objname)
return getattr(proxied, self.attrname)
def __set__(self, instance, value):
if instance is None:
raise NotImplementedError()
else:
proxied = getattr(instance, self.objname)
setattr(proxied, self.attrname, value)
def _unbound_getter(objname, methodname):
def _method_getter(s, *args, **kwargs):
obj = getattr(s, objname)
meth = getattr(obj, methodname)
return meth(*args, **kwargs)
return _method_getter
class IndexView(object):
def __init__(self, attr, index):
self.attr = attr
self.index = index
def __get__(self, instance, owner):
return getattr(instance, self.attr)[self.index]
class Synonym(object):
""" An attribute (class or intance) that is just a synonym for another.
"""
def __init__(self, name):
self.name = name
def __get__(self, instance, owner):
return getattr(instance, self.name)
def __set__(self, instance, value):
setattr(instance, self.name, value)
class Attribute(object):
"""For overriding a property in a superclass - turns the attribute back
into a normal instance attribute"""
def __init__(self, name):
self.name = name
def __get__(self, instance, cls):
return getattr(instance, self.name)
def __set__(self, instance, value):
return setattr(instance, self.name, value)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/utils/classes.py | .py | 6,291 | 226 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import collections
from .descriptors import Alias
class Categorizer(dict):
"""
Create a dict of lists from an iterable, with dict keys given by keyfn
"""
def __init__(self, keyfn, iterable):
super().__init__()
self.keyfn = keyfn
for item in iterable:
self.add(item)
def add(self, item):
key = self.keyfn(item)
if key not in self:
self[key] = []
self[key].append(item)
class NewUserDict(collections.MutableMapping):
""" Reimplementation of UserDict with new-style classes but without subclassing dict.
In addition to the normal dict methods, the only addition here is the ``data`` attribute
that gives us an actual ``dict`` to store things in
Unlike dict, pickles easily.
Unlike UserDict, uses new-style classes.
"""
def __init__(self, *args, **kwargs):
self.data = dict(*args, **kwargs)
__delitem__ = Alias('data.__delitem__')
__setitem__ = Alias('data.__setitem__')
__getitem__ = Alias('data.__getitem__')
__len__ = Alias('data.__len__')
__iter__ = Alias('data.__iter__')
class ExclusiveList(object):
""" Behaves like a list, but won't allow items with duplicate keys to be added.
"""
def __init__(self, iterable=None, key=None):
self._keys = collections.OrderedDict()
if key is None:
self._keyfn = self._identity
else:
self._keyfn = key
if iterable is not None:
self.extend(iterable)
def append(self, obj):
k = self._keyfn(obj)
if k in self._keys:
raise KeyError("'%s' can't be added because its key '%s' already exists" % (obj, k))
else:
self._keys[k] = obj
def clear(self):
self._keys = collections.OrderedDict()
@staticmethod
def _identity(obj):
return obj
def __iter__(self):
return iter(self._keys.values())
def __len__(self):
return len(self._keys)
def __getitem__(self, item):
return list(self._keys.values())[item]
def remove(self, obj):
k = self._keyfn(obj)
stored = self._keys[k]
if obj is not stored:
raise KeyError(obj)
else:
self._keys.pop(k)
def extend(self, iterable):
for item in iterable:
self.append(item)
def pop(self, index=None):
if index is None:
return self._keys.popitem()[1]
else:
k = list(self._keys.keys())[index]
return self._keys.pop(k)
def __repr__(self):
return '%s(%s)' % (type(self).__name__, list(self._keys.values()))
__str__ = __repr__
class DotDict(object):
""" An attribute-accessible dictionary that preserves insertion order
"""
def __init__(self, *args, **kwargs):
self._od = collections.OrderedDict(*args, **kwargs)
self._init = True
def __delattr__(self, item):
if not self.__dict__.get('_init', False):
super().__delattr__(item)
else:
try:
del self._od[item]
except KeyError:
raise AttributeError()
def __delitem__(self, key):
if not self.__dict__.get('_init', False):
raise TypeError()
else:
del self._od[key]
def __dir__(self):
return list(self.keys()) + super().__dir__()
def __getstate__(self):
return {'od': self._od}
def __setstate__(self, state):
self._od = state['od']
self._init = True
def copy(self):
return self.__class__(self._od.copy())
def copydict(self):
""" Returns a copy of the core dictionary in its native class
"""
return self._od.copy()
def __eq__(self, other):
try:
return self._od == other._od
except AttributeError:
return False
def __repr__(self):
return str(self._od).replace('OrderedDict', self.__class__.__name__)
def __getattr__(self, key):
if not self.__dict__.get('_init', False):
return self.__getattribute__(key)
if key in self._od:
return self._od[key]
else:
raise AttributeError(key)
def __setattr__(self, key, val):
if not self.__dict__.get('_init', False):
super().__setattr__(key, val)
else:
self._od[key] = val
def __bool__(self):
return bool(self._od)
__nonzero__ = __bool__
for _v in ('keys values items __iter__ __getitem__ __len__ __contains__ clear '
' __setitem__ pop setdefault get update').split():
setattr(DotDict, _v, Alias('_od.%s' % _v))
def named_dict(l):
""" Creates a DotDict from a list of items that have a ``name`` attribute
Args:
l (List[object]): list of objects that have a ``name`` or ``__name__`` attribute
Returns:
DotDict[str, object]: mapping of objects' names to objects
Example:
>>> import moldesign as mdt
>>> m1 = mdt.from_name('benzene')
>>> m2 = mdt.from_name('propane')
>>> d = named_dict([m1, m2, DotDict])
>>> list(d.keys())
['benzene', 'propane', 'DotDict']
>>> d.propane
<propane (Molecule), 11 atoms>
>>> d.DotDict
moldesign.utils.classes.DotDict
"""
return DotDict((_namegetter(obj), obj) for obj in l)
def _namegetter(obj):
try:
return obj.name
except AttributeError:
return obj.__name__
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/utils/__init__.py | .py | 844 | 25 | # Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import absolute_import
from .exportutils import *
from . import docparsers
from .callsigs import *
from .descriptors import *
from .classes import *
from .databases import *
from .utils import *
from .numerical import *
from .json_extension import *
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/utils/databases.py | .py | 2,281 | 82 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import json
import zlib
import future.utils
from . import Alias
if future.utils.PY2:
import dumbdbm
else:
import dbm.dumb as dumbdbm
class CompressedJsonDbm(object):
""" Quick-and-dirty interface to a DBM file
"""
def __init__(self, filename, flag='r', dbm=dumbdbm):
self.dbm = dbm
if hasattr(dbm, 'open'):
self.db = self.dbm.open(filename, flag)
else:
self.db = self.dbm(filename, flag)
def __getattr__(self, item):
return getattr(self.db, item)
def __dir__(self):
return list(self.__dict__.keys()) + dir(self.db)
def __len__(self):
return len(self.db)
def __getitem__(self, key):
gzvalue = self.db[key]
return json.loads(zlib.decompress(gzvalue).decode())
def __setitem__(self, key, value):
gzvalue = zlib.compress(json.dumps(value))
self.db[key] = gzvalue
__contains__ = Alias('db.__contains__')
class ReadOnlyDumb(dumbdbm._Database):
""" A read-only subclass of dumbdbm
All possible operations that could result in a disk write have been turned into no-ops or raise
exceptions
"""
def _commit(self):
# Does nothing!
pass
def __setitem__(self, key, value):
raise NotImplementedError('This is a read-only database')
def __delitem__(self, key):
raise NotImplementedError('This is a read-only database')
def _addkey(self, *args):
assert False, 'Should never be here - this is a read-only database'
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/utils/numerical.py | .py | 3,902 | 107 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
from . import Alias
class ResizableArray(object):
""" Behaves like a numpy array, but with fast extends and appends for the first index.
Similar to python lists, the underlying array is reallocated in large chunks whenever the
number of elements grows beyond the current memory allocation.
"""
#@args_from(np.array)
def __init__(self, *args, **kwargs):
self._array = np.array(*args, **kwargs)
self._len = len(self._array)
self._subarray = self._array[:self._len]
self._size = self._len
def __getattr__(self, item):
if item == '_subarray':
return self.__getattribute__('_subarray')
return getattr(self._subarray, item)
def __repr__(self):
return '%s(%s)' % (self.__class__.__name__, repr(self._subarray))
def append(self, item):
self.extend([item])
def extend(self, its):
try:
ll = len(its)
except TypeError:
its = list(its)
ll = len(its)
newlen = self._len + ll
if newlen > self._size:
self._resize(newlen)
for item in its:
self._array[self._len] = item
self._len += 1
self._subarray = self._array[:self._len]
def _resize(self, minsize):
newsize = round_up_to_power_of_two(minsize)
if newsize <= self._size:
return
newshape = (newsize,) + self._array.shape[1:]
newarray = np.empty(newshape, dtype=self._array.dtype)
newarray[:self._len] = self._array
self._array = newarray
self._size = newsize
# delegate magic methods as well - this is a list of all math-related array methods
_ARRAYMAGIC = ('__abs__', '__add__', '__and__', '__array__', '__contains__', '__copy__',
'__deepcopy__', '__delitem__', '__delslice__', '__div__', '__divmod__', '__eq__',
'__float__', '__floordiv__', '__ge__', '__getitem__', '__getslice__', '__gt__',
'__hex__', '__iadd__', '__iand__', '__idiv__', '__ifloordiv__', '__ilshift__',
'__imod__', '__imul__', '__index__', '__int__', '__invert__', '__ior__', '__ipow__',
'__irshift__', '__isub__', '__itruediv__', '__ixor__', '__le__', '__len__',
'__long__', '__lshift__', '__lt__', '__mod__', '__mul__', '__ne__', '__neg__',
'__nonzero__', '__oct__', '__or__', '__pos__', '__pow__', '__radd__', '__rand__',
'__rdiv__', '__rdivmod__', '__rfloordiv__', '__rlshift__', '__rmod__', '__rmul__',
'__ror__', '__rpow__', '__rrshift__', '__rshift__', '__rsub__', '__rtruediv__',
'__rxor__', '__setitem__', '__setslice__', '__str__', '__sub__',
'__truediv__', '__xor__')
for _methname in _ARRAYMAGIC:
setattr(ResizableArray, _methname, Alias('_subarray.%s' % _methname))
def round_up_to_power_of_two(n):
"""
From http://stackoverflow.com/a/14267825/1958900
"""
if n < 0:
raise TypeError("Nonzero positive integers only")
elif n == 0:
return 1
else:
return 1 << (n-1).bit_length()
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/utils/exportutils.py | .py | 1,476 | 50 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import inspect
__all__ = 'exports exports_names'.split()
def exports(f):
""" Add a function to its module's __all__ attribute
"""
all_list = _get_module_all(1)
all_list.append(f.__name__)
return f
def exports_names(*names):
""" Add names to this module's __all__ attribute
"""
all_list = _get_module_all(1)
all_list.extend(names)
def _get_module_all(depth):
"""
Get a reference to the __all__ attribute of the module calling the function that
calls this function :)
FROM http://stackoverflow.com/q/6187355/1958900"""
frm = inspect.stack()[depth+1]
mod = inspect.getmodule(frm[0])
if not hasattr(mod, '__all__'):
mod.__all__ = []
return mod.__all__
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/utils/utils.py | .py | 9,726 | 329 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
import future.utils
from functools import reduce
import fractions
import operator
import os
import re
import sys
import tempfile
from html.parser import HTMLParser
def make_none(*args, **kwargs):
return None
def if_not_none(item, default):
""" Equivalent to `item if item is not None else default` """
if item is None:
return default
else:
return item
class MLStripper(HTMLParser):
""" Strips markup language tags from a string.
FROM http://stackoverflow.com/a/925630/1958900
"""
def __init__(self):
if not future.utils.PY2:
super().__init__()
self.reset()
self.fed = []
self.strict = False
self.convert_charrefs = True
def handle_data(self, d):
self.fed.append(d)
def get_data(self):
return ''.join(self.fed)
def html_to_text(html):
"""
FROM http://stackoverflow.com/a/925630/1958900
"""
s = MLStripper()
s.unescape = True # convert HTML entities to text
s.feed(html)
return s.get_data()
def printflush(s, newline=True):
if newline:
print(s)
else:
print(s, end=' ')
sys.stdout.flush()
def which(cmd, mode=os.F_OK | os.X_OK, path=None):
"""Given a command, mode, and a PATH string, return the path which
conforms to the given mode on the PATH, or None if there is no such
file.
`mode` defaults to os.F_OK | os.X_OK. `path` defaults to the result
of os.environ.get("PATH"), or can be overridden with a custom search
path.
Note:
Copied without modification from Python 3.6.1 ``shutil.which`
source code
"""
# Check that a given file can be accessed with the correct mode.
# Additionally check that `file` is not a directory, as on Windows
# directories pass the os.access check.
def _access_check(fn, mode):
return (os.path.exists(fn) and os.access(fn, mode)
and not os.path.isdir(fn))
# If we're given a path with a directory part, look it up directly rather
# than referring to PATH directories. This includes checking relative to the
# current directory, e.g. ./script
if os.path.dirname(cmd):
if _access_check(cmd, mode):
return cmd
return None
if path is None:
path = os.environ.get("PATH", os.defpath)
if not path:
return None
path = path.split(os.pathsep)
if sys.platform == "win32":
# The current directory takes precedence on Windows.
if not os.curdir in path:
path.insert(0, os.curdir)
# PATHEXT is necessary to check on Windows.
pathext = os.environ.get("PATHEXT", "").split(os.pathsep)
# See if the given file matches any of the expected path extensions.
# This will allow us to short circuit when given "python.exe".
# If it does match, only test that one, otherwise we have to try
# others.
if any(cmd.lower().endswith(ext.lower()) for ext in pathext):
files = [cmd]
else:
files = [cmd + ext for ext in pathext]
else:
# On other platforms you don't have things like PATHEXT to tell you
# what file suffixes are executable, so just pass on cmd as-is.
files = [cmd]
seen = set()
for dir in path:
normdir = os.path.normcase(dir)
if not normdir in seen:
seen.add(normdir)
for thefile in files:
name = os.path.join(dir, thefile)
if _access_check(name, mode):
return name
return None
class methodcaller(object):
"""The pickleable implementation of the standard library operator.methodcaller.
This was copied without modification from:
https://github.com/python/cpython/blob/065990fa5bd30fb3ca61b90adebc7d8cb3f16b5a/Lib/operator.py
The c-extension version is not pickleable, so we keep a copy of the pure-python standard library
code here. See https://bugs.python.org/issue22955
Original documentation:
Return a callable object that calls the given method on its operand.
After f = methodcaller('name'), the call f(r) returns r.name().
After g = methodcaller('name', 'date', foo=1), the call g(r) returns
r.name('date', foo=1).
"""
__slots__ = ('_name', '_args', '_kwargs')
def __init__(*args, **kwargs):
if len(args) < 2:
msg = "methodcaller needs at least one argument, the method name"
raise TypeError(msg)
self = args[0]
self._name = args[1]
if not isinstance(self._name, future.utils.native_str):
raise TypeError('method name must be a string')
self._args = args[2:]
self._kwargs = kwargs
def __call__(self, obj):
return getattr(obj, self._name)(*self._args, **self._kwargs)
def __repr__(self):
args = [repr(self._name)]
args.extend(list(map(repr, self._args)))
args.extend('%s=%r' % (k, v) for k, v in list(self._kwargs.items()))
return '%s.%s(%s)' % (self.__class__.__module__,
self.__class__.__name__,
', '.join(args))
def __reduce__(self):
if not self._kwargs:
return self.__class__, (self._name,) + self._args
else:
from functools import partial
return partial(self.__class__, self._name, **self._kwargs), self._args
class textnotify(object):
""" Print a single, immediately flushed line to log the execution of a block.
Prints 'done' at the end of the line (or 'ERROR' if an uncaught exception)
Examples:
>>> import time
>>> with textnotify('starting to sleep'):
>>> time.sleep(3)
starting to sleep...done
>>> with textnotify('raising an exception...'):
>>> raise ValueError()
raising an exception...error
ValueError [...]
"""
def __init__(self, startmsg):
if startmsg.strip()[-3:] != '...':
startmsg = startmsg.strip() + '...'
self.startmsg = startmsg
def __enter__(self):
printflush(self.startmsg, newline=False)
def __exit__(self, exc_type, exc_val, exc_tb):
if exc_type is None:
printflush('done')
else:
printflush('ERROR')
class BaseTable(object):
def __init__(self, categories, fileobj=None):
self.categories = categories
self.lines = []
self.fileobj = fileobj
def add_line(self, obj):
if hasattr(obj, 'keys'):
newline = [obj.get(cat, '') for cat in self.categories]
else:
assert len(obj) == len(self.categories)
newline = obj
self.lines.append(newline)
self.writeline(newline)
def writeline(self, newline):
raise NotImplementedError()
def getstring(self):
raise NotImplementedError()
class MarkdownTable(BaseTable):
def __init__(self, *categories):
super().__init__(categories)
def markdown(self, replace=None):
if replace is None: replace = {}
outlines = ['| ' + ' | '.join(self.categories) + ' |',
'|-' + ''.join('|-' for x in self.categories) + '|']
for line in self.lines:
nextline = [str(replace.get(val, val)) for val in line]
outlines.append('| ' + ' | '.join(nextline) + ' |')
return '\n'.join(outlines)
def writeline(self, newline):
pass
def getstring(self):
return self.markdown()
def binomial_coefficient(n, k):
# credit to http://stackoverflow.com/users/226086/nas-banov
return int(reduce(operator.mul,
(fractions.Fraction(n - i, i + 1) for i in range(k)), 1))
def pairwise_displacements(a):
"""
:type a: numpy.array
from http://stackoverflow.com/questions/22390418/pairwise-displacement-vectors-among-set-of-points
"""
import numpy as np
n = a.shape[0]
d = a.shape[1]
c = binomial_coefficient(n, 2)
out = np.zeros((c, d))
l = 0
r = l + n - 1
for sl in range(1, n): # no point1 - point1!
out[l:r] = a[:n - sl] - a[sl:]
l = r
r += n - (sl + 1)
return out
def is_printable(s):
import string
for c in s:
if c not in string.printable:
return False
else:
return True
class _RedirectStream(object):
"""From python3.4 stdlib
"""
_stream = None
def __init__(self, new_target):
self._new_target = new_target
# We use a list of old targets to make this CM re-entrant
self._old_targets = []
def __enter__(self):
self._old_targets.append(getattr(sys, self._stream))
setattr(sys, self._stream, self._new_target)
return self._new_target
def __exit__(self, exctype, excinst, exctb):
setattr(sys, self._stream, self._old_targets.pop())
class redirect_stderr(_RedirectStream):
"""From python3.4 stdlib"""
_stream = "stderr"
GETFLOAT = re.compile(r'-?\d+(\.\d+)?(e[-+]?\d+)') # matches numbers, e.g. 1, -2.0, 3.5e50, 0.001e-10
def from_filepath(func, filelike):
"""Run func on a temporary *path* assigned to filelike"""
if type(filelike) == str:
return func(filelike)
else:
with tempfile.NamedTemporaryFile() as outfile:
outfile.write(filelike.read().encode()) # hack - prob need to detect bytes
outfile.flush()
result = func(outfile.name)
return result
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/utils/json_extension.py | .py | 1,405 | 42 | # Copyright 2016 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import absolute_import
import json
from . import args_from
# TODO: defined JSON types that we can serialize directly into MDT objects OR
# use a JSON "pickling" library (only if there's more complexity than covered here already)
class JsonEncoder(json.JSONEncoder):
def default(self, obj):
if hasattr(obj, 'to_json'):
return obj.to_json()
elif hasattr(obj, 'tolist'):
return obj.tolist()
else:
raise TypeError('No seralizer for object "%s" (class: %s)'
% (obj,obj.__class__.__name__))
@args_from(json.dump)
def json_dump(*args, **kwargs):
return json.dump(*args, cls=JsonEncoder, **kwargs)
@args_from(json.dumps)
def json_dumps(*args, **kwargs):
return json.dumps(*args, cls=JsonEncoder, **kwargs)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/utils/apply_copyright.sh | .sh | 729 | 22 | #!/bin/bash
for file in `grep -L "Copyright 2016 Autodesk Inc." *.py`; do
mv $file{.bak}
cat > $file <<EOF
# Copyright 2016 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
EOF
cat $file.bak >> $file
done
| Shell |
3D | Autodesk/molecular-design-toolkit | moldesign/utils/callsigs.py | .py | 9,122 | 259 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import functools
import inspect
import os
from functools import wraps
import collections
import funcsigs
from .utils import if_not_none
from .docparsers import GoogleDocArgumentInjector
def args_from(original_function,
only=None,
allexcept=None,
inject_kwargs=None,
inject_docs=None,
wraps=None,
update_docstring_args=False):
"""
Decorator to transfer call signatures - helps to hide ugly *args and **kwargs in delegated calls
Args:
original_function (callable): the function to take the call signature from
only (List[str]): only transfer these arguments (incompatible with `allexcept`)
wraps (bool): Transfer documentation and attributes from original_function to
decorated_function, using functools.wraps (default: True if call signature is
unchanged, False otherwise)
allexcept (List[str]): transfer all except these arguments (incompatible with `only`)
inject_kwargs (dict): Inject new kwargs into the call signature
(of the form ``{argname: defaultvalue}``)
inject_docs (dict): Add or modifies argument documentation (requires google-style
docstrings) with a dict of the form `{argname: "(type): description"}`
update_docstring_args (bool): Update "arguments" section of the docstring using the
original function's documentation (requires google-style docstrings and wraps=False)
Note:
To use arguments from a classes' __init__ method, pass the class itself as
``original_function`` - this will also allow us to inject the documentation
Returns:
Decorator function
"""
# NEWFEATURE - verify arguments?
if only and allexcept:
raise ValueError('Error in keyword arguments - '
'pass *either* "only" or "allexcept", not both')
origname = get_qualified_name(original_function)
if hasattr(original_function, '__signature__'):
sig = original_function.__signature__.replace()
else:
sig = funcsigs.signature(original_function)
# Modify the call signature if necessary
if only or allexcept or inject_kwargs:
wraps = if_not_none(wraps, False)
newparams = []
if only:
for param in only:
newparams.append(sig.parameters[param])
elif allexcept:
for name, param in sig.parameters.items():
if name not in allexcept:
newparams.append(param)
else:
newparams = list(sig.parameters.values())
if inject_kwargs:
for name, default in inject_kwargs.items():
newp = funcsigs.Parameter(name, funcsigs.Parameter.POSITIONAL_OR_KEYWORD,
default=default)
newparams.append(newp)
newparams.sort(key=lambda param: param._kind)
sig = sig.replace(parameters=newparams)
else:
wraps = if_not_none(wraps, True)
# Get the docstring arguments
if update_docstring_args:
original_docs = GoogleDocArgumentInjector(original_function.__doc__)
argument_docstrings = collections.OrderedDict((p.name, original_docs.args[p.name])
for p in newparams)
def decorator(f):
"""Modify f's call signature (using the `__signature__` attribute)"""
if wraps:
fname = original_function.__name__
f = functools.wraps(original_function)(f)
f.__name__ = fname # revert name change
else:
fname = f.__name__
f.__signature__ = sig
if update_docstring_args or inject_kwargs:
if not update_docstring_args:
argument_docstrings = GoogleDocArgumentInjector(f.__doc__).args
docs = GoogleDocArgumentInjector(f.__doc__)
docs.args = argument_docstrings
if not hasattr(f, '__orig_docs'):
f.__orig_docs = []
f.__orig_docs.append(f.__doc__)
f.__doc__ = docs.new_docstring()
# Only for building sphinx documentation:
if os.environ.get('SPHINX_IS_BUILDING_DOCS', ""):
sigstring = '%s%s\n' % (fname, sig)
if hasattr(f, '__doc__') and f.__doc__ is not None:
f.__doc__ = sigstring + f.__doc__
else:
f.__doc__ = sigstring
return f
return decorator
def kwargs_from(reference_function, mod_docs=True):
""" Replaces ``**kwargs`` in a call signature with keyword arguments from another function.
Args:
reference_function (function): function to get kwargs from
mod_docs (bool): whether to modify the decorated function's docstring
Note:
``mod_docs`` works ONLY for google-style docstrings
"""
refsig = funcsigs.signature(reference_function)
origname = get_qualified_name(reference_function)
kwparams = []
for name, param in refsig.parameters.items():
if param.default != param.empty or param.kind in (param.VAR_KEYWORD, param.KEYWORD_ONLY):
if param.name[0] != '_':
kwparams.append(param)
if mod_docs:
refdocs = GoogleDocArgumentInjector(reference_function.__doc__)
def decorator(f):
sig = funcsigs.signature(f)
fparams = []
found_varkeyword = None
for name, param in sig.parameters.items():
if param.kind == param.VAR_KEYWORD:
fparams.extend(kwparams)
found_varkeyword = name
else:
fparams.append(param)
if not found_varkeyword:
raise TypeError("Function has no **kwargs wildcard.")
f.__signature__ = sig.replace(parameters=fparams)
if mod_docs:
docs = GoogleDocArgumentInjector(f.__doc__)
new_args = collections.OrderedDict()
for argname, doc in docs.args.items():
if argname == found_varkeyword:
for param in kwparams:
default_argdoc = '%s: argument for %s' % (param.name, origname)
new_args[param.name] = refdocs.args.get(param.name, default_argdoc)
else:
new_args[argname] = doc
docs.args = new_args
if not hasattr(f, '__orig_docs'):
f.__orig_docs = []
f.__orig_docs.append(f.__doc__)
f.__doc__ = docs.new_docstring()
return f
return decorator
def get_qualified_name(original_function):
if inspect.ismethod(original_function):
origname = '.'.join([original_function.__module__,
original_function.__self__.__class__.__name__,
original_function.__name__])
return ':meth:`%s`' % origname
else:
origname = original_function.__module__+'.'+original_function.__name__
return ':meth:`%s`' % origname
class DocInherit(object):
"""
Allows methods to inherit docstrings from their superclasses
FROM http://code.activestate.com/recipes/576862/
"""
def __init__(self, mthd):
self.mthd = mthd
self.name = mthd.__name__
def __get__(self, obj, cls):
if obj:
return self.get_with_inst(obj, cls)
else:
return self.get_no_inst(cls)
def get_with_inst(self, obj, cls):
overridden = getattr(super(), self.name, None)
@wraps(self.mthd, assigned=('__name__','__module__'))
def f(*args, **kwargs):
return self.mthd(obj, *args, **kwargs)
return self.use_parent_doc(f, overridden)
def get_no_inst(self, cls):
for parent in cls.__mro__[1:]:
overridden = getattr(parent, self.name, None)
if overridden: break
@wraps(self.mthd, assigned=('__name__','__module__'))
def f(*args, **kwargs):
return self.mthd(*args, **kwargs)
return self.use_parent_doc(f, overridden)
def use_parent_doc(self, func, source):
if source is None:
raise NameError("Can't find '%s' in parents"%self.name)
func.__doc__ = source.__doc__
return func
#idiomatic decorator name
doc_inherit = DocInherit | Python |
3D | Autodesk/molecular-design-toolkit | moldesign/utils/docparsers/__init__.py | .py | 46 | 2 | from .google import GoogleDocArgumentInjector
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/utils/docparsers/google.py | .py | 22,562 | 649 | """
Routines for runtime docstring argument injection
This file contains HEAVILY modified routines from sphinx.ext.napoleon, from version 1.4.4
This has been vendored into MDT because the modification makes use of
private functions which have already changed in the dev branch.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
:copyright: Copyright 2007-2016 by the Sphinx team, see sphinxlicense/AUTHORS.
:license: BSD, see sphinxlicense/LICENSE for details.
"""
from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
from past.builtins import basestring
import collections
import re
import sys
_google_section_regex = re.compile(r'^(\s|\w)+:\s*$')
_google_typed_arg_regex = re.compile(r'\s*(.+?)\s*\(\s*(.+?)\s*\)')
_single_colon_regex = re.compile(r'(?<!:):(?!:)')
_xref_regex = re.compile(r'(:\w+:\S+:`.+?`|:\S+:`.+?`|`.+?`)')
_bullet_list_regex = re.compile(r'^(\*|\+|\-)(\s+\S|\s*$)')
_enumerated_list_regex = re.compile(
r'^(?P<paren>\()?'
r'(\d+|#|[ivxlcdm]+|[IVXLCDM]+|[a-zA-Z])'
r'(?(paren)\)|\.)(\s+\S|\s*$)')
class GoogleDocArgumentInjector(object):
SECTIONS = set('args arguments parameters'.split())
def __init__(self, docstring, prepare=True):
# this routine has been modified - it's been streamlined for the current purpose
if prepare:
if docstring is None:
self.docstring = []
else:
self.docstring = prepare_docstring(docstring)
elif isinstance(docstring, basestring):
self.docstring = docstring.splitlines()
else:
self.docstring = docstring
self.lines_before_args = []
self.arg_section = []
self.lines_after_args = []
self.args = collections.OrderedDict()
self.arg_indent = None
self.arg_section_name = 'Args' # default, can be overwritten by the actual section name
self._what = 'function'
self._lines = list(self.docstring)
self._line_iter = modify_iter(self.docstring, modifier=lambda s: s.rstrip())
self._parsed_lines = []
self._is_in_section = False
self._section_indent = 0
self._sections = {
'args': self._parse_parameters_section,
'arguments': self._parse_parameters_section,
'attributes': None,
'example': None,
'examples': None,
'keyword args': None,
'keyword arguments': None,
'methods': None,
'note': None,
'notes': None,
'other parameters': None,
'parameters': self._parse_parameters_section,
'return': None,
'returns': None,
'raises': None,
'references': None,
'see also': None,
'todo': None,
'warning': None,
'warnings': None,
'warns': None,
'yield': None,
'yields': None,
}
self.parse()
def new_docstring(self):
""" Create a new docstring with the current state of the argument list
Returns:
str: docstring with modified argument list
"""
newlines = list(self.lines_before_args)
if self.args:
newlines.append(' '*self.arg_indent + self.arg_section_name + ':')
newlines.extend(self._indent(list(self.args.values()), self.arg_indent+4))
newlines.append('')
newlines.extend(self.lines_after_args)
return '\n'.join(newlines)
def parse(self):
""" This method is a modified version of GoogleDocstring._parse
"""
self._parsed_lines = self._consume_empty()
found_args = lines_are_args = False
while self._line_iter.has_next():
if self._is_section_header():
try:
section = self._consume_section_header()
self._is_in_section = True
self._section_indent = self._get_current_indent()
lines = [section + ':']
if section.lower() in self.SECTIONS:
lines.extend(self._sections[section.lower()](section))
found_args = True
lines_are_args = True
else:
lines.extend(self._consume_to_next_section())
finally:
self._is_in_section = False
self._section_indent = 0
else:
if not self._parsed_lines:
lines = self._consume_contiguous()+self._consume_empty()
else:
lines = self._consume_to_next_section()
if lines_are_args:
lines_are_args = False
self.arg_section.extend(lines)
elif found_args:
self.lines_after_args.extend(lines)
else:
self.lines_before_args.extend(lines)
self._parsed_lines.extend(lines)
if self.arg_indent is None:
self.arg_indent = self._get_current_indent()
def _parse_parameters_section(self, section):
""" This method was heavily modified to store information instead of formatting it for rst
"""
self.arg_section_name = section
fields = self._consume_fields()
num_indent = self._get_current_indent()
self.arg_indent = num_indent
lines = []
for _name, _type, _desc in fields:
_desc = self._strip_empty(_desc)
if isinstance(_desc, list):
_desc = '\n '.join(_desc)
if _type:
line = '%s (%s): %s' % (_name, _type, _desc)
else:
line = '%s: %s' % (_name, _desc)
self.args[_name.lstrip('\*')] = line
lines.append(line)
lines = self._indent(lines, num_indent+4)
if lines[-1].strip():
lines.append('')
return lines
def _indent(self, lines, n=4):
# MDT: modified to include breaks within lines
sp = ' ' * n
return [sp + line.replace('\n', '\n'+sp) for line in lines]
######################################################
### All routines below are unmodified ###
######################################################
def lines(self):
"""Return the parsed lines of the docstring in reStructuredText format.
Returns
-------
:obj:`list` of :obj:`str`
The lines of the docstring in a list.
"""
return self._parsed_lines
def _consume_indented_block(self, indent=1):
lines = []
line = self._line_iter.peek()
while(not self._is_section_break() and
(not line or self._is_indented(line, indent))):
lines.append(next(self._line_iter))
line = self._line_iter.peek()
return lines
def _consume_contiguous(self):
lines = []
while (self._line_iter.has_next() and
self._line_iter.peek() and
not self._is_section_header()):
lines.append(next(self._line_iter))
return lines
def _consume_empty(self):
lines = []
line = self._line_iter.peek()
while self._line_iter.has_next() and not line:
lines.append(next(self._line_iter))
line = self._line_iter.peek()
return lines
def _consume_field(self, parse_type=True, prefer_type=False):
line = next(self._line_iter)
before, colon, after = self._partition_field_on_colon(line)
_name, _type, _desc = before, '', after
if parse_type:
match = _google_typed_arg_regex.match(before)
if match:
_name = match.group(1)
_type = match.group(2)
_name = self._escape_args_and_kwargs(_name)
if prefer_type and not _type:
_type, _name = _name, _type
indent = self._get_indent(line) + 1
_desc = [_desc] + self._dedent(self._consume_indented_block(indent))
_desc = self.__class__(_desc, prepare=False).lines()
return _name, _type, _desc
def _consume_fields(self, parse_type=True, prefer_type=False):
self._consume_empty()
fields = []
while not self._is_section_break():
_name, _type, _desc = self._consume_field(parse_type, prefer_type)
if _name or _type or _desc:
fields.append((_name, _type, _desc,))
return fields
def _consume_section_header(self):
section = next(self._line_iter)
stripped_section = section.strip(':')
if stripped_section.lower() in self._sections:
section = stripped_section
return section
def _consume_to_end(self):
lines = []
while self._line_iter.has_next():
lines.append(next(self._line_iter))
return lines
def _consume_to_next_section(self):
self._consume_empty()
lines = []
while not self._is_section_break():
lines.append(next(self._line_iter))
return lines + self._consume_empty()
def _dedent(self, lines, full=False):
if full:
return [line.lstrip() for line in lines]
else:
min_indent = self._get_min_indent(lines)
return [line[min_indent:] for line in lines]
def _escape_args_and_kwargs(self, name):
if name[:2] == '**':
return r'\*\*' + name[2:]
elif name[:1] == '*':
return r'\*' + name[1:]
else:
return name
def _fix_field_desc(self, desc):
if self._is_list(desc):
desc = [''] + desc
elif desc[0].endswith('::'):
desc_block = desc[1:]
indent = self._get_indent(desc[0])
block_indent = self._get_initial_indent(desc_block)
if block_indent > indent:
desc = [''] + desc
else:
desc = ['', desc[0]] + self._indent(desc_block, 4)
return desc
def _get_current_indent(self, peek_ahead=0):
line = self._line_iter.peek(peek_ahead + 1)[peek_ahead]
while line != self._line_iter.sentinel:
if line:
return self._get_indent(line)
peek_ahead += 1
line = self._line_iter.peek(peek_ahead + 1)[peek_ahead]
return 0
def _get_indent(self, line):
for i, s in enumerate(line):
if not s.isspace():
return i
return len(line)
def _get_initial_indent(self, lines):
for line in lines:
if line:
return self._get_indent(line)
return 0
def _get_min_indent(self, lines):
min_indent = None
for line in lines:
if line:
indent = self._get_indent(line)
if min_indent is None:
min_indent = indent
elif indent < min_indent:
min_indent = indent
return min_indent or 0
def _is_indented(self, line, indent=1):
for i, s in enumerate(line):
if i >= indent:
return True
elif not s.isspace():
return False
return False
def _is_list(self, lines):
if not lines:
return False
if _bullet_list_regex.match(lines[0]):
return True
if _enumerated_list_regex.match(lines[0]):
return True
if len(lines) < 2 or lines[0].endswith('::'):
return False
indent = self._get_indent(lines[0])
next_indent = indent
for line in lines[1:]:
if line:
next_indent = self._get_indent(line)
break
return next_indent > indent
def _is_section_header(self):
section = self._line_iter.peek().lower()
match = _google_section_regex.match(section)
if match and section.strip(':') in self._sections:
header_indent = self._get_indent(section)
section_indent = self._get_current_indent(peek_ahead=1)
return section_indent > header_indent
return False
def _is_section_break(self):
line = self._line_iter.peek()
return (not self._line_iter.has_next() or
self._is_section_header() or
(self._is_in_section and
line and
not self._is_indented(line, self._section_indent)))
def _partition_field_on_colon(self, line):
before_colon = []
after_colon = []
colon = ''
found_colon = False
for i, source in enumerate(_xref_regex.split(line)):
if found_colon:
after_colon.append(source)
else:
m = _single_colon_regex.search(source)
if (i % 2) == 0 and m:
found_colon = True
colon = source[m.start(): m.end()]
before_colon.append(source[:m.start()])
after_colon.append(source[m.end():])
else:
before_colon.append(source)
return ("".join(before_colon).strip(),
colon,
"".join(after_colon).strip())
def _strip_empty(self, lines):
if lines:
start = -1
for i, line in enumerate(lines):
if line:
start = i
break
if start == -1:
lines = []
end = -1
for i in reversed(range(len(lines))):
line = lines[i]
if line:
end = i
break
if start > 0 or end + 1 < len(lines):
lines = lines[start:end + 1]
return lines
class peek_iter(object):
"""An iterator object that supports peeking ahead.
Parameters
----------
o : iterable or callable
`o` is interpreted very differently depending on the presence of
`sentinel`.
If `sentinel` is not given, then `o` must be a collection object
which supports either the iteration protocol or the sequence protocol.
If `sentinel` is given, then `o` must be a callable object.
sentinel : any value, optional
If given, the iterator will call `o` with no arguments for each
call to its `next` method; if the value returned is equal to
`sentinel`, :exc:`StopIteration` will be raised, otherwise the
value will be returned.
See Also
--------
`peek_iter` can operate as a drop in replacement for the built-in
`iter <https://docs.python.org/2/library/functions.html#iter>`_ function.
Attributes
----------
sentinel
The value used to indicate the iterator is exhausted. If `sentinel`
was not given when the `peek_iter` was instantiated, then it will
be set to a new object instance: ``object()``.
"""
def __init__(self, *args):
"""__init__(o, sentinel=None)"""
self._iterable = iter(*args)
self._cache = collections.deque()
if len(args) == 2:
self.sentinel = args[1]
else:
self.sentinel = object()
def __iter__(self):
return self
def __next__(self, n=None):
# note: prevent 2to3 to transform self.next() in next(self) which
# causes an infinite loop !
return getattr(self, 'next')(n)
def _fillcache(self, n):
"""Cache `n` items. If `n` is 0 or None, then 1 item is cached."""
if not n:
n = 1
try:
while len(self._cache) < n:
self._cache.append(next(self._iterable))
except StopIteration:
while len(self._cache) < n:
self._cache.append(self.sentinel)
def has_next(self):
"""Determine if iterator is exhausted.
Returns
-------
bool
True if iterator has more items, False otherwise.
Note
----
Will never raise :exc:`StopIteration`.
"""
return self.peek() != self.sentinel
def next(self, n=None):
"""Get the next item or `n` items of the iterator.
Parameters
----------
n : int or None
The number of items to retrieve. Defaults to None.
Returns
-------
item or list of items
The next item or `n` items of the iterator. If `n` is None, the
item itself is returned. If `n` is an int, the items will be
returned in a list. If `n` is 0, an empty list is returned.
Raises
------
StopIteration
Raised if the iterator is exhausted, even if `n` is 0.
"""
self._fillcache(n)
if not n:
if self._cache[0] == self.sentinel:
raise StopIteration
if n is None:
result = self._cache.popleft()
else:
result = []
else:
if self._cache[n - 1] == self.sentinel:
raise StopIteration
result = [self._cache.popleft() for i in range(n)]
return result
def peek(self, n=None):
"""Preview the next item or `n` items of the iterator.
The iterator is not advanced when peek is called.
Returns
-------
item or list of items
The next item or `n` items of the iterator. If `n` is None, the
item itself is returned. If `n` is an int, the items will be
returned in a list. If `n` is 0, an empty list is returned.
If the iterator is exhausted, `peek_iter.sentinel` is returned,
or placed as the last item in the returned list.
Note
----
Will never raise :exc:`StopIteration`.
"""
self._fillcache(n)
if n is None:
result = self._cache[0]
else:
result = [self._cache[i] for i in range(n)]
return result
class modify_iter(peek_iter):
"""An iterator object that supports modifying items as they are returned.
Parameters
----------
o : iterable or callable
`o` is interpreted very differently depending on the presence of
`sentinel`.
If `sentinel` is not given, then `o` must be a collection object
which supports either the iteration protocol or the sequence protocol.
If `sentinel` is given, then `o` must be a callable object.
sentinel : any value, optional
If given, the iterator will call `o` with no arguments for each
call to its `next` method; if the value returned is equal to
`sentinel`, :exc:`StopIteration` will be raised, otherwise the
value will be returned.
modifier : callable, optional
The function that will be used to modify each item returned by the
iterator. `modifier` should take a single argument and return a
single value. Defaults to ``lambda x: x``.
If `sentinel` is not given, `modifier` must be passed as a keyword
argument.
Attributes
----------
modifier : callable
`modifier` is called with each item in `o` as it is iterated. The
return value of `modifier` is returned in lieu of the item.
Values returned by `peek` as well as `next` are affected by
`modifier`. However, `modify_iter.sentinel` is never passed through
`modifier`; it will always be returned from `peek` unmodified.
Example
-------
>>> a = [" A list ",
... " of strings ",
... " with ",
... " extra ",
... " whitespace. "]
>>> modifier = lambda s: s.strip().replace('with', 'without')
>>> for s in modify_iter(a, modifier=modifier):
... print('"%s"' % s)
"A list"
"of strings"
"without"
"extra"
"whitespace."
"""
def __init__(self, *args, **kwargs):
"""__init__(o, sentinel=None, modifier=lambda x: x)"""
if 'modifier' in kwargs:
self.modifier = kwargs['modifier']
elif len(args) > 2:
self.modifier = args[2]
args = args[:2]
else:
self.modifier = lambda x: x
if not callable(self.modifier):
raise TypeError('modify_iter(o, modifier): '
'modifier must be callable')
super().__init__(*args)
def _fillcache(self, n):
"""Cache `n` modified items. If `n` is 0 or None, 1 item is cached.
Each item returned by the iterator is passed through the
`modify_iter.modified` function before being cached.
"""
if not n:
n = 1
try:
while len(self._cache) < n:
self._cache.append(self.modifier(next(self._iterable)))
except StopIteration:
while len(self._cache) < n:
self._cache.append(self.sentinel)
def prepare_docstring(s, ignore=1):
"""Convert a docstring into lines of parseable reST. Remove common leading
indentation, where the indentation of a given number of lines (usually just
one) is ignored.
Return the docstring as a list of lines usable for inserting into a docutils
ViewList (used as argument of nested_parse().) An empty line is added to
act as a separator between this docstring and following content.
"""
lines = s.expandtabs().splitlines()
# Find minimum indentation of any non-blank lines after ignored lines.
margin = sys.maxsize
for line in lines[ignore:]:
content = len(line.lstrip())
if content:
indent = len(line) - content
margin = min(margin, indent)
# Remove indentation from ignored lines.
for i in range(ignore):
if i < len(lines):
lines[i] = lines[i].lstrip()
if margin < sys.maxsize:
for i in range(ignore, len(lines)):
lines[i] = lines[i][margin:]
# Remove any leading blank lines.
while lines and not lines[0]:
lines.pop(0)
# make sure there is an empty line at the end
if lines and lines[-1]:
lines.append('')
return lines | Python |
3D | Autodesk/molecular-design-toolkit | moldesign/interfaces/ambertools.py | .py | 6,291 | 161 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import moldesign as mdt
from .. import compute, utils
from ..compute import packages
from .. import units as u
from ..molecules import AtomicProperties
@utils.kwargs_from(mdt.compute.run_job)
def calc_am1_bcc_charges(mol, **kwargs):
"""Calculate am1 bcc charges
Args:
mol (moldesign.Molecule): assign partial charges to this molecule
(they will be stored at ``mol.properties['am1-bcc']``)
Note:
This will implicity run an AM1 energy minimization before calculating the final
partial charges. For more control over this process, use the
``moldesign.models.SQMPotential`` energy model to calculate the charges.
Returns:
Mapping[moldesign.Atom, units.Scalar[charge]]: AM1-BCC partial charges on each atom
"""
return _antechamber_calc_charges(mol, 'bcc', 'am1-bcc', kwargs)
@utils.kwargs_from(mdt.compute.run_job)
def calc_gasteiger_charges(mol, **kwargs):
"""Calculate gasteiger charges
Args:
mol (moldesign.Molecule): assign partial charges to this molecule
Returns:
Mapping[moldesign.Atom, units.Scalar[charge]]: gasteiger partial charges on each atom
(they will be stored at ``mol.properties['gasteiger']``)
"""
return _antechamber_calc_charges(mol, 'gas', 'gasteiger', kwargs)
def _antechamber_calc_charges(mol, ambname, chargename, kwargs):
charge = utils.if_not_none(mol.charge, 0)
command = 'antechamber -fi mol2 -i mol.mol2 -fo mol2 -o out.mol2 -c %s -an n'%ambname
if charge != 0:
command += ' -nc %d' % charge.value_in(u.q_e)
def finish_job(job):
"""Callback to complete the job"""
lines = iter(job.get_output('out.mol2').read().split('\n'))
charges = {}
line = next(lines)
while line.strip()[:len('@<TRIPOS>ATOM')] != '@<TRIPOS>ATOM':
line = next(lines)
line = next(lines)
while line.strip()[:len('@<TRIPOS>BOND')] != '@<TRIPOS>BOND':
fields = line.split()
idx = int(fields[0])-1
assert mol.atoms[idx].name == fields[1]
charges[mol.atoms[idx]] = u.q_e*float(fields[-1])
line = next(lines)
mol.properties[chargename] = AtomicProperties(charges)
return charges
job = packages.antechamber.make_job(command=command,
name="%s, %s" % (chargename, mol.name),
inputs={'mol.mol2': mol.write(format='mol2')},
when_finished=finish_job)
return compute.run_job(job, _return_result=True, **kwargs)
@utils.kwargs_from(mdt.compute.run_job)
def build_bdna(sequence, **kwargs):
""" Uses Ambertools' Nucleic Acid Builder to build a 3D double-helix B-DNA structure.
Args:
sequence (str): DNA sequence for one of the strands (a complementary sequence will
automatically be created)
**kwargs: arguments for :meth:`compute.run_job`
Returns:
moldesign.Molecule: B-DNA double helix
"""
print('DeprecationWarning: build_bdna is deprecated. '
"Use `build_dna_helix(sequence, helix_type='b')` instead")
return build_dna_helix(sequence, helix_type='b', **kwargs)
@utils.kwargs_from(mdt.compute.run_job)
def build_dna_helix(sequence, helix_type='B', **kwargs):
""" Uses Ambertools' Nucleic Acid Builder to build a 3D DNA double-helix.
Args:
sequence (str): DNA sequence for one of the strands (a complementary sequence will
automatically be created)
helix_type (str): Type of helix - 'A'=Arnott A-DNA
'B'=B-DNA (from standard templates and helical params),
'LB'=Langridge B-DNA,
'AB'=Arnott B-DNA,
'SB'=Sasisekharan left-handed B-DNA
**kwargs: arguments for :meth:`compute.run_job`
All helix types except 'B' are taken from fiber diffraction data (see the refernce for details)
Returns:
moldesign.Molecule: B-DNA double helix
References:
See NAB / AmberTools documentation: http://ambermd.org/doc12/Amber16.pdf, pg 771-2
"""
infile = ['molecule m;']
if helix_type.lower() == 'b':
infile.append('m = bdna( "%s" );' % sequence.lower())
else:
infile.append('m = fd_helix( "%sdna", "%s", "dna" );'
% (helix_type.lower(), sequence.lower()))
infile.append('putpdb( "helix.pdb", m, "-wwpdb");\n')
def finish_job(job):
mol = mdt.fileio.read_pdb(job.get_output('helix.pdb').open(), assign_ccd_bonds=False)
if mol.num_chains == 1:
assert mol.num_residues % 2 == 0
oldchain = mol.chains[0]
oldchain.name = oldchain.pdbindex = oldchain.pdbname = 'A'
newchain = mdt.Chain('B')
for residue in mol.residues[mol.num_residues//2:]:
residue.chain = newchain
mol = mdt.Molecule(mol)
mdt.helpers.assign_biopolymer_bonds(mol)
mol.name = '%s-DNA Helix: %s' % (helix_type.upper(), sequence)
return mol
job = packages.nab.make_job(command='nab -o buildbdna build.nab && ./buildbdna',
inputs={'build.nab': '\n'.join(infile)},
name='NAB_build_dna',
when_finished=finish_job)
return mdt.compute.run_job(job, _return_result=True, **kwargs)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/interfaces/opsin_interface.py | .py | 1,509 | 44 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import moldesign as mdt
from .. import utils
from ..compute import packages
@utils.kwargs_from(mdt.compute.run_job)
def name_to_smiles(name,
**kwargs):
command = 'opsin -osmi input.txt output.txt'
def finish_job(job):
smistring = job.get_output('output.txt').read().strip()
if not smistring:
raise ValueError('Could not parse chemical name "%s"' % name)
else:
return smistring
job = packages.opsin.make_job(command=command,
name="opsin, %s" % name,
inputs={'input.txt': name + '\n'},
when_finished=finish_job)
return mdt.compute.run_job(job, _return_result=True, **kwargs)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/interfaces/symmol_interface.py | .py | 10,144 | 260 | from __future__ import print_function, absolute_import, division
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import re
import numpy as np
import moldesign as mdt
from .. import units as u
from .. import utils
from ..compute import packages
IMAGE = 'symmol'
#@doi('10.1107/S0021889898002180')
def run_symmol(mol, tolerance=0.1 * u.angstrom):
import fortranformat
line_writer = fortranformat.FortranRecordWriter('(a6,i2,6f9.5)')
if mol.num_atoms == 2:
return _get_twoatom_symmetry(mol)
infile = ['1.0 1.0 1.0 90.0 90.0 90.0', # line 1: indicates XYZ coordinates
# line 2: numbers indicate: mass weighted moment of inertia,
# tolerance interpretation, tolerance value,
# larger tolerance value (not used)
'1 0 %f 0.0' % tolerance.value_in(u.angstrom)]
for atom in mol.atoms:
infile.append(line_writer.write((atom.element, 1,
atom.x.value_in(u.angstrom),
atom.y.value_in(u.angstrom),
atom.z.value_in(u.angstrom),
0.0, 0.0, 0.0)))
infile.append('')
command = 'symmol < sym.in'
inputs = {'sym.in': '\n'.join(infile)}
job = packages.symmol.make_job(command=command,
inputs=inputs,
name="symmol, %s" % mol.name)
job = mdt.compute.run_job(job)
data = parse_output(mol, job.get_output('symmol.out'))
_prune_symmetries(data)
symm = mdt.geom.MolecularSymmetry(
mol, data.symbol, data.rms,
orientation=get_aligned_coords(mol, data),
elems=data.elems,
_job=job)
return symm
def _get_twoatom_symmetry(mol):
""" Symmol doesn't deal with continuous symmetries, so this is hardcoded
"""
com_pos = mol.positions-mol.com
ident = mdt.geom.SymmetryElement(mol,
idx=0,
symbol='C1',
matrix=np.identity(3),
csm=0.0*u.angstrom,
max_diff=0.0*u.angstrom)
# Note: for a continuous symmetry, so the 'matrix' should really be an infinitesimal transform.
# This doesn't come up a lot practically, so we just put a small generator here instead.
# The rotation is through an irrational angle so that it does in fact generate the full
# symmetry group
transmat = mdt.external.transformations.rotation_matrix(1/np.sqrt(20), com_pos[0])
axis_rot = mdt.geom.SymmetryElement(mol,
idx=1,
symbol='Cinf_v',
matrix=transmat[:3,:3],
csm=0.0*u.angstrom,
max_diff=0.0*u.angstrom)
elems = [ident, axis_rot]
# This is for the mirror plane / inversion center between the two atoms
if mol.atoms[0].atnum == mol.atoms[1].atnum and mol.atoms[0].mass == mol.atoms[1].mass:
reflmat = mdt.external.transformations.reflection_matrix([0,0,0], com_pos[0])
elems.append(mdt.geom.SymmetryElement(mol,
idx=2,
symbol='Cs',
matrix=reflmat[:3,:3],
csm=0.0*u.default.length,
max_diff=0.0*u.default.length))
elems.append(mdt.geom.SymmetryElement(mol,
idx=2,
symbol='Ci',
matrix=-1 * np.identity(3),
csm=0.0*u.default.length,
max_diff=0.0*u.default.length))
term_symbol = 'Dinf_h'
else:
term_symbol = axis_rot.symbol
symm = mdt.geom.MolecularSymmetry(mol, term_symbol, 0.0 * u.default.length,
orientation=com_pos,
elems=elems)
return symm
def _prune_symmetries(data):
""" Remove identical symmetries
"""
found = {}
for elem in data.elems:
found.setdefault(elem.symbol, [])
for otherelem in found[elem.symbol]:
if (np.abs(elem.matrix.T - otherelem.matrix) < 1e-11).all():
break
else:
found[elem.symbol].append(elem)
newelems = []
for val in found.values():
newelems.extend(val)
data.elems = newelems
MATRIXSTRING = 'ORTHOGONALIZATION MATRIX'.split()
ELEMENTSTRING = 'Symmetry element its CSM and Max.Diff. Symmetry element its CSM and Max.Diff.'.split()
TRANSFORMATIONSTRING = 'SYMMETRY GROUP MATRICES'.split()
NOSYMM = 'NO SYMMETRY EXISTS WITHIN GIVEN TOLERANCE'.split()
ELEMPARSER = re.compile('(\d+)\) \[(...)\]\s+(\S+)\s+([\-0-9\.]+)\s+([\-0-9\.]+)')
# this regex parses '1) [E ] x,y,z 0.0000 0.0000' -> [1, 'E ', 'x,y,z','0.0000','0.0000']
MATRIXPARSER = re.compile('(\d+)\s+CSM =\s+([\d\.]+)\s+MAX. DIFF. \(Angstrom\)=([\d\.]+)\s+TYPE (\S+)')
# this parses ' 4 CSM = 0.06 MAX. DIFF. (Angstrom)=0.0545 TYPE C3' -> [4, 0.06, 0.545, C3]
def parse_output(mol, outfile):
lines = iter(outfile)
data = utils.DotDict()
while True:
l = next(lines)
fields = l.split()
if fields == NOSYMM:
data.symbol = 'C1'
data.rms = data.cms = 0.0 * u.angstrom
data.elems = []
data.orthmat = np.identity(3)
return data
elif fields == MATRIXSTRING: # get coordinates along principal axes
data.orthmat = np.zeros((3, 3))
for i in range(3):
data.orthmat[i] = list(map(float, next(lines).split()))
elif fields[:2] == 'Schoenflies symbol'.split():
data.symbol = fields[3]
data.csm = float(fields[6]) * u.angstrom
data.rms = float(fields[-1]) * u.angstrom
elif fields == ELEMENTSTRING:
data.elems = []
while True:
try:
l = next(lines)
except StopIteration:
break
if l.strip() == '': break
parsed = ELEMPARSER.findall(l)
for p in parsed:
elem = mdt.geom.SymmetryElement(mol,
idx=int(p[0])-1,
symbol=p[1].strip(),
matrix=_string_to_matrix(p[2]),
csm=float(p[3]),
max_diff=float(p[4]) * u.angstrom)
if elem.symbol == 'E': elem.symbol = 'C1'
data.elems.append(elem)
break
elif fields == TRANSFORMATIONSTRING:
data.elems = []
l = next(lines)
while True:
while l.strip() == '':
try: l = next(lines)
except StopIteration: return data
eleminfo = MATRIXPARSER.findall(l)
if not eleminfo:
return data # we're done
assert len(eleminfo) == 1
info = eleminfo[0]
matrix = np.zeros((3, 3))
for i in range(3):
l = next(lines)
matrix[i, :] = list(map(float, l.split()))
e = mdt.geom.SymmetryElement(mol,
matrix=matrix,
idx=int(info[0])-1,
csm=float(info[1]) * u.angstrom,
max_diff=float(info[2]) * u.angstrom,
symbol=info[3])
if e.symbol == 'E':
e.symbol = 'C1'
e.matrix = matrix
data.elems.append(e)
l = next(lines)
return data
DIMNUMS = {'x': 0, 'y': 1, 'z': 2}
TRANSFORM_PARSER = re.compile('([+\-]?)([0-9\.]*)([xyz])')
# this regex transforms '3z-5.3x+y' -> [('','3','z'),('-','5.3','x'),('+','','y')]
def _string_to_matrix(string):
"""
Symmol often returns a symmetry operation as something like "+x,-z,+y"
This means that the x axis is mapped onto x, y axis is mapped onto -z, and +y is mapped onto z.
We translate this into a transformation matrix here.
:param string: A string representing axis mapping, of the form 'x,-z,x+y'
:return: 3x3 transformation matrix
"""
mat = []
for dim in string.split(','):
row = np.zeros(3)
components = TRANSFORM_PARSER.findall(dim)
for sign, factor, dimname in components:
if factor.strip() == '': factor = '1'
idim = DIMNUMS[dimname]
row[idim] = float(sign + factor)
row = row / np.sqrt(row.dot(row)) # normalize
mat.append(row)
return np.array(mat)
def get_aligned_coords(mol, data):
com = mol.com
centerpos = mol.positions - com
orthcoords = (centerpos.T.ldot(data.orthmat)).T
return orthcoords
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/interfaces/pdbfixer_interface.py | .py | 11,774 | 312 | from __future__ import print_function, absolute_import, division
import string
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from past.builtins import basestring
import io
import re
import numpy as np
import moldesign as mdt
from .. import units as u
from ..compute import packages
from ..utils import exports
from . import openmm as opm
@exports
def mol_to_fixer(mol):
import pdbfixer
fixer = pdbfixer.PDBFixer(pdbfile=io.StringIO(mol.write(format='pdb')))
return fixer
@exports
def fixer_to_mol(f):
return opm.topology_to_mol(f.topology, positions=f.positions)
@packages.pdbfixer.runsremotely
def mutate_residues(mol, residue_map):
""" Create a mutant with point mutations (returns a copy - leaves the original unchanged)
Mutations may be specified in one of two ways:
1) As a dictionary mapping residue objects to the 3-letter name of the amino acid they
will be mutated into: ``{mol.residues[3]: 'ALA'}``
2) As a list of mutation strings: ``['A43M', '332S', 'B.53N']`` (see below)
Mutation strings have the form:
``[chain name .][initial amino acid code](residue index)(mutant amino acid code)``
If the chain name is omited, the mutation will be applied to all chains (if possible).
The initial amino acid code may also be omitted.
Examples:
>>> mutate_residues(mol, {mol.residues[5]: 'ALA'}) # mutate residue 5 to ALA
>>> mutate_residues(mol, 'A43M') # In all chains with ALA43 mutate it to MET43
>>> mutate_residues(mol, ['A.332S', 'B.120S']) # Mutate Chain A res 332 and B 120 to SER
>>> mutate_residues(mol, ['B.C53N']) # Mutate Cysteine 53 in chain B to Asparagine
Args:
mol (moldesign.Molecule): molecule to create mutant from
residue_map (Dict[moldesign.Residue:str] OR List[str]): list of mutations (see above for
allowed formats)
Returns:
moldesign.Molecule: the mutant
"""
fixer = mol_to_fixer(mol)
chain_mutations = {}
mutation_strs = []
if not hasattr(residue_map, 'items'):
residue_map = _mut_strs_to_map(mol, residue_map)
if not residue_map:
raise ValueError("No mutations specified!")
for res, newres in residue_map.items():
chain_mutations.setdefault(res.chain.pdbname, {})[res] = residue_map[res]
mutation_strs.append(_mutation_as_str(res, newres))
for chainid, mutations in chain_mutations.items():
mutstrings = ['%s-%d-%s' % (res.resname, res.pdbindex, newname)
for res, newname in mutations.items()]
fixer.applyMutations(mutstrings, chainid)
temp_mutant = fixer_to_mol(fixer)
_pdbfixer_chainnames_to_letter(temp_mutant)
# PDBFixer reorders atoms, so to keep things consistent, we'll graft the mutated residues
# into an MDT structure
assert temp_mutant.num_residues == mol.num_residues # shouldn't change number of residues
residues_to_copy = []
old_residue_map = {}
for oldres, mutant_res in zip(mol.residues, temp_mutant.residues):
if oldres in residue_map:
residues_to_copy.append(mutant_res)
mutant_res.mol = None
mutant_res.chain = oldres.chain
old_residue_map[oldres] = mutant_res
else:
residues_to_copy.append(oldres)
# Bonds between original and mutated backbone atoms will be removed when
# creating the new mutant molecule because the original and mutated atoms
# reference different molecules.
#
# Make a list of bonds referencing atoms in the original molecule that
# is used later to recreate bonds between original and mutated backbone
# atoms.
orig_bonds = []
for res in residues_to_copy:
if not res.backbone:
continue
for atom in res.backbone:
for bond_atom in atom.bond_graph:
if bond_atom.residue in residue_map:
mutant_res = old_residue_map[bond_atom.residue]
mutant_atom = mutant_res.atoms[bond_atom.name]
orig_bonds.append((atom,mutant_atom,atom.bond_graph[bond_atom]))
metadata = {'origin': mol.metadata.copy(),
'mutations': mutation_strs}
mutant_mol = mdt.Molecule(residues_to_copy, name='Mutant of "%s"' % mol, metadata=metadata)
# Add bonds between the original and mutated backbone atoms.
for atom,mut_atom,order in orig_bonds:
chainID = atom.chain.name
residues = mutant_mol.chains[chainID].residues
new_atom = residues[atom.residue.name].atoms[atom.name]
new_mut_atom = residues[mut_atom.residue.name].atoms[mut_atom.name]
new_atom.bond_to(new_mut_atom, order)
return mutant_mol
def _pdbfixer_chainnames_to_letter(pdbfixermol):
for chain in pdbfixermol.chains:
try:
if chain.name.isdigit():
chain.name = string.ascii_uppercase[int(chain.name)-1]
except (ValueError, TypeError, IndexError):
continue # not worth crashing over
def _mutation_as_str(res, newres):
""" Create mutation string for storage as metadata.
Note that this will include the name of the chain, if available, as a prefix:
Examples:
>>> res = mdt.Residue(resname='ALA', pdbindex='23', chain=mdt.Chain(name=None))
>>> _mutation_as_str(res, 'TRP')
'A23W'
>>> res = mdt.Residue(resname='ALA', pdbindex='23', chain=mdt.Chain(name='C'))
>>> _mutation_as_str(res, 'TRP')
'C.A23W'
Args:
res (moldesign.Residue): residue to be mutated
newres (str): 3-letter residue code for new amino acid
Returns:
str: mutation string
References:
Nomenclature for the description of sequence variations
J.T. den Dunnen, S.E. Antonarakis: Hum Genet 109(1): 121-124, 2001
Online at http://www.hgmd.cf.ac.uk/docs/mut_nom.html#protein
"""
try: # tries to describe mutation using standard
mutstr = '%s%s%s' % (res.code, res.pdbindex,
mdt.data.RESIDUE_ONE_LETTER.get(newres, '?'))
if res.chain.pdbname:
mutstr = '%s.%s' % (res.chain.pdbname, mutstr)
return mutstr
except (TypeError, ValueError) as e:
print('WARNING: failed to construct mutation code: %s' % e)
return '%s -> %s' % (str(res), newres)
MUT_RE = re.compile(r'(.*\.)?([^\d]*)(\d+)([^\d]+)') # parses mutation strings
def _mut_strs_to_map(mol, strs):
if isinstance(strs, basestring):
strs = [strs]
mutmap = {}
for s in strs:
match = MUT_RE.match(s)
if match is None:
raise ValueError("Failed to parse mutation string '%s'" % s)
chainid, initialcode, residx, finalcode = match.groups()
if chainid is not None:
parent = mol.chains[chainid[:-1]]
else:
parent = mol # queries the whole molecule
newresname = mdt.data.RESIDUE_CODE_TO_NAME[finalcode]
query = {'pdbindex': int(residx)}
if initialcode:
query['code'] = initialcode
residues = parent.get_residues(**query)
if len(residues) == 0:
raise ValueError("Mutation '%s' did not match any residues" % s)
for res in residues:
assert res not in mutmap, "Multiple mutations for %s" % res
mutmap[res] = newresname
return mutmap
@packages.pdbfixer.runsremotely
def add_water(mol, min_box_size=None, padding=None,
ion_concentration=0.0, neutralize=True,
positive_ion='Na+', negative_ion='Cl-'):
""" Solvate a molecule in a water box with optional ions
Args:
mol (moldesign.Molecule): solute molecule
min_box_size (u.Scalar[length] or u.Vector[length]): size of the water box - either
a vector of x,y,z dimensions, or just a uniform cube length. Either this or
``padding`` (or both) must be passed
padding (u.Scalar[length]): distance to edge of water box from the solute in each dimension
neutralize (bool): add ions to neutralize solute charge (in
addition to specified ion concentration)
positive_ion (str): type of positive ions to add, if needed. Allowed values
(from OpenMM modeller) are Cs, K, Li, Na (the default) and Rb
negative_ion (str): type of negative ions to add, if needed. Allowed values
(from OpenMM modeller) are Cl (the default), Br, F, and I
ion_concentration (float or u.Scalar[molarity]): ionic concentration in addition to
whatever is needed to neutralize the solute. (if float is passed, we assume the
number is Molar)
Returns:
moldesign.Molecule: new Molecule object containing both solvent and solute
"""
import pdbfixer
if padding is None and min_box_size is None:
raise ValueError('Solvate arguments: must pass padding or min_box_size or both.')
# add +s and -s to ion names if not already present
if positive_ion[-1] != '+':
assert positive_ion[-1] != '-'
positive_ion += '+'
if negative_ion[-1] != '-':
assert negative_ion[-1] != '+'
negative_ion += '-'
ion_concentration = u.MdtQuantity(ion_concentration)
if ion_concentration.dimensionless:
ion_concentration *= u.molar
ion_concentration = opm.pint2simtk(ion_concentration)
# calculate box size - in each dimension, use the largest of min_box_size or
# the calculated padding
boxsize = np.zeros(3) * u.angstrom
if min_box_size:
boxsize[:] = min_box_size
if padding:
ranges = mol.positions.max(axis=0) - mol.positions.min(axis=0)
for idim, r in enumerate(ranges):
boxsize[idim] = max(boxsize[idim], r+padding)
assert (boxsize >= 0.0).all()
modeller = opm.mol_to_modeller(mol)
# Creating my fixers directly from Topology objs
ff = pdbfixer.PDBFixer.__dict__['_createForceField'](None, modeller.getTopology(), True)
modeller.addSolvent(ff,
boxSize=opm.pint2simtk(boxsize),
positiveIon=positive_ion,
negativeIon=negative_ion,
ionicStrength=ion_concentration,
neutralize=neutralize)
solv_tempmol = opm.topology_to_mol(modeller.getTopology(),
positions=modeller.getPositions(),
name='%s with water box' % mol.name)
_pdbfixer_chainnames_to_letter(solv_tempmol)
# PDBFixer reorders atoms, so to keep things consistent, we'll graft the mutated residues
# into an MDT structure
newmol_atoms = [mol]
for residue in solv_tempmol.residues[mol.num_residues:]:
newmol_atoms.append(residue)
newmol = mdt.Molecule(newmol_atoms,
name="Solvated %s" % mol,
metadata={'origin':mol.metadata})
assert newmol.num_atoms == solv_tempmol.num_atoms
assert newmol.num_residues == solv_tempmol.num_residues
return newmol
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/interfaces/biopython_interface.py | .py | 5,289 | 151 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import itertools
import string
import Bio.PDB
import Bio.PDB.MMCIF2Dict
import numpy as np
import moldesign as mdt
from moldesign import units as u
from moldesign.helpers.pdb import BioAssembly
from moldesign.utils import exports
@exports
def biopython_to_mol(struc):
"""Convert a biopython PDB structure to an MDT molecule.
Note:
Biopython doesn't deal with bond data, so no bonds will be present
in the Molecule
Args:
struc (Bio.PDB.Structure.Structure): Biopython PDB structure to convert
Returns:
moldesign.Molecule: converted molecule
"""
# TODO: assign bonds using 1) CONECT records, 2) residue templates, 3) distance
newatoms = []
backup_chain_names = list(string.ascii_uppercase)
for chain in struc.get_chains():
tmp, pdbidx, pdbid = chain.get_full_id()
if not pdbid.strip():
pdbid = backup_chain_names.pop()
newchain = mdt.Chain(pdbname=pdbid.strip())
for residue in chain.get_residues():
newresidue = mdt.Residue(pdbname=residue.resname.strip(),
pdbindex=residue.id[1])
newchain.add(newresidue)
for atom in residue.get_atom():
elem = atom.element
if len(elem) == 2:
elem = elem[0] + elem[1].lower()
newatom = mdt.Atom(element=elem,
name=atom.get_name(),
pdbname=atom.get_name(),
pdbindex=atom.get_serial_number())
newatom.position = atom.coord * u.angstrom
newresidue.add(newatom)
newatoms.append(newatom)
return mdt.Molecule(newatoms, name=struc.get_full_id()[0])
def get_mmcif_assemblies(fileobj=None, mmcdata=None):
"""Parse an mmCIF file, return biomolecular assembly specifications
Args:
fileobj (file-like): File-like object for the PDB file
(this object will be rewound before returning)
mmcdata (dict): dict version of complete mmCIF data structure (if passed, this will
not be read again from fileobj)
Returns:
Mapping[str, BioAssembly]: dict mapping assembly ids to BioAssembly instances
"""
if mmcdata is None:
mmcdata = get_mmcif_data(fileobj)
if '_pdbx_struct_assembly.id' not in mmcdata:
return {} # no assemblies present
# Get assembly metadata
ids = mmcdata['_pdbx_struct_assembly.id']
details = mmcdata['_pdbx_struct_assembly.details']
chains = mmcdata['_pdbx_struct_assembly_gen.asym_id_list']
opers = mmcdata['_pdbx_struct_assembly_gen.oper_expression']
transform_ids = mmcdata['_pdbx_struct_oper_list.id']
# Get matrix transformations
tmat = np.zeros((4, 4)).tolist()
for i in range(3): # construct displacement vector
tmat[i][3] = mmcdata['_pdbx_struct_oper_list.vector[%d]' % (i+1)]
for i, j in itertools.product(range(0, 3), range(0, 3)): # construct rotation matrix
tmat[i][j] = mmcdata['_pdbx_struct_oper_list.matrix[%d][%d]' % (i+1, j+1)]
transforms = _make_transform_dict(tmat, transform_ids)
# Make sure it's a list
if not isinstance(ids, list):
ids = [ids]
details = [details]
chains = [chains]
opers = [opers]
# now create the assembly specifications
assemblies = {}
for id, detail, chainlist, operlist in zip(ids, details, chains, opers):
assert id not in assemblies
transforms = [transforms[i] for i in operlist.split(',')]
assemblies[id] = BioAssembly(detail, chainlist.split(','), transforms)
return assemblies
def _make_transform_dict(tmat, transform_ids):
if isinstance(transform_ids, list):
for i, j in itertools.product(range(0, 3), range(0, 4)):
tmat[i][j] = list(map(float, tmat[i][j]))
tmat[3][3] = [1.0]*len(transform_ids)
tmat[3][0] = tmat[3][1] = tmat[3][2] = [0.0]*len(transform_ids)
tmat = np.array(tmat)
transforms = {id: tmat[:, :, i] for i, id in enumerate(transform_ids)}
else:
for i, j in itertools.product(range(0, 4), range(0, 4)):
tmat[i][j] = float(tmat[i][j])
tmat[3][3] = 1.0
tmat = np.array(tmat)
transforms = {transform_ids: tmat}
return transforms
def get_mmcif_data(fileobj):
mmcdata = Bio.PDB.MMCIF2Dict.MMCIF2Dict(fileobj)
fileobj.seek(0) # rewind for future access
return mmcdata
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/interfaces/tleap_interface.py | .py | 12,300 | 321 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from past.builtins import basestring
import os
import re
import tempfile
import moldesign as mdt
from . import ambertools
from .. import units as u
from .. import compute
from .. import utils
from .. import forcefields
from ..compute import packages
IMAGE = 'ambertools'
@utils.kwargs_from(mdt.compute.run_job)
def create_ff_parameters(mol, charges='esp', baseff='gaff2', **kwargs):
"""Parameterize ``mol``, typically using GAFF parameters.
This will both assign a forcefield to the molecule (at ``mol.ff``) and produce the parameters
so that they can be used in other systems (e.g., so that this molecule can be simulated
embedded in a larger protein)
Note:
'am1-bcc' and 'gasteiger' partial charges will be automatically computed if necessary.
Other charge types must be precomputed.
Args:
mol (moldesign.Molecule):
charges (str or dict): what partial charges to use? Can be a dict (``{atom:charge}``) OR
a string, in which case charges will be read from
``mol.properties.[charges name]``; typical values will be 'esp', 'mulliken',
'am1-bcc', etc. Use 'zero' to set all charges to 0 (for QM/MM and testing)
baseff (str): Name of the gaff-like forcefield file (default: gaff2)
Returns:
TLeapForcefield: Forcefield object for this residue
"""
# Check that there's only 1 residue, give it a name
assert mol.num_residues == 1
if mol.residues[0].resname is None:
mol.residues[0].resname = 'UNL'
print('Assigned residue name "UNL" to %s' % mol)
resname = mol.residues[0].resname
# check that atoms have unique names
if len(set(atom.name for atom in mol.atoms)) != mol.num_atoms:
raise ValueError('This molecule does not have uniquely named atoms, cannot assign FF')
if charges == 'am1-bcc' and 'am1-bcc' not in mol.properties:
ambertools.calc_am1_bcc_charges(mol)
elif charges == 'gasteiger' and 'gasteiger' not in mol.properties:
ambertools.calc_gasteiger_charges(mol)
elif charges == 'esp' and 'esp' not in mol.properties:
# TODO: use NWChem ESP to calculate
raise NotImplementedError()
if charges == 'zero':
charge_array = [0.0 for atom in mol.atoms]
elif isinstance(charges, basestring):
charge_array = u.array([mol.properties[charges][atom] for atom in mol.atoms])
if not charge_array.dimensionless: # implicitly convert floats to fundamental charge units
charge_array = charge_array.to(u.q_e).magnitude
else:
charge_array = [charges[atom] for atom in mol.atoms]
inputs = {'mol.mol2': mol.write(format='mol2'),
'mol.charges': '\n'.join(map(str, charge_array))}
cmds = ['antechamber -i mol.mol2 -fi mol2 -o mol_charged.mol2 '
' -fo mol2 -c rc -cf mol.charges -rn %s' % resname,
'parmchk -i mol_charged.mol2 -f mol2 -o mol.frcmod',
'tleap -f leap.in',
'sed -e "s/tempresname/%s/g" mol_rename.lib > mol.lib' % resname]
base_forcefield = forcefields.TLeapLib(baseff)
inputs['leap.in'] = '\n'.join(["source leaprc.%s" % baseff,
"tempresname = loadmol2 mol_charged.mol2",
"fmod = loadamberparams mol.frcmod",
"check tempresname",
"saveoff tempresname mol_rename.lib",
"saveamberparm tempresname mol.prmtop mol.inpcrd",
"quit\n"])
def finish_job(j):
leapcmds = ['source leaprc.gaff2']
files = {}
for fname, f in j.glob_output("*.lib").items():
leapcmds.append('loadoff %s' % fname)
files[fname] = f
for fname, f in j.glob_output("*.frcmod").items():
leapcmds.append('loadAmberParams %s' % fname)
files[fname] = f
param = forcefields.TLeapForcefield(leapcmds, files)
param.add_ff(base_forcefield)
param.assign(mol)
return param
job = packages.tleap.make_job(command=' && '.join(cmds),
inputs=inputs,
when_finished=finish_job,
name="GAFF assignment: %s" % mol.name)
return mdt.compute.run_job(job, _return_result=True, **kwargs)
class AmberParameters(object):
""" Forcefield parameters for a system in amber ``prmtop`` format
"""
def __getstate__(self):
state = self.__dict__.copy()
state['job'] = None
return state
def __init__(self, prmtop, inpcrd, job=None):
self.prmtop = prmtop
self.inpcrd = inpcrd
self.job = job
def to_parmed(self):
import parmed
prmtoppath = os.path.join(tempfile.mkdtemp(), 'prmtop')
self.prmtop.put(prmtoppath)
pmd = parmed.load_file(prmtoppath)
return pmd
@utils.kwargs_from(compute.run_job)
def _run_tleap_assignment(mol, leapcmds, files=None, **kwargs):
"""
Drives tleap to create a prmtop and inpcrd file. Specifically uses the AmberTools 16
tleap distribution.
Defaults are as recommended in the ambertools manual.
Args:
mol (moldesign.Molecule): Molecule to set up
leapcmds (List[str]): list of the commands to load the forcefields
files (List[pyccc.FileReference]): (optional) list of additional files
to send
**kwargs: keyword arguments to :meth:`compute.run_job`
References:
Ambertools Manual, http://ambermd.org/doc12/Amber16.pdf. See page 33 for forcefield
recommendations.
"""
leapstr = leapcmds[:]
inputs = {}
if files is not None:
inputs.update(files)
inputs['input.pdb'] = mol.write(format='pdb')
leapstr.append('mol = loadpdb input.pdb\n'
"check mol\n"
"saveamberparm mol output.prmtop output.inpcrd\n"
"savepdb mol output.pdb\n"
"quit\n")
inputs['input.leap'] = '\n'.join(leapstr)
job = packages.tleap.make_job(command='tleap -f input.leap',
inputs=inputs,
name="tleap, %s" % mol.name)
return compute.run_job(job, **kwargs)
def _prep_for_tleap(mol):
""" Returns a modified *copy* that's been modified for input to tleap
Makes the following modifications:
1. Reassigns all residue IDs
2. Assigns tleap-appropriate cysteine resnames
"""
change = False
clean = mdt.Molecule(mol.atoms)
for residue in clean.residues:
residue.pdbindex = residue.index+1
if residue.resname == 'CYS': # deal with cysteine states
if 'SG' not in residue.atoms or 'HG' in residue.atoms:
continue # sulfur's missing, we'll let tleap create it
else:
sulfur = residue.atoms['SG']
if sulfur.formal_charge == -1*u.q_e:
residue.resname = 'CYM'
change = True
continue
# check for a reasonable hybridization state
if sulfur.formal_charge != 0 or sulfur.num_bonds not in (1, 2):
raise ValueError("Unknown sulfur hybridization state for %s"
% sulfur)
# check for a disulfide bond
for otheratom in sulfur.bonded_atoms:
if otheratom.residue is not residue:
if otheratom.name != 'SG' or otheratom.residue.resname not in ('CYS', 'CYX'):
raise ValueError('Unknown bond from cysteine sulfur (%s)' % sulfur)
# if we're here, this is a cystine with a disulfide bond
print('INFO: disulfide bond detected. Renaming %s from CYS to CYX' % residue)
sulfur.residue.resname = 'CYX'
clean._rebuild_from_atoms()
return clean
ATOMSPEC = re.compile(r'\.R<(\S+) ([\-0-9]+)>\.A<(\S+) ([\-0-9]+)>')
def _parse_tleap_errors(job, molin):
# TODO: special messages for known problems (e.g. histidine)
msg = []
unknown_res = set() # so we can print only one error per unkonwn residue
lineiter = iter(job.stdout.split('\n'))
offset = utils.if_not_none(molin.residues[0].pdbindex, 1)
reslookup = {str(i+offset): r for i,r in enumerate(molin.residues)}
def _atom_from_re(s):
resname, residx, atomname, atomidx = s
r = reslookup[residx]
a = r[atomname]
return a
def unusual_bond(l):
atomre1, atomre2 = ATOMSPEC.findall(l)
try:
a1, a2 = _atom_from_re(atomre1), _atom_from_re(atomre2)
except KeyError:
a1 = a2 = None
r1 = reslookup[atomre1[1]]
r2 = reslookup[atomre2[1]]
return forcefields.errors.UnusualBond(l, (a1, a2), (r1, r2))
def _parse_tleap_logline(line):
fields = line.split()
if fields[0:2] == ['Unknown', 'residue:']:
# EX: "Unknown residue: 3TE number: 499 type: Terminal/beginning"
res = molin.residues[int(fields[4])]
unknown_res.add(res)
return forcefields.errors.UnknownResidue(line, res)
elif fields[:4] == 'Warning: Close contact of'.split():
# EX: "Warning: Close contact of 1.028366 angstroms between .R<DC5 1>.A<HO5' 1> and .R<DC5 81>.A<P 9>"
return unusual_bond(line)
elif fields[:6] == 'WARNING: There is a bond of'.split():
# Matches two lines, EX:
# "WARNING: There is a bond of 34.397700 angstroms between:"
# "------- .R<DG 92>.A<O3' 33> and .R<DG 93>.A<P 1>"
nextline = next(lineiter)
return unusual_bond(line+nextline)
elif fields[:5] == 'Created a new atom named:'.split():
# EX: "Created a new atom named: P within residue: .R<DC5 81>"
residue = reslookup[fields[-1][:-1]]
if residue in unknown_res:
return None # suppress atoms from an unknown res ...
atom = residue[fields[5]]
return forcefields.errors.UnknownAtom(line, residue, atom)
elif fields[:2] == ('FATAL:', 'Atom'):
# EX: "FATAL: Atom .R<ARQ 1>.A<C30 6> does not have a type."
assert fields[-5:] == "does not have a type.".split()
atom = _atom_from_re(ATOMSPEC.findall(line)[0])
return forcefields.errors.UnknownAtom(line, atom.residue, atom)
elif (fields[:5] == '** No torsion terms for'.split() or
fields[:5] == 'Could not find angle parameter:'.split() or
fields[:5] == 'Could not find bond parameter for:'.split()):
# EX: " ** No torsion terms for ca-ce-c3-hc"
# EX: "Could not find bond parameter for: -"
# EX: "Could not find angle parameter: - -"
return forcefields.errors.MissingTerms(line.strip())
else: # ignore this line
return None
while True:
try:
line = next(lineiter)
except StopIteration:
break
try:
errmsg = _parse_tleap_logline(line)
except (KeyError, ValueError):
print("WARNING: failed to process TLeap message '%s'" % line)
msg.append(forcefields.errors.ForceFieldMessage(line))
else:
if errmsg is not None:
msg.append(errmsg)
return msg
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/interfaces/__init__.py | .py | 571 | 20 | from . import ambertools
from . import biopython_interface
from . import nbo_interface
from . import openbabel
from . import openmm
from . import opsin_interface
from . import parmed_interface
from . import pdbfixer_interface
from . import pyscf_interface
from . import symmol_interface
from . import tleap_interface
# These statements only import functions for python object conversion,
# i.e. mol_to_[pkg] and [pkg]_to_mol
from .biopython_interface import *
from .openbabel import *
from .openmm import *
from .pyscf_interface import *
from .parmed_interface import *
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/interfaces/nbo_interface.py | .py | 9,611 | 265 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
import moldesign as mdt
from .. import units as u
from .. import utils
SIGMA_UTF = u"\u03C3"
PI_UTF = u"\u03C0"
def run_nbo(mol, requests=('nlmo', 'nbo'),
image='nbo',
engine=None):
wfn = mol.wfn
inputs = {'in.47': make_nbo_input_file(mol, requests)}
command = 'gennbo.i4.exe in.47'
engine = utils.if_not_none(engine, mdt.compute.config.get_engine())
imagename = mdt.compute.get_image_path(image)
job = engine.launch(imagename,
command,
inputs=inputs,
name="nbo, %s" % mol.name)
mdt.helpers.display_log(job.get_display_object(), "nbo, %s"%mol.name)
job.wait()
parsed_data = parse_nbo(job.get_output('FILE.10'),
len(mol.wfn.aobasis))
for orbtype, data in parsed_data.items():
if orbtype[0] == 'P': # copy data from the orthogonal orbitals
orthdata = parsed_data[orbtype[1:]]
for key in 'bond_names iatom jatom stars bondnums num_bonded_atoms'.split():
data[key] = orthdata[key]
data.occupations = [None for orb in data.coeffs]
add_orbitals(mol, wfn, data, orbtype)
wfn._nbo_job = job
def add_orbitals(mol, wfn, orbdata, orbtype):
orbs = []
for i in range(len(orbdata.coeffs)):
bond = None
atoms = [mol.atoms[orbdata.iatom[i] - 1]]
if orbdata.bond_names[i] == 'RY':
bname = '%s Ryd*' % atoms[0].name
nbotype = 'rydberg'
utf_name = bname
elif orbdata.bond_names[i] == 'LP':
bname = '%s lone pair' % atoms[0].name
nbotype = 'lone pair'
utf_name = bname
elif orbdata.bond_names[i] == 'LV':
bname = '%s lone vacancy' % atoms[0].name
nbotype = 'lone vacancy'
utf_name = bname
elif orbdata.num_bonded_atoms[i] == 1:
bname = '%s Core' % atoms[0].name
nbotype = 'core'
utf_name = bname
else:
atoms.append(mol.atoms[orbdata.jatom[i] - 1])
bond = mdt.Bond(*atoms)
if orbdata.bondnums[i] == 1: # THIS IS NOT CORRECT
nbotype = 'sigma'
utf_type = SIGMA_UTF
else:
nbotype = 'pi'
utf_type = PI_UTF
bname = '%s%s (%s - %s)' % (nbotype, orbdata.stars[i],
atoms[0].name, atoms[1].name)
utf_name = '%s%s (%s - %s)' % (utf_type, orbdata.stars[i],
atoms[0].name, atoms[1].name)
name = '%s %s' % (bname, orbtype)
orbs.append(mdt.Orbital(orbdata.coeffs[i],
wfn=wfn, occupation=orbdata.occupations[i],
atoms=atoms, name=name,
nbotype=nbotype,
bond=bond,
unicode_name=utf_name,
_data=orbdata))
return wfn.add_orbitals(orbs, orbtype=orbtype)
def make_nbo_input_file(mol, requests):
"""
:param mol:
:type mol: moldesign.molecules.Molecule
:return:
"""
# Units: angstroms, hartrees
wfn = mol.wfn
orbs = wfn.molecular_orbitals
nbofile = []
# TODO: check for open shell wfn (OPEN keyword)
# TODO: check normalization, orthogonalization
nbofile.append(" $GENNBO BODM NATOMS=%d NBAS=%d $END" %
(mol.num_atoms, len(wfn.aobasis)))
commands = ['NBOSUM']
for r in requests:
commands.append('AO%s=W10' % r.upper())
if r[0] != 'P': commands.append('%s' % r.upper())
nbofile.append('$NBO %s $END' % (' '.join(commands)))
nbofile.append("$COORD\n %s" % mol.name)
for iatom, atom in enumerate(mol.atoms):
#TODO: deal with pseudopotential electrons
x, y, z = list(map(repr, atom.position.value_in(u.angstrom)))
nbofile.append("%d %d %s %s %s" % (atom.atnum, atom.atnum,
x, y, z))
nbofile.append("$END")
nbofile.append("$BASIS")
nbofile.append(' CENTER = ' +
' '.join(str(1+bfn.atom.index) for bfn in wfn.aobasis))
nbofile.append(" LABEL = " +
' '.join(str(AOLABELS[bfn.orbtype]) for bfn in wfn.aobasis))
nbofile.append('$END')
#TODO: deal with CI wavefunctions ($WF keyword)
nbofile.append('$OVERLAP')
append_matrix(nbofile, wfn.aobasis.overlaps)
nbofile.append('$END')
nbofile.append('$DENSITY')
append_matrix(nbofile, wfn.density_matrix)
nbofile.append('$END')
return '\n '.join(nbofile)
def parse_nbo(f, nbasis):
lines = f.__iter__()
parsed = {}
while True:
try:
l = next(lines)
except StopIteration:
break
fields = l.split()
if fields[1:5] == 'in the AO basis:'.split():
orbname = fields[0]
assert orbname[-1] == 's'
orbname = orbname[:-1]
next(lines)
if orbname[0] == 'P': # these are pre-orthogonal orbitals, it only prints the coefficients
coeffs = _parse_wrapped_matrix(lines, nbasis)
parsed[orbname] = utils.DotDict(coeffs=np.array(coeffs))
else: # there's more complete information available
parsed[orbname] = read_orbital_set(lines, nbasis)
return parsed
def read_orbital_set(lineiter, nbasis):
# First, get the actual matrix
mat = _parse_wrapped_matrix(lineiter, nbasis)
# First, occupation numbers
occupations = list(map(float,_get_wrapped_separated_vals(lineiter, nbasis)))
# Next, a line of things that always appear to be ones (for spin orbitals maybe?)
oneline = _get_wrapped_separated_vals(lineiter, nbasis)
for x in oneline: assert x == '1'
# next is number of atoms involved in the bond
num_bonded_atoms = list(map(int, _get_wrapped_separated_vals(lineiter, nbasis)))
bond_names = _get_wrapped_separated_vals(lineiter, nbasis)
# Next indicates whether real or virtual
stars = _get_wrapped_column_vals(lineiter, nbasis)
for s in stars: assert (s == '' or s == '*')
# number of bonds between this pair of atoms
bondnums = list(map(int, _get_wrapped_separated_vals(lineiter, nbasis)))
# first atom index (1-based)
iatom = list(map(int, _get_wrapped_separated_vals(lineiter, nbasis)))
jatom = list(map(int, _get_wrapped_separated_vals(lineiter, nbasis)))
# The rest appears to be 0 most of the time ...
return utils.DotDict(coeffs=np.array(mat),
iatom=iatom, jatom=jatom, bondnums=bondnums,
bond_names=bond_names,
num_bonded_atoms=num_bonded_atoms,
stars=stars, occupations=occupations)
def _parse_wrapped_matrix(lineiter, nbasis):
mat = []
for i in range(nbasis):
currline = list(map(float, _get_wrapped_separated_vals(lineiter, nbasis)))
assert len(currline) == nbasis
mat.append(currline)
return mat
def _get_wrapped_separated_vals(lineiter, nbasis):
vals = []
while True:
l = next(lineiter)
vals.extend(l.split())
if len(vals) == nbasis:
break
assert len(vals) < nbasis
return vals
def _get_wrapped_column_vals(lineiter, nbasis):
vals = []
while True:
l = next(lineiter.next)[1:]
lenl = len(l)
for i in range(20):
if lenl <= 3*i + 1: break
vals.append(l[3*i: 3*i + 3].strip())
if len(vals) == nbasis:
break
assert len(vals) < nbasis
return vals
def append_matrix(l, mat):
for row in mat:
icol = 0
while icol < len(row):
l.append(' ' + ' '.join(map(repr, row[icol:icol + 6])))
icol += 6
AOLABELS = {'s': 1, 'px': 101, 'py': 102, 'pz': 103,
"dxx": 201, "dxy": 202, "dxz": 203, "dyy": 204, "dyz": 205, "dzz": 206,
"fxxx": 301, "fxxy": 302, "fxxz": 303, "fxyy": 304, "fxyz": 305,
"fxzz": 306, "fyyy": 307, "fyyz": 308, "fyzz": 309, "fzzz": 310,
"gxxxx": 401, "gxxxy": 402, "gxxxz": 403, "gxxyy": 404, "gxxyz": 405,
"gxxzz": 406, "gxyyy": 407, "gxyyz": 408, "gxyzz": 409, "gxzzz": 410,
"gyyyy": 411, "gyyyz": 412, "gyyzz": 413, "gyzzz": 414, "gzzzz": 415, # end of cartesian
# start of spherical:
'p(x)': 151, 'p(y)': 152, 'p(z)': 153,
"d(xy)": 251, "d(xz)": 252, "d(yz)": 253, "d(x2-y2)": 254, "d(z2)": 255,
"f(z(5z2-3r2))": 351, "f(x(5z2-r2))": 352, "f(y(5z2-r2))": 353, "f(z(x2-y2))": 354, "f(xyz)": 355,
"f(x(x2-3y2))": 356, "f(y(3x2-y2))": 357}
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/interfaces/openbabel.py | .py | 10,502 | 321 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import sys
import string
import moldesign as mdt
from ..compute import packages
from .. import units as u
from ..utils import exports
def read_stream(filelike, format, name=None):
""" Read a molecule from a file-like object
Note:
Currently only reads the first conformation in a file
Args:
filelike: a file-like object to read a file from
format (str): File format: pdb, sdf, mol2, bbll, etc.
name (str): name to assign to molecule
Returns:
moldesign.Molecule: parsed result
"""
molstring = str(filelike.read()) # openbabel chokes on unicode
return read_string(molstring, format, name=name)
@packages.openbabel.runsremotely
def read_string(molstring, format, name=None):
""" Read a molecule from a file-like object
Note:
Currently only reads the first conformation in a file
Args:
molstring (str): string containing file contents
format (str): File format: pdb, sdf, mol2, bbll, etc.
name (str): name to assign to molecule
Returns:
moldesign.Molecule: parsed result
"""
import pybel as pb
pbmol = pb.readstring(format, molstring)
mol = pybel_to_mol(pbmol, name=name)
return mol
@packages.openbabel.runsremotely
def write_string(mol, format):
""" Create a file from the passed molecule
Args:
mol (moldesign.Molecule): molecule to write
format (str): File format: pdb, sdf, mol2, bbll, etc.
Returns:
str: contents of the file
References:
https://openbabel.org/docs/dev/FileFormats/Overview.html
"""
pbmol = mol_to_pybel(mol)
if format == 'smi': # TODO: always kekulize, never aromatic
outstr = pbmol.write(format=format).strip()
else:
outstr = pbmol.write(format=format)
return str(outstr)
@packages.openbabel.runsremotely
def guess_bond_orders(mol):
"""Use OpenBabel to guess bond orders using geometry and functional group templates.
Args:
mol (moldesign.Molecule): Molecule to perceive the bonds of
Returns:
moldesign.Molecule: New molecule with assigned bonds
"""
# TODO: pH, formal charges
pbmol = mol_to_pybel(mol)
pbmol.OBMol.PerceiveBondOrders()
newmol = pybel_to_mol(pbmol)
return newmol
@packages.openbabel.runsremotely
def add_hydrogen(mol):
"""Add hydrogens to saturate atomic valences.
Args:
mol (moldesign.Molecule): Molecule to saturate
Returns:
moldesign.Molecule: New molecule with all valences saturated
"""
pbmol = mol_to_pybel(mol)
pbmol.OBMol.AddHydrogens()
newmol = pybel_to_mol(pbmol, reorder_atoms_by_residue=True)
mdt.helpers.assign_unique_hydrogen_names(newmol)
return newmol
@exports
def mol_to_pybel(mdtmol):
""" Translate a moldesign molecule object into a pybel molecule object.
Note:
The focus is on translating topology and biomolecular structure -
we don't translate any metadata.
Args:
mdtmol (moldesign.Molecule): molecule to translate
Returns:
pybel.Molecule: translated molecule
"""
import openbabel as ob
import pybel as pb
obmol = ob.OBMol()
obmol.BeginModify()
atommap = {}
resmap = {}
for atom in mdtmol.atoms:
obatom = obmol.NewAtom()
obatom.SetAtomicNum(atom.atnum)
atommap[atom] = obatom
pos = atom.position.value_in(u.angstrom)
obatom.SetVector(*pos)
if atom.residue and atom.residue not in resmap:
obres = obmol.NewResidue()
resmap[atom.residue] = obres
obres.SetChain(str(atom.chain.pdbname)[0] if atom.chain.pdbname else 'Z')
obres.SetName(str(atom.residue.pdbname) if atom.residue.pdbname else 'UNL')
obres.SetNum(str(atom.residue.pdbindex) if atom.residue.pdbindex else 0)
else:
obres = resmap[atom.residue]
obres.AddAtom(obatom)
obres.SetHetAtom(obatom, not atom.residue.is_standard_residue)
obres.SetAtomID(obatom, str(atom.name))
obres.SetSerialNum(obatom,
mdt.utils.if_not_none(atom.pdbindex, atom.index+1))
for atom in mdtmol.bond_graph:
a1 = atommap[atom]
for nbr, order in mdtmol.bond_graph[atom].items():
a2 = atommap[nbr]
if a1.GetIdx() > a2.GetIdx():
obmol.AddBond(a1.GetIdx(), a2.GetIdx(), order)
obmol.EndModify()
pbmol = pb.Molecule(obmol)
for atom in atommap:
idx = atommap[atom].GetIdx()
obatom = obmol.GetAtom(idx)
obatom.SetFormalCharge(int(atom.formal_charge.value_in(u.q_e)))
return pbmol
@exports
def pybel_to_mol(pbmol,
reorder_atoms_by_residue=False,
primary_structure=True,
**kwargs):
""" Translate a pybel molecule object into a moldesign object.
Note:
The focus is on translating topology and biomolecular structure - we don't translate any metadata.
Args:
pbmol (pybel.Molecule): molecule to translate
reorder_atoms_by_residue (bool): change atom order so that all atoms in a residue are stored
contiguously
primary_structure (bool): translate primary structure data as well as atomic data
**kwargs (dict): keyword arguments to moldesign.Molecule __init__ method
Returns:
moldesign.Molecule: translated molecule
"""
newatom_map = {}
newresidues = {}
newchains = {}
newatoms = mdt.AtomList([])
backup_chain_names = list(string.ascii_uppercase)
for pybatom in pbmol.atoms:
obres = pybatom.OBAtom.GetResidue()
name = obres.GetAtomID(pybatom.OBAtom).strip()
if pybatom.atomicnum == 67:
print(("WARNING: openbabel parsed atom serial %d (name:%s) as Holmium; "
"correcting to hydrogen. ") % (pybatom.OBAtom.GetIdx(), name))
atnum = 1
elif pybatom.atomicnum == 0:
print("WARNING: openbabel failed to parse atom serial %d (name:%s); guessing %s. " % (
pybatom.OBAtom.GetIdx(), name, name[0]))
atnum = mdt.data.ATOMIC_NUMBERS[name[0]]
else:
atnum = pybatom.atomicnum
mdtatom = mdt.Atom(atnum=atnum, name=name,
formal_charge=pybatom.formalcharge * u.q_e,
pdbname=name, pdbindex=pybatom.OBAtom.GetIdx())
newatom_map[pybatom.OBAtom.GetIdx()] = mdtatom
mdtatom.position = pybatom.coords * u.angstrom
if primary_structure:
obres = pybatom.OBAtom.GetResidue()
resname = obres.GetName()
residx = obres.GetIdx()
chain_id = obres.GetChain()
chain_id_num = obres.GetChainNum()
if chain_id_num not in newchains:
# create new chain
if not mdt.utils.is_printable(chain_id.strip()) or not chain_id.strip():
chain_id = backup_chain_names.pop()
print('WARNING: assigned name %s to unnamed chain object @ %s' % (
chain_id, hex(chain_id_num)))
chn = mdt.Chain(pdbname=str(chain_id))
newchains[chain_id_num] = chn
else:
chn = newchains[chain_id_num]
if residx not in newresidues:
# Create new residue
pdb_idx = obres.GetNum()
res = mdt.Residue(pdbname=resname,
pdbindex=pdb_idx)
newresidues[residx] = res
chn.add(res)
res.chain = chn
else:
res = newresidues[residx]
res.add(mdtatom)
newatoms.append(mdtatom)
for ibond in range(pbmol.OBMol.NumBonds()):
obbond = pbmol.OBMol.GetBond(ibond)
a1 = newatom_map[obbond.GetBeginAtomIdx()]
a2 = newatom_map[obbond.GetEndAtomIdx()]
order = obbond.GetBondOrder()
bond = mdt.Bond(a1, a2)
bond.order = order
if reorder_atoms_by_residue and primary_structure:
resorder = {}
for atom in newatoms:
resorder.setdefault(atom.residue, len(resorder))
newatoms.sort(key=lambda a: resorder[a.residue])
return mdt.Molecule(newatoms, **kwargs)
def from_smiles(smi, name=None):
""" Translate a smiles string to a 3D structure.
This method uses OpenBabel to generate a plausible 3D conformation of the 2D SMILES topology.
We only use the first result from the conformation generator.
Args:
smi (str): smiles string
name (str): name to assign to molecule (default - the smiles string)
Returns:
moldesign.Molecule: the translated molecule
"""
return _string_to_3d_mol(smi, 'smi', name)
def from_inchi(inchi, name=None):
""" Translate an INCHI string to a 3D structure.
This method uses OpenBabel to generate a plausible 3D conformation of the 2D SMILES topology.
We only use the first result from the conformation generator.
Args:
smi (str): smiles string
name (str): name to assign to molecule (default - the smiles string)
Returns:
moldesign.Molecule: the translated molecule
"""
return _string_to_3d_mol(inchi, 'inchi', name)
@packages.openbabel.runsremotely
def _string_to_3d_mol(s, fmt, name):
import pybel as pb
if name is None: name = s
pbmol = pb.readstring(fmt, str(s)) # avoid passing unicode by casting to str
pbmol.addh()
pbmol.make3D()
mol = pybel_to_mol(pbmol,
name=name,
primary_structure=False)
mdt.helpers.atom_name_check(mol)
return mol
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/interfaces/pyscf_interface.py | .py | 4,498 | 127 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import future.utils
import numpy as np
import moldesign.units as u
from .. import compute
from ..utils import if_not_none, redirect_stderr
from .. import orbitals
from ..utils import exports
from ..compute import packages
if future.utils.PY2:
from cStringIO import StringIO
else:
from io import StringIO
@exports
def mol_to_pyscf(mol, basis, symmetry=None, charge=0, positions=None):
"""Convert an MDT molecule to a PySCF "Mole" object"""
from pyscf import gto
pyscfmol = gto.Mole()
positions = if_not_none(positions, mol.positions)
pyscfmol.atom = [[atom.elem, pos.value_in(u.angstrom)]
for atom, pos in zip(mol.atoms, positions)]
pyscfmol.basis = basis
pyscfmol.charge = charge
if symmetry is not None:
pyscfmol.symmetry = symmetry
with redirect_stderr(StringIO()) as builderr:
pyscfmol.build()
builderr.seek(0)
for line in builderr:
if line.strip() == 'Warn: Ipython shell catchs sys.args':
continue
else:
print('PYSCF: ' + line)
return pyscfmol
# PYSCF appears to have weird names for spherical components?
SPHERICAL_NAMES = {'y^3': (3, -3), 'xyz': (3, -2), 'yz^2': (3, -1), 'z^3': (3, 0),
'xz^2': (3, 1), 'zx^2': (3, 2), 'x^3': (3, 3),
'x2-y2': (2, 2)}
SPHERICAL_NAMES.update(orbitals.ANGULAR_NAME_TO_COMPONENT)
# TODO: need to handle parameters for max iterations,
# level shifts, requiring convergence, restarts, initial guesses
class StatusLogger(object):
LEN = 15
def __init__(self, description, columns, logger):
self.logger = logger
self.description = description
self.columns = columns
self._init = False
self._row_format = ("{:<%d}" % self.LEN) + ("{:>%d}" % self.LEN) * (len(columns) - 1)
def __call__(self, info):
if not self._init:
self.logger.status('Starting energy model calculation: %s' % self.description)
self.logger.status(self._row_format.format(*self.columns))
self.logger.status(self._row_format.format(*['-' * (self.LEN - 2) for i in self.columns]))
self._init = True
self.logger.status(self._row_format.format(*[info.get(c, 'n/a') for c in self.columns]))
@packages.pyscf.runsremotely
def get_eris_in_basis(basis, orbs):
""" Get electron repulsion integrals transformed into this basis (in form eri[i,j,k,l] = (ij|kl))
"""
from pyscf import ao2mo
pmol = mol_to_pyscf(basis.wfn.mol, basis=basis.basisname)
eri = ao2mo.full(pmol, orbs.T, compact=True) * u.hartree
eri.defunits_inplace()
return orbitals.ERI4FoldTensor(eri, orbs)
@packages.pyscf.runsremotely
def basis_values(mol, basis, coords, coeffs=None, positions=None):
""" Calculate the orbital's value at a position in space
Args:
mol (moldesign.Molecule): Molecule to attach basis set to
basis (moldesign.orbitals.BasisSet): set of basis functions
coords (Array[length]): List of coordinates (with shape ``(len(coords), 3)``)
coeffs (Vector): List of ao coefficients (optional; if not passed, all basis fn
values are returned)
Returns:
Array[length**(-1.5)]: if ``coeffs`` is not passed, an array of basis fn values at each
coordinate. Otherwise, a list of orbital values at each coordinate
"""
from pyscf.dft import numint
# TODO: more than just create the basis by name ...
pmol = mol_to_pyscf(mol, basis=basis.basisname, positions=positions)
aovals = numint.eval_ao(pmol, np.ascontiguousarray(coords.value_in(u.bohr))) * (u.a0**-1.5)
if coeffs is None:
return aovals
else:
return aovals.dot(coeffs.T)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/interfaces/parmed_interface.py | .py | 9,298 | 302 | from __future__ import print_function, absolute_import, division
import io
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from past.builtins import basestring
import collections
import itertools
import future.utils
import moldesign as mdt
from .. import units as u
from .. import utils
if future.utils.PY2:
from cStringIO import StringIO
else:
from io import StringIO
def read_mmcif(f, reassign_chains=True):
"""Parse an mmCIF file (using the parmEd parser) and return a molecule
Args:
f (file): file-like object containing the mmCIF file
reassign_chains (bool): reassign chain IDs from ``auth_asym_id`` to ``label_asym_id``
Returns:
moldesign.Molecule: parsed molecule
"""
import parmed
parmedmol = parmed.read_CIF(f)
mol = parmed_to_mdt(parmedmol)
if reassign_chains:
f.seek(0)
mol = _reassign_chains(f, mol)
mdt.helpers.assign_biopolymer_bonds(mol)
return mol
def read_pdb(f):
"""Parse an mmCIF file (using the parmEd parser) and return a molecule
Args:
f (file): file-like object containing the mmCIF file
Returns:
moldesign.Molecule: parsed molecule
"""
import parmed
parmedmol = parmed.read_PDB(f)
mol = parmed_to_mdt(parmedmol)
return mol
def write_pdb(mol, fileobj):
""" Write a PDB file to a buffer
Args:
mol (moldesign.Molecule): molecule to write as pdb
fileobj (io.IOBase): buffer to write to - bytes and text interfaces are acceptable
"""
pmedmol = mol_to_parmed(mol)
tempfile = StringIO()
pmedmol.write_pdb(tempfile, renumber=False)
if not isinstance(fileobj, io.TextIOBase) or 'b' in getattr(fileobj, 'mode', ''):
binaryobj = fileobj
fileobj = io.TextIOWrapper(binaryobj)
wrapped = True
else:
wrapped = False
_insert_conect_records(mol, pmedmol, tempfile, write_to=fileobj)
if wrapped:
fileobj.flush()
fileobj.detach()
CONECT = 'CONECT %4d'
def _insert_conect_records(mol, pmdmol, pdbfile, write_to=None):
""" Inserts TER records to indicate the end of the biopolymeric part of a chain
Put CONECT records at the end of a pdb file that doesn't have them
Args:
mol (moldesign.Molecule): the MDT version of the molecule that pdbfile describes
pdbfile (TextIO OR str): pdb file (file-like or string)
Returns:
TextIO OR str: copy of the pdb file with added TER records - it will be
returned as the same type passed (i.e., as a filelike buffer or as a string)
"""
conect_bonds = mdt.helpers.get_conect_pairs(mol)
def get_atomseq(atom):
return pmdmol.atoms[atom.index].number
pairs = collections.OrderedDict()
for atom, nbrs in conect_bonds.items():
pairs[get_atomseq(atom)] = list(map(get_atomseq, nbrs))
if isinstance(pdbfile, basestring):
pdbfile = StringIO(pdbfile)
if write_to is None:
newf = StringIO()
else:
newf = write_to
pdbfile.seek(0)
for line in pdbfile:
if line.split() == ['END']:
for a1idx in pairs:
for istart in range(0, len(pairs[a1idx]), 4):
pairindices = ''.join(("%5d" % idx) for idx in pairs[a1idx][istart:istart+4])
newf.write(str(CONECT % a1idx + pairindices + '\n'))
newf.write(str(line))
def write_mmcif(mol, fileobj):
mol_to_parmed(mol).write_cif(fileobj)
@utils.exports
def parmed_to_mdt(pmdmol):
""" Convert parmed Structure to MDT Structure
Args:
pmdmol (parmed.Structure): parmed structure to convert
Returns:
mdt.Molecule: converted molecule
"""
atoms = collections.OrderedDict()
residues = {}
chains = {}
masses = [pa.mass for pa in pmdmol.atoms] * u.dalton
positions = [[pa.xx, pa.xy, pa.xz] for pa in pmdmol.atoms] * u.angstrom
for iatom, patm in enumerate(pmdmol.atoms):
if patm.residue.chain not in chains:
chains[patm.residue.chain] = mdt.Chain(pdbname=patm.residue.chain)
chain = chains[patm.residue.chain]
if patm.residue not in residues:
residues[patm.residue] = mdt.Residue(resname=patm.residue.name,
pdbindex=patm.residue.number)
residues[patm.residue].chain = chain
chain.add(residues[patm.residue])
residue = residues[patm.residue]
atom = mdt.Atom(name=patm.name,
atnum=patm.atomic_number,
pdbindex=patm.number,
mass=masses[iatom])
atom.position = positions[iatom]
atom.residue = residue
residue.add(atom)
assert patm not in atoms
atoms[patm] = atom
for pbnd in pmdmol.bonds:
atoms[pbnd.atom1].bond_to(atoms[pbnd.atom2], int(pbnd.order))
mol = mdt.Molecule(list(atoms.values()),
metadata=_get_pdb_metadata(pmdmol))
return mol
def _get_pdb_metadata(pmdmol):
metadata = utils.DotDict(description=pmdmol.title)
authors = getattr(pmdmol, 'journal_authors', None)
if authors:
metadata.pdb_authors = authors
experimental = getattr(pmdmol, 'experimental', None)
if experimental:
metadata.pdb_experimental = experimental
box_vectors = getattr(pmdmol, 'box_vectors', None)
if box_vectors:
metadata.pdb_box_vectors = box_vectors
doi = getattr(pmdmol, 'doi', None)
if doi:
metadata.pdb_doi = doi
metadata.url = "http://dx.doi.org/%s" % doi
return metadata
@utils.exports
def mol_to_parmed(mol):
""" Convert MDT Molecule to parmed Structure
Args:
mol (moldesign.Molecule):
Returns:
parmed.Structure
"""
import parmed
struc = parmed.Structure()
struc.title = mol.name
pmedatoms = []
for atom in mol.atoms:
pmedatm = parmed.Atom(atomic_number=atom.atomic_number,
name=atom.name,
mass=atom.mass.value_in(u.dalton),
number=utils.if_not_none(atom.pdbindex, -1))
pmedatm.xx, pmedatm.xy, pmedatm.xz = atom.position.value_in(u.angstrom)
pmedatoms.append(pmedatm)
struc.add_atom(pmedatm,
resname=utils.if_not_none(atom.residue.resname, 'UNL'),
resnum=utils.if_not_none(atom.residue.pdbindex, -1),
chain=utils.if_not_none(atom.chain.name, ''))
for bond in mol.bonds:
struc.bonds.append(parmed.Bond(pmedatoms[bond.a1.index],
pmedatoms[bond.a2.index],
order=bond.order))
return struc
def _reassign_chains(f, mol):
""" Change chain ID assignments to the mmCIF standard (parmed uses author assignments)
If the required fields don't exist, a copy of the molecule is returned unchanged.
Args:
f (file): mmcif file/stream
mol (moldesign.Molecule): molecule with default parmed assignemnts
Returns:
moldesign.Molecule: new molecule with reassigned chains
"""
data = mdt.interfaces.biopython_interface.get_mmcif_data(f)
f.seek(0)
try:
poly_seq_ids = _aslist(data['_pdbx_poly_seq_scheme.asym_id'])
nonpoly_ids = _aslist(data['_pdbx_nonpoly_scheme.asym_id'])
except KeyError:
return mol.copy(name=mol.name)
newchain_names = set(poly_seq_ids + nonpoly_ids)
newchains = {name: mdt.Chain(name) for name in newchain_names}
residue_iterator = itertools.chain(
zip(_aslist(data['_pdbx_poly_seq_scheme.mon_id']),
_aslist(data['_pdbx_poly_seq_scheme.pdb_seq_num']),
_aslist(data['_pdbx_poly_seq_scheme.pdb_strand_id']),
_aslist(data['_pdbx_poly_seq_scheme.asym_id'])),
zip(_aslist(data['_pdbx_nonpoly_scheme.mon_id']),
_aslist(data['_pdbx_nonpoly_scheme.pdb_seq_num']),
_aslist(data['_pdbx_nonpoly_scheme.pdb_strand_id']),
_aslist(data['_pdbx_nonpoly_scheme.asym_id'])))
reschains = {(rname, ridx, rchain): newchains[chainid]
for rname, ridx, rchain, chainid in residue_iterator}
for residue in mol.residues:
newchain = reschains[residue.resname, str(residue.pdbindex), residue.chain.name]
residue.chain = newchain
return mdt.Molecule(mol.atoms,
name=mol.name, metadata=mol.metadata)
def _aslist(l):
if isinstance(l, list):
return l
else:
return [l]
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/interfaces/openmm.py | .py | 12,178 | 349 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import itertools
import numpy as np
import pyccc
import moldesign as mdt
from ..compute import packages
from ..utils import from_filepath
from .. import units as u
from ..utils import exports
class OpenMMPickleMixin(object):
def __getstate__(self):
mystate = self.__dict__.copy()
if 'sim' in mystate:
assert 'sim_args' not in mystate
sim = mystate.pop('sim')
mystate['sim_args'] = (sim.topology, sim.system, sim.integrator)
return mystate
def __setstate__(self, state):
from simtk.openmm import app
if 'sim_args' in state:
assert 'sim' not in state
args = state.pop('sim_args')
state['sim'] = app.Simulation(*args)
self.__dict__.update(state)
# This is a factory for the MdtReporter class. It's here so that we don't have to import
# simtk.openmm.app at the module level
def MdtReporter(mol, report_interval):
from simtk.openmm.app import StateDataReporter
class MdtReporter(StateDataReporter):
"""
We'll use this class to capture all the information we need about a trajectory
It's pretty basic - the assumption is that there will be more processing on the client side
"""
def __init__(self, mol, report_interval):
self.mol = mol
self.report_interval = report_interval
self.trajectory = mdt.Trajectory(mol)
self.annotation = None
self.last_report_time = None
self.logger = mdt.helpers.DynamicsLog()
def __del__(self):
try:
super().__del__()
except AttributeError:
pass # suppress irritating error msgs
def report_from_mol(self, **kwargs):
self.mol.calculate()
if self.annotation is not None:
kwargs.setdefault('annotation', self.annotation)
self.report(self.mol.energy_model.sim,
self.mol.energy_model.sim.context.getState(getEnergy=True,
getForces=True,
getPositions=True,
getVelocities=True),
settime=self.mol.time)
def report(self, simulation, state, settime=None):
""" Callback for dynamics after the specified interval
Args:
simulation (simtk.openmm.app.Simulation): simulation to report on
state (simtk.openmm.State): state of the simulation
"""
# TODO: make sure openmm masses are the same as MDT masses
settime = settime if settime is not None else simtk2pint(state.getTime())
report = dict(
positions=simtk2pint(state.getPositions()),
momenta=simtk2pint(state.getVelocities())*self.mol.dim_masses,
forces=simtk2pint(state.getForces()),
time=settime,
vectors=simtk2pint(state.getPeriodicBoxVectors()),
potential_energy=simtk2pint(state.getPotentialEnergy()))
if self.annotation is not None: report['annotation'] = self.annotation
if settime:
self.last_report_time = report['time']
self.trajectory.new_frame(properties=report)
self.logger.print_step(self.mol, properties=report)
def describeNextReport(self, simulation):
"""
Returns:
tuple: A five element tuple. The first element is the number of steps
until the next report. The remaining elements specify whether
that report will require positions, velocities, forces, and
energies respectively.
"""
steps = self.report_interval - simulation.currentStep % self.report_interval
return (steps, True, True, True, True)
return MdtReporter(mol, report_interval)
PINT_NAMES = {'mole': u.avogadro,
'degree': u.degrees,
'radian': u.radians,
'elementary charge': u.q_e}
@exports
def simtk2pint(quantity, flat=False):
""" Converts a quantity from the simtk unit system to the internal unit system
Args:
quantity (simtk.unit.quantity.Quantity): quantity to convert
flat (bool): if True, flatten 3xN arrays to 3N
Returns:
mdt.units.MdtQuantity: converted to MDT unit system
"""
from simtk import unit as stku
mag = np.array(quantity._value)
if quantity.unit == stku.radian:
return mag * u.radians
if quantity.unit == stku.degree:
return mag * u.degrees
for dim, exp in itertools.chain(quantity.unit.iter_scaled_units(),
quantity.unit.iter_top_base_units()):
if dim.name in PINT_NAMES:
pintunit = PINT_NAMES[dim.name]
else:
pintunit = u.ureg.parse_expression(dim.name)
mag = mag * (pintunit**exp)
if flat:
mag = np.reshape(mag, (np.product(mag.shape),))
return u.default.convert(mag)
@exports
def pint2simtk(quantity):
""" Converts a quantity from the pint to simtk unit system.
Note SimTK has a less extensive collection that pint. May need to have pint convert
to SI first
"""
from simtk import unit as stku
SIMTK_NAMES = {'ang': stku.angstrom,
'fs': stku.femtosecond,
'nm': stku.nanometer,
'ps': stku.picosecond}
newvar = quantity._magnitude
for dim, exp in quantity._units.items():
if dim in SIMTK_NAMES:
stkunit = SIMTK_NAMES[dim]
else:
stkunit = getattr(stku, dim)
newvar = newvar * stkunit ** exp
return newvar
@packages.openmm.runsremotely
def _amber_to_mol(prmtop_file, inpcrd_file):
""" Convert an amber prmtop and inpcrd file to an MDT molecule
Args:
prmtop_file (file-like): topology file in amber prmtop format
inpcrd_file (file-like): coordinate file in amber crd format
Returns:
moldesign.Molecule: Molecule parsed from amber output
"""
from simtk.openmm import app
prmtop = from_filepath(app.AmberPrmtopFile, prmtop_file)
inpcrd = from_filepath(app.AmberInpcrdFile, inpcrd_file)
mol = topology_to_mol(prmtop.topology,
positions=inpcrd.positions,
velocities=inpcrd.velocities)
return mol
if packages.openmm.is_installed():
def amber_to_mol(prmtop_file, inpcrd_file):
if not isinstance(prmtop_file, pyccc.FileContainer):
prmtop_file = pyccc.LocalFile(prmtop_file)
if not isinstance(inpcrd_file, pyccc.FileContainer):
inpcrd_file = pyccc.LocalFile(inpcrd_file)
return _amber_to_mol(prmtop_file, inpcrd_file)
else:
amber_to_mol = _amber_to_mol
exports(amber_to_mol)
@exports
def topology_to_mol(topo, name=None, positions=None, velocities=None, assign_bond_orders=True):
""" Convert an OpenMM topology object into an MDT molecule.
Args:
topo (simtk.openmm.app.topology.Topology): topology to convert
name (str): name to assign to molecule
positions (list): simtk list of atomic positions
velocities (list): simtk list of atomic velocities
assign_bond_orders (bool): assign bond orders from templates (simtk topologies
do not store bond orders)
"""
from simtk import unit as stku
# Atoms
atommap = {}
newatoms = []
masses = u.amu*[atom.element.mass.value_in_unit(stku.amu) for atom in topo.atoms()]
for atom,mass in zip(topo.atoms(), masses):
newatom = mdt.Atom(atnum=atom.element.atomic_number,
name=atom.name,
mass=mass)
atommap[atom] = newatom
newatoms.append(newatom)
# Coordinates
if positions is not None:
poslist = np.array([p.value_in_unit(stku.nanometer) for p in positions]) * u.nm
poslist.ito(u.default.length)
for newatom, position in zip(newatoms, poslist):
newatom.position = position
if velocities is not None:
velolist = np.array([v.value_in_unit(stku.nanometer/stku.femtosecond) for v in velocities]) * u.nm/u.fs
velolist = u.default.convert(velolist)
for newatom, velocity in zip(newatoms, velolist):
newatom.momentum = newatom.mass * simtk2pint(velocity)
# Biounits
chains = {}
for chain in topo.chains():
if chain.id not in chains:
chains[chain.id] = mdt.Chain(name=chain.id, index=chain.index)
newchain = chains[chain.id]
for residue in chain.residues():
newresidue = mdt.Residue(name='%s%d' % (residue.name,
residue.index),
chain=newchain,
pdbindex=int(residue.id),
pdbname=residue.name)
newchain.add(newresidue)
for atom in residue.atoms():
newatom = atommap[atom]
newatom.residue = newresidue
newresidue.add(newatom)
# Bonds
bonds = {}
for bond in topo.bonds():
a1, a2 = bond
na1, na2 = atommap[a1], atommap[a2]
if na1 not in bonds:
bonds[na1] = {}
if na2 not in bonds:
bonds[na2] = {}
b = mdt.Bond(na1, na2)
b.order = 1
if name is None:
name = 'Unnamed molecule from OpenMM'
newmol = mdt.Molecule(newatoms, name=name)
if assign_bond_orders:
for residue in newmol.residues:
try:
residue.assign_template_bonds()
except (KeyError, ValueError):
pass
return newmol
@exports
def mol_to_topology(mol):
""" Create an openmm topology object from an MDT molecule
Args:
mol (moldesign.Molecule): molecule to copy topology from
Returns:
simtk.openmm.app.Topology: topology of the molecule
"""
from simtk.openmm import app
top = app.Topology()
chainmap = {chain: top.addChain(chain.name) for chain in mol.chains}
resmap = {res: top.addResidue(res.resname, chainmap[res.chain], str(res.pdbindex))
for res in mol.residues}
atommap = {atom: top.addAtom(atom.name,
app.Element.getBySymbol(atom.element),
resmap[atom.residue],
id=str(atom.pdbindex))
for atom in mol.atoms}
for bond in mol.bonds:
top.addBond(atommap[bond.a1], atommap[bond.a2])
return top
@exports
def mol_to_modeller(mol):
from simtk.openmm import app
if mol.is_small_molecule:
if not mol.residues[0].resname:
mol.residues[0].resname = 'UNL'
mol.residues[0].pdbindex = 1
if not mol.chains[0].pdbname:
mol.chains[0].pdbname = 'A'
return app.Modeller(mol_to_topology(mol), pint2simtk(mol.positions))
def list_openmmplatforms():
from simtk import openmm
return [openmm.Platform.getPlatform(ip).getName()
for ip in range(openmm.Platform.getNumPlatforms())]
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/units/tools.py | .py | 7,651 | 245 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from .. import utils
from .quantity import *
def unitsum(iterable):
"""
Faster method to compute sums of iterables if they're all in the right units
Args:
iterable (Iter[MdtQuantity]): iterable to sum over
Returns:
MdtQuantity: the sum
"""
g0 = next(iterable).copy()
for item in iterable:
if item.units == g0.units:
g0._magnitude += item._magnitude
else:
g0 += item
return g0
def dot(a1, a2):
""" Dot product that respects units
Args:
a1 (MdtQuantity or np.ndarray): First term in dot product
a2 (MdtQuantity or np.ndarray): Second term in dot product
Returns:
MdtQuantity or np.ndarray: dot product (MdtQuantity if either input has units, ndarray else)
"""
if isinstance(a2, MdtQuantity):
return a2.ldot(a1)
else: # this will work whether or not a1 has units
return a1.dot(a2)
@utils.args_from(np.linspace)
def linspace(start, stop, **kwargs):
u1 = getattr(start, 'units', ureg.dimensionless)
u2 = getattr(stop, 'units', ureg.dimensionless)
if u1 == u2 == ureg.dimensionless:
return np.linspace(start, stop, **kwargs)
else:
q1mag = start.magnitude
q2mag = stop.value_in(start.units)
return np.linspace(q1mag, q2mag, **kwargs) * start.units
def arrays_almost_equal(a1, a2):
""" Return true if arrays are almost equal up to numerical noise
Note:
This is assumes that absolute differences less than 1e-12 are insignificant. It is
therefore more likely to return "True" for very small numbers and
"False" for very big numbers. Caveat emptor.
Args:
a1 (MdtQuantity or np.ndarray): first array
a2 (MdtQuantity or np.ndarray): second array
Returns:
bool: True if arrays differ by no more than numerical noise in any element
Raises:
DimensionalityError: if the arrays have incompatible units
"""
a1units = False
if isinstance(a1, MdtQuantity):
if a1.dimensionless:
a1mag = a1.value_in(ureg.dimensionless)
else:
a1units = True
a1mag = a1.magnitude
else:
a1mag = a1
if isinstance(a2, MdtQuantity):
if a2.dimensionless:
if a1units:
raise DimensionalityError(a1.units, ureg.dimensionless,
"Cannot compare objects")
else:
a2mag = a2.value_in(ureg.dimensionless)
elif not a1units:
raise DimensionalityError(ureg.dimensionless, a2.units,
"Cannot compare objects")
else:
a2mag = a2.value_in(a1.units)
else:
if a1units:
raise DimensionalityError(a1.units, ureg.dimensionless,
"Cannot compare objects")
else:
a2mag = a2
return np.allclose(a1mag, a2mag, atol=1e-12)
def from_json(j):
"""
Convert a JSON description to a quantity.
This is the inverse of :meth:`moldesign.units.quantity.MDTQuantity.to_json`
Args:
j (dict): ``{value: <float>, units: <str>}``
Returns:
moldesign.units.quantity.MDTQuantity
"""
return j['value'] * ureg(j['units'])
def get_units(q):
""" Return the base unit system of an quantity or arbitrarily-nested iterables of quantities
Note: This routine will dive on the first element of iterables until a quantity with units
until the units can be determined. It will not check the remaining elements of the iterable
for consistency
Examples:
>>> from moldesign import units
>>> units.get_units(1.0 * units.angstrom)
<Unit('angstrom')>
>>> units.get_units(np.array([1.0, 2, 3.0]))
<Unit('dimensionless')>
>>> # We dive on the first element of each iterable until we can determine a unit system:
>>> units.get_units([[1.0 * u.dalton, 3.0 * u.eV], ['a'], 'gorilla'])
<Unit('amu')>
Args:
q (MdtQuantity or numeric): quantity to test
Returns:
MdtUnit: the quantity's units
"""
if isinstance(q, MdtUnit):
return q
x = q
while True:
try:
x = next(x.__iter__())
except (AttributeError, TypeError):
break
else:
if isinstance(x, str):
raise TypeError('Found string data while trying to determine units')
q = MdtQuantity(x)
if q.dimensionless:
return ureg.dimensionless
else:
return q.units
def array(qlist, defunits=False, _baseunit=None):
""" Facilitates creating an array with units - like numpy.array, but it also checks
units for all components of the array.
Note:
Unlike numpy.array, these arrays must have numeric type - this routine will
raise a ValueError if a non-square array is passed.
Args:
qlist (List[MdtQuantity]): List-like object of quantity objects
defunits (bool): if True, convert the array to the default units
Returns:
MdtQuantity: ndarray-like object with standardized units
Raises:
DimensionalityError: if the array has inconsistent units
ValueError: if the array could not be converted to a square numpy array
"""
from . import default
if hasattr(qlist, 'units') and hasattr(qlist, 'magnitude'):
return MdtQuantity(qlist)
if _baseunit is None:
_baseunit = get_units(qlist)
if _baseunit.dimensionless:
return _make_nparray(qlist)
if defunits:
_baseunit = default.get_default(_baseunit)
if hasattr(qlist, 'to'): # if already a quantity, just convert and return
return qlist.to(_baseunit)
try: # try to create a quantity
return _baseunit * [array(item, _baseunit=_baseunit).value_in(_baseunit) for item in qlist]
except TypeError: # if here, one or more objects cannot be converted to quantities
raise DimensionalityError(_baseunit, ureg.dimensionless,
extra_msg='Object "%s" does not have units' % qlist)
def _make_nparray(q):
""" Turns a list of dimensionless numbers into a numpy array. Does not permit object arrays
"""
if hasattr(q, 'units'):
return q.value_in(ureg.dimensionless)
try:
arr = np.array([_make_nparray(x) for x in q])
if arr.dtype == 'O':
raise ValueError("Could not create numpy array of numeric data - is your input square?")
else:
return arr
except TypeError:
return q
#@utils.args_from(np.broadcast_to)
def broadcast_to(arr, *args, **kwargs):
units = arr.units
newarr = np.zeros(2) * units
tmp = np.broadcast_to(arr, *args, **kwargs)
newarr._magnitude = tmp
return newarr
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/units/quantity.py | .py | 11,689 | 361 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from past.builtins import basestring
import operator
import copy
from os.path import join, abspath, dirname
import numpy as np
from pint import UnitRegistry, set_application_registry, DimensionalityError, UndefinedUnitError
from ..utils import ResizableArray
# Set up pint's unit definitions
ureg = UnitRegistry()
unit_def_file = join(abspath(dirname(__file__)), '..', '_static_data','pint_atomic_units.txt')
ureg.load_definitions(unit_def_file)
ureg.default_system = 'nano'
set_application_registry(ureg)
class MdtUnit(ureg.Unit):
"""
Pickleable version of pint's Unit class.
"""
def __reduce__(self):
return _get_unit, (str(self),)
@property
def units(self):
return self
def convert(self, value):
""" Returns quantity converted to these units
Args:
value (MdtQuantity or Numeric): value to convert
Returns:
MdtQuantity: converted value
Raises:
DimensionalityError: if the quantity does not have these units' dimensionality
"""
if hasattr(value, 'to'):
return value.to(self)
elif self.dimensionless:
return value * self
else:
raise DimensionalityError('Cannot convert "%s" to units of "%s"' % (value, self))
def value_of(self, value):
""" Returns numeric value of the quantity in these units
Args:
value (MdtQuantity or Numeric): value to convert
Returns:
Numeric: value in this object's units
Raises:
DimensionalityError: if the quantity does not have these units' dimensionality
"""
v = self.convert(value)
return v.magnitude
def _get_unit(unitname):
"""pickle helper for deserializing MdtUnit objects"""
return getattr(ureg, unitname)
class MdtQuantity(ureg.Quantity):
"""
This is a 'patched' version of pint's quantities that can be pickled (slightly hacky)
and supports more numpy operations.
Users should never need to instantiate this directly - instead, construct
MDT quantities by multiplying numbers/arrays with the pre-defined units
Examples:
>>> 5.0 * units.femtoseconds
>>> [1.0,2.0,3.0] * units.eV
"""
# Patching some ufunc intercepts - these don't all necessarily work
_Quantity__prod_units = ureg.Quantity._Quantity__prod_units.copy()
_Quantity__prod_units['dot'] = 'mul'
_Quantity__prod_units['cross'] = 'mul'
_Quantity__copy_units = ureg.Quantity._Quantity__copy_units[:]
_Quantity__copy_units.extend(('diagonal', 'append', '_broadcast_to'))
_Quantity__handled = ureg.Quantity._Quantity__handled + ('diagonal', 'append', 'dot')
# For pickling - prevent delegation to the built-in types' __getnewargs__ methods:
def __getattr__(self, item):
if item == '__getnewargs__':
raise AttributeError('__getnewargs__ not accessible in this class')
else:
return super(MdtQuantity, self).__getattr__(item)
def __reduce__(self):
replacer = list(super(MdtQuantity, self).__reduce__())
replacer[0] = MdtQuantity
return tuple(replacer)
def __deepcopy__(self, memo):
result = copy.deepcopy(self.magnitude, memo) * self.get_units()
memo[id(self)] = result
return result
def __hash__(self):
m = self._magnitude
if isinstance(m, np.ndarray) and m.shape == ():
m = float(m)
return hash((m, str(self.units)))
def __setitem__(self, key, value):
from . import array as quantityarray
try: # Speed up item assignment by overriding pint's implementation
if self.units == value.units:
self.magnitude[key] = value._magnitude
else:
self.magnitude[key] = value.value_in(self.units)
except AttributeError:
if isinstance(value, basestring):
raise TypeError("Cannot assign units to a string ('%s')"%value)
try: # fallback to pint's implementation
super().__setitem__(key, value)
except (TypeError, ValueError):
# one last ditch effort to create a more well-behaved object
super().__setitem__(key, quantityarray(value))
def __eq__(self, other):
return self.compare(other, operator.eq)
@property
def shape(self):
return self.magnitude.shape
@shape.setter
def shape(self, value):
self.magnitude.shape = value
def compare(self, other, op):
""" Augments the :class:`pint._Quantity` method with the following features:
- Comparisons to dimensionless 0 can proceed without unit checking
"""
other = MdtQuantity(other)
try:
iszero = other.magnitude == 0.0 and other.dimensionless
except ValueError:
iszero = False
if iszero:
return op(self.magnitude, other.magnitude)
else:
return op(self.magnitude, other.value_in(self.units))
def get_units(self):
"""
Return the base unit system of an quantity
"""
x = self
while True:
try: x = next(x.__iter__())
except (AttributeError, TypeError): break
try:
y = 1.0 * x
y._magnitude = 1.0
return y
except AttributeError:
return 1.0
def norm(self):
"""L2-norm of this object including units
Returns:
Scalar: L2-norm
"""
units = self.get_units()
return units * np.linalg.norm(self._magnitude)
def normalized(self):
""" Normalizes a vector or matrix
Returns:
np.ndarray: L2-normalized copy of this array (no units)
"""
from ..mathutils import normalized
return normalized(self.magnitude)
def dot(self, other):
""" Dot product that correctly multiplies units
Returns:
Array
"""
if hasattr(other, 'get_units'):
units = self.get_units() * other.get_units()
else:
units = self.get_units()
return units * np.dot(self, other)
def cross(self, other):
""" Cross product that correctly multiplies units
Returns:
Array
"""
if hasattr(other, 'get_units'):
units = self.get_units() * other.get_units()
else:
units = self.get_units()
return units * np.cross(self, other)
def ldot(self, other):
""" Left-multiplication version of dot that correctly multiplies units
This is mathematically equivalent to ``other.dot(self)``, but preserves units even if ``other``
is a plain numpy array
Args:
other (MdtQuantity or np.ndarray): quantity to take the dot product with
Examples:
>>> mat1 = np.ones((3,2))
>>> vec1 = np.array([-3.0,2.0]) * u.angstrom
>>> vec1.ldot(mat1)
<Quantity([-1. -1. -1.], 'ang')>
>>> # This won't work because "mat1", a numpy array, doesn't respect units
>>> mat1.dot(vec1)
"""
if hasattr(other, 'get_units'):
units = self.get_units() * other.get_units()
else:
units = self.get_units()
return units * np.dot(other, self)
def __mod__(self, other):
my_units = self.get_units()
s_mag = self.magnitude
o_mag = other.value_in(my_units)
m = s_mag % o_mag
return m * my_units
# backwards-compatible name
value_in = ureg.Quantity.m_as
def defunits_value(self):
return self.defunits().magnitude
# defunits = ureg.Quantity.to_base_units # replacing this with the new pint implementation
def defunits(self):
"""Return this quantity in moldesign's default unit system (as specified in moldesign.units.default)"""
from . import default
return default.convert(self)
# defunits_inplace = ureg.Quantity.ito_base_units # replacing this with the new pint implementation
def defunits_inplace(self):
"""Internally convert quantity to default units"""
from . import default
newunit = default.get_baseunit(self)
return self.ito(newunit)
def to_simtk(self):
""" Return a SimTK quantity object
"""
from moldesign.interfaces.openmm import pint2simtk
return pint2simtk(self)
def to_json(self):
""" Convert to a simple JSON format
Returns:
dict: ``{value: <float>, units: <str>}``
Examples:
>>> from moldesign.units import angstrom
>>> q = 1.0 * angstrom
>>> q.to_json()
{'units':'angstrom', value: 1.0}
"""
mag = self.magnitude
if isinstance(mag, np.ndarray):
mag = mag.tolist()
return {'value': mag,
'units': str(self.units)}
def make_resizable(self):
self._magnitude = ResizableArray(self._magnitude)
def append(self, item):
from .tools import array
try:
mag = item.value_in(self.units)
except AttributeError: # handles lists of quantities
mag = array(item).value_in(self.units)
self._magnitude.append(mag)
def extend(self, items):
from . import array
mags = array(items).value_in(self.units)
self._magnitude.append(mags)
# monkeypatch pint's unit registry to return BuckyballQuantities
ureg.Quantity = MdtQuantity
ureg.Unit = MdtUnit
# These synonyms are here solely so that we can write descriptive docstrings
# TODO: use typing module to turn these into real abstract types, with dimensional parameterization
class Scalar(MdtQuantity):
""" A scalar quantity (i.e., a single floating point number) with attached units
"""
def __init__(self, *args):
raise NotImplementedError('This is an abstract class - use MdtQuantity instead')
class Vector(MdtQuantity):
""" A vector quantity (i.e., a list of floats) with attached units that behaves like a
1-dimensional numpy array with units
"""
def __init__(self, *args):
raise NotImplementedError('This is an abstract class - use MdtQuantity instead')
class Array(MdtQuantity):
""" A matrix quantity (i.e., a matrix of floats) with attached units that behaves like a
2-dimensional numpy array with units
"""
def __init__(self, *args):
raise NotImplementedError('This is an abstract class - use MdtQuantity instead')
class Tensor(MdtQuantity):
""" A multidimensional array of floats with attached units that behaves like a
multidimensional numpy array with units
"""
def __init__(self, *args):
raise NotImplementedError('This is an abstract class - use MdtQuantity instead')
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/units/__init__.py | .py | 95 | 4 | from .quantity import *
from .constants import *
from .tools import *
from .unitsystem import * | Python |
3D | Autodesk/molecular-design-toolkit | moldesign/units/constants.py | .py | 1,972 | 69 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from .quantity import *
dimensionless = ureg.dimensionless
# Constants
unity = ureg.angstrom / ureg.angstrom
imi = 1.0j
pi = np.pi
sqrtpi = np.sqrt(np.pi)
sqrt2 = np.sqrt(2.0)
epsilon_0 = ureg.epsilon_0
c = ureg.speed_of_light
alpha = ureg.fine_structure_constant
hbar = ureg.hbar
boltz = boltzmann_constant = k_b = ureg.boltzmann_constant
avogadro = (1.0 * ureg.mole * ureg.avogadro_number).to(unity).magnitude
# atomic units
hartree = ureg.hartree
a0 = bohr = ureg.bohr
atomic_time = t0 = ureg.t0
electron_mass = m_e = ureg.electron_mass
electron_charge = q_e = ureg.elementary_charge
# useful units
fs = femtoseconds = ureg.femtosecond
ps = picoseconds = ureg.picosecond
ns = nanoseconds = ureg.nanosecond
eV = electronvolts = ureg.eV
kcalpermol = ureg.kcalpermol
gpermol = ureg.gpermol
kjpermol = ureg.kjpermol
radians = radian = rad = ureg.rad
degrees = degree = deg = ureg.degrees
amu = da = dalton = ureg.amu
kelvin = ureg.kelvin
nm = ureg.nanometers
angstrom = ureg.angstrom
molar = ureg.mole / ureg.liter
debye = ureg.debye
# sets default unit systems
def_length = angstrom
def_time = fs
def_vel = angstrom / fs
def_mass = amu
def_momentum = def_mass * def_vel
def_force = def_momentum / def_time
def_energy = eV
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/units/unitsystem.py | .py | 6,681 | 190 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from .constants import *
class UnitSystem(object):
""" Class for standardizing units - specifies preferred units for length, mass, energy etc.
In MDT, many methods will automatically convert output using the UnitSystem at
``moldesign.units.default``
Args:
length (MdtUnit): length units
mass (MdtUnit): mass units
time (MdtUnit): time units
energy (MdtUnit): energy units
temperature (MdtUnit): temperature units (default: kelvin)
force (MdtUnit): force units (default: energy/length)
momentum (MdtUnit): momentum units (default: mass * length / time)
angle (MdtUnit): angle units (default: radians)
charge (MdtUnit): charge units (default: fundamental charge)
"""
def __init__(self, length, mass, time, energy,
temperature=kelvin,
force=None, momentum=None,
angle=radians,
charge=q_e):
self.length = length
self.mass = mass
self.time = time
self.energy = energy
self.temperature = temperature
self.force = force
self.momentum = momentum
self.angle = angle
self.charge = charge
def __getitem__(self, item):
""" For convenience when using pint dimensionality descriptions.
This aliases self['item'] = self['[item]'] = self.item,
e.g. self['length'] = self['[length]'] = self.length
"""
itemname = item.lstrip('[').rstrip(']')
return getattr(self, itemname)
@property
def force(self):
if self._force is None:
return self.energy / self.length
else:
return self._force
@force.setter
def force(self, f):
self._force = f
@property
def momentum(self):
if self._momentum is None:
return self.mass * self.length / self.time
else:
return self._momentum
@momentum.setter
def momentum(self, f):
self._momentum = f
def convert(self, quantity):
""" Convert a quantity into this unit system.
Args:
quantity (MdtQuantity or MdtUnit): quantity to convert
"""
baseunit = self.get_baseunit(quantity)
if baseunit == ureg.dimensionless:
return quantity * ureg.dimensionless
else:
result = quantity.to(baseunit)
return result
def get_default(self, q):
""" Return the default unit system for objects with these dimensions
Args:
q (MdtQuantity or MdtUnit): quantity to get default units for
Returns:
MdtUnit: Proper units for this quantity
"""
return self.get_baseunit(1.0 * q).units
def convert_if_possible(self, quantity):
if isinstance(quantity, MdtQuantity):
return self.convert(quantity)
else:
return quantity
def get_baseunit(self, quantity):
""" Get units of a quantity, list or array
Args:
quantity (Any): any number or list-like object with units
Raises:
TypeError: if the passed object cannot have units (e.g., it's a string or ``None``)
Returns:
MdtUnit: units found in the passed object
"""
try:
dims = dict(quantity.dimensionality)
except AttributeError:
try:
q = quantity[0]
except (TypeError, StopIteration):
if isinstance(quantity, (int, float, complex)):
return ureg.dimensionless
raise TypeError('This type of object cannot have physical units')
if isinstance(q, str):
raise TypeError('This type of object cannot have physical units')
try:
return self.get_baseunit(q)
except (IndexError, TypeError): # Assume dimensionless
return ureg.dimensionless
baseunit = ureg.dimensionless
# Factor out force units
if self._force:
if '[length]' in dims and '[mass]' in dims and '[time]' in dims:
while dims['[length]'] >= 1 and dims['[mass]'] >= 1 and dims['[time]'] <= -2:
baseunit *= self['force']
dims['[length]'] -= 1
dims['[mass]'] -= 1
dims['[time]'] += 2
# Factor out energy units
if '[length]' in dims and '[mass]' in dims and '[time]' in dims:
while dims['[length]'] >= 1 and dims['[mass]'] >= 1 and dims['[time]'] <= -2:
baseunit *= self['energy']
dims['[length]'] -= 2
dims['[mass]'] -= 1
dims['[time]'] += 2
# Factor out momentum units
if self._momentum:
if '[length]' in dims and '[mass]' in dims and '[time]' in dims:
while dims['[length]'] >= 1 and dims['[mass]'] >= 1 and dims['[time]'] <= -1:
baseunit *= self['momentum']
dims['[length]'] -= 1
dims['[mass]'] -= 1
dims['[time]'] += 1
if '[current]' in dims:
dims.setdefault('[charge]', 0)
dims.setdefault('[time]', 0)
dims['[charge]'] += dims['[current]']
dims['[time]'] -= dims['[current]']
dims.pop('[current]')
# Otherwise, just use the units
for unit in dims:
if dims[unit] == 0:
continue
try:
baseunit *= self[unit]**dims[unit]
except AttributeError:
baseunit *= ureg[unit]**dims[unit]
return baseunit.units
default = UnitSystem(length=angstrom, mass=amu, time=fs, energy=eV)
atomic_units = UnitSystem(length=a0, mass=m_e, time=t0, energy=hartree)
nano_si = UnitSystem(length=nm, mass=dalton, time=fs, energy=kjpermol) | Python |
3D | Autodesk/molecular-design-toolkit | moldesign/tools/__init__.py | .py | 120 | 8 | def toplevel(o):
__all__.append(o.__name__)
return o
__all__ = []
from .topology import *
from .build import *
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/tools/topology.py | .py | 7,884 | 223 | """
This module contains various utility functions that are exposed to API users
"""
from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import moldesign as mdt
from moldesign import units as u
from . import toplevel, __all__ as _pkgall
from moldesign.interfaces.openbabel import add_hydrogen, guess_bond_orders
from moldesign.interfaces.pdbfixer_interface import mutate_residues, add_water
from moldesign.interfaces.tleap_interface import create_ff_parameters
from moldesign.interfaces.ambertools import calc_am1_bcc_charges, calc_gasteiger_charges
_pkgall.extend(('add_hydrogen guess_bond_orders mutate_residues add_water'
' create_ff_parameters calc_am1_bcc_charges calc_gasteiger_charges ').split())
ATNUM_VALENCE_CHARGE = {6: {3: -1, 4: 0},
7: {2: -1, 3: 0, 4: 1},
8: {1: -1, 2: 0, 3: 1},
9: {1: 0, 2: 1}}
ION_CHARGE = {1: 1, # H
11: 1, # Na+
19: 1, # K+
12: 2, # Mg 2+
20: 2, # Ca 2+
9: -1, # F-
17: -1, # Cl-
35: -1, # Br-
53: -1} # I-
@toplevel
def assign_formal_charges(mol, ignore_nonzero=True):
""" Assign formal charges to C,N,O,F atoms in this molecule based on valence
Args:
mol (moldesign.Molecule): Molecule to assign formal charges to. The formal charges of its
atoms and its total charge will be adjusted in place.
ignore_nonzero (bool): If formal charge is already set to a nonzero value, ignore this atom
Note:
This method ONLY applies to C,N, O and F, based on a simple valence model.
These results should be manually inspected for consistency.
Raises:
UnhandledValenceError: for cases not handled by the simple valence model
References:
These assignments are illustrated by the formal charge patterns in
http://www.chem.ucla.edu/~harding/tutorials/formalcharge.pdf
"""
from moldesign.exceptions import UnhandledValenceError
# TODO: scrape formal charge data from the PDB chem comp dictionary
# cache these values in case we fail to assign charges
totalcharge = mol.charge
oldcharges = [atom.formal_charge for atom in mol.atoms]
for atom in mol.atoms:
if ignore_nonzero and atom.formal_charge != 0:
continue
v = atom.valence
newcharge = None
if atom.atnum in ATNUM_VALENCE_CHARGE:
if v in ATNUM_VALENCE_CHARGE[atom.atnum]:
newcharge = ATNUM_VALENCE_CHARGE[atom.atnum][v]
else:
for oldcharge, a in zip(oldcharges, mol.atoms):
a.oldcharge = oldcharge
mol.charge = totalcharge
raise UnhandledValenceError(atom)
elif atom in ION_CHARGE and v == 0:
newcharge = ION_CHARGE[atom.atnum]
if newcharge is not None:
mol.charge += newcharge * u.q_e - atom.formal_charge
atom.formal_charge = newcharge * u.q_e
@toplevel
def set_hybridization_and_saturate(mol):
""" Assign bond orders, saturate with hydrogens, and assign formal charges
Specifically, this is a convenience function that runs:
``mdt.guess_bond_orders``, ``mdt.add_hydrogen``, and ``mdt.assign_formal_charges``
Note:
This does NOT add missing residues to biochemical structures. This functionality will be
available as :meth:`moldesign.add_missing_residues`
Args:
mol (moldesign.Molecule): molecule to clean
Returns:
moldesign.Molecule: cleaned version of the molecule
"""
m1 = mdt.guess_bond_orders(mol)
m2 = mdt.add_hydrogen(m1)
assign_formal_charges(m2)
return m2
@toplevel
def guess_histidine_states(mol):
""" Attempt to assign protonation states to histidine residues.
Note:
This function is highly unlikely to give accurate results! It is intended for convenience
when histidine states can easily be guessed from already-present hydrogens or when they are
judged to be relatively unimportant.
This can be done simply by renaming HIS residues:
1. If HE2 and HD1 are present, the residue is renamed to HIP
2. If only HE2 is present, the residue is renamed to HIE
3. Otherwise, the residue is renamed to HID (the most common form)
Args:
mol (moldesign.Molecule): molecule to change (in place)
"""
for residue in mol.residues:
if residue.resname == 'HIS':
oldname = str(residue)
if 'HE2' in residue and 'HD1' in residue:
residue.resname = 'HIP'
elif 'HE2' in residue:
residue.resname = 'HIE'
else:
residue.resname = 'HID'
print('Renaming %s from HIS to %s' % (oldname, residue.resname))
@toplevel
def split_chains(mol, distance_threshold=1.75*u.angstrom):
""" Split a molecule's chains into unbroken biopolymers and groups of non-polymers
This function is non-destructive - the passed molecule will not be modified.
Specifically, this function will:
- Split any chain with non-contiguous biopolymeric pieces into single, contiguous polymers
- Remove any solvent molecules from a chain into their own chain
- Isolate ligands from each chain into their own chains
Args:
mol (mdt.Molecule): Input molecule
distance_threshold (u.Scalar[length]): if not ``None``, the maximum distance between
adjacent residues for which we consider them "contiguous". For PDB data, values greater
than 1.4 Angstrom are eminently reasonable; the default threshold of 1.75 Angstrom is
purposefully set to be extremely cautious (and still much lower than the distance to
the *next* nearest neighbor, generally around 2.5 Angstrom)
Returns:
mdt.Molecule: molecule with separated chains
"""
tempmol = mol.copy()
def bonded(r1, r2):
if r2 not in r1.bonded_residues:
return False
if distance_threshold is not None and r1.distance(r2) > distance_threshold:
return False
return True
def addto(chain, res):
res.chain = None
chain.add(res)
allchains = [mdt.Chain(tempmol.chains[0].name)]
for chain in tempmol.chains:
chaintype = chain.residues[0].type
solventchain = mdt.Chain(None)
ligandchain = mdt.Chain(None)
for ires, residue in enumerate(chain.residues):
if residue.type == 'unknown':
thischain = ligandchain
elif residue.type in ('water', 'solvent', 'ion'):
thischain = solventchain
else:
assert residue.type == chaintype
if ires != 0 and not bonded(residue.prev_residue, residue):
allchains.append(mdt.Chain(None))
thischain = allchains[-1]
addto(thischain, residue)
for c in (solventchain, ligandchain):
if c.num_atoms > 0:
allchains.append(c)
return mdt.Molecule(allchains)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/tools/build.py | .py | 3,448 | 86 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import string
import moldesign as mdt
import moldesign.molecules
from moldesign.interfaces.ambertools import build_bdna, build_dna_helix
from . import toplevel, __all__ as _pkgall
_pkgall.extend(['build_bdna', 'build_dna_helix'])
@toplevel
def build_assembly(mol, assembly_name):
""" Create biological assembly using a bioassembly specification.
This routine builds a biomolecular assembly using the specification from a PDB header (if
present, this data can be found in the "REMARK 350" lines in the PDB file). Assemblies are
author-assigned structures created by copying, translating, and rotating a subset of the
chains in the PDB file.
See Also:
http://pdb101.rcsb.org/learn/guide-to-understanding-pdb-data/biological-assemblies
Args:
mol (moldesign.Molecule): Molecule with assembly data (assembly data will be created by the
PDB parser at ``molecule.properties.bioassembly``)
assembly_name (str OR int): id of the biomolecular assembly to build.
Returns:
mol (moldesign.Molecule): molecule containing the complete assembly
Raises:
AttributeError: If the molecule does not contain any biomolecular assembly data
KeyError: If the specified assembly is not present
"""
if isinstance(assembly_name, int): assembly_name = str(assembly_name)
if 'bioassemblies' not in mol.properties:
raise AttributeError('This molecule does not contain any biomolecular assembly data')
try:
asm = mol.properties.bioassemblies[assembly_name]
except KeyError:
raise KeyError(('The specified assembly name ("%s") was not found. The following '
'assemblies are present: %s') %
(assembly_name,
', '.join(list(mol.properties.bioassemblies.keys()))))
# Make sure each chain gets a unique name - up to all the letters in the alphabet, anyway
used_chain_names = set()
alpha = iter(string.ascii_uppercase)
# Create the new molecule by copying, transforming, and renaming the original chains
all_atoms = moldesign.molecules.atomcollections.AtomList()
for i, t in enumerate(asm.transforms):
for chain_name in asm.chains:
chain = mol.chains[chain_name].copy()
chain.transform(t)
while chain.name in used_chain_names:
chain.name = next(alpha)
used_chain_names.add(chain.name)
chain.pdbname = chain.pdbindex = chain.name
all_atoms.extend(chain.atoms)
newmol = mdt.Molecule(all_atoms,
name="%s (bioassembly %s)" % (mol.name, assembly_name))
return newmol | Python |
3D | Autodesk/molecular-design-toolkit | moldesign/_notebooks/Tutorial 2. Biochemical basics.ipynb | .ipynb | 6,849 | 264 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<span style=\"float:right\"><a href=\"http://moldesign.bionano.autodesk.com/\" target=\"_blank\" title=\"About\">About</a> <a href=\"https://github.com/autodesk/molecular-design-toolkit/issues\" target=\"_blank\" title=\"Issues\">Issues</a> <a href=\"http://bionano.autodesk.com/MolecularDesignToolkit/explore.html\" target=\"_blank\" title=\"Tutorials\">Tutorials</a> <a href=\"http://autodesk.github.io/molecular-design-toolkit/\" target=\"_blank\" title=\"Documentation\">Documentation</a></span>\n",
"</span>\n",
"\n",
"<br>\n",
"\n",
"\n",
"<center><h1>Tutorial 2: Playing with proteins</h1></center>\n",
"\n",
"Here, you'll see how to build, visualize, and simulate a protein structure from the PDB."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# First, import MDT\n",
"import moldesign as mdt\n",
"from moldesign import units as u\n",
"\n",
"# This sets up your notebook to draw inline plots:\n",
"%matplotlib inline\n",
"import numpy as np\n",
"from matplotlib.pylab import *\n",
"\n",
"try: import seaborn\n",
"except ImportError: pass"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Contents\n",
"=======\n",
"---\n",
" - [1. Download from PDB](#1.-Download-from-PDB)\n",
" - [2. Strip water and assign forcefield](#2.-Strip-water-and-assign-forcefield)\n",
" - [3. Set up energy model and minimize](#3.-Set-up-energy-model-and-minimize)\n",
" - [4. Add integrator and run dynamics](#4.-Add-integrator-and-run-dynamics)\n",
" - [5. Some simple analysis](#5.-Some-simple-analysis)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 1. Download from PDB\n",
"In this example, we'll look at `1YU8`, a crystal structure of the Villin Headpiece."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"one_yu8 = mdt.read('data/1yu8.pdb')\n",
"one_yu8.draw()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"By evaluating the `one_yu8` variable, you can get some basic biochemical information, including metadata about missing residues in this crystal structure (hover over the amino acid sequence to get more information)."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"one_yu8"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 2. Strip water and assign forcefield\n",
"\n",
"Next, we isolate the protein and prepare it using the default Amber forcefield parameters."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"headpiece = mdt.Molecule([res for res in one_yu8.residues if res.type == 'protein'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ff = mdt.forcefields.DefaultAmber()\n",
"protein = ff.create_prepped_molecule(headpiece)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 3. Set up energy model and minimize\n",
"\n",
"Next, we'll set up a full molecular mechanics model using OpenMM, then run a minimization and visualize it."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"protein.set_energy_model(mdt.models.OpenMMPotential)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"protein.configure_methods()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mintraj = protein.minimize()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mintraj.draw()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 4. Add integrator and run dynamics"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"protein.set_integrator(mdt.integrators.OpenMMLangevin,\n",
" temperature=300*u.kelvin,\n",
" timestep=2.0*u.fs,\n",
" frame_interval=2.0*u.ps)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"traj = protein.run(20*u.ps)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"traj.draw()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 5. Some simple analysis\n",
"As in tutorial 1, tutorial objects permit a range of timeseries-based analyses."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Plot kinetic energy vs. time\n",
"plot(traj.time, traj.kinetic_energy)\n",
"xlabel('time / %s' % u.default.time); ylabel('energy / %s' % u.default.energy)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Plot time evolution of PHE47's sidechain rotation\n",
"residue = protein.chains[0].residues['PHE47']\n",
"plot(traj.time, traj.dihedral(residue['CA'], residue['CB']).to(u.degrees))\n",
"\n",
"title('sidechain rotation vs time')\n",
"xlabel('time / %s' % u.default.time); ylabel(u'angle / º')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Plot distance between C-terminus and N-terminus\n",
"chain = protein.chains[0]\n",
"plot(traj.time, traj.distance(chain.n_terminal.atoms['N'],\n",
" chain.c_terminal.atoms['C']))\n",
"\n",
"plt.title('bond length vs time')\n",
"xlabel('time / %s' % u.default.time); ylabel('distance / %s' % u.default.length)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3"
}
},
"nbformat": 4,
"nbformat_minor": 1
} | Unknown |
3D | Autodesk/molecular-design-toolkit | moldesign/_notebooks/Example 4. HIV Protease bound to an inhibitor.ipynb | .ipynb | 10,729 | 350 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<span style=\"float:right\"><a href=\"http://moldesign.bionano.autodesk.com/\" target=\"_blank\" title=\"About\">About</a> <a href=\"https://github.com/autodesk/molecular-design-toolkit/issues\" target=\"_blank\" title=\"Issues\">Issues</a> <a href=\"http://bionano.autodesk.com/MolecularDesignToolkit/explore.html\" target=\"_blank\" title=\"Tutorials\">Tutorials</a> <a href=\"http://autodesk.github.io/molecular-design-toolkit/\" target=\"_blank\" title=\"Documentation\">Documentation</a></span>\n",
"</span>\n",
"\n",
"<br>\n",
"\n",
"<center><h1>Example 4: The Dynamics of HIV Protease bound to a small molecule </h1> </center>\n",
"\n",
"This notebook prepares a co-crystallized protein / small molecule ligand structure from [the PDB database](http://www.rcsb.org/pdb/home/home.do) and prepares it for molecular dynamics simulation. \n",
"\n",
" - _Author_: [Aaron Virshup](https://github.com/avirshup), Autodesk Research<br>\n",
" - _Created on_: August 9, 2016\n",
" - _Tags_: HIV Protease, small molecule, ligand, drug, PDB, MD"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import moldesign as mdt\n",
"import moldesign.units as u"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Contents\n",
"=======\n",
"---\n",
" - [I. The crystal structure](#I.-The-crystal-structure)\n",
" - [A. Download and visualize](#A.-Download-and-visualize)\n",
" - [B. Try assigning a forcefield](#B.-Try-assigning-a-forcefield)\n",
" - [II. Parameterizing a small molecule](#II.-Parameterizing-a-small-molecule)\n",
" - [A. Isolate the ligand](#A.-Isolate-the-ligand)\n",
" - [B. Assign bond orders and hydrogens](#B.-Assign-bond-orders-and-hydrogens)\n",
" - [C. Generate forcefield parameters](#C.-Generate-forcefield-parameters)\n",
" - [III. Prepping the protein](#III.-Prepping-the-protein)\n",
" - [A. Strip waters](#A.-Strip-waters)\n",
" - [B. Histidine](#B.-Histidine)\n",
" - [IV. Prep for dynamics](#IV.-Prep-for-dynamics)\n",
" - [A. Assign the forcefield](#A.-Assign-the-forcefield)\n",
" - [B. Attach and configure simulation methods](#B.-Attach-and-configure-simulation-methods)\n",
" - [D. Equilibrate the protein](#D.-Equilibrate-the-protein)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"## I. The crystal structure\n",
"\n",
"First, we'll download and investigate the [3AID crystal structure](http://www.rcsb.org/pdb/explore.do?structureId=3aid).\n",
"\n",
"### A. Download and visualize"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"protease = mdt.from_pdb('3AID')\n",
"protease"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"protease.draw()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### B. Try assigning a forcefield"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This structure is not ready for MD - this command will raise a `ParameterizationError` Exception. After running this calculation, click on the **Errors/Warnings** tab to see why."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"amber_ff = mdt.forcefields.DefaultAmber()\n",
"newmol = amber_ff.create_prepped_molecule(protease)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You should see 3 errors: \n",
" 1. The residue name `ARQ` not recognized\n",
" 1. Atom `HD1` in residue `HIS69`, chain `A` was not recognized\n",
" 1. Atom `HD1` in residue `HIS69`, chain `B` was not recognized\n",
" \n",
"(There's also a warning about bond distances, but these can be generally be fixed with an energy minimization before running dynamics)\n",
"\n",
"We'll start by tackling the small molecule \"ARQ\"."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## II. Parameterizing a small molecule\n",
"We'll use the GAFF (generalized Amber force field) to create force field parameters for the small ligand.\n",
"\n",
"### A. Isolate the ligand\n",
"Click on the ligand to select it, then we'll use that selection to create a new molecule."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"sel = mdt.widgets.ResidueSelector(protease)\n",
"sel"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"drugres = mdt.Molecule(sel.selected_residues[0])\n",
"drugres.draw2d(width=700, show_hydrogens=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### B. Assign bond orders and hydrogens\n",
"A PDB file provides only limited information; they often don't provide indicate bond orders, hydrogen locations, or formal charges. These can be added, however, with the `add_missing_pdb_data` tool:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"drugmol = mdt.tools.set_hybridization_and_saturate(drugres)\n",
"drugmol.draw(width=500)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"drugmol.draw2d(width=700, show_hydrogens=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### C. Generate forcefield parameters\n",
"\n",
"We'll next generate forcefield parameters using this ready-to-simulate structure.\n",
"\n",
"**NOTE**: for computational speed, we use the `gasteiger` charge model. This is not advisable for production work! `am1-bcc` or `esp` are far likelier to produce sensible results."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"drug_parameters = mdt.create_ff_parameters(drugmol, charges='gasteiger')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## III. Prepping the protein\n",
"\n",
"Section II. dealt with getting forcefield parameters for an unknown small molecule. Next, we'll prep the other part of the structure.\n",
"\n",
"### A. Strip waters\n",
"\n",
"Waters in crystal structures are usually stripped from a simulation as artifacts of the crystallization process. Here, we'll remove the waters from the protein structure."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dehydrated = mdt.Molecule([atom for atom in protease.atoms if atom.residue.type != 'water'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### B. Histidine\n",
"Histidine is notoriously tricky, because it exists in no less than three different protonation states at biological pH (7.4) - the \"delta-protonated\" form, referred to with residue name `HID`; the \"epsilon-protonated\" form aka `HIE`; and the doubly-protonated form `HIP`, which has a +1 charge. Unfortunately, crystallography isn't usually able to resolve the difference between these three.\n",
"\n",
"Luckily, these histidines are pretty far from the ligand binding site, so their protonation is unlikely to affect the dynamics. We'll therefore use the `guess_histidine_states` function to assign a reasonable starting guess."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mdt.guess_histidine_states(dehydrated)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## IV. Prep for dynamics\n",
"\n",
"With these problems fixed, we can succesfully assigne a forcefield and set up the simulation.\n",
"\n",
"### A. Assign the forcefield\n",
"Now that we have parameters for the drug and have dealt with histidine, the forcefield assignment will succeed:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"amber_ff = mdt.forcefields.DefaultAmber()\n",
"amber_ff.add_ff(drug_parameters)\n",
"sim_mol = amber_ff.create_prepped_molecule(dehydrated)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### B. Attach and configure simulation methods\n",
"\n",
"Armed with the forcefield parameters, we can connect an energy model to compute energies and forces, and an integrator to create trajectories:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"sim_mol.set_energy_model(mdt.models.OpenMMPotential, implicit_solvent='obc', cutoff=8.0*u.angstrom)\n",
"sim_mol.set_integrator(mdt.integrators.OpenMMLangevin, timestep=2.0*u.fs)\n",
"sim_mol.configure_methods()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### C. Equilibrate the protein\n",
"The next series of cells first minimize the crystal structure to remove clashes, then heats the system to 300K."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mintraj = sim_mol.minimize()\n",
"mintraj.draw()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"traj = sim_mol.run(20*u.ps)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"viewer = traj.draw(display=True)\n",
"viewer.autostyle()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3"
}
},
"nbformat": 4,
"nbformat_minor": 1
} | Unknown |
3D | Autodesk/molecular-design-toolkit | moldesign/_notebooks/Getting Started.ipynb | .ipynb | 2,498 | 80 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"\n",
"<br>\n",
"\n",
"# Get started \n",
"\n",
"Get started with these step-by-step demonstration notebooks. Check out the accompanying [video tutorials](https://www.youtube.com/channel/UCRmzThLOYJ3Tx1e81fXRfOA).\n",
"\n",
"* [Tutorial 1. Making a molecule](Tutorial 1. Making a molecule.ipynb)\n",
"* [Tutorial 2. Biochemical basics](Tutorial 2. Biochemical basics.ipynb)\n",
"* [Tutorial 3. Quantum Chemistry](Tutorial 3. Quantum Chemistry.ipynb)\n",
"\n",
"\n",
"# Keep going\n",
"\n",
"* [Example 1. Build and simulate DNA](Example 1. Build and simulate DNA.ipynb)\n",
"* [Example 2. UV-vis absorption spectra](Example 2. UV-vis absorption spectra.ipynb)\n",
"* [Example 3. Simulating a crystal structure](Example 3. Simulating a crystal structure.ipynb)\n",
"* [Example 4. HIV Protease bound to an inhibitor](Example 4. HIV Protease bound to an inhibitor.ipynb)\n",
"* [Example 5. Enthalpic barriers](Example 5. Enthalpic barriers.ipynb)\n",
"\n",
"\n",
"# Read the docs\n",
"* [Molecular Design Toolkit Documentation](http://autodesk.github.io/molecular-design-toolkit/)\n",
"* [Using Jupyter Notebooks](http://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/what_is_jupyter.html \"Title\")\n",
"\n",
"\n",
"# Get in touch\n",
" * [Learn more](http://lifesciences.autodesk.com/) about Life Sciences at Autodesk.\n",
"\n",
"\n",
"# Get help\n",
" * [File a bug report](https://github.com/autodesk/molecular-design-toolkit/issues)\n",
" * [Contact us](mailto:moleculardesigntoolkit@autodesk.com)\n",
"\n",
"Contact us at moleculardesigntoolkit@autodesk.com\n",
"\n",
"\n",
""
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
| Unknown |
3D | Autodesk/molecular-design-toolkit | moldesign/_notebooks/Tutorial 3. Quantum Chemistry.ipynb | .ipynb | 10,473 | 415 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<span style=\"float:right\"><a href=\"http://moldesign.bionano.autodesk.com/\" target=\"_blank\" title=\"About\">About</a> <a href=\"https://github.com/autodesk/molecular-design-toolkit/issues\" target=\"_blank\" title=\"Issues\">Issues</a> <a href=\"http://bionano.autodesk.com/MolecularDesignToolkit/explore.html\" target=\"_blank\" title=\"Tutorials\">Tutorials</a> <a href=\"http://autodesk.github.io/molecular-design-toolkit/\" target=\"_blank\" title=\"Documentation\">Documentation</a></span>\n",
"</span>\n",
"\n",
"<br>\n",
"\n",
"\n",
"<center><h1>Tutorial 3: Intro to Quantum Chemistry </h1> </center>\n",
"---\n",
"\n",
"This tutorial shows how to select a quantum chemistry method, visualize orbitals, and analyze the electronic wavefunction."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import numpy as np\n",
"from matplotlib.pylab import *\n",
"try: import seaborn #optional, makes plots look nicer\n",
"except ImportError: pass\n",
"\n",
"import moldesign as mdt\n",
"from moldesign import units as u"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## I. Build and minimize minimal basis set hydrogen\n",
"\n",
"### A. Build the molecule\n",
"This cell builds H<sub>2</sub> by creating the two atoms, and explicitly setting their positions.\n",
"\n",
"**Try editing this cell to**:\n",
" * Create HeH<sup>+</sup>\n",
" * Create H<sub>3</sub><sup>+</sup>\n",
" * Change the atoms' initial positions"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"atom1 = mdt.Atom('H')\n",
"atom2 = mdt.Atom('H')\n",
"atom1.bond_to(atom2,1)\n",
"atom2.x = 2.0 * u.angstrom\n",
"\n",
"h2 = mdt.Molecule([atom1,atom2], name='H2', charge=0)\n",
"h2.draw(height=300)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### B. Run a hartree-fock calculation\n",
"The next cell adds the RHF energy model to our molecule, then triggers a calculation.\n",
"\n",
"**Try editing this cell to**:\n",
" * Change the atomic basis\n",
" * Get a list of other available energy models (type `mdt.models.` and then hit the `[tab]` key)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"h2.set_energy_model(mdt.models.RHF, basis='3-21g')\n",
"h2.calculate()\n",
"\n",
"print('Calculated properties:', h2.properties.keys())\n",
"\n",
"print('Potential energy:', h2.potential_energy)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### C. Visualize the orbitals\n",
"After running the calculation, we have enough information to visualize the molecular orbitals."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"h2.draw_orbitals()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### D. Minimize the energy\n",
"Here, we'll run a quick energy minimization then visualize how the hydrogen nuclei AND the atomic wavefunctions changed."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"minimization = h2.minimize(frame_interval=1, nsteps=10)\n",
"minimization.draw_orbitals()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# II. Analyzing the wavefunction\n",
"\n",
"The wavefunction created during QM calculations will be stored as an easy-to-analyze python object:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"wfn = h2.wfn\n",
"wfn"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## A. Molecular orbital data\n",
"First, let's examine the molecular orbitals. The overlaps, fock matrix, coefficents, and density matrix are all available as 2D numpy arrays (with units where applicable).\n",
"\n",
"We'll specifically look at the \"canonical\" orbitals that result from Hartree-Fock calculations."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mos = wfn.orbitals.canonical\n",
"mos"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"MOs are, of course, a linear combination of AOs:\n",
"\n",
"\\begin{equation} \\left| \\text{MO}_i \\right \\rangle = \\sum_j c_{ij} \\left| \\text{AO}_j \\right\\rangle \\end{equation}\n",
"\n",
"The coefficient $c_{ij}$ is stored at `mos.coeffs[i,j]`"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mos.coeffs"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Most MO sets are orthogonal; their overlaps will often be the identity matrix (plus some small numerical noise)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mos.overlaps"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"By definition, the fock matrix should be orthogonal as well; the orbital energies are on its diagonal."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"matshow(mos.fock.value_in(u.eV), cmap=cm.seismic)\n",
"colorbar(label='fock element/eV')\n",
"title('Fock matrix')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The `MolecularOrbitals` class also offers several methods to transform operators into different bases. For instance, the `overlap` method creates an overlap matrix between the AOs and MOs, where `olap[i,j]` is the overlap between MO _i_ and AO _j_:\n",
"\\begin{equation}\n",
"\\text{olap[i,j]} = \\left\\langle MO_i \\middle| AO_j \\right \\rangle\n",
"\\end{equation}"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"olap = mos.overlap(wfn.aobasis)\n",
"olap"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Various other matrices are available from this this object, such as the two-electron Hamiltonian terms:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"matshow(mos.h2e.value_in(u.eV), cmap=cm.inferno)\n",
"colorbar(label='2-electron hamiltonian term / eV')\n",
"title('2-electron hamiltonian')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## B. Individual orbitals\n",
"\n",
"You can work with inidividual orbitals as well. For instance, to get a list (in order) of our four atomic orbitals (i.e., the basis functions):"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"aos = wfn.orbitals.atomic\n",
"aos[:]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's grab the lowest orbital and examine some of its properties:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"orb = aos[0]\n",
"print('Name:', orb.name)\n",
"print('Energy:', orb.energy)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Orbital objects also give you access to various matrix elements:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ha_1s = aos[0]\n",
"hb_1s = aos[3]\n",
"\n",
"print('Overlap between 1s orbitals: ', ha_1s.overlap(hb_1s))\n",
"print('Fock element between 1s orbitals', ha_1s.fock_element(hb_1s))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## C. Basis functions\n",
"\n",
"An object representing the wavefunction's basis functions is available at `wfn.aobasis`"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"wfn.aobasis"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It stores a list of `AtomicBasisFunction` objects:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"basis_function = wfn.aobasis[0]\n",
"print('Name:', basis_function.name)\n",
"print('Angular quantum number:', basis_function.l)\n",
"print('Azimuthal quantum number:', basis_function.m)\n",
"print('Centered at:', basis_function.center)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Each basis function is defined as a linear combination of \"primitive\" 3D Gaussian functions:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"basis_function.primitives"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And these primitives can themselves be examined:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"primitive = basis_function.primitives[0]\n",
"print(primitive)\n",
"print(\"Coeff:\", primitive.coeff)\n",
"print(\"Alpha:\", primitive.alpha)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3"
}
},
"nbformat": 4,
"nbformat_minor": 1
} | Unknown |
3D | Autodesk/molecular-design-toolkit | moldesign/_notebooks/Example 1. Build and simulate DNA.ipynb | .ipynb | 9,215 | 330 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<span style=\"float:right\"><a href=\"http://moldesign.bionano.autodesk.com/\" target=\"_blank\" title=\"About\">About</a> <a href=\"https://github.com/autodesk/molecular-design-toolkit/issues\" target=\"_blank\" title=\"Issues\">Issues</a> <a href=\"http://bionano.autodesk.com/MolecularDesignToolkit/explore.html\" target=\"_blank\" title=\"Tutorials\">Tutorials</a> <a href=\"http://autodesk.github.io/molecular-design-toolkit/\" target=\"_blank\" title=\"Documentation\">Documentation</a></span>\n",
"</span>\n",
"\n",
"<br>\n",
"\n",
"<center><h1>Example 1: Build and simulate DNA </h1> </center>\n",
"---\n",
"\n",
"\n",
"This notebook builds a small DNA double helix, assigns a forcefield to it, and runs a molecular dynamics simulation.\n",
"\n",
" - _Author_: [Aaron Virshup](https://github.com/avirshup), Autodesk Research<br>\n",
" - _Created on_: July 1, 2016\n",
" - _Tags_: DNA, molecular dynamics\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import moldesign as mdt\n",
"from moldesign import units as u\n",
"\n",
"%matplotlib inline\n",
"from matplotlib.pyplot import *\n",
"\n",
"# seaborn is optional -- it makes plots nicer\n",
"try: import seaborn \n",
"except ImportError: pass"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Contents\n",
"=======\n",
"---\n",
" - [1. Create a DNA helix](#1.-Create-a-DNA-helix)\n",
" - [2. Forcefield](#2.-Forcefield)\n",
" - [3. Constraints](#3.-Constraints)\n",
" - [4. MD Setup](#4.-MD-Setup)\n",
" - [5. Minimization](#5.-Minimization)\n",
" - [6. Dynamics](#6.-Dynamics)\n",
" - [7. Analysis](#7.-Analysis)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1. Create a DNA helix"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dna_structure = mdt.build_dna_helix('ACTGACTG', helix_type='b')\n",
"dna_structure.draw()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dna_structure"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2. Forcefield\n",
"The cell below adds forcefield parameters to the molecule.\n",
"\n",
"**NOTE:** This molecule because is not missing expected atoms. If your molecule _is_ missing atoms (e.g., it's missing its hydrogens), use the `Forcefield.create_prepped_molecule` method instead of `Forcefield.assign`.\n",
"\n",
"**Click on the ERRORS/WARNING tab** to see any warnings raised during assignment."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ff = mdt.forcefields.DefaultAmber()\n",
"ff.assign(dna_structure)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3. Constraints\n",
"This section uses an interactive selection to constrain parts of the DNA.\n",
"\n",
"After executing the following cells, **click on the 3' and 5' bases:**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"rs = mdt.widgets.ResidueSelector(dna_structure)\n",
"rs"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"if len(rs.selected_residues) == 0:\n",
" raise ValueError(\"You didn't click on anything!\")\n",
" \n",
"rs.selected_residues"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for residue in rs.selected_residues:\n",
" print('Constraining position for residue %s' % residue)\n",
" \n",
" for atom in residue.atoms:\n",
" dna_structure.constrain_atom(atom)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Of course, fixing the positions of the terminal base pairs is a fairly extreme step. For extra credit, see if you can find a less heavy-handed keep the terminal base pairs bonded. (Try using tab-completion to see what other constraint methods are available)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 4. MD Setup\n",
"This section adds an OpenMM energy model and a Langevin integrator to the DNA."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dna_structure.set_energy_model(mdt.models.OpenMMPotential,\n",
" implicit_solvent='obc')\n",
"\n",
"dna_structure.set_integrator(mdt.integrators.OpenMMLangevin,\n",
" timestep=2.0*u.fs,\n",
" temperature=300.0*u.kelvin,\n",
" frame_interval=1.0*u.ps)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can interactively configure these methods:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dna_structure.configure_methods()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 5. Minimization\n",
"\n",
"Nearly every MD simulation should be preceded by an energy minimization, especially for crystal structure data. This will remove any energetically catastrophic clashes between atoms and prevent our simulation from blowing up."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"trajectory = dna_structure.minimize(nsteps=200)\n",
"trajectory.draw()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plot(trajectory.potential_energy)\n",
"\n",
"xlabel('steps');ylabel('energy / %s' % trajectory.unit_system.energy)\n",
"title('Energy relaxation'); grid('on')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 6. Dynamics\n",
"We're ready to run 25 picoseconds of dynamics at room temperature (that's 300º Kelvin). This will probably take a few minutes - if you're on an especially pokey computer, you might want to reduce the length of the simulation."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"traj = dna_structure.run(run_for=25.0*u.ps)\n",
"traj.draw()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 7. Analysis\n",
"The trajectory object (named `traj`) gives direct access to the timeseries data:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plot(traj.time, traj.kinetic_energy, label='kinetic energy')\n",
"plot(traj.time, traj.potential_energy - traj.potential_energy[0], label='potential_energy')\n",
"xlabel('time / {time.units}'.format(time=traj.time))\n",
"ylabel('energy / {energy.units}'.format(energy=traj.kinetic_energy))\n",
"title('Energy vs. time'); legend(); grid('on')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Using the trajectory's 'plot' method will autogenerate axes labels with the appropriate units\n",
"traj.plot('time','kinetic_temperature')\n",
"title('Temperature'); grid('on')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This cell sets up an widget that plots the RMSDs of any selected group of atoms.\n",
"**Select a group of atoms, then click \"Run plot_rmsd\" to generate a plot**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from ipywidgets import interact_manual\n",
"from IPython.display import display\n",
"\n",
"rs = mdt.widgets.ResidueSelector(dna_structure)\n",
"def plot_rmsd(): \n",
" plot(traj.time, traj.rmsd(rs.selected_atoms))\n",
" xlabel('time / fs'); ylabel(u'RMSD / Å')\n",
"interact_manual(plot_rmsd, description='plot rmsd')\n",
"rs"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3"
}
},
"nbformat": 4,
"nbformat_minor": 1
} | Unknown |
3D | Autodesk/molecular-design-toolkit | moldesign/_notebooks/Tutorial 1. Making a molecule.ipynb | .ipynb | 7,813 | 289 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<span style=\"float:right\"><a href=\"http://moldesign.bionano.autodesk.com/\" target=\"_blank\" title=\"About\">About</a> <a href=\"https://github.com/autodesk/molecular-design-toolkit/issues\" target=\"_blank\" title=\"Issues\">Issues</a> <a href=\"http://bionano.autodesk.com/MolecularDesignToolkit/explore.html\" target=\"_blank\" title=\"Tutorials\">Tutorials</a> <a href=\"http://autodesk.github.io/molecular-design-toolkit/\" target=\"_blank\" title=\"Documentation\">Documentation</a></span>\n",
"</span>\n",
"\n",
"<br>\n",
"\n",
"<center><h1>Tutorial 1: Making a molecule</h1></center>\n",
"\n",
"This notebook gets you started with MDT - you'll build a small molecule, visualize it, and run a basic calculation."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Contents\n",
"=======\n",
"---\n",
" - [1. Import the toolkit](#1.-Import-the-toolkit)\n",
" - [A. Optional: Set up your computing backend](#A.-Optional:-Set-up-your-computing-backend)\n",
" - [2. Build it](#2.-Read-in-the-molecule)\n",
" - [3. View it](#3.-Visualize-it)\n",
" - [4. Simulate it](#4.-Simulate-it)\n",
" - [5. Minimize it](#5.-Minimize-it)\n",
" - [6. Write it](#6.-Write-it)\n",
" - [7. Examine it](#7.-Examine-it)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1. Import the toolkit\n",
"This cell loads the toolkit and its unit system. To execute a cell, click on it, then press <kbd>shift</kbd> + <kbd>enter</kbd>. (If you're new to the notebook environment, you may want to check out [this helpful cheat sheet](https://nbviewer.jupyter.org/github/jupyter/notebook/blob/master/docs/source/examples/Notebook/Notebook%20Basics.ipynb))."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import moldesign as mdt\n",
"import moldesign.units as u"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Optional: configuration options\n",
"If you'd like to set some basic MDT configuration options, you can execute the following cell to create a GUI configuration editor:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mdt.configure()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2. Read in a molecular structure\n",
"\n",
"Let's get started by reading in a molecular structure file.\n",
"\n",
"When you execute this cell, you'll use `mdt.read` function to parse an XYZ-format file to create an MDT molecule object named, appropriately enough, `molecule`:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"molecule = mdt.read('data/butane.xyz')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Jupyter notebooks will automatically print out the value of the last statement in any cell. When you evaluate a `Molecule`, as in the cell below, you'll get some quick summary data:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"molecule"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3. Visualize it\n",
"MDT molecules have three built-in visualization methods - `draw`, `draw2d`, and `draw3d`. Try them out!"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"viewer = molecule.draw()\n",
"viewer # we tell Jupyter to draw the viewer by putting it on the last line of the cell"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Try clicking on some of the atoms in the visualization you've just created.\n",
"\n",
"Afterwards, you can retrieve a list of the Python objects representing the atoms you clicked on:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(viewer.selected_atoms)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 4. Simulate it\n",
"\n",
"So far, we've created a 3D molecular structure and visualized it right in the notebook.\n",
"\n",
"If you sat through [VSEPR theory](https://en.wikipedia.org/wiki/VSEPR_theory) in P. Chem, you might notice this molecule (butane) is looking decidedly non-optimal. Luckily, we can use simulation to predict a better structure.\n",
"\n",
"We're specifically going to run a basic type of Quantum Chemistry calculation called \"Hartree-Fock\", which will give us information about the molecule's orbitals and energy."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"molecule.set_energy_model(mdt.models.RHF, basis='sto-3g')\n",
"properties = molecule.calculate()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(properties.keys())\n",
"print('Energy: ', properties['potential_energy'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"molecule.draw_orbitals()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 5. Minimize it\n",
"\n",
"Next, an energy minimization - that is, we're going to move the atoms around in order to find a minimum energy conformation. This is a great way to start cleaning up the messy structure we started with. The calculation might take a second or two ..."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mintraj = molecule.minimize()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mintraj.draw_orbitals()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 6. Write it"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"molecule.write('my_first_molecule.xyz')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mintraj.write('my_first_minimization.P.gz')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 7. Play with it\n",
"There are any number of directions to go from here. See how badly you can distort the geometry:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mdt.widgets.GeometryBuilder(molecule)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"molecule.calculate_potential_energy()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3"
}
},
"nbformat": 4,
"nbformat_minor": 1
} | Unknown |
3D | Autodesk/molecular-design-toolkit | moldesign/_notebooks/Example 5. Enthalpic barriers.ipynb | .ipynb | 9,049 | 308 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<span style=\"float:right\"><a href=\"http://moldesign.bionano.autodesk.com/\" target=\"_blank\" title=\"About\">About</a> <a href=\"https://github.com/autodesk/molecular-design-toolkit/issues\" target=\"_blank\" title=\"Issues\">Issues</a> <a href=\"http://bionano.autodesk.com/MolecularDesignToolkit/explore.html\" target=\"_blank\" title=\"Tutorials\">Tutorials</a> <a href=\"http://autodesk.github.io/molecular-design-toolkit/\" target=\"_blank\" title=\"Documentation\">Documentation</a></span>\n",
"</span>\n",
"\n",
"<br>\n",
"\n",
"<center><h1>Example 5: Calculating torsional barriers with relaxation </h1> </center>\n",
"\n",
"---\n",
"\n",
"This workflow calculates the enthalpic barrier of a small alkane.\n",
"\n",
" - _Author_: [Aaron Virshup](https://github.com/avirshup), Autodesk Research<br>\n",
" - _Created on_: September 23, 2016\n",
" - _Tags_: reaction path, constrained minimization, torsion, enthalpic\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import moldesign as mdt\n",
"from moldesign import units as u\n",
"\n",
"%matplotlib notebook\n",
"from matplotlib.pyplot import *\n",
"try: import seaborn # optional, makes graphs look better\n",
"except ImportError: pass\n",
"\n",
"u.default.energy = u.kcalpermol # use kcal/mol for energy"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Contents\n",
"=======\n",
"---\n",
" - [I. Create and minimize the molecule](#I.-Create-and-minimize-the-molecule)\n",
" - [II. Select the torsional bond](#II.-Select-the-torsional-bond)\n",
" - [III. Rigid rotation scan](#III.-Rigid-rotation-scan)\n",
" - [IV. Relaxed rotation scan](#IV.-Relaxed-rotation-scan)\n",
" - [V. Plot the potential energy surfaces](#V.-Plot-the-potential-energy-surfaces)\n",
" - [VI. Investigate conformational changes](#VI.-Investigate-conformational-changes)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# I. Create and minimize the molecule"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mol = mdt.from_smiles('CCCC')\n",
"mol.draw()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mol.set_energy_model(mdt.models.GaffSmallMolecule)\n",
"mol.energy_model.configure()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"minimization = mol.minimize(nsteps=40)\n",
"minimization.draw()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# II. Select the torsional bond\n",
"\n",
"Next, we use the `BondSelector` to pick the bond that we'll rotate around."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"bs = mdt.widgets.BondSelector(mol)\n",
"bs"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"twist = mdt.DihedralMonitor(bs.selected_bonds[0])\n",
"twist"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# III. Rigid rotation scan\n",
"\n",
"First, we'll perform a simple energy scan, simply by rotating around the bond and calculating the energy at each point.\n",
"\n",
"This gives us only an _upper bound_ on the enthalpic rotation barrier. This is because we keep the molecule rigid, except for the single rotating bond."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"angles = np.arange(-150, 210, 5) * u.degree"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"rigid = mdt.Trajectory(mol)\n",
"for angle in angles:\n",
" twist.value = angle\n",
" mol.calculate()\n",
" rigid.new_frame(annotation='angle: %s, energy: %s' % (twist.value.to(u.degrees), mol.potential_energy))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"rigid.draw()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"figure()\n",
"plot(angles, rigid.potential_energy)\n",
"xlabel(u'dihedral / º'); ylabel('energy / kcal/mol')\n",
"xticks(np.arange(-120,211,30))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# IV. Relaxed rotation scan\n",
"\n",
"Next, we'll get the *right* barrier (up to the accuracy of the energy model).\n",
"\n",
"Here, we'll rotate around the bond, but then perform a _constrained minimization_ at each rotation point. This will allow all other degrees of freedom to relax, thus finding lower energies at each point along the path. \n",
"\n",
"_Note_: In order to break any spurious symmetries, this loop also adds a little bit of random noise to each structure before performing the minimization."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"constraint = twist.constrain()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"relaxed = mdt.Trajectory(mol)\n",
"for angle in angles:\n",
" print(angle,':')\n",
" \n",
" #add random noise to break symmetry\n",
" mol.positions += np.random.random(mol.positions.shape) * 0.01*u.angstrom\n",
" mol.positions -= mol.center_of_mass\n",
" \n",
" twist.value = angle\n",
" constraint.value = angle\n",
" \n",
" t = mol.minimize(nsteps=100)\n",
" relaxed.new_frame(annotation='angle: %s, energy: %s' % (twist.value.to(u.degrees), mol.potential_energy))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"relaxed.draw()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# V. Plot the potential energy surfaces\n",
"\n",
"If you plotted butane's rotation around its central bond, you'll see [three stable points](https://en.wikipedia.org/wiki/Alkane_stereochemistry#Conformation): two at about ±60º (the _gauche_ conformations), and one at 180º (the _anti_ conformation).\n",
"\n",
"You will likely see a large differences in the energetics of the relaxed and rigid scans; depending on the exact starting conformation, the rigid scan can overestimate the rotation barrier by as much as 5 kcal/mol!"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"figure()\n",
"plot(angles, rigid.potential_energy, label='rigid')\n",
"plot(angles, relaxed.potential_energy, label='relaxed')\n",
"plot(angles, abs(rigid.potential_energy - relaxed.potential_energy), label='error')\n",
"xlabel(u'dihedral / º'); ylabel('energy / kcal/mol'); legend()\n",
"xticks(np.arange(-120,211,30))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# VI. Investigate conformational changes\n",
"\n",
"This cell illustrates a simple interactive \"app\" - select the bonds you're interested in, then click the \"show_dihedral\" button to show their relaxed angles as a function of the central twist during the `relaxed` scan."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from ipywidgets import interact_manual\n",
"\n",
"bs = mdt.widgets.BondSelector(mol)\n",
"def show_dihedral():\n",
" figure()\n",
" for bond in bs.selected_bonds:\n",
" dihemon = mdt.DihedralMonitor(bond)\n",
" plot(angles, dihemon(relaxed).to(u.degrees), label=str(bond))\n",
" legend(); xlabel(u'central twist / º'); ylabel(u'bond twist / º')\n",
"interact_manual(show_dihedral)\n",
"bs"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3"
}
},
"nbformat": 4,
"nbformat_minor": 1
} | Unknown |
3D | Autodesk/molecular-design-toolkit | moldesign/_notebooks/Example 3. Simulating a crystal structure.ipynb | .ipynb | 10,039 | 382 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<span style=\"float:right\"><a href=\"http://moldesign.bionano.autodesk.com/\" target=\"_blank\" title=\"About\">About</a> <a href=\"https://github.com/autodesk/molecular-design-toolkit/issues\" target=\"_blank\" title=\"Issues\">Issues</a> <a href=\"http://bionano.autodesk.com/MolecularDesignToolkit/explore.html\" target=\"_blank\" title=\"Tutorials\">Tutorials</a> <a href=\"http://autodesk.github.io/molecular-design-toolkit/\" target=\"_blank\" title=\"Documentation\">Documentation</a></span>\n",
"</span>\n",
"\n",
"<br>\n",
"\n",
"<center><h1>Example 3: Simulating a Holliday Junction PDB assembly </h1> </center>\n",
"\n",
"---\n",
"\n",
"This notebook takes a crystal structure from the PDB and prepares it for simulation.\n",
"\n",
" - _Author_: [Aaron Virshup](https://github.com/avirshup), Autodesk Research\n",
" - _Created on_: July 1, 2016\n",
" - _Tags_: DNA, holliday junction, assembly, PDB, MD"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"from matplotlib.pyplot import *\n",
"\n",
"import moldesign as mdt\n",
"from moldesign import units as u"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Contents\n",
"=======\n",
"---\n",
" - [A. View the crystal structure](#A.-View-the-crystal-structure)\n",
" - [B. Build the biomolecular assembly](#B.-Build-the-biomolecular-assembly)\n",
" - [C. Isolate the DNA](#C.-Isolate-the-DNA)\n",
" - [D. Prep for simulation](#D.-Prep-for-simulation)\n",
" - [E. Dynamics - equilibration](#E.-Dynamics---equilibration)\n",
" - [F. Dynamics - production](#F.-Dynamics---production)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## A. View the crystal structure\n",
"\n",
"We start by downloading the [1KBU](http://www.rcsb.org/pdb/explore.do?structureId=1kbu) crystal structure.\n",
"\n",
"It will generate several warnings. Especially note that it contains [biomolecular \"assembly\"](http://pdb101.rcsb.org/learn/guide-to-understanding-pdb-data/biological-assemblies) information. This means that the file from PDB doesn't contain the complete structure, but we can generate the missing parts using symmetry operations."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"xtal = mdt.from_pdb('1kbu')\n",
"xtal.draw()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## B. Build the biomolecular assembly\n",
"\n",
"As you can read in the warning, 1KBU only has one biomolecular assembly, conveniently named `'1'`. This cell builds and views it:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"assembly = mdt.build_assembly(xtal, 1)\n",
"assembly.draw()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"By evaulating the `assembly` object (it's a normal instance of the `moldesign.Molecule` class), we can get some information about it's content:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"assembly"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Because we're only interested in DNA, we'll create a new molecule using only the DNA residues, and then assign a forcefield to it."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## C. Isolate the DNA\n",
"\n",
"This example will focus only on the DNA components of this structure, so we'll isolate the DNA atoms and create a new molecule from them.\n",
"\n",
"We could do this with a list comprehension, e.g.\n",
"`mdt.Molecule([atom for atom in assembly.atoms if atom.residue.type == 'dna'])`\n",
"\n",
"Here, however we'll use a shortcut for this - the `molecule.get_atoms` method, which allows you to run queries on the atoms:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dna_atoms = assembly.get_atoms('dna')\n",
"dna_only = mdt.Molecule(dna_atoms)\n",
"dna_only.draw3d(display=True)\n",
"dna_only"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## D. Prep for simulation\n",
"Next, we'll assign a forcefield and energy model, then minimize the structure."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ff = mdt.forcefields.DefaultAmber()\n",
"dna = ff.create_prepped_molecule(dna_only)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dna.set_energy_model(mdt.models.OpenMMPotential, implicit_solvent='obc')\n",
"dna.configure_methods()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"minimization = dna.minimize()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"minimization.draw()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## E. Dynamics - equilibration\n",
"The structure is ready. We'll associate an integrator with the molecule, then do a 2 step equilibration - first freezing the peptide backbone and running 300K dynamics, then unfreezing and continuing dyanmics."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Freeze the backbone:\n",
"for residue in dna.residues:\n",
" for atom in residue.backbone:\n",
" dna.constrain_atom(atom)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dna.set_integrator(mdt.integrators.OpenMMLangevin,\n",
" timestep=2.0*u.fs,\n",
" frame_interval=1.0*u.ps,\n",
" remove_rotation=True)\n",
"dna.integrator.configure()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And now we run it. This is may take a while, depending on your hardware."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"equil1 = dna.run(20.0*u.ps)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"equil1.draw()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Next**, we'll remove the constraints and do full dynamics:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dna.clear_constraints()\n",
"equil2 = dna.run(20.0*u.ps)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"equil = equil1 + equil2\n",
"equil.draw()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plot(equil2.time, equil2.rmsd())\n",
"xlabel('time / fs'); ylabel(u'rmsd / Å'); grid()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**NOTE:** THIS IS NOT A SUFFICIENT EQUILIBRATION FOR PRODUCTION MOLECULAR DYNAMICS! \n",
"\n",
"In practice, before going to \"production\", we would *at least* want to run dynamics until the RMSD and thermodynamic observabled have converged. A variety of equilibration protocols are used in practice, including slow heating, reduced coupling, multiple constraints, etc."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## F. Dynamics - production\n",
"\n",
"Assuming that we're satisfied with our system's equilibration, we now gather data for \"production\". This will take a while."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"trajectory = dna.run(40.0*u.ps)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"trajectory.draw()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## G. Save your results\n",
"Any MDT object can be saved to disk. We recommend saving objects with the \"Pickle\" format to make sure that all the data is preserved.\n",
"\n",
"This cell saves the final trajectory to disk as a compressed pickle file:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"trajectory.write('holliday_traj.P.gz')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To load the saved object, use:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"traj = mdt.read('holliday_traj.P.gz')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"traj.draw()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3"
}
},
"nbformat": 4,
"nbformat_minor": 1
} | Unknown |
3D | Autodesk/molecular-design-toolkit | moldesign/_notebooks/Example 2. UV-vis absorption spectra.ipynb | .ipynb | 7,656 | 243 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<span style=\"float:right\"><a href=\"http://moldesign.bionano.autodesk.com/\" target=\"_blank\" title=\"About\">About</a> <a href=\"https://github.com/autodesk/molecular-design-toolkit/issues\" target=\"_blank\" title=\"Issues\">Issues</a> <a href=\"http://bionano.autodesk.com/MolecularDesignToolkit/explore.html\" target=\"_blank\" title=\"Tutorials\">Tutorials</a> <a href=\"http://autodesk.github.io/molecular-design-toolkit/\" target=\"_blank\" title=\"Documentation\">Documentation</a></span>\n",
"</span>\n",
"\n",
"<br>\n",
"\n",
"<center><h1>Example 2: Using MD sampling to calculate UV-Vis spectra</h1> </center>\n",
"\n",
"---\n",
"\n",
"This notebook uses basic quantum chemical calculations to calculate the absorption spectra of a small molecule.\n",
"\n",
" - _Author_: [Aaron Virshup](https://github.com/avirshup), Autodesk Research<br>\n",
" - _Created on_: September 23, 2016\n",
" - _Tags_: excited states, CASSCF, absorption, sampling\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import numpy as np\n",
"from matplotlib.pylab import *\n",
"\n",
"try: import seaborn #optional, makes plots look nicer\n",
"except ImportError: pass\n",
"\n",
"import moldesign as mdt\n",
"from moldesign import units as u"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Contents\n",
"=======\n",
"---\n",
" - [Single point](#Single-point)\n",
" - [Sampling](#Sampling)\n",
" - [Post-processing](#Post-processing)\n",
" - [Create spectrum](#Create-spectrum)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Single point\n",
"\n",
"Let's start with calculating the vertical excitation energy and oscillator strengths at the ground state minimum (aka Franck-Condon) geometry.\n",
"\n",
"Note that the active space and number of included states here is system-specific."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"qmmol = mdt.from_name('benzene')\n",
"qmmol.set_energy_model(mdt.models.CASSCF, active_electrons=6,\n",
" active_orbitals=6, state_average=6, basis='sto-3g')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"properties = qmmol.calculate()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This cell print a summary of the possible transitions. \n",
"\n",
"Note: you can convert excitation energies directly to nanometers using [Pint](https://pint.readthedocs.io) by calling `energy.to('nm', 'spectroscopy')`."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"for fstate in range(1, len(qmmol.properties.state_energies)):\n",
" excitation_energy = properties.state_energies[fstate] - properties.state_energies[0]\n",
" \n",
" print('--- Transition from S0 to S%d ---' % fstate ) \n",
" print('Excitation wavelength: %s' % excitation_energy.to('nm', 'spectroscopy'))\n",
" print('Oscillator strength: %s' % qmmol.properties.oscillator_strengths[0,fstate])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Sampling\n",
"\n",
"Of course, molecular spectra aren't just a set of discrete lines - they're broadened by several mechanisms. We'll treat vibrations here by sampling the molecule's motion on the ground state at 300 Kelvin.\n",
"\n",
"To do this, we'll sample its geometries as it moves on the ground state by:\n",
" 1. Create a copy of the molecule\n",
" 2. Assign a forcefield (GAFF2/AM1-BCC)\n",
" 3. Run dynamics for 5 ps, taking a snapshot every 250 fs, for a total of 20 separate geometries."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mdmol = mdt.Molecule(qmmol)\n",
"mdmol.set_energy_model(mdt.models.GaffSmallMolecule)\n",
"mdmol.minimize()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mdmol.set_integrator(mdt.integrators.OpenMMLangevin, frame_interval=250*u.fs,\n",
" timestep=0.5*u.fs, constrain_hbonds=False, remove_rotation=True,\n",
" remove_translation=True, constrain_water=False)\n",
"mdtraj = mdmol.run(5.0 * u.ps)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Post-processing\n",
"\n",
"Next, we calculate the spectrum at each sampled geometry. Depending on your computer speed and if PySCF is installed locally, this may take up to several minutes to run."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"post_traj = mdt.Trajectory(qmmol)\n",
"for frame in mdtraj:\n",
" qmmol.positions = frame.positions\n",
" qmmol.calculate()\n",
" post_traj.new_frame()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This cell plots the results - wavelength vs. oscillator strength at each geometry for each transition:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"wavelengths_to_state = []\n",
"oscillators_to_state = []\n",
"\n",
"for i in range(1, len(qmmol.properties.state_energies)):\n",
" wavelengths_to_state.append(\n",
" (post_traj.state_energies[:,i] - post_traj.potential_energy).to('nm', 'spectroscopy'))\n",
" oscillators_to_state.append([o[0,i] for o in post_traj.oscillator_strengths])\n",
" \n",
"for istate, (w,o) in enumerate(zip(wavelengths_to_state, oscillators_to_state)):\n",
" plot(w,o, label='S0 -> S%d'%(istate+1),\n",
" marker='o', linestyle='none')\n",
"xlabel('wavelength / nm'); ylabel('oscillator strength'); legend()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Create spectrum\n",
"\n",
"We're finally ready to calculate a spectrum - we'll create a histogram of all calculated transition wavelengths over all states, weighted by the oscillator strengths."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from itertools import chain\n",
"all_wavelengths = u.array(list(chain(*wavelengths_to_state)))\n",
"all_oscs = u.array(list(chain(*oscillators_to_state)))\n",
"hist(all_wavelengths, weights=all_oscs, bins=50)\n",
"xlabel('wavelength / nm')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3"
}
},
"nbformat": 4,
"nbformat_minor": 1
} | Unknown |
3D | Autodesk/molecular-design-toolkit | moldesign/_notebooks/nbscripts/strip_nb_output.py | .py | 1,747 | 55 | #!/usr/bin/env python
"""strip outputs from an IPython Notebook
Opens a notebook, strips its output, and writes the outputless version to the original file.
Useful mainly as a git pre-commit hook for users who don't want to track output in VCS.
This does mostly the same thing as the `Clear All Output` command in the notebook UI.
Adapted from rom https://gist.github.com/minrk/6176788 to work with
git filter driver
FROM https://github.com/cfriedline/ipynb_template/blob/master/nbstripout
"""
import sys
from future.utils import PY2
from nbformat import v4
def strip_output(nb):
"""strip the outputs from a notebook object"""
# set metadata explicitly as python 3
nb.metadata = {"kernelspec": {"display_name": "Python 3",
"language": "python",
"name": "python3"},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3"}}
for cell in nb.cells:
if 'outputs' in cell:
cell['outputs'] = []
if 'execution_count' in cell:
cell['execution_count'] = None
if 'metadata' in cell:
cell['metadata'] = {}
return nb
if __name__ == '__main__':
nb = v4.reads(sys.stdin.read())
nb = strip_output(nb)
output = v4.writes(nb)
if type(output) == str and PY2:
output = output.encode('utf-8')
sys.stdout.write(output)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/_notebooks/nbscripts/gen_example_md.py | .py | 237 | 13 | #!/usr/bin/env python
from __future__ import print_function
import glob
for f in glob.glob('Example*.ipynb'):
print('* [%s](%s)' % (f[:-6], f))
print()
for f in glob.glob('Tutorial*.ipynb'):
print('* [%s](%s)' % (f[:-6], f))
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/_notebooks/nbscripts/gen_toc.py | .py | 817 | 42 | #!/usr/bin/env python
from __future__ import print_function
import sys, os
from nbformat import v4
def parse_line(line):
if not line.startswith('#'):
return None
ilevel = 0
for char in line:
if char == '#': ilevel += 1
else: break
name = line[ilevel:].strip()
return ilevel, name
if __name__ == '__main__':
with open(sys.argv[1], 'r') as nbfile:
nb = v4.reads(nbfile.read())
print('Contents\n=======\n---')
for cell in nb.cells:
if cell['cell_type'] == 'markdown':
for line in cell['source'].splitlines():
header = parse_line(line)
if header is None: continue
ilevel, name = header
print(' '*(ilevel-1) + ' - [%s](#%s)'%(name, name.replace(' ','-')))
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/external/__init__.py | .py | 29 | 1 | from . import transformations | Python |
3D | Autodesk/molecular-design-toolkit | moldesign/external/pathlib.py | .py | 1,191 | 40 | # Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Exposes the correct version of pathlib, with some compatibility help for python 2
"""
from __future__ import absolute_import
from future.utils import PY2 as _PY2
if _PY2:
from pathlib2 import *
try:
import pathlib as _backportpathlib
except ImportError:
_backportpathlib = None
if _backportpathlib:
def _backport_pathlib_fixup(p):
if isinstance(p, _backportpathlib.Path):
return Path(str(p))
else:
return p
else:
def _backport_pathlib_fixup(p):
return p
else:
from pathlib import *
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/external/transformations.py | .py | 66,070 | 1,922 | # -*- coding: utf-8 -*-
# transformations.py
# Copyright (c) 2006-2015, Christoph Gohlke
# Copyright (c) 2006-2015, The Regents of the University of California
# Produced at the Laboratory for Fluorescence Dynamics
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of the copyright holders nor the names of any
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
"""Homogeneous Transformation Matrices and Quaternions.
A library for calculating 4x4 matrices for translating, rotating, reflecting,
scaling, shearing, projecting, orthogonalizing, and superimposing arrays of
3D homogeneous coordinates as well as for converting between rotation matrices,
Euler angles, and quaternions. Also includes an Arcball control object and
functions to decompose transformation matrices.
:Author:
`Christoph Gohlke <http://www.lfd.uci.edu/~gohlke/>`_
:Organization:
Laboratory for Fluorescence Dynamics, University of California, Irvine
:Version: 2015.07.18
Requirements
------------
* `CPython 2.7 or 3.4 <http://www.python.org>`_
* `Numpy 1.9 <http://www.numpy.org>`_
* `Transformations.c 2015.07.18 <http://www.lfd.uci.edu/~gohlke/>`_
(recommended for speedup of some functions)
Notes
-----
The API is not stable yet and is expected to change between revisions.
This Python code is not optimized for speed. Refer to the transformations.c
module for a faster implementation of some functions.
Documentation in HTML format can be generated with epydoc.
Matrices (M) can be inverted using numpy.linalg.inv(M), be concatenated using
numpy.dot(M0, M1), or transform homogeneous coordinate arrays (v) using
numpy.dot(M, v) for shape (4, \*) column vectors, respectively
numpy.dot(v, M.T) for shape (\*, 4) row vectors ("array of points").
This module follows the "column vectors on the right" and "row major storage"
(C contiguous) conventions. The translation components are in the right column
of the transformation matrix, i.e. M[:3, 3].
The transpose of the transformation matrices may have to be used to interface
with other graphics systems, e.g. with OpenGL's glMultMatrixd(). See also [16].
Calculations are carried out with numpy.float64 precision.
Vector, point, quaternion, and matrix function arguments are expected to be
"array like", i.e. tuple, list, or numpy arrays.
Return types are numpy arrays unless specified otherwise.
Angles are in radians unless specified otherwise.
Quaternions w+ix+jy+kz are represented as [w, x, y, z].
A triple of Euler angles can be applied/interpreted in 24 ways, which can
be specified using a 4 character string or encoded 4-tuple:
*Axes 4-string*: e.g. 'sxyz' or 'ryxy'
- first character : rotations are applied to 's'tatic or 'r'otating frame
- remaining characters : successive rotation axis 'x', 'y', or 'z'
*Axes 4-tuple*: e.g. (0, 0, 0, 0) or (1, 1, 1, 1)
- inner axis: code of axis ('x':0, 'y':1, 'z':2) of rightmost matrix.
- parity : even (0) if inner axis 'x' is followed by 'y', 'y' is followed
by 'z', or 'z' is followed by 'x'. Otherwise odd (1).
- repetition : first and last axis are same (1) or different (0).
- frame : rotations are applied to static (0) or rotating (1) frame.
Other Python packages and modules for 3D transformations and quaternions:
* `Transforms3d <https://pypi.python.org/pypi/transforms3d>`_
includes most code of this module.
* `Blender.mathutils <http://www.blender.org/api/blender_python_api>`_
* `numpy-dtypes <https://github.com/numpy/numpy-dtypes>`_
References
----------
(1) Matrices and transformations. Ronald Goldman.
In "Graphics Gems I", pp 472-475. Morgan Kaufmann, 1990.
(2) More matrices and transformations: shear and pseudo-perspective.
Ronald Goldman. In "Graphics Gems II", pp 320-323. Morgan Kaufmann, 1991.
(3) Decomposing a matrix into simple transformations. Spencer Thomas.
In "Graphics Gems II", pp 320-323. Morgan Kaufmann, 1991.
(4) Recovering the data from the transformation matrix. Ronald Goldman.
In "Graphics Gems II", pp 324-331. Morgan Kaufmann, 1991.
(5) Euler angle conversion. Ken Shoemake.
In "Graphics Gems IV", pp 222-229. Morgan Kaufmann, 1994.
(6) Arcball rotation control. Ken Shoemake.
In "Graphics Gems IV", pp 175-192. Morgan Kaufmann, 1994.
(7) Representing attitude: Euler angles, unit quaternions, and rotation
vectors. James Diebel. 2006.
(8) A discussion of the solution for the best rotation to relate two sets
of vectors. W Kabsch. Acta Cryst. 1978. A34, 827-828.
(9) Closed-form solution of absolute orientation using unit quaternions.
BKP Horn. J Opt Soc Am A. 1987. 4(4):629-642.
(10) Quaternions. Ken Shoemake.
http://www.sfu.ca/~jwa3/cmpt461/files/quatut.pdf
(11) From quaternion to matrix and back. JMP van Waveren. 2005.
http://www.intel.com/cd/ids/developer/asmo-na/eng/293748.htm
(12) Uniform random rotations. Ken Shoemake.
In "Graphics Gems III", pp 124-132. Morgan Kaufmann, 1992.
(13) Quaternion in molecular modeling. CFF Karney.
J Mol Graph Mod, 25(5):595-604
(14) New method for extracting the quaternion from a rotation matrix.
Itzhack Y Bar-Itzhack, J Guid Contr Dynam. 2000. 23(6): 1085-1087.
(15) Multiple View Geometry in Computer Vision. Hartley and Zissermann.
Cambridge University Press; 2nd Ed. 2004. Chapter 4, Algorithm 4.7, p 130.
(16) Column Vectors vs. Row Vectors.
http://steve.hollasch.net/cgindex/math/matrix/column-vec.html
Examples
--------
>>> alpha, beta, gamma = 0.123, -1.234, 2.345
>>> origin, xaxis, yaxis, zaxis = [0, 0, 0], [1, 0, 0], [0, 1, 0], [0, 0, 1]
>>> I = identity_matrix()
>>> Rx = rotation_matrix(alpha, xaxis)
>>> Ry = rotation_matrix(beta, yaxis)
>>> Rz = rotation_matrix(gamma, zaxis)
>>> R = concatenate_matrices(Rx, Ry, Rz)
>>> euler = euler_from_matrix(R, 'rxyz')
>>> numpy.allclose([alpha, beta, gamma], euler)
True
>>> Re = euler_matrix(alpha, beta, gamma, 'rxyz')
>>> is_same_transform(R, Re)
True
>>> al, be, ga = euler_from_matrix(Re, 'rxyz')
>>> is_same_transform(Re, euler_matrix(al, be, ga, 'rxyz'))
True
>>> qx = quaternion_about_axis(alpha, xaxis)
>>> qy = quaternion_about_axis(beta, yaxis)
>>> qz = quaternion_about_axis(gamma, zaxis)
>>> q = quaternion_multiply(qx, qy)
>>> q = quaternion_multiply(q, qz)
>>> Rq = quaternion_matrix(q)
>>> is_same_transform(R, Rq)
True
>>> S = scale_matrix(1.23, origin)
>>> T = translation_matrix([1, 2, 3])
>>> Z = shear_matrix(beta, xaxis, origin, zaxis)
>>> R = random_rotation_matrix(numpy.random.rand(3))
>>> M = concatenate_matrices(T, R, Z, S)
>>> scale, shear, angles, trans, persp = decompose_matrix(M)
>>> numpy.allclose(scale, 1.23)
True
>>> numpy.allclose(trans, [1, 2, 3])
True
>>> numpy.allclose(shear, [0, math.tan(beta), 0])
True
>>> is_same_transform(R, euler_matrix(axes='sxyz', *angles))
True
>>> M1 = compose_matrix(scale, shear, angles, trans, persp)
>>> is_same_transform(M, M1)
True
>>> v0, v1 = random_vector(3), random_vector(3)
>>> M = rotation_matrix(angle_between_vectors(v0, v1), vector_product(v0, v1))
>>> v2 = numpy.dot(v0, M[:3,:3].T)
>>> numpy.allclose(unit_vector(v1), unit_vector(v2))
True
"""
from __future__ import division, print_function
from builtins import object
import math
import numpy
__version__ = '2015.07.18'
__docformat__ = 'restructuredtext en'
__all__ = ()
def identity_matrix():
"""Return 4x4 identity/unit matrix.
>>> I = identity_matrix()
>>> numpy.allclose(I, numpy.dot(I, I))
True
>>> numpy.sum(I), numpy.trace(I)
(4.0, 4.0)
>>> numpy.allclose(I, numpy.identity(4))
True
"""
return numpy.identity(4)
def translation_matrix(direction):
"""Return matrix to translate by direction vector.
>>> v = numpy.random.random(3) - 0.5
>>> numpy.allclose(v, translation_matrix(v)[:3, 3])
True
"""
M = numpy.identity(4)
M[:3, 3] = direction[:3]
return M
def translation_from_matrix(matrix):
"""Return translation vector from translation matrix.
>>> v0 = numpy.random.random(3) - 0.5
>>> v1 = translation_from_matrix(translation_matrix(v0))
>>> numpy.allclose(v0, v1)
True
"""
return numpy.array(matrix, copy=False)[:3, 3].copy()
def reflection_matrix(point, normal):
"""Return matrix to mirror at plane defined by point and normal vector.
>>> v0 = numpy.random.random(4) - 0.5
>>> v0[3] = 1.
>>> v1 = numpy.random.random(3) - 0.5
>>> R = reflection_matrix(v0, v1)
>>> numpy.allclose(2, numpy.trace(R))
True
>>> numpy.allclose(v0, numpy.dot(R, v0))
True
>>> v2 = v0.copy()
>>> v2[:3] += v1
>>> v3 = v0.copy()
>>> v2[:3] -= v1
>>> numpy.allclose(v2, numpy.dot(R, v3))
True
"""
normal = unit_vector(normal[:3])
M = numpy.identity(4)
M[:3, :3] -= 2.0 * numpy.outer(normal, normal)
M[:3, 3] = (2.0 * numpy.dot(point[:3], normal)) * normal
return M
def reflection_from_matrix(matrix):
"""Return mirror plane point and normal vector from reflection matrix.
>>> v0 = numpy.random.random(3) - 0.5
>>> v1 = numpy.random.random(3) - 0.5
>>> M0 = reflection_matrix(v0, v1)
>>> point, normal = reflection_from_matrix(M0)
>>> M1 = reflection_matrix(point, normal)
>>> is_same_transform(M0, M1)
True
"""
M = numpy.array(matrix, dtype=numpy.float64, copy=False)
# normal: unit eigenvector corresponding to eigenvalue -1
w, V = numpy.linalg.eig(M[:3, :3])
i = numpy.where(abs(numpy.real(w) + 1.0) < 1e-8)[0]
if not len(i):
raise ValueError("no unit eigenvector corresponding to eigenvalue -1")
normal = numpy.real(V[:, i[0]]).squeeze()
# point: any unit eigenvector corresponding to eigenvalue 1
w, V = numpy.linalg.eig(M)
i = numpy.where(abs(numpy.real(w) - 1.0) < 1e-8)[0]
if not len(i):
raise ValueError("no unit eigenvector corresponding to eigenvalue 1")
point = numpy.real(V[:, i[-1]]).squeeze()
point /= point[3]
return point, normal
def rotation_matrix(angle, direction, point=None):
"""Return matrix to rotate about axis defined by point and direction.
>>> R = rotation_matrix(math.pi/2, [0, 0, 1], [1, 0, 0])
>>> numpy.allclose(numpy.dot(R, [0, 0, 0, 1]), [1, -1, 0, 1])
True
>>> angle = (random.random() - 0.5) * (2*math.pi)
>>> direc = numpy.random.random(3) - 0.5
>>> point = numpy.random.random(3) - 0.5
>>> R0 = rotation_matrix(angle, direc, point)
>>> R1 = rotation_matrix(angle-2*math.pi, direc, point)
>>> is_same_transform(R0, R1)
True
>>> R0 = rotation_matrix(angle, direc, point)
>>> R1 = rotation_matrix(-angle, -direc, point)
>>> is_same_transform(R0, R1)
True
>>> I = numpy.identity(4, numpy.float64)
>>> numpy.allclose(I, rotation_matrix(math.pi*2, direc))
True
>>> numpy.allclose(2, numpy.trace(rotation_matrix(math.pi/2,
... direc, point)))
True
"""
sina = math.sin(angle)
cosa = math.cos(angle)
direction = unit_vector(direction[:3])
# rotation matrix around unit vector
R = numpy.diag([cosa, cosa, cosa])
R += numpy.outer(direction, direction) * (1.0 - cosa)
direction *= sina
R += numpy.array([[ 0.0, -direction[2], direction[1]],
[ direction[2], 0.0, -direction[0]],
[-direction[1], direction[0], 0.0]])
M = numpy.identity(4)
M[:3, :3] = R
if point is not None:
# rotation not around origin
point = numpy.array(point[:3], dtype=numpy.float64, copy=False)
M[:3, 3] = point - numpy.dot(R, point)
return M
def rotation_from_matrix(matrix):
"""Return rotation angle and axis from rotation matrix.
>>> angle = (random.random() - 0.5) * (2*math.pi)
>>> direc = numpy.random.random(3) - 0.5
>>> point = numpy.random.random(3) - 0.5
>>> R0 = rotation_matrix(angle, direc, point)
>>> angle, direc, point = rotation_from_matrix(R0)
>>> R1 = rotation_matrix(angle, direc, point)
>>> is_same_transform(R0, R1)
True
"""
R = numpy.array(matrix, dtype=numpy.float64, copy=False)
R33 = R[:3, :3]
# direction: unit eigenvector of R33 corresponding to eigenvalue of 1
w, W = numpy.linalg.eig(R33.T)
i = numpy.where(abs(numpy.real(w) - 1.0) < 1e-8)[0]
if not len(i):
raise ValueError("no unit eigenvector corresponding to eigenvalue 1")
direction = numpy.real(W[:, i[-1]]).squeeze()
# point: unit eigenvector of R33 corresponding to eigenvalue of 1
w, Q = numpy.linalg.eig(R)
i = numpy.where(abs(numpy.real(w) - 1.0) < 1e-8)[0]
if not len(i):
raise ValueError("no unit eigenvector corresponding to eigenvalue 1")
point = numpy.real(Q[:, i[-1]]).squeeze()
point /= point[3]
# rotation angle depending on direction
cosa = (numpy.trace(R33) - 1.0) / 2.0
if abs(direction[2]) > 1e-8:
sina = (R[1, 0] + (cosa-1.0)*direction[0]*direction[1]) / direction[2]
elif abs(direction[1]) > 1e-8:
sina = (R[0, 2] + (cosa-1.0)*direction[0]*direction[2]) / direction[1]
else:
sina = (R[2, 1] + (cosa-1.0)*direction[1]*direction[2]) / direction[0]
angle = math.atan2(sina, cosa)
return angle, direction, point
def scale_matrix(factor, origin=None, direction=None):
"""Return matrix to scale by factor around origin in direction.
Use factor -1 for point symmetry.
>>> v = (numpy.random.rand(4, 5) - 0.5) * 20
>>> v[3] = 1
>>> S = scale_matrix(-1.234)
>>> numpy.allclose(numpy.dot(S, v)[:3], -1.234*v[:3])
True
>>> factor = random.random() * 10 - 5
>>> origin = numpy.random.random(3) - 0.5
>>> direct = numpy.random.random(3) - 0.5
>>> S = scale_matrix(factor, origin)
>>> S = scale_matrix(factor, origin, direct)
"""
if direction is None:
# uniform scaling
M = numpy.diag([factor, factor, factor, 1.0])
if origin is not None:
M[:3, 3] = origin[:3]
M[:3, 3] *= 1.0 - factor
else:
# nonuniform scaling
direction = unit_vector(direction[:3])
factor = 1.0 - factor
M = numpy.identity(4)
M[:3, :3] -= factor * numpy.outer(direction, direction)
if origin is not None:
M[:3, 3] = (factor * numpy.dot(origin[:3], direction)) * direction
return M
def scale_from_matrix(matrix):
"""Return scaling factor, origin and direction from scaling matrix.
>>> factor = random.random() * 10 - 5
>>> origin = numpy.random.random(3) - 0.5
>>> direct = numpy.random.random(3) - 0.5
>>> S0 = scale_matrix(factor, origin)
>>> factor, origin, direction = scale_from_matrix(S0)
>>> S1 = scale_matrix(factor, origin, direction)
>>> is_same_transform(S0, S1)
True
>>> S0 = scale_matrix(factor, origin, direct)
>>> factor, origin, direction = scale_from_matrix(S0)
>>> S1 = scale_matrix(factor, origin, direction)
>>> is_same_transform(S0, S1)
True
"""
M = numpy.array(matrix, dtype=numpy.float64, copy=False)
M33 = M[:3, :3]
factor = numpy.trace(M33) - 2.0
try:
# direction: unit eigenvector corresponding to eigenvalue factor
w, V = numpy.linalg.eig(M33)
i = numpy.where(abs(numpy.real(w) - factor) < 1e-8)[0][0]
direction = numpy.real(V[:, i]).squeeze()
direction /= vector_norm(direction)
except IndexError:
# uniform scaling
factor = (factor + 2.0) / 3.0
direction = None
# origin: any eigenvector corresponding to eigenvalue 1
w, V = numpy.linalg.eig(M)
i = numpy.where(abs(numpy.real(w) - 1.0) < 1e-8)[0]
if not len(i):
raise ValueError("no eigenvector corresponding to eigenvalue 1")
origin = numpy.real(V[:, i[-1]]).squeeze()
origin /= origin[3]
return factor, origin, direction
def projection_matrix(point, normal, direction=None,
perspective=None, pseudo=False):
"""Return matrix to project onto plane defined by point and normal.
Using either perspective point, projection direction, or none of both.
If pseudo is True, perspective projections will preserve relative depth
such that Perspective = dot(Orthogonal, PseudoPerspective).
>>> P = projection_matrix([0, 0, 0], [1, 0, 0])
>>> numpy.allclose(P[1:, 1:], numpy.identity(4)[1:, 1:])
True
>>> point = numpy.random.random(3) - 0.5
>>> normal = numpy.random.random(3) - 0.5
>>> direct = numpy.random.random(3) - 0.5
>>> persp = numpy.random.random(3) - 0.5
>>> P0 = projection_matrix(point, normal)
>>> P1 = projection_matrix(point, normal, direction=direct)
>>> P2 = projection_matrix(point, normal, perspective=persp)
>>> P3 = projection_matrix(point, normal, perspective=persp, pseudo=True)
>>> is_same_transform(P2, numpy.dot(P0, P3))
True
>>> P = projection_matrix([3, 0, 0], [1, 1, 0], [1, 0, 0])
>>> v0 = (numpy.random.rand(4, 5) - 0.5) * 20
>>> v0[3] = 1
>>> v1 = numpy.dot(P, v0)
>>> numpy.allclose(v1[1], v0[1])
True
>>> numpy.allclose(v1[0], 3-v1[1])
True
"""
M = numpy.identity(4)
point = numpy.array(point[:3], dtype=numpy.float64, copy=False)
normal = unit_vector(normal[:3])
if perspective is not None:
# perspective projection
perspective = numpy.array(perspective[:3], dtype=numpy.float64,
copy=False)
M[0, 0] = M[1, 1] = M[2, 2] = numpy.dot(perspective-point, normal)
M[:3, :3] -= numpy.outer(perspective, normal)
if pseudo:
# preserve relative depth
M[:3, :3] -= numpy.outer(normal, normal)
M[:3, 3] = numpy.dot(point, normal) * (perspective+normal)
else:
M[:3, 3] = numpy.dot(point, normal) * perspective
M[3, :3] = -normal
M[3, 3] = numpy.dot(perspective, normal)
elif direction is not None:
# parallel projection
direction = numpy.array(direction[:3], dtype=numpy.float64, copy=False)
scale = numpy.dot(direction, normal)
M[:3, :3] -= numpy.outer(direction, normal) / scale
M[:3, 3] = direction * (numpy.dot(point, normal) / scale)
else:
# orthogonal projection
M[:3, :3] -= numpy.outer(normal, normal)
M[:3, 3] = numpy.dot(point, normal) * normal
return M
def projection_from_matrix(matrix, pseudo=False):
"""Return projection plane and perspective point from projection matrix.
Return values are same as arguments for projection_matrix function:
point, normal, direction, perspective, and pseudo.
>>> point = numpy.random.random(3) - 0.5
>>> normal = numpy.random.random(3) - 0.5
>>> direct = numpy.random.random(3) - 0.5
>>> persp = numpy.random.random(3) - 0.5
>>> P0 = projection_matrix(point, normal)
>>> result = projection_from_matrix(P0)
>>> P1 = projection_matrix(*result)
>>> is_same_transform(P0, P1)
True
>>> P0 = projection_matrix(point, normal, direct)
>>> result = projection_from_matrix(P0)
>>> P1 = projection_matrix(*result)
>>> is_same_transform(P0, P1)
True
>>> P0 = projection_matrix(point, normal, perspective=persp, pseudo=False)
>>> result = projection_from_matrix(P0, pseudo=False)
>>> P1 = projection_matrix(*result)
>>> is_same_transform(P0, P1)
True
>>> P0 = projection_matrix(point, normal, perspective=persp, pseudo=True)
>>> result = projection_from_matrix(P0, pseudo=True)
>>> P1 = projection_matrix(*result)
>>> is_same_transform(P0, P1)
True
"""
M = numpy.array(matrix, dtype=numpy.float64, copy=False)
M33 = M[:3, :3]
w, V = numpy.linalg.eig(M)
i = numpy.where(abs(numpy.real(w) - 1.0) < 1e-8)[0]
if not pseudo and len(i):
# point: any eigenvector corresponding to eigenvalue 1
point = numpy.real(V[:, i[-1]]).squeeze()
point /= point[3]
# direction: unit eigenvector corresponding to eigenvalue 0
w, V = numpy.linalg.eig(M33)
i = numpy.where(abs(numpy.real(w)) < 1e-8)[0]
if not len(i):
raise ValueError("no eigenvector corresponding to eigenvalue 0")
direction = numpy.real(V[:, i[0]]).squeeze()
direction /= vector_norm(direction)
# normal: unit eigenvector of M33.T corresponding to eigenvalue 0
w, V = numpy.linalg.eig(M33.T)
i = numpy.where(abs(numpy.real(w)) < 1e-8)[0]
if len(i):
# parallel projection
normal = numpy.real(V[:, i[0]]).squeeze()
normal /= vector_norm(normal)
return point, normal, direction, None, False
else:
# orthogonal projection, where normal equals direction vector
return point, direction, None, None, False
else:
# perspective projection
i = numpy.where(abs(numpy.real(w)) > 1e-8)[0]
if not len(i):
raise ValueError(
"no eigenvector not corresponding to eigenvalue 0")
point = numpy.real(V[:, i[-1]]).squeeze()
point /= point[3]
normal = - M[3, :3]
perspective = M[:3, 3] / numpy.dot(point[:3], normal)
if pseudo:
perspective -= normal
return point, normal, None, perspective, pseudo
def clip_matrix(left, right, bottom, top, near, far, perspective=False):
"""Return matrix to obtain normalized device coordinates from frustum.
The frustum bounds are axis-aligned along x (left, right),
y (bottom, top) and z (near, far).
Normalized device coordinates are in range [-1, 1] if coordinates are
inside the frustum.
If perspective is True the frustum is a truncated pyramid with the
perspective point at origin and direction along z axis, otherwise an
orthographic canonical view volume (a box).
Homogeneous coordinates transformed by the perspective clip matrix
need to be dehomogenized (divided by w coordinate).
>>> frustum = numpy.random.rand(6)
>>> frustum[1] += frustum[0]
>>> frustum[3] += frustum[2]
>>> frustum[5] += frustum[4]
>>> M = clip_matrix(perspective=False, *frustum)
>>> numpy.dot(M, [frustum[0], frustum[2], frustum[4], 1])
array([-1., -1., -1., 1.])
>>> numpy.dot(M, [frustum[1], frustum[3], frustum[5], 1])
array([ 1., 1., 1., 1.])
>>> M = clip_matrix(perspective=True, *frustum)
>>> v = numpy.dot(M, [frustum[0], frustum[2], frustum[4], 1])
>>> v / v[3]
array([-1., -1., -1., 1.])
>>> v = numpy.dot(M, [frustum[1], frustum[3], frustum[4], 1])
>>> v / v[3]
array([ 1., 1., -1., 1.])
"""
if left >= right or bottom >= top or near >= far:
raise ValueError("invalid frustum")
if perspective:
if near <= _EPS:
raise ValueError("invalid frustum: near <= 0")
t = 2.0 * near
M = [[t/(left-right), 0.0, (right+left)/(right-left), 0.0],
[0.0, t/(bottom-top), (top+bottom)/(top-bottom), 0.0],
[0.0, 0.0, (far+near)/(near-far), t*far/(far-near)],
[0.0, 0.0, -1.0, 0.0]]
else:
M = [[2.0/(right-left), 0.0, 0.0, (right+left)/(left-right)],
[0.0, 2.0/(top-bottom), 0.0, (top+bottom)/(bottom-top)],
[0.0, 0.0, 2.0/(far-near), (far+near)/(near-far)],
[0.0, 0.0, 0.0, 1.0]]
return numpy.array(M)
def shear_matrix(angle, direction, point, normal):
"""Return matrix to shear by angle along direction vector on shear plane.
The shear plane is defined by a point and normal vector. The direction
vector must be orthogonal to the plane's normal vector.
A point P is transformed by the shear matrix into P" such that
the vector P-P" is parallel to the direction vector and its extent is
given by the angle of P-P'-P", where P' is the orthogonal projection
of P onto the shear plane.
>>> angle = (random.random() - 0.5) * 4*math.pi
>>> direct = numpy.random.random(3) - 0.5
>>> point = numpy.random.random(3) - 0.5
>>> normal = numpy.cross(direct, numpy.random.random(3))
>>> S = shear_matrix(angle, direct, point, normal)
>>> numpy.allclose(1, numpy.linalg.det(S))
True
"""
normal = unit_vector(normal[:3])
direction = unit_vector(direction[:3])
if abs(numpy.dot(normal, direction)) > 1e-6:
raise ValueError("direction and normal vectors are not orthogonal")
angle = math.tan(angle)
M = numpy.identity(4)
M[:3, :3] += angle * numpy.outer(direction, normal)
M[:3, 3] = -angle * numpy.dot(point[:3], normal) * direction
return M
def shear_from_matrix(matrix):
"""Return shear angle, direction and plane from shear matrix.
>>> angle = (random.random() - 0.5) * 4*math.pi
>>> direct = numpy.random.random(3) - 0.5
>>> point = numpy.random.random(3) - 0.5
>>> normal = numpy.cross(direct, numpy.random.random(3))
>>> S0 = shear_matrix(angle, direct, point, normal)
>>> angle, direct, point, normal = shear_from_matrix(S0)
>>> S1 = shear_matrix(angle, direct, point, normal)
>>> is_same_transform(S0, S1)
True
"""
M = numpy.array(matrix, dtype=numpy.float64, copy=False)
M33 = M[:3, :3]
# normal: cross independent eigenvectors corresponding to the eigenvalue 1
w, V = numpy.linalg.eig(M33)
i = numpy.where(abs(numpy.real(w) - 1.0) < 1e-4)[0]
if len(i) < 2:
raise ValueError("no two linear independent eigenvectors found %s" % w)
V = numpy.real(V[:, i]).squeeze().T
lenorm = -1.0
for i0, i1 in ((0, 1), (0, 2), (1, 2)):
n = numpy.cross(V[i0], V[i1])
w = vector_norm(n)
if w > lenorm:
lenorm = w
normal = n
normal /= lenorm
# direction and angle
direction = numpy.dot(M33 - numpy.identity(3), normal)
angle = vector_norm(direction)
direction /= angle
angle = math.atan(angle)
# point: eigenvector corresponding to eigenvalue 1
w, V = numpy.linalg.eig(M)
i = numpy.where(abs(numpy.real(w) - 1.0) < 1e-8)[0]
if not len(i):
raise ValueError("no eigenvector corresponding to eigenvalue 1")
point = numpy.real(V[:, i[-1]]).squeeze()
point /= point[3]
return angle, direction, point, normal
def decompose_matrix(matrix):
"""Return sequence of transformations from transformation matrix.
matrix : array_like
Non-degenerative homogeneous transformation matrix
Return tuple of:
scale : vector of 3 scaling factors
shear : list of shear factors for x-y, x-z, y-z axes
angles : list of Euler angles about static x, y, z axes
translate : translation vector along x, y, z axes
perspective : perspective partition of matrix
Raise ValueError if matrix is of wrong type or degenerative.
>>> T0 = translation_matrix([1, 2, 3])
>>> scale, shear, angles, trans, persp = decompose_matrix(T0)
>>> T1 = translation_matrix(trans)
>>> numpy.allclose(T0, T1)
True
>>> S = scale_matrix(0.123)
>>> scale, shear, angles, trans, persp = decompose_matrix(S)
>>> scale[0]
0.123
>>> R0 = euler_matrix(1, 2, 3)
>>> scale, shear, angles, trans, persp = decompose_matrix(R0)
>>> R1 = euler_matrix(*angles)
>>> numpy.allclose(R0, R1)
True
"""
M = numpy.array(matrix, dtype=numpy.float64, copy=True).T
if abs(M[3, 3]) < _EPS:
raise ValueError("M[3, 3] is zero")
M /= M[3, 3]
P = M.copy()
P[:, 3] = 0.0, 0.0, 0.0, 1.0
if not numpy.linalg.det(P):
raise ValueError("matrix is singular")
scale = numpy.zeros((3, ))
shear = [0.0, 0.0, 0.0]
angles = [0.0, 0.0, 0.0]
if any(abs(M[:3, 3]) > _EPS):
perspective = numpy.dot(M[:, 3], numpy.linalg.inv(P.T))
M[:, 3] = 0.0, 0.0, 0.0, 1.0
else:
perspective = numpy.array([0.0, 0.0, 0.0, 1.0])
translate = M[3, :3].copy()
M[3, :3] = 0.0
row = M[:3, :3].copy()
scale[0] = vector_norm(row[0])
row[0] /= scale[0]
shear[0] = numpy.dot(row[0], row[1])
row[1] -= row[0] * shear[0]
scale[1] = vector_norm(row[1])
row[1] /= scale[1]
shear[0] /= scale[1]
shear[1] = numpy.dot(row[0], row[2])
row[2] -= row[0] * shear[1]
shear[2] = numpy.dot(row[1], row[2])
row[2] -= row[1] * shear[2]
scale[2] = vector_norm(row[2])
row[2] /= scale[2]
shear[1:] /= scale[2]
if numpy.dot(row[0], numpy.cross(row[1], row[2])) < 0:
numpy.negative(scale, scale)
numpy.negative(row, row)
angles[1] = math.asin(-row[0, 2])
if math.cos(angles[1]):
angles[0] = math.atan2(row[1, 2], row[2, 2])
angles[2] = math.atan2(row[0, 1], row[0, 0])
else:
#angles[0] = math.atan2(row[1, 0], row[1, 1])
angles[0] = math.atan2(-row[2, 1], row[1, 1])
angles[2] = 0.0
return scale, shear, angles, translate, perspective
def compose_matrix(scale=None, shear=None, angles=None, translate=None,
perspective=None):
"""Return transformation matrix from sequence of transformations.
This is the inverse of the decompose_matrix function.
Sequence of transformations:
scale : vector of 3 scaling factors
shear : list of shear factors for x-y, x-z, y-z axes
angles : list of Euler angles about static x, y, z axes
translate : translation vector along x, y, z axes
perspective : perspective partition of matrix
>>> scale = numpy.random.random(3) - 0.5
>>> shear = numpy.random.random(3) - 0.5
>>> angles = (numpy.random.random(3) - 0.5) * (2*math.pi)
>>> trans = numpy.random.random(3) - 0.5
>>> persp = numpy.random.random(4) - 0.5
>>> M0 = compose_matrix(scale, shear, angles, trans, persp)
>>> result = decompose_matrix(M0)
>>> M1 = compose_matrix(*result)
>>> is_same_transform(M0, M1)
True
"""
M = numpy.identity(4)
if perspective is not None:
P = numpy.identity(4)
P[3, :] = perspective[:4]
M = numpy.dot(M, P)
if translate is not None:
T = numpy.identity(4)
T[:3, 3] = translate[:3]
M = numpy.dot(M, T)
if angles is not None:
R = euler_matrix(angles[0], angles[1], angles[2], 'sxyz')
M = numpy.dot(M, R)
if shear is not None:
Z = numpy.identity(4)
Z[1, 2] = shear[2]
Z[0, 2] = shear[1]
Z[0, 1] = shear[0]
M = numpy.dot(M, Z)
if scale is not None:
S = numpy.identity(4)
S[0, 0] = scale[0]
S[1, 1] = scale[1]
S[2, 2] = scale[2]
M = numpy.dot(M, S)
M /= M[3, 3]
return M
def orthogonalization_matrix(lengths, angles):
"""Return orthogonalization matrix for crystallographic cell coordinates.
Angles are expected in degrees.
The de-orthogonalization matrix is the inverse.
>>> O = orthogonalization_matrix([10, 10, 10], [90, 90, 90])
>>> numpy.allclose(O[:3, :3], numpy.identity(3, float) * 10)
True
>>> O = orthogonalization_matrix([9.8, 12.0, 15.5], [87.2, 80.7, 69.7])
>>> numpy.allclose(numpy.sum(O), 43.063229)
True
"""
a, b, c = lengths
angles = numpy.radians(angles)
sina, sinb, _ = numpy.sin(angles)
cosa, cosb, cosg = numpy.cos(angles)
co = (cosa * cosb - cosg) / (sina * sinb)
return numpy.array([
[ a*sinb*math.sqrt(1.0-co*co), 0.0, 0.0, 0.0],
[-a*sinb*co, b*sina, 0.0, 0.0],
[ a*cosb, b*cosa, c, 0.0],
[ 0.0, 0.0, 0.0, 1.0]])
def affine_matrix_from_points(v0, v1, shear=True, scale=True, usesvd=True):
"""Return affine transform matrix to register two point sets.
v0 and v1 are shape (ndims, \*) arrays of at least ndims non-homogeneous
coordinates, where ndims is the dimensionality of the coordinate space.
If shear is False, a similarity transformation matrix is returned.
If also scale is False, a rigid/Euclidean transformation matrix
is returned.
By default the algorithm by Hartley and Zissermann [15] is used.
If usesvd is True, similarity and Euclidean transformation matrices
are calculated by minimizing the weighted sum of squared deviations
(RMSD) according to the algorithm by Kabsch [8].
Otherwise, and if ndims is 3, the quaternion based algorithm by Horn [9]
is used, which is slower when using this Python implementation.
The returned matrix performs rotation, translation and uniform scaling
(if specified).
>>> v0 = [[0, 1031, 1031, 0], [0, 0, 1600, 1600]]
>>> v1 = [[675, 826, 826, 677], [55, 52, 281, 277]]
>>> affine_matrix_from_points(v0, v1)
array([[ 0.14549, 0.00062, 675.50008],
[ 0.00048, 0.14094, 53.24971],
[ 0. , 0. , 1. ]])
>>> T = translation_matrix(numpy.random.random(3)-0.5)
>>> R = random_rotation_matrix(numpy.random.random(3))
>>> S = scale_matrix(random.random())
>>> M = concatenate_matrices(T, R, S)
>>> v0 = (numpy.random.rand(4, 100) - 0.5) * 20
>>> v0[3] = 1
>>> v1 = numpy.dot(M, v0)
>>> v0[:3] += numpy.random.normal(0, 1e-8, 300).reshape(3, -1)
>>> M = affine_matrix_from_points(v0[:3], v1[:3])
>>> numpy.allclose(v1, numpy.dot(M, v0))
True
More examples in superimposition_matrix()
"""
v0 = numpy.array(v0, dtype=numpy.float64, copy=True)
v1 = numpy.array(v1, dtype=numpy.float64, copy=True)
ndims = v0.shape[0]
if ndims < 2 or v0.shape[1] < ndims or v0.shape != v1.shape:
raise ValueError("input arrays are of wrong shape or type")
# move centroids to origin
t0 = -numpy.mean(v0, axis=1)
M0 = numpy.identity(ndims+1)
M0[:ndims, ndims] = t0
v0 += t0.reshape(ndims, 1)
t1 = -numpy.mean(v1, axis=1)
M1 = numpy.identity(ndims+1)
M1[:ndims, ndims] = t1
v1 += t1.reshape(ndims, 1)
if shear:
# Affine transformation
A = numpy.concatenate((v0, v1), axis=0)
u, s, vh = numpy.linalg.svd(A.T)
vh = vh[:ndims].T
B = vh[:ndims]
C = vh[ndims:2*ndims]
t = numpy.dot(C, numpy.linalg.pinv(B))
t = numpy.concatenate((t, numpy.zeros((ndims, 1))), axis=1)
M = numpy.vstack((t, ((0.0,)*ndims) + (1.0,)))
elif usesvd or ndims != 3:
# Rigid transformation via SVD of covariance matrix
u, s, vh = numpy.linalg.svd(numpy.dot(v1, v0.T))
# rotation matrix from SVD orthonormal bases
R = numpy.dot(u, vh)
if numpy.linalg.det(R) < 0.0:
# R does not constitute right handed system
R -= numpy.outer(u[:, ndims-1], vh[ndims-1, :]*2.0)
s[-1] *= -1.0
# homogeneous transformation matrix
M = numpy.identity(ndims+1)
M[:ndims, :ndims] = R
else:
# Rigid transformation matrix via quaternion
# compute symmetric matrix N
xx, yy, zz = numpy.sum(v0 * v1, axis=1)
xy, yz, zx = numpy.sum(v0 * numpy.roll(v1, -1, axis=0), axis=1)
xz, yx, zy = numpy.sum(v0 * numpy.roll(v1, -2, axis=0), axis=1)
N = [[xx+yy+zz, 0.0, 0.0, 0.0],
[yz-zy, xx-yy-zz, 0.0, 0.0],
[zx-xz, xy+yx, yy-xx-zz, 0.0],
[xy-yx, zx+xz, yz+zy, zz-xx-yy]]
# quaternion: eigenvector corresponding to most positive eigenvalue
w, V = numpy.linalg.eigh(N)
q = V[:, numpy.argmax(w)]
q /= vector_norm(q) # unit quaternion
# homogeneous transformation matrix
M = quaternion_matrix(q)
if scale and not shear:
# Affine transformation; scale is ratio of RMS deviations from centroid
v0 *= v0
v1 *= v1
M[:ndims, :ndims] *= math.sqrt(numpy.sum(v1) / numpy.sum(v0))
# move centroids back
M = numpy.dot(numpy.linalg.inv(M1), numpy.dot(M, M0))
M /= M[ndims, ndims]
return M
def superimposition_matrix(v0, v1, scale=False, usesvd=True):
"""Return matrix to transform given 3D point set into second point set.
v0 and v1 are shape (3, \*) or (4, \*) arrays of at least 3 points.
The parameters scale and usesvd are explained in the more general
affine_matrix_from_points function.
The returned matrix is a similarity or Euclidean transformation matrix.
This function has a fast C implementation in transformations.c.
>>> v0 = numpy.random.rand(3, 10)
>>> M = superimposition_matrix(v0, v0)
>>> numpy.allclose(M, numpy.identity(4))
True
>>> R = random_rotation_matrix(numpy.random.random(3))
>>> v0 = [[1,0,0], [0,1,0], [0,0,1], [1,1,1]]
>>> v1 = numpy.dot(R, v0)
>>> M = superimposition_matrix(v0, v1)
>>> numpy.allclose(v1, numpy.dot(M, v0))
True
>>> v0 = (numpy.random.rand(4, 100) - 0.5) * 20
>>> v0[3] = 1
>>> v1 = numpy.dot(R, v0)
>>> M = superimposition_matrix(v0, v1)
>>> numpy.allclose(v1, numpy.dot(M, v0))
True
>>> S = scale_matrix(random.random())
>>> T = translation_matrix(numpy.random.random(3)-0.5)
>>> M = concatenate_matrices(T, R, S)
>>> v1 = numpy.dot(M, v0)
>>> v0[:3] += numpy.random.normal(0, 1e-9, 300).reshape(3, -1)
>>> M = superimposition_matrix(v0, v1, scale=True)
>>> numpy.allclose(v1, numpy.dot(M, v0))
True
>>> M = superimposition_matrix(v0, v1, scale=True, usesvd=False)
>>> numpy.allclose(v1, numpy.dot(M, v0))
True
>>> v = numpy.empty((4, 100, 3))
>>> v[:, :, 0] = v0
>>> M = superimposition_matrix(v0, v1, scale=True, usesvd=False)
>>> numpy.allclose(v1, numpy.dot(M, v[:, :, 0]))
True
"""
v0 = numpy.array(v0, dtype=numpy.float64, copy=False)[:3]
v1 = numpy.array(v1, dtype=numpy.float64, copy=False)[:3]
return affine_matrix_from_points(v0, v1, shear=False,
scale=scale, usesvd=usesvd)
def euler_matrix(ai, aj, ak, axes='sxyz'):
"""Return homogeneous rotation matrix from Euler angles and axis sequence.
ai, aj, ak : Euler's roll, pitch and yaw angles
axes : One of 24 axis sequences as string or encoded tuple
>>> R = euler_matrix(1, 2, 3, 'syxz')
>>> numpy.allclose(numpy.sum(R[0]), -1.34786452)
True
>>> R = euler_matrix(1, 2, 3, (0, 1, 0, 1))
>>> numpy.allclose(numpy.sum(R[0]), -0.383436184)
True
>>> ai, aj, ak = (4*math.pi) * (numpy.random.random(3) - 0.5)
>>> for axes in _AXES2TUPLE.keys():
... R = euler_matrix(ai, aj, ak, axes)
>>> for axes in _TUPLE2AXES.keys():
... R = euler_matrix(ai, aj, ak, axes)
"""
try:
firstaxis, parity, repetition, frame = _AXES2TUPLE[axes]
except (AttributeError, KeyError):
_TUPLE2AXES[axes] # validation
firstaxis, parity, repetition, frame = axes
i = firstaxis
j = _NEXT_AXIS[i+parity]
k = _NEXT_AXIS[i-parity+1]
if frame:
ai, ak = ak, ai
if parity:
ai, aj, ak = -ai, -aj, -ak
si, sj, sk = math.sin(ai), math.sin(aj), math.sin(ak)
ci, cj, ck = math.cos(ai), math.cos(aj), math.cos(ak)
cc, cs = ci*ck, ci*sk
sc, ss = si*ck, si*sk
M = numpy.identity(4)
if repetition:
M[i, i] = cj
M[i, j] = sj*si
M[i, k] = sj*ci
M[j, i] = sj*sk
M[j, j] = -cj*ss+cc
M[j, k] = -cj*cs-sc
M[k, i] = -sj*ck
M[k, j] = cj*sc+cs
M[k, k] = cj*cc-ss
else:
M[i, i] = cj*ck
M[i, j] = sj*sc-cs
M[i, k] = sj*cc+ss
M[j, i] = cj*sk
M[j, j] = sj*ss+cc
M[j, k] = sj*cs-sc
M[k, i] = -sj
M[k, j] = cj*si
M[k, k] = cj*ci
return M
def euler_from_matrix(matrix, axes='sxyz'):
"""Return Euler angles from rotation matrix for specified axis sequence.
axes : One of 24 axis sequences as string or encoded tuple
Note that many Euler angle triplets can describe one matrix.
>>> R0 = euler_matrix(1, 2, 3, 'syxz')
>>> al, be, ga = euler_from_matrix(R0, 'syxz')
>>> R1 = euler_matrix(al, be, ga, 'syxz')
>>> numpy.allclose(R0, R1)
True
>>> angles = (4*math.pi) * (numpy.random.random(3) - 0.5)
>>> for axes in _AXES2TUPLE.keys():
... R0 = euler_matrix(axes=axes, *angles)
... R1 = euler_matrix(axes=axes, *euler_from_matrix(R0, axes))
... if not numpy.allclose(R0, R1): print(axes, "failed")
"""
try:
firstaxis, parity, repetition, frame = _AXES2TUPLE[axes.lower()]
except (AttributeError, KeyError):
_TUPLE2AXES[axes] # validation
firstaxis, parity, repetition, frame = axes
i = firstaxis
j = _NEXT_AXIS[i+parity]
k = _NEXT_AXIS[i-parity+1]
M = numpy.array(matrix, dtype=numpy.float64, copy=False)[:3, :3]
if repetition:
sy = math.sqrt(M[i, j]*M[i, j] + M[i, k]*M[i, k])
if sy > _EPS:
ax = math.atan2( M[i, j], M[i, k])
ay = math.atan2( sy, M[i, i])
az = math.atan2( M[j, i], -M[k, i])
else:
ax = math.atan2(-M[j, k], M[j, j])
ay = math.atan2( sy, M[i, i])
az = 0.0
else:
cy = math.sqrt(M[i, i]*M[i, i] + M[j, i]*M[j, i])
if cy > _EPS:
ax = math.atan2( M[k, j], M[k, k])
ay = math.atan2(-M[k, i], cy)
az = math.atan2( M[j, i], M[i, i])
else:
ax = math.atan2(-M[j, k], M[j, j])
ay = math.atan2(-M[k, i], cy)
az = 0.0
if parity:
ax, ay, az = -ax, -ay, -az
if frame:
ax, az = az, ax
return ax, ay, az
def euler_from_quaternion(quaternion, axes='sxyz'):
"""Return Euler angles from quaternion for specified axis sequence.
>>> angles = euler_from_quaternion([0.99810947, 0.06146124, 0, 0])
>>> numpy.allclose(angles, [0.123, 0, 0])
True
"""
return euler_from_matrix(quaternion_matrix(quaternion), axes)
def quaternion_from_euler(ai, aj, ak, axes='sxyz'):
"""Return quaternion from Euler angles and axis sequence.
ai, aj, ak : Euler's roll, pitch and yaw angles
axes : One of 24 axis sequences as string or encoded tuple
>>> q = quaternion_from_euler(1, 2, 3, 'ryxz')
>>> numpy.allclose(q, [0.435953, 0.310622, -0.718287, 0.444435])
True
"""
try:
firstaxis, parity, repetition, frame = _AXES2TUPLE[axes.lower()]
except (AttributeError, KeyError):
_TUPLE2AXES[axes] # validation
firstaxis, parity, repetition, frame = axes
i = firstaxis + 1
j = _NEXT_AXIS[i+parity-1] + 1
k = _NEXT_AXIS[i-parity] + 1
if frame:
ai, ak = ak, ai
if parity:
aj = -aj
ai /= 2.0
aj /= 2.0
ak /= 2.0
ci = math.cos(ai)
si = math.sin(ai)
cj = math.cos(aj)
sj = math.sin(aj)
ck = math.cos(ak)
sk = math.sin(ak)
cc = ci*ck
cs = ci*sk
sc = si*ck
ss = si*sk
q = numpy.empty((4, ))
if repetition:
q[0] = cj*(cc - ss)
q[i] = cj*(cs + sc)
q[j] = sj*(cc + ss)
q[k] = sj*(cs - sc)
else:
q[0] = cj*cc + sj*ss
q[i] = cj*sc - sj*cs
q[j] = cj*ss + sj*cc
q[k] = cj*cs - sj*sc
if parity:
q[j] *= -1.0
return q
def quaternion_about_axis(angle, axis):
"""Return quaternion for rotation about axis.
>>> q = quaternion_about_axis(0.123, [1, 0, 0])
>>> numpy.allclose(q, [0.99810947, 0.06146124, 0, 0])
True
"""
q = numpy.array([0.0, axis[0], axis[1], axis[2]])
qlen = vector_norm(q)
if qlen > _EPS:
q *= math.sin(angle/2.0) / qlen
q[0] = math.cos(angle/2.0)
return q
def quaternion_matrix(quaternion):
"""Return homogeneous rotation matrix from quaternion.
>>> M = quaternion_matrix([0.99810947, 0.06146124, 0, 0])
>>> numpy.allclose(M, rotation_matrix(0.123, [1, 0, 0]))
True
>>> M = quaternion_matrix([1, 0, 0, 0])
>>> numpy.allclose(M, numpy.identity(4))
True
>>> M = quaternion_matrix([0, 1, 0, 0])
>>> numpy.allclose(M, numpy.diag([1, -1, -1, 1]))
True
"""
q = numpy.array(quaternion, dtype=numpy.float64, copy=True)
n = numpy.dot(q, q)
if n < _EPS:
return numpy.identity(4)
q *= math.sqrt(2.0 / n)
q = numpy.outer(q, q)
return numpy.array([
[1.0-q[2, 2]-q[3, 3], q[1, 2]-q[3, 0], q[1, 3]+q[2, 0], 0.0],
[ q[1, 2]+q[3, 0], 1.0-q[1, 1]-q[3, 3], q[2, 3]-q[1, 0], 0.0],
[ q[1, 3]-q[2, 0], q[2, 3]+q[1, 0], 1.0-q[1, 1]-q[2, 2], 0.0],
[ 0.0, 0.0, 0.0, 1.0]])
def quaternion_from_matrix(matrix, isprecise=False):
"""Return quaternion from rotation matrix.
If isprecise is True, the input matrix is assumed to be a precise rotation
matrix and a faster algorithm is used.
>>> q = quaternion_from_matrix(numpy.identity(4), True)
>>> numpy.allclose(q, [1, 0, 0, 0])
True
>>> q = quaternion_from_matrix(numpy.diag([1, -1, -1, 1]))
>>> numpy.allclose(q, [0, 1, 0, 0]) or numpy.allclose(q, [0, -1, 0, 0])
True
>>> R = rotation_matrix(0.123, (1, 2, 3))
>>> q = quaternion_from_matrix(R, True)
>>> numpy.allclose(q, [0.9981095, 0.0164262, 0.0328524, 0.0492786])
True
>>> R = [[-0.545, 0.797, 0.260, 0], [0.733, 0.603, -0.313, 0],
... [-0.407, 0.021, -0.913, 0], [0, 0, 0, 1]]
>>> q = quaternion_from_matrix(R)
>>> numpy.allclose(q, [0.19069, 0.43736, 0.87485, -0.083611])
True
>>> R = [[0.395, 0.362, 0.843, 0], [-0.626, 0.796, -0.056, 0],
... [-0.677, -0.498, 0.529, 0], [0, 0, 0, 1]]
>>> q = quaternion_from_matrix(R)
>>> numpy.allclose(q, [0.82336615, -0.13610694, 0.46344705, -0.29792603])
True
>>> R = random_rotation_matrix()
>>> q = quaternion_from_matrix(R)
>>> is_same_transform(R, quaternion_matrix(q))
True
>>> R = euler_matrix(0.0, 0.0, numpy.pi/2.0)
>>> numpy.allclose(quaternion_from_matrix(R, isprecise=False),
... quaternion_from_matrix(R, isprecise=True))
True
"""
M = numpy.array(matrix, dtype=numpy.float64, copy=False)[:4, :4]
if isprecise:
q = numpy.empty((4, ))
t = numpy.trace(M)
if t > M[3, 3]:
q[0] = t
q[3] = M[1, 0] - M[0, 1]
q[2] = M[0, 2] - M[2, 0]
q[1] = M[2, 1] - M[1, 2]
else:
i, j, k = 1, 2, 3
if M[1, 1] > M[0, 0]:
i, j, k = 2, 3, 1
if M[2, 2] > M[i, i]:
i, j, k = 3, 1, 2
t = M[i, i] - (M[j, j] + M[k, k]) + M[3, 3]
q[i] = t
q[j] = M[i, j] + M[j, i]
q[k] = M[k, i] + M[i, k]
q[3] = M[k, j] - M[j, k]
q *= 0.5 / math.sqrt(t * M[3, 3])
else:
m00 = M[0, 0]
m01 = M[0, 1]
m02 = M[0, 2]
m10 = M[1, 0]
m11 = M[1, 1]
m12 = M[1, 2]
m20 = M[2, 0]
m21 = M[2, 1]
m22 = M[2, 2]
# symmetric matrix K
K = numpy.array([[m00-m11-m22, 0.0, 0.0, 0.0],
[m01+m10, m11-m00-m22, 0.0, 0.0],
[m02+m20, m12+m21, m22-m00-m11, 0.0],
[m21-m12, m02-m20, m10-m01, m00+m11+m22]])
K /= 3.0
# quaternion is eigenvector of K that corresponds to largest eigenvalue
w, V = numpy.linalg.eigh(K)
q = V[[3, 0, 1, 2], numpy.argmax(w)]
if q[0] < 0.0:
numpy.negative(q, q)
return q
def quaternion_multiply(quaternion1, quaternion0):
"""Return multiplication of two quaternions.
>>> q = quaternion_multiply([4, 1, -2, 3], [8, -5, 6, 7])
>>> numpy.allclose(q, [28, -44, -14, 48])
True
"""
w0, x0, y0, z0 = quaternion0
w1, x1, y1, z1 = quaternion1
return numpy.array([-x1*x0 - y1*y0 - z1*z0 + w1*w0,
x1*w0 + y1*z0 - z1*y0 + w1*x0,
-x1*z0 + y1*w0 + z1*x0 + w1*y0,
x1*y0 - y1*x0 + z1*w0 + w1*z0], dtype=numpy.float64)
def quaternion_conjugate(quaternion):
"""Return conjugate of quaternion.
>>> q0 = random_quaternion()
>>> q1 = quaternion_conjugate(q0)
>>> q1[0] == q0[0] and all(q1[1:] == -q0[1:])
True
"""
q = numpy.array(quaternion, dtype=numpy.float64, copy=True)
numpy.negative(q[1:], q[1:])
return q
def quaternion_inverse(quaternion):
"""Return inverse of quaternion.
>>> q0 = random_quaternion()
>>> q1 = quaternion_inverse(q0)
>>> numpy.allclose(quaternion_multiply(q0, q1), [1, 0, 0, 0])
True
"""
q = numpy.array(quaternion, dtype=numpy.float64, copy=True)
numpy.negative(q[1:], q[1:])
return q / numpy.dot(q, q)
def quaternion_real(quaternion):
"""Return real part of quaternion.
>>> quaternion_real([3, 0, 1, 2])
3.0
"""
return float(quaternion[0])
def quaternion_imag(quaternion):
"""Return imaginary part of quaternion.
>>> quaternion_imag([3, 0, 1, 2])
array([ 0., 1., 2.])
"""
return numpy.array(quaternion[1:4], dtype=numpy.float64, copy=True)
def quaternion_slerp(quat0, quat1, fraction, spin=0, shortestpath=True):
"""Return spherical linear interpolation between two quaternions.
>>> q0 = random_quaternion()
>>> q1 = random_quaternion()
>>> q = quaternion_slerp(q0, q1, 0)
>>> numpy.allclose(q, q0)
True
>>> q = quaternion_slerp(q0, q1, 1, 1)
>>> numpy.allclose(q, q1)
True
>>> q = quaternion_slerp(q0, q1, 0.5)
>>> angle = math.acos(numpy.dot(q0, q))
>>> numpy.allclose(2, math.acos(numpy.dot(q0, q1)) / angle) or \
numpy.allclose(2, math.acos(-numpy.dot(q0, q1)) / angle)
True
"""
q0 = unit_vector(quat0[:4])
q1 = unit_vector(quat1[:4])
if fraction == 0.0:
return q0
elif fraction == 1.0:
return q1
d = numpy.dot(q0, q1)
if abs(abs(d) - 1.0) < _EPS:
return q0
if shortestpath and d < 0.0:
# invert rotation
d = -d
numpy.negative(q1, q1)
angle = math.acos(d) + spin * math.pi
if abs(angle) < _EPS:
return q0
isin = 1.0 / math.sin(angle)
q0 *= math.sin((1.0 - fraction) * angle) * isin
q1 *= math.sin(fraction * angle) * isin
q0 += q1
return q0
def random_quaternion(rand=None):
"""Return uniform random unit quaternion.
rand: array like or None
Three independent random variables that are uniformly distributed
between 0 and 1.
>>> q = random_quaternion()
>>> numpy.allclose(1, vector_norm(q))
True
>>> q = random_quaternion(numpy.random.random(3))
>>> len(q.shape), q.shape[0]==4
(1, True)
"""
if rand is None:
rand = numpy.random.rand(3)
else:
assert len(rand) == 3
r1 = numpy.sqrt(1.0 - rand[0])
r2 = numpy.sqrt(rand[0])
pi2 = math.pi * 2.0
t1 = pi2 * rand[1]
t2 = pi2 * rand[2]
return numpy.array([numpy.cos(t2)*r2, numpy.sin(t1)*r1,
numpy.cos(t1)*r1, numpy.sin(t2)*r2])
def random_rotation_matrix(rand=None):
"""Return uniform random rotation matrix.
rand: array like
Three independent random variables that are uniformly distributed
between 0 and 1 for each returned quaternion.
>>> R = random_rotation_matrix()
>>> numpy.allclose(numpy.dot(R.T, R), numpy.identity(4))
True
"""
return quaternion_matrix(random_quaternion(rand))
class Arcball(object):
"""Virtual Trackball Control.
>>> ball = Arcball()
>>> ball = Arcball(initial=numpy.identity(4))
>>> ball.place([320, 320], 320)
>>> ball.down([500, 250])
>>> ball.drag([475, 275])
>>> R = ball.matrix()
>>> numpy.allclose(numpy.sum(R), 3.90583455)
True
>>> ball = Arcball(initial=[1, 0, 0, 0])
>>> ball.place([320, 320], 320)
>>> ball.setaxes([1, 1, 0], [-1, 1, 0])
>>> ball.constrain = True
>>> ball.down([400, 200])
>>> ball.drag([200, 400])
>>> R = ball.matrix()
>>> numpy.allclose(numpy.sum(R), 0.2055924)
True
>>> ball.next()
"""
def __init__(self, initial=None):
"""Initialize virtual trackball control.
initial : quaternion or rotation matrix
"""
self._axis = None
self._axes = None
self._radius = 1.0
self._center = [0.0, 0.0]
self._vdown = numpy.array([0.0, 0.0, 1.0])
self._constrain = False
if initial is None:
self._qdown = numpy.array([1.0, 0.0, 0.0, 0.0])
else:
initial = numpy.array(initial, dtype=numpy.float64)
if initial.shape == (4, 4):
self._qdown = quaternion_from_matrix(initial)
elif initial.shape == (4, ):
initial /= vector_norm(initial)
self._qdown = initial
else:
raise ValueError("initial not a quaternion or matrix")
self._qnow = self._qpre = self._qdown
def place(self, center, radius):
"""Place Arcball, e.g. when window size changes.
center : sequence[2]
Window coordinates of trackball center.
radius : float
Radius of trackball in window coordinates.
"""
self._radius = float(radius)
self._center[0] = center[0]
self._center[1] = center[1]
def setaxes(self, *axes):
"""Set axes to constrain rotations."""
if axes is None:
self._axes = None
else:
self._axes = [unit_vector(axis) for axis in axes]
@property
def constrain(self):
"""Return state of constrain to axis mode."""
return self._constrain
@constrain.setter
def constrain(self, value):
"""Set state of constrain to axis mode."""
self._constrain = bool(value)
def down(self, point):
"""Set initial cursor window coordinates and pick constrain-axis."""
self._vdown = arcball_map_to_sphere(point, self._center, self._radius)
self._qdown = self._qpre = self._qnow
if self._constrain and self._axes is not None:
self._axis = arcball_nearest_axis(self._vdown, self._axes)
self._vdown = arcball_constrain_to_axis(self._vdown, self._axis)
else:
self._axis = None
def drag(self, point):
"""Update current cursor window coordinates."""
vnow = arcball_map_to_sphere(point, self._center, self._radius)
if self._axis is not None:
vnow = arcball_constrain_to_axis(vnow, self._axis)
self._qpre = self._qnow
t = numpy.cross(self._vdown, vnow)
if numpy.dot(t, t) < _EPS:
self._qnow = self._qdown
else:
q = [numpy.dot(self._vdown, vnow), t[0], t[1], t[2]]
self._qnow = quaternion_multiply(q, self._qdown)
def next(self, acceleration=0.0):
"""Continue rotation in direction of last drag."""
q = quaternion_slerp(self._qpre, self._qnow, 2.0+acceleration, False)
self._qpre, self._qnow = self._qnow, q
def matrix(self):
"""Return homogeneous rotation matrix."""
return quaternion_matrix(self._qnow)
def arcball_map_to_sphere(point, center, radius):
"""Return unit sphere coordinates from window coordinates."""
v0 = (point[0] - center[0]) / radius
v1 = (center[1] - point[1]) / radius
n = v0*v0 + v1*v1
if n > 1.0:
# position outside of sphere
n = math.sqrt(n)
return numpy.array([v0/n, v1/n, 0.0])
else:
return numpy.array([v0, v1, math.sqrt(1.0 - n)])
def arcball_constrain_to_axis(point, axis):
"""Return sphere point perpendicular to axis."""
v = numpy.array(point, dtype=numpy.float64, copy=True)
a = numpy.array(axis, dtype=numpy.float64, copy=True)
v -= a * numpy.dot(a, v) # on plane
n = vector_norm(v)
if n > _EPS:
if v[2] < 0.0:
numpy.negative(v, v)
v /= n
return v
if a[2] == 1.0:
return numpy.array([1.0, 0.0, 0.0])
return unit_vector([-a[1], a[0], 0.0])
def arcball_nearest_axis(point, axes):
"""Return axis, which arc is nearest to point."""
point = numpy.array(point, dtype=numpy.float64, copy=False)
nearest = None
mx = -1.0
for axis in axes:
t = numpy.dot(arcball_constrain_to_axis(point, axis), point)
if t > mx:
nearest = axis
mx = t
return nearest
# epsilon for testing whether a number is close to zero
_EPS = numpy.finfo(float).eps * 4.0
# axis sequences for Euler angles
_NEXT_AXIS = [1, 2, 0, 1]
# map axes strings to/from tuples of inner axis, parity, repetition, frame
_AXES2TUPLE = {
'sxyz': (0, 0, 0, 0), 'sxyx': (0, 0, 1, 0), 'sxzy': (0, 1, 0, 0),
'sxzx': (0, 1, 1, 0), 'syzx': (1, 0, 0, 0), 'syzy': (1, 0, 1, 0),
'syxz': (1, 1, 0, 0), 'syxy': (1, 1, 1, 0), 'szxy': (2, 0, 0, 0),
'szxz': (2, 0, 1, 0), 'szyx': (2, 1, 0, 0), 'szyz': (2, 1, 1, 0),
'rzyx': (0, 0, 0, 1), 'rxyx': (0, 0, 1, 1), 'ryzx': (0, 1, 0, 1),
'rxzx': (0, 1, 1, 1), 'rxzy': (1, 0, 0, 1), 'ryzy': (1, 0, 1, 1),
'rzxy': (1, 1, 0, 1), 'ryxy': (1, 1, 1, 1), 'ryxz': (2, 0, 0, 1),
'rzxz': (2, 0, 1, 1), 'rxyz': (2, 1, 0, 1), 'rzyz': (2, 1, 1, 1)}
_TUPLE2AXES = dict((v, k) for k, v in list(_AXES2TUPLE.items()))
def vector_norm(data, axis=None, out=None):
"""Return length, i.e. Euclidean norm, of ndarray along axis.
>>> v = numpy.random.random(3)
>>> n = vector_norm(v)
>>> numpy.allclose(n, numpy.linalg.norm(v))
True
>>> v = numpy.random.rand(6, 5, 3)
>>> n = vector_norm(v, axis=-1)
>>> numpy.allclose(n, numpy.sqrt(numpy.sum(v*v, axis=2)))
True
>>> n = vector_norm(v, axis=1)
>>> numpy.allclose(n, numpy.sqrt(numpy.sum(v*v, axis=1)))
True
>>> v = numpy.random.rand(5, 4, 3)
>>> n = numpy.empty((5, 3))
>>> vector_norm(v, axis=1, out=n)
>>> numpy.allclose(n, numpy.sqrt(numpy.sum(v*v, axis=1)))
True
>>> vector_norm([])
0.0
>>> vector_norm([1])
1.0
"""
data = numpy.array(data, dtype=numpy.float64, copy=True)
if out is None:
if data.ndim == 1:
return math.sqrt(numpy.dot(data, data))
data *= data
out = numpy.atleast_1d(numpy.sum(data, axis=axis))
numpy.sqrt(out, out)
return out
else:
data *= data
numpy.sum(data, axis=axis, out=out)
numpy.sqrt(out, out)
def unit_vector(data, axis=None, out=None):
"""Return ndarray normalized by length, i.e. Euclidean norm, along axis.
>>> v0 = numpy.random.random(3)
>>> v1 = unit_vector(v0)
>>> numpy.allclose(v1, v0 / numpy.linalg.norm(v0))
True
>>> v0 = numpy.random.rand(5, 4, 3)
>>> v1 = unit_vector(v0, axis=-1)
>>> v2 = v0 / numpy.expand_dims(numpy.sqrt(numpy.sum(v0*v0, axis=2)), 2)
>>> numpy.allclose(v1, v2)
True
>>> v1 = unit_vector(v0, axis=1)
>>> v2 = v0 / numpy.expand_dims(numpy.sqrt(numpy.sum(v0*v0, axis=1)), 1)
>>> numpy.allclose(v1, v2)
True
>>> v1 = numpy.empty((5, 4, 3))
>>> unit_vector(v0, axis=1, out=v1)
>>> numpy.allclose(v1, v2)
True
>>> list(unit_vector([]))
[]
>>> list(unit_vector([1]))
[1.0]
"""
if out is None:
data = numpy.array(data, dtype=numpy.float64, copy=True)
if data.ndim == 1:
data /= math.sqrt(numpy.dot(data, data))
return data
else:
if out is not data:
out[:] = numpy.array(data, copy=False)
data = out
length = numpy.atleast_1d(numpy.sum(data*data, axis))
numpy.sqrt(length, length)
if axis is not None:
length = numpy.expand_dims(length, axis)
data /= length
if out is None:
return data
def random_vector(size):
"""Return array of random doubles in the half-open interval [0.0, 1.0).
>>> v = random_vector(10000)
>>> numpy.all(v >= 0) and numpy.all(v < 1)
True
>>> v0 = random_vector(10)
>>> v1 = random_vector(10)
>>> numpy.any(v0 == v1)
False
"""
return numpy.random.random(size)
def vector_product(v0, v1, axis=0):
"""Return vector perpendicular to vectors.
>>> v = vector_product([2, 0, 0], [0, 3, 0])
>>> numpy.allclose(v, [0, 0, 6])
True
>>> v0 = [[2, 0, 0, 2], [0, 2, 0, 2], [0, 0, 2, 2]]
>>> v1 = [[3], [0], [0]]
>>> v = vector_product(v0, v1)
>>> numpy.allclose(v, [[0, 0, 0, 0], [0, 0, 6, 6], [0, -6, 0, -6]])
True
>>> v0 = [[2, 0, 0], [2, 0, 0], [0, 2, 0], [2, 0, 0]]
>>> v1 = [[0, 3, 0], [0, 0, 3], [0, 0, 3], [3, 3, 3]]
>>> v = vector_product(v0, v1, axis=1)
>>> numpy.allclose(v, [[0, 0, 6], [0, -6, 0], [6, 0, 0], [0, -6, 6]])
True
"""
return numpy.cross(v0, v1, axis=axis)
def angle_between_vectors(v0, v1, directed=True, axis=0):
"""Return angle between vectors.
If directed is False, the input vectors are interpreted as undirected axes,
i.e. the maximum angle is pi/2.
>>> a = angle_between_vectors([1, -2, 3], [-1, 2, -3])
>>> numpy.allclose(a, math.pi)
True
>>> a = angle_between_vectors([1, -2, 3], [-1, 2, -3], directed=False)
>>> numpy.allclose(a, 0)
True
>>> v0 = [[2, 0, 0, 2], [0, 2, 0, 2], [0, 0, 2, 2]]
>>> v1 = [[3], [0], [0]]
>>> a = angle_between_vectors(v0, v1)
>>> numpy.allclose(a, [0, 1.5708, 1.5708, 0.95532])
True
>>> v0 = [[2, 0, 0], [2, 0, 0], [0, 2, 0], [2, 0, 0]]
>>> v1 = [[0, 3, 0], [0, 0, 3], [0, 0, 3], [3, 3, 3]]
>>> a = angle_between_vectors(v0, v1, axis=1)
>>> numpy.allclose(a, [1.5708, 1.5708, 1.5708, 0.95532])
True
"""
v0 = numpy.array(v0, dtype=numpy.float64, copy=False)
v1 = numpy.array(v1, dtype=numpy.float64, copy=False)
dot = numpy.sum(v0 * v1, axis=axis)
dot /= vector_norm(v0, axis=axis) * vector_norm(v1, axis=axis)
return numpy.arccos(dot if directed else numpy.fabs(dot))
def inverse_matrix(matrix):
"""Return inverse of square transformation matrix.
>>> M0 = random_rotation_matrix()
>>> M1 = inverse_matrix(M0.T)
>>> numpy.allclose(M1, numpy.linalg.inv(M0.T))
True
>>> for size in range(1, 7):
... M0 = numpy.random.rand(size, size)
... M1 = inverse_matrix(M0)
... if not numpy.allclose(M1, numpy.linalg.inv(M0)): print(size)
"""
return numpy.linalg.inv(matrix)
def concatenate_matrices(*matrices):
"""Return concatenation of series of transformation matrices.
>>> M = numpy.random.rand(16).reshape((4, 4)) - 0.5
>>> numpy.allclose(M, concatenate_matrices(M))
True
>>> numpy.allclose(numpy.dot(M, M.T), concatenate_matrices(M, M.T))
True
"""
M = numpy.identity(4)
for i in matrices:
M = numpy.dot(M, i)
return M
def is_same_transform(matrix0, matrix1):
"""Return True if two matrices perform same transformation.
>>> is_same_transform(numpy.identity(4), numpy.identity(4))
True
>>> is_same_transform(numpy.identity(4), random_rotation_matrix())
False
"""
matrix0 = numpy.array(matrix0, dtype=numpy.float64, copy=True)
matrix0 /= matrix0[3, 3]
matrix1 = numpy.array(matrix1, dtype=numpy.float64, copy=True)
matrix1 /= matrix1[3, 3]
return numpy.allclose(matrix0, matrix1)
def _import_module(name, package=None, warn=True, prefix='_py_', ignore='_'):
"""Try import all public attributes from module into global namespace.
Existing attributes with name clashes are renamed with prefix.
Attributes starting with underscore are ignored by default.
Return True on successful import.
"""
import warnings
from importlib import import_module
try:
if not package:
module = import_module(name)
else:
module = import_module('.' + name, package=package)
except ImportError:
if warn:
warnings.warn("failed to import module %s" % name)
else:
for attr in dir(module):
if ignore and attr.startswith(ignore):
continue
if prefix:
if attr in globals():
globals()[prefix + attr] = globals()[attr]
elif warn:
warnings.warn("no Python implementation of " + attr)
globals()[attr] = getattr(module, attr)
return True
#_import_module('_transformations')
if __name__ == "__main__":
import doctest
import random # used in doctests
numpy.set_printoptions(suppress=True, precision=5)
doctest.testmod()
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/external/pyquante2/__init__.py | .py | 0 | 0 | null | Python |
3D | Autodesk/molecular-design-toolkit | moldesign/external/pyquante2/utils.py | .py | 6,283 | 243 | """
utils.py - Simple utilility funtions used in pyquante2.
"""
import numpy as np
from math import factorial,lgamma
from itertools import combinations_with_replacement,combinations
from functools import reduce
def pairs(it): return combinations_with_replacement(it,2)
def upairs(it): return combinations(it,2)
def fact2(n):
"""
fact2(n) - n!!, double factorial of n
>>> fact2(0)
1
>>> fact2(1)
1
>>> fact2(3)
3
>>> fact2(8)
384
>>> fact2(-1)
1
"""
return reduce(int.__mul__,range(n,0,-2),1)
def norm2(a): return np.dot(a,a)
def binomial(n,k):
"""
Binomial coefficient
>>> binomial(5,2)
10
>>> binomial(10,5)
252
"""
if n == k: return 1
assert n>k, "Attempting to call binomial(%d,%d)" % (n,k)
return factorial(n)//(factorial(k)*factorial(n-k))
def Fgamma(m,x):
"""
Incomplete gamma function
>>> np.isclose(Fgamma(0,0),1.0)
True
"""
SMALL=1e-12
x = max(x,SMALL)
return 0.5*pow(x,-m-0.5)*gamm_inc(m+0.5,x)
# def gamm_inc_scipy(a,x):
# """
# Demonstration on how to replace the gamma calls with scipy.special functions.
# By default, pyquante only requires numpy, but this may change as scipy
# builds become more stable.
# >>> np.isclose(gamm_inc_scipy(0.5,1),1.49365)
# True
# >>> np.isclose(gamm_inc_scipy(1.5,2),0.6545103)
# True
# >>> np.isclose(gamm_inc_scipy(2.5,1e-12),0)
# True
# """
# from scipy.special import gamma,gammainc
# return gamma(a)*gammainc(a,x)
def gamm_inc(a,x):
"""
Incomple gamma function \gamma; computed from NumRec routine gammp.
>>> np.isclose(gamm_inc(0.5,1),1.49365)
True
>>> np.isclose(gamm_inc(1.5,2),0.6545103)
True
>>> np.isclose(gamm_inc(2.5,1e-12),0)
True
"""
assert (x > 0 and a >= 0), "Invalid arguments in routine gamm_inc: %s,%s" % (x,a)
if x < (a+1.0): #Use the series representation
gam,gln = _gser(a,x)
else: #Use continued fractions
gamc,gln = _gcf(a,x)
gam = 1-gamc
return np.exp(gln)*gam
def _gser(a,x):
"Series representation of Gamma. NumRec sect 6.1."
ITMAX=100
EPS=3.e-7
gln=lgamma(a)
assert(x>=0),'x < 0 in gser'
if x == 0 : return 0,gln
ap = a
delt = sum = 1./a
for i in range(ITMAX):
ap=ap+1.
delt=delt*x/ap
sum=sum+delt
if abs(delt) < abs(sum)*EPS: break
else:
print('a too large, ITMAX too small in gser')
gamser=sum*np.exp(-x+a*np.log(x)-gln)
return gamser,gln
def _gcf(a,x):
"Continued fraction representation of Gamma. NumRec sect 6.1"
ITMAX=100
EPS=3.e-7
FPMIN=1.e-30
gln=lgamma(a)
b=x+1.-a
c=1./FPMIN
d=1./b
h=d
for i in range(1,ITMAX+1):
an=-i*(i-a)
b=b+2.
d=an*d+b
if abs(d) < FPMIN: d=FPMIN
c=b+an/c
if abs(c) < FPMIN: c=FPMIN
d=1./d
delt=d*c
h=h*delt
if abs(delt-1.) < EPS: break
else:
print('a too large, ITMAX too small in gcf')
gammcf=np.exp(-x+a*np.log(x)-gln)*h
return gammcf,gln
def trace2(A,B):
"Return trace(AB) of matrices A and B"
return np.sum(A*B)
def dmat(c,nclosed,nopen=0):
"""Form the density matrix from the first nclosed orbitals of c. If nopen != 0,
add in half the density matrix from the next nopen orbitals.
"""
d = np.dot(c[:,:nclosed],c[:,:nclosed].T)
if nopen > 0:
d += 0.5*np.dot(c[:,nclosed:(nclosed+nopen)],c[:,nclosed:(nclosed+nopen)].T)
return d
def symorth(S):
"Symmetric orthogonalization"
E,U = np.linalg.eigh(S)
n = len(E)
Shalf = np.identity(n,'d')
for i in range(n):
Shalf[i,i] /= np.sqrt(E[i])
return simx(Shalf,U,True)
def canorth(S):
"Canonical orthogonalization U/sqrt(lambda)"
E,U = np.linalg.eigh(S)
for i in range(len(E)):
U[:,i] = U[:,i] / np.sqrt(E[i])
return U
def cholorth(S):
"Cholesky orthogonalization"
return np.linalg.inv(np.linalg.cholesky(S)).T
def simx(A,B,transpose=False):
"Similarity transform B^T(AB) or B(AB^T) (if transpose)"
if transpose:
return np.dot(B,np.dot(A,B.T))
return np.dot(B.T,np.dot(A,B))
def ao2mo(H,C): return simx(H,C)
def mo2ao(H,C,S): return simx(H,np.dot(S,C),transpose=True)
def geigh(H,S):
"Solve the generalized eigensystem Hc = ESc"
A = cholorth(S)
E,U = np.linalg.eigh(simx(H,A))
return E,np.dot(A,U)
def parseline(line,format):
"""\
Given a line (a string actually) and a short string telling
how to format it, return a list of python objects that result.
The format string maps words (as split by line.split()) into
python code:
x -> Nothing; skip this word
s -> Return this word as a string
i -> Return this word as an int
d -> Return this word as an int
f -> Return this word as a float
Basic parsing of strings:
>>> parseline('Hello, World','ss')
['Hello,', 'World']
You can use 'x' to skip a record; you also don't have to parse
every record:
>>> parseline('1 2 3 4','xdd')
[2, 3]
>>> parseline('C1 0.0 0.0 0.0','sfff')
['C1', 0.0, 0.0, 0.0]
Should this return an empty list?
>>> parseline('This line wont be parsed','xx')
"""
xlat = {'x':None,'s':str,'f':float,'d':int,'i':int}
result = []
words = line.split()
for i in range(len(format)):
f = format[i]
trans = xlat.get(f,None)
if trans: result.append(trans(words[i]))
if len(result) == 0: return None
if len(result) == 1: return result[0]
return result
def colorscale(mag, cmin, cmax):
"""
Return a tuple of floats between 0 and 1 for R, G, and B.
From Python Cookbook (9.11?)
"""
# Normalize to 0-1
try:
x = float(mag-cmin)/(cmax-cmin)
except ZeroDivisionError:
x = 0.5 # cmax == cmin
blue = min((max((4*(0.75-x), 0.)), 1.))
red = min((max((4*(x-0.25), 0.)), 1.))
green = min((max((4*abs(x-0.5)-1., 0.)), 1.))
return red, green, blue
#Todo: replace with np.isclose
#def isnear(a,b,tol=1e-6): return abs(a-b) < tol
if __name__ == '__main__':
import doctest
doctest.testmod()
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/external/pyquante2/one.py | .py | 7,343 | 254 | """
One electron integrals.
"""
from numpy import pi,exp,floor,array,isclose
from math import factorial
## BEGIN MODIFIED CODE:
#from pyquante2.utils import binomial, fact2, Fgamma, norm2
from .utils import binomial, fact2, Fgamma, norm2
#END MODIFIED CODE
# Notes:
# The versions S,T,V include the normalization constants
# The version overlap,kinetic,nuclear_attraction do not.
# This is so, for example, the kinetic routines can call the potential routines
# without the normalization constants getting in the way.
def S(a,b):
"""
Simple interface to the overlap function.
>>> from pyquante2 import pgbf,cgbf
>>> s = pgbf(1)
>>> isclose(S(s,s),1.0)
True
>>> sc = cgbf(exps=[1],coefs=[1])
>>> isclose(S(sc,sc),1.0)
True
>>> sc = cgbf(exps=[1],coefs=[1])
>>> isclose(S(sc,s),1.0)
True
>>> isclose(S(s,sc),1.0)
True
"""
if b.contracted:
return sum(cb*S(pb,a) for (cb,pb) in b)
elif a.contracted:
return sum(ca*S(b,pa) for (ca,pa) in a)
return a.norm*b.norm*overlap(a.exponent,a.powers,
a.origin,b.exponent,b.powers,b.origin)
def T(a,b):
"""
Simple interface to the kinetic function.
>>> from pyquante2 import pgbf,cgbf
>>> from pyquante2.basis.pgbf import pgbf
>>> s = pgbf(1)
>>> isclose(T(s,s),1.5)
True
>>> sc = cgbf(exps=[1],coefs=[1])
>>> isclose(T(sc,sc),1.5)
True
>>> sc = cgbf(exps=[1],coefs=[1])
>>> isclose(T(sc,s),1.5)
True
>>> isclose(T(s,sc),1.5)
True
"""
if b.contracted:
return sum(cb*T(pb,a) for (cb,pb) in b)
elif a.contracted:
return sum(ca*T(b,pa) for (ca,pa) in a)
return a.norm*b.norm*kinetic(a.exponent,a.powers,a.origin,
b.exponent,b.powers,b.origin)
def V(a,b,C):
"""
Simple interface to the nuclear attraction function.
>>> from pyquante2 import pgbf,cgbf
>>> s = pgbf(1)
>>> isclose(V(s,s,(0,0,0)),-1.595769)
True
>>> sc = cgbf(exps=[1],coefs=[1])
>>> isclose(V(sc,sc,(0,0,0)),-1.595769)
True
>>> sc = cgbf(exps=[1],coefs=[1])
>>> isclose(V(sc,s,(0,0,0)),-1.595769)
True
>>> isclose(V(s,sc,(0,0,0)),-1.595769)
True
"""
if b.contracted:
return sum(cb*V(pb,a,C) for (cb,pb) in b)
elif a.contracted:
return sum(ca*V(b,pa,C) for (ca,pa) in a)
return a.norm*b.norm*nuclear_attraction(a.exponent,a.powers,a.origin,
b.exponent,b.powers,b.origin,C)
def overlap(alpha1,lmn1,A,alpha2,lmn2,B):
"""
Full form of the overlap integral. Taken from THO eq. 2.12
>>> isclose(overlap(1,(0,0,0),array((0,0,0),'d'),1,(0,0,0),array((0,0,0),'d')),1.968701)
True
"""
l1,m1,n1 = lmn1
l2,m2,n2 = lmn2
rab2 = norm2(A-B)
gamma = alpha1+alpha2
P = gaussian_product_center(alpha1,A,alpha2,B)
pre = pow(pi/gamma,1.5)*exp(-alpha1*alpha2*rab2/gamma)
wx = overlap1d(l1,l2,P[0]-A[0],P[0]-B[0],gamma)
wy = overlap1d(m1,m2,P[1]-A[1],P[1]-B[1],gamma)
wz = overlap1d(n1,n2,P[2]-A[2],P[2]-B[2],gamma)
return pre*wx*wy*wz
def overlap1d(l1,l2,PAx,PBx,gamma):
"""
The one-dimensional component of the overlap integral. Taken from THO eq. 2.12
>>> isclose(overlap1d(0,0,0,0,1),1.0)
True
"""
total = 0
for i in range(1+int(floor(0.5*(l1+l2)))):
total += binomial_prefactor(2*i,l1,l2,PAx,PBx)* \
fact2(2*i-1)/pow(2*gamma,i)
return total
def gaussian_product_center(alpha1,A,alpha2,B):
"""
The center of the Gaussian resulting from the product of two Gaussians:
>>> gaussian_product_center(1,array((0,0,0),'d'),1,array((0,0,0),'d'))
array([ 0., 0., 0.])
"""
return (alpha1*A+alpha2*B)/(alpha1+alpha2)
def binomial_prefactor(s,ia,ib,xpa,xpb):
"""
The integral prefactor containing the binomial coefficients from Augspurger and Dykstra.
>>> binomial_prefactor(0,0,0,0,0)
1
"""
total= 0
for t in range(s+1):
if s-ia <= t <= ib:
total += binomial(ia,s-t)*binomial(ib,t)* \
pow(xpa,ia-s+t)*pow(xpb,ib-t)
return total
def kinetic(alpha1,lmn1,A,alpha2,lmn2,B):
"""
The full form of the kinetic energy integral
>>> isclose(kinetic(1,(0,0,0),array((0,0,0),'d'),1,(0,0,0),array((0,0,0),'d')),2.953052)
True
"""
l1,m1,n1 = lmn1
l2,m2,n2 = lmn2
term0 = alpha2*(2*(l2+m2+n2)+3)*\
overlap(alpha1,(l1,m1,n1),A,\
alpha2,(l2,m2,n2),B)
term1 = -2*pow(alpha2,2)*\
(overlap(alpha1,(l1,m1,n1),A,
alpha2,(l2+2,m2,n2),B)
+ overlap(alpha1,(l1,m1,n1),A,
alpha2,(l2,m2+2,n2),B)
+ overlap(alpha1,(l1,m1,n1),A,
alpha2,(l2,m2,n2+2),B))
term2 = -0.5*(l2*(l2-1)*overlap(alpha1,(l1,m1,n1),A,
alpha2,(l2-2,m2,n2),B) +
m2*(m2-1)*overlap(alpha1,(l1,m1,n1),A,
alpha2,(l2,m2-2,n2),B) +
n2*(n2-1)*overlap(alpha1,(l1,m1,n1),A,
alpha2,(l2,m2,n2-2),B))
return term0+term1+term2
def nuclear_attraction(alpha1,lmn1,A,alpha2,lmn2,B,C):
"""
Full form of the nuclear attraction integral
>>> isclose(nuclear_attraction(1,(0,0,0),array((0,0,0),'d'),1,(0,0,0),array((0,0,0),'d'),array((0,0,0),'d')),-3.141593)
True
"""
l1,m1,n1 = lmn1
l2,m2,n2 = lmn2
gamma = alpha1+alpha2
P = gaussian_product_center(alpha1,A,alpha2,B)
rab2 = norm2(A-B)
rcp2 = norm2(C-P)
dPA = P-A
dPB = P-B
dPC = P-C
Ax = A_array(l1,l2,dPA[0],dPB[0],dPC[0],gamma)
Ay = A_array(m1,m2,dPA[1],dPB[1],dPC[1],gamma)
Az = A_array(n1,n2,dPA[2],dPB[2],dPC[2],gamma)
total = 0.
for I in range(l1+l2+1):
for J in range(m1+m2+1):
for K in range(n1+n2+1):
total += Ax[I]*Ay[J]*Az[K]*Fgamma(I+J+K,rcp2*gamma)
val= -2*pi/gamma*exp(-alpha1*alpha2*rab2/gamma)*total
return val
def A_term(i,r,u,l1,l2,PAx,PBx,CPx,gamma):
"""
THO eq. 2.18
>>> A_term(0,0,0,0,0,0,0,0,1)
1.0
>>> A_term(0,0,0,0,1,1,1,1,1)
1.0
>>> A_term(1,0,0,0,1,1,1,1,1)
-1.0
>>> A_term(0,0,0,1,1,1,1,1,1)
1.0
>>> A_term(1,0,0,1,1,1,1,1,1)
-2.0
>>> A_term(2,0,0,1,1,1,1,1,1)
1.0
>>> A_term(2,0,1,1,1,1,1,1,1)
-0.5
>>> A_term(2,1,0,1,1,1,1,1,1)
0.5
"""
return pow(-1,i)*binomial_prefactor(i,l1,l2,PAx,PBx)*\
pow(-1,u)*factorial(i)*pow(CPx,i-2*r-2*u)*\
pow(0.25/gamma,r+u)/factorial(r)/factorial(u)/factorial(i-2*r-2*u)
def A_array(l1,l2,PA,PB,CP,g):
"""
THO eq. 2.18 and 3.1
>>> A_array(0,0,0,0,0,1)
[1.0]
>>> A_array(0,1,1,1,1,1)
[1.0, -1.0]
>>> A_array(1,1,1,1,1,1)
[1.5, -2.5, 1.0]
"""
Imax = l1+l2+1
A = [0]*Imax
for i in range(Imax):
for r in range(int(floor(i/2)+1)):
for u in range(int(floor((i-2*r)/2)+1)):
I = i-2*r-u
A[I] = A[I] + A_term(i,r,u,l1,l2,PA,PB,CP,g)
return A
if __name__ == '__main__':
import doctest; doctest.testmod()
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/mathutils/__init__.py | .py | 67 | 3 | from .vectormath import *
from .eigen import *
from .grids import * | Python |
3D | Autodesk/molecular-design-toolkit | moldesign/mathutils/spherical_harmonics.py | .py | 6,809 | 199 | from __future__ import print_function, absolute_import, division
from future import standard_library
standard_library.install_aliases()
from future.builtins import *
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
__all__ = ['SPHERE_TO_CART']
def cart_to_polar_angles(coords):
if len(coords.shape) == 2:
r_xy_2 = np.sum(coords[:,:2]**2, axis=1)
theta = np.arctan2(np.sqrt(r_xy_2), coords[:,2])
phi = np.arctan2(coords[:,1], coords[:,0])
return theta, phi
else:
assert len(coords) == 3 and len(coords.shape) == 1
r_xy_2 = np.sum(coords[:2]**2)
theta = np.arctan2(np.sqrt(r_xy_2), coords[2])
phi = np.arctan2(coords[1], coords[0])
return theta, phi
class Y(object):
r""" A real-valued spherical harmonic function
These functions are orthonormalized over the sphere such that
.. math::
\int d^2\Omega \: Y_{lm}(\theta, \phi) Y_{l'm'}(\theta, \phi) = \delta_{l,l'} \delta_{m,m'}
References:
https://en.wikipedia.org/wiki/Table_of_spherical_harmonics#Real_spherical_harmonics
"""
def __init__(self, l, m):
self.l = l
self.m = m
self._posneg = -1
if self.m < 0:
self._posneg *= -1
if self.m % 2 == 0:
self._posneg *= -1
def __call__(self, coords):
from scipy.special import sph_harm
theta, phi = cart_to_polar_angles(coords)
if self.m == 0:
return (sph_harm(self.m, self.l, phi, theta)).real
vplus = sph_harm(abs(self.m), self.l, phi, theta)
vminus = sph_harm(-abs(self.m), self.l, phi, theta)
value = np.sqrt(1/2.0) * (self._posneg*vplus + vminus)
if self.m < 0:
return -value.imag
else:
return value.real
class Cart(object):
def __init__(self, px, py, pz, coeff):
self.powers = np.array([px, py, pz], dtype='int')
self.coeff = coeff
self._l = self.powers.sum()
def __call__(self, coords):
""" Evaluate this function at the given list of coordinates
Args:
coords (Vector[len=3] or Matrix[matrix=shape(*,3)): coordinate(s) at which to evaluate
Returns:
Scalar or Vector: value of the function at these coordinates
"""
c = coords**self.powers
if len(coords.shape) == 2:
r_l = (coords**2).sum(axis=1) ** (-self._l / 2.0)
return self.coeff * np.product(c, axis=1) * r_l
else:
r_l = (coords**2).sum() ** (-self._l / 2.0)
return self.coeff * np.product(c) * r_l
def __iter__(self):
yield self # for interface compatibility with the CartSum class
class CartSum(object):
def __init__(self, coeff, carts):
self.coeff = coeff
prefacs = []
powers = []
self.l = None
for cart in carts:
powers.append(np.array(cart[:3], dtype='int'))
prefacs.append(np.array(cart[3]))
if self.l is None:
self.l = sum(cart[:3])
else:
assert self.l == sum(cart[:3])
self.prefactors = np.array(prefacs)
self.powers = np.array(powers)
def __call__(self, coords):
# likely can speed this up a lot using clever numpy broadcasting
if len(coords.shape) == 2:
c = np.zeros((len(coords), ))
axis = 1
r_l = (coords**2).sum(axis=1) ** (-self.l / 2.0)
else:
c = 0.0
axis = None
r_l = (coords**2).sum() ** (-self.l / 2.0)
for factor, power in zip(self.prefactors, self.powers):
c += factor * np.product(coords**power, axis=axis)
return c * self.coeff * r_l
def __iter__(self):
for pf, (px, py, pz) in zip(self.prefactors, self.powers):
yield Cart(px, py, pz, coeff=self.coeff*pf)
def sqrt_x_over_pi(num, denom):
return np.sqrt(num / (denom*np.pi))
############ s ############
SPHERE_TO_CART = {(0, 0): Cart(0, 0, 0, sqrt_x_over_pi(1, 4)),
############ p ############
(1, -1): Cart(0, 1, 0, sqrt_x_over_pi(3, 4)),
(1, 0): Cart(0, 0, 1, sqrt_x_over_pi(3, 4)),
(1, 1): Cart(1, 0, 0, sqrt_x_over_pi(3, 4)),
############ d ############
(2, -2): Cart(1, 1, 0, sqrt_x_over_pi(15, 4)),
(2, -1): Cart(0, 1, 1, sqrt_x_over_pi(15, 4)),
(2, 0): CartSum(sqrt_x_over_pi(5, 16),
[(2, 0, 0, -1.0),
(0, 2, 0, -1.0),
(0, 0, 2, 2.0)]),
(2, 1): Cart(1, 0, 1, sqrt_x_over_pi(15, 4)),
(2, 2): CartSum(sqrt_x_over_pi(15, 16),
[(2, 0, 0, 1.0),
(0, 2, 0, -1.0)]),
############ f ############
(3, -3): CartSum(sqrt_x_over_pi(35, 32),
[(2, 1, 0, 3.0),
(0, 3, 0, -1.0)]),
(3, -2): Cart(1, 1, 1, sqrt_x_over_pi(105, 4)),
(3, -1): CartSum(sqrt_x_over_pi(21, 32),
[(0, 1, 2, 4.0),
(2, 1, 0, -1.0),
(0, 3, 0, -1.0)]),
(3, 0): CartSum(sqrt_x_over_pi(7, 16),
[(0, 0, 3, 2.0),
(2, 0, 1, -3.0),
(0, 2, 1, -3.0)]),
(3, 1): CartSum(sqrt_x_over_pi(21, 32),
[(1, 0, 2, 4.0),
(3, 0, 0, -1.0),
(1, 2, 0, -1.0)]),
(3, 2): CartSum(sqrt_x_over_pi(105, 16),
[(2, 0, 1, 1.0),
(0, 2, 1, -1.0)]),
(3, 3): CartSum(sqrt_x_over_pi(35, 32),
[(3, 0, 0, 1.0),
(1, 2, 0, -3.0)]),
} | Python |
3D | Autodesk/molecular-design-toolkit | moldesign/mathutils/vectormath.py | .py | 5,770 | 191 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
from .. import units as u
from ..utils import exports
@exports
def perpendicular(vec):
""" Return arbitrary unit vector(s) perpendicular to one or more vectors.
This obviously doesn't have a unique solution, but is useful for various computations.
Args:
vec (Vector or List[Vector]): 3-D vector or list thereof
Returns:
vec (np.ndarray): normalized unit vector in a perpendicular direction
"""
vectorized = len(vec.shape) > 1
direction = normalized(vec)
if vectorized:
cross_axis = np.array([[0.0, 0.0, 1.0] if d[2] < 0.9 else [0.0, 1.0, 0.0]
for d in direction])
else:
if abs(direction[2]) < 0.9:
cross_axis = np.array([0.0, 0.0, 1.0])
else:
cross_axis = np.array([0.0, 1.0, 0.0])
perp = normalized(np.cross(direction, cross_axis))
return perp
@exports
def norm(vec):
""" Calculate norm of a vector or list thereof
Args:
vec (Vector or List[Vector]): vector(s) to compute norm of
Returns:
Scalar or List[Scalar]: norms
"""
if len(vec.shape) == 1: # it's just a single column vector
return np.sqrt(vec.dot(vec))
else: # treat as list of vectors
return np.sqrt((vec*vec).sum(axis=1))
@exports
def normalized(vector, zero_as_zero=True):
""" Create normalized versions of a vector or lists of vectors.
Args:
vector (Vector or List[Vector]): vector(s) to be normalized
zero_as_zero (bool): if True, return a 0-vector if a 0-vector is passed; otherwise, will
follow default system behavior (depending on numpy's configuration)
Returns:
Vector or List[Vector]: normalized vector(s)
"""
vec = getattr(vector, 'magnitude', vector) # strip units right away if necessary
mag = norm(vec)
if len(vec.shape) == 1: # it's just a single column vector
if mag == 0.0 and zero_as_zero:
return vec*0.0
else:
return vec/mag
else: # treat as list of vectors
if zero_as_zero:
mag[mag == 0.0] = 1.0 # prevent div by 0
return vec / mag[:, None]
@exports
def alignment_rotation(v1, v2, handle_linear=True):
""" Calculate rotation angle(s) and axi(e)s to make v1 parallel with v2
Args:
v1 (vector or List[Vector]): 3-dimensional vector(s) to create rotation for
v2 (vector or List[Vector]): 3-dimensional vector(s) to make v1 parallel to
handle_linear (bool): if v1 is parallel or anti-parallel to v2, return an arbitrary
vector perpendicular to both as the axis (otherwise, returns a 0-vector)
Returns:
MdtQuantity[angle]: angle between the two
np.ndarray[len=3]: rotation axis (unit vector)
References:
https://stackoverflow.com/a/10145056/1958900
"""
e1 = normalized(v1)
e2 = normalized(v2)
vectorize = len(e1.shape) > 1
normal = np.cross(e1, e2)
s = norm(normal)
if vectorize:
c = (e1*e2).sum(axis=1)
if handle_linear:
linear_indices = s == 0.0
if linear_indices.any():
normal[linear_indices] = perpendicular(v1[linear_indices])
s[linear_indices] = 1.0
else:
c = np.dot(e1, e2)
if handle_linear and s == 0.0:
normal = perpendicular(v1)
s = 1.0
angle = np.arctan2(s, c)
return angle*u.radian, normal / s
@exports
def safe_arccos(costheta):
""" Version of arccos that can handle numerical noise greater than 1.0
"""
if hasattr(costheta, 'shape') and costheta.shape: # vector version
assert (np.abs(costheta)-1.0 < 1.0e-13).all()
costheta[costheta > 1.0] = 1.0
costheta[costheta < -1.0] = -1.0
return np.arccos(costheta)
else:
if abs(costheta) > 1.0:
assert abs(costheta) - 1.0 < 1.0e-14
return u.pi
else:
return np.arccos(costheta)
@exports
def sub_angles(a, b):
""" Subtract two angles, keeping the result within [-180,180)
"""
return normalize_angle(a - b)
@exports
def normalize_angle(c):
""" Normalize an angle to the interval [-180,180)
"""
return (c + 180.0 * u.degrees) % (360.0 * u.degrees) - (180.0 * u.degrees)
@exports
def apply_4x4_transform(trans, vecs):
"""
Applies a 4x4 transformation vector so one or more 3-D position vector
:param trans:
:param vecs:
:return: transformed position vector
"""
has_units = False
if hasattr(vecs, 'get_units'):
has_units = True
units = vecs.get_units()
vecs = vecs.magnitude
if len(vecs.shape) == 1:
v = np.ones(4)
v[:3] = vecs
vt = trans.dot(v)
result = vt[:3] / vt[3]
else:
v = np.ones((4, len(vecs)))
v[:3, :] = vecs.T
vt = trans.dot(v)
result = (vt[:3] / vt[3]).T
if has_units:
result = result * units
return result
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/mathutils/grids.py | .py | 5,650 | 164 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import itertools
import numpy as np
from .. import utils
from .. import units as u
@utils.exports
class VolumetricGrid(object):
""" Creates a 3D, rectangular grid of points
Args:
xrange (Tuple[len=2]): (min,max) in x direction
yrange (Tuple[len=2]): (min,max) in y direction
zrange (Tuple[len=2]): (min,max) in z direction
xpoints (int): number of grid lines in x direction (default: npoints)
ypoints (int): number of grid lines in y direction (default: npoints)
zpoints (int): number of grid lines in z direction (default: npoints)
npoints (int): synonym for "xpoints"
"""
dx, dy, dz = (utils.IndexView('deltas', i) for i in range(3))
xr, yr, zr = (utils.IndexView('ranges', i) for i in range(3))
xpoints, ypoints, zpoints = (utils.IndexView('points', i) for i in range(3))
xspace, yspace, zspace = (utils.IndexView('spaces', i) for i in range(3))
def __init__(self, xrange, yrange, zrange,
xpoints=None, ypoints=None, zpoints=None,
npoints=32):
if xpoints is not None:
npoints = xpoints
self.points = np.array([xpoints if xpoints is not None else npoints,
ypoints if ypoints is not None else npoints,
zpoints if zpoints is not None else npoints],
dtype='int')
self.ranges = u.array([xrange, yrange, zrange])
self.deltas = (self.ranges[:,1] - self.ranges[:,0]) / (self.points - 1.0)
self.spaces = [u.linspace(*r, num=p) for r,p in zip(self.ranges, self.points)]
@property
def ndims(self):
return len(self.ranges)
ndim = num_dims = ndims
@property
def origin(self):
""" Vector[len=3]: the origin of the grid (the lowermost corner in each dimension)
"""
origin = [r[0] for r in (self.ranges)]
try:
return u.array(origin)
except u.DimensionalityError:
return origin
@property
def npoints(self):
""" int: total number of grid points in this grid
"""
return np.product(self.points)
def iter_points(self):
""" Iterate through every point on the grid.
Always iterates in the same order. The x-index is the most slowly varying,
the z-index is the fastest.
Yields:
Vector[len=3]: x,y,z coordinate of each point on the grid
"""
for i,j,k in itertools.product(*map(range, self.points)):
yield self.origin + self.deltas * [i,j,k]
def allpoints(self):
""" Return an array of all coordinates on the grid.
This obviously takes a lot of memory, but is useful for evaluating vectorized functions
on this grid. Points are returned in the same order as ``iter_points``.
Yields:
Matrix[shape=(self.npoints**3,3)]: x,y,z coordinate of each point on the grid
"""
return _cartesian_product(self.spaces)
def _cartesian_product(arrays):
""" Fast grid creation routine from @senderle on Stack Overflow. This is awesome.
Modifications:
1. Module import names
2. Unit handling
References:
https://stackoverflow.com/a/11146645/1958900
"""
import functools
# AMV mod for units handling
units = getattr(arrays[0], 'units', u.ureg.dimensionless)
# original code
broadcastable = np.ix_(*arrays)
broadcasted = np.broadcast_arrays(*broadcastable)
rows, cols = functools.reduce(np.multiply, broadcasted[0].shape), len(broadcasted)
out = np.empty(rows * cols, dtype=broadcasted[0].dtype)
start, end = 0, rows
for a in broadcasted:
out[start:end] = a.reshape(-1)
start, end = end, end + rows
result = out.reshape(cols, rows).T
# AMV mod for units handling
if units == u.ureg.dimensionless:
return result
else:
# do it this way to avoid copying a huge array
quantity = u.MdtQuantity(result, units=units)
return quantity
@utils.exports
def padded_grid(positions, padding, npoints=25):
""" Creates a 3D, rectangular grid of points surrounding a set of positions
The points in the grid are evenly spaced in each dimension, but spacing may differ between
in different dimensions.
Args:
positions (Matrix[shape=(*,3)]): positions to create the grid around
padding (Scalar): how far to extend the grid past the positions in each dimension
npoints (int): number of points in each direction (total number of points is npoints**3)
Returns:
VolumetricGrid: grid object
"""
mins = positions.min(axis=0)-padding
maxes = positions.max(axis=0)+padding
xr = (mins[0], maxes[0])
yr = (mins[1], maxes[1])
zr = (mins[2], maxes[2])
return VolumetricGrid(xr, yr, zr, npoints)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/mathutils/eigen.py | .py | 3,708 | 101 | from __future__ import print_function, absolute_import, division
from future import standard_library
standard_library.install_aliases()
from future.builtins import *
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from .. import units as u
from ..utils import exports
from ..mathutils import normalized
@exports
class Eigenspace(object):
""" Holds sets of eigenvactors and eigenvalues, offers helpful methods for organizing them.
Args:
evals (List[Scalar]): list of eigenvalues
evecs (List[Vector]): list of eigenvectors (in the same order as eigenvalues). These will
automatically be normalized
Note:
The eigenvectors from many eigenvector solvers - notably including scipy's - will need to be
transposed to fit the form of ``evecs`` here!
It's generally assumed that Eigenspace objects will be subclassed to wrap various bits of
eignproblem-related functionality.
"""
def __init__(self, evals, evecs):
if len(evals) != len(evecs):
raise ValueError('Eigenvalues and eigenvectors have different lengths!')
self.evals = u.array(evals)
self.evecs = u.array([normalized(evec, zero_as_zero=True)
for evec in evecs])
def __str__(self):
return "%s of dimension %s" % (self.__class__.__name__, len(self.evals))
def sort(self, largest_first=True, key=abs):
""" Sort the eigenvectors and values in place*
By default, this sorts from largest to smallest by the _absolute magnitude_ of the
eigenvalues.
Note:
*this sort is only "in place" in the sense that it mutates the data in this instance;
note that it still uses auxiliary memroy
Args:
largest_first (bool): sort from largest to smallest (equivalent to ``reverse=True`` in a
standard python sort, except that it is true by default here)
key (callable): function of the form ``f(eigenval)`` OR ``f(eval, evec)``.
By default, sorts by the ``abs`` of the eigenvalues
"""
try: # construct the sorting function
result = key(self.evals[0], self.evecs[0])
except TypeError:
def keyfn(t):
return key(t[0])
else:
def keyfn(t):
return key(t[0], t[1])
evals, evecs = zip(*sorted(zip(self.evals.copy(), self.evecs.copy()),
key=keyfn, reverse=largest_first))
self.evals[:] = evals
self.evecs[:] = evecs
def transform(self, coords):
""" Transform a list of coordinates (or just a single one) into this eigenbasis
Args:
coords (List[Vector] or Vector): coordinate(s) to transform
Returns:
List[Vector] or vector: transformed coordinate(s)
"""
c = u.array(coords)
dims = len(c.shape)
if dims == 1:
return u.dot(self.evecs, c)
elif dims == 2:
return u.dot(self.evecs, c.T).T
else:
raise ValueError('Transform accepts only 1- or 2-dimensional arrays')
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/min/scipy.py | .py | 5,685 | 159 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from .. import units as u
from ..utils import exports
from .base import MinimizerBase
from .. import exceptions
from . import toplevel
class ScipyMinimizer(MinimizerBase):
""" SciPy's implementation of the BFGS method, with gradients if available.
Args:
bfgs_threshold (u.Scalar[force]): Maximum force on a single atom
Note:
This implementation will fail rapidly if large forces are present (>> 1 eV/angstrom).
"""
_strip_units = True
_METHOD_NAME = None
_TAKES_FTOL = False
_TAKES_GTOL = False
def _run(self):
import scipy.optimize
if self.mol.constraints and self._METHOD_NAME == 'bfgs':
raise exceptions.NotSupportedError('BFGS minimization does not '
'support constrained minimization')
print('Starting geometry optimization: SciPy/%s with %s gradients'%(
self._METHOD_NAME, self.gradtype))
options = {'disp': True}
if self.nsteps is not None:
options['maxiter'] = self.nsteps
if self.gradtype == 'analytical':
grad = self.grad
else: grad = None
if self.force_tolerance is not None:
if self._TAKES_GTOL:
options['gtol'] = self.force_tolerance.defunits().magnitude
elif self._TAKES_FTOL:
print('WARNING: this method does not use force to measure convergence; '
'approximating force_tolerance keyword')
options['ftol'] = (self.force_tolerance * u.angstrom / 50.0).defunits_value()
else:
print('WARNING: no convergence criteria for this method; using defaults')
self._optimize_kwargs = dict(method=self._METHOD_NAME,
options=options)
self._constraint_multiplier = 1.0
result = scipy.optimize.minimize(self.objective,
self._coords_to_vector(self.mol.positions),
jac=grad,
callback=self.callback,
constraints=self._make_constraints(),
**self._optimize_kwargs)
if self.mol.constraints:
result = self._force_constraint_convergence(result)
self.traj.info = result
finalprops = self._calc_cache[tuple(result.x)]
self.mol.positions = finalprops.positions
self.mol.properties = finalprops
def _force_constraint_convergence(self, result):
""" Make sure that all constraints are satisfied, ramp up the constraint functions if not
Note - if additional iterations are necessary, this will destroy the scipy optimize results
object stored at self.traj.info. Not sure what to do about that
"""
import scipy.optimize
for i in range(5):
for constraint in self.mol.constraints:
if not constraint.satisfied():
break
else:
return result
print('Constraints not satisfied; raising penalties ...')
self._constraint_multiplier *= 10.0
result = scipy.optimize.minimize(self.objective,
self._coords_to_vector(self.mol.positions),
jac=self.grad if self.gradtype=='analytical' else None,
callback=self.callback,
constraints=self._make_constraints(),
**self._optimize_kwargs)
return result
def _make_constraints(self):
from .. import geom
constraints = []
for constraint in geom.get_base_constraints(self.mol.constraints):
fun, jac = self._make_constraint_funs(constraint)
constraints.append(dict(type='eq',
fun=fun,
jac=jac))
return constraints
def _make_constraint_funs(self, const):
def fun(v):
self._sync_positions(v)
return const.error().defunits_value() * self._constraint_multiplier
def jac(v):
self._sync_positions(v)
return (const.gradient().defunits_value().reshape(self.mol.num_atoms*3)
* self._constraint_multiplier)
return fun, jac
@exports
class BFGS(ScipyMinimizer):
_METHOD_NAME = 'bfgs'
_TAKES_GTOL = True
bfgs = BFGS._as_function('bfgs')
exports(bfgs)
toplevel(bfgs)
@exports
class SequentialLeastSquares(ScipyMinimizer):
_METHOD_NAME = 'SLSQP'
_TAKES_FTOL = True
sequential_least_squares = SequentialLeastSquares._as_function('sequential_least_squares')
exports(sequential_least_squares)
toplevel(sequential_least_squares)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/min/descent.py | .py | 5,961 | 153 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
import moldesign as mdt
from .. import units as u
from ..utils import exports
from .base import MinimizerBase
from . import toplevel
@exports
class GradientDescent(MinimizerBase):
""" A careful (perhaps overly careful) gradient descent implementation designed to relax
structures far from equilibrium.
A backtracking line search is performed along the steepest gradient direction.
The maximum move for any single atom is also limited by ``max_atom_move``
Note:
This algorithm is good at stably removing large forces, but it's very poorly suited to
locating any type of critical point; don't use this to find a minimum!
References:
https://www.math.washington.edu/~burke/crs/408/lectures/L7-line-search.pdf
Args:
mol (moldesign.Molecule): molecule to minimize
max_atom_move (Scalar[length]): maximum displacement of a single atom
scaling (Scalar[length/force]): unit of displacement per unit force
gamma (float): number between 0 and 1 indicating scale factor for backtracking search
control (float): threshold for terminating line search; this is a proportion
(0<=``control``<=1) of the expected function decrease
**kwargs (dict): kwargs from :class:`MinimizerBase`
"""
_strip_units = False
def __init__(self, mol,
max_atom_move=0.05*u.angstrom,
scaling=0.01*u.angstrom**2/u.eV,
gamma=0.4, control=0.25,
**kwargs):
super().__init__(mol, **kwargs)
assert 'forces' in self.request_list, 'Gradient descent requires built-in gradients'
self.max_atom_move = max_atom_move
self.scaling = scaling
self.gamma = gamma
self.control = control
self._last_energy = None
self._constraintlist = None
def _run(self):
print('Starting geometry optimization: built-in gradient descent')
lastenergy = self.objective(self._coords_to_vector(self.mol.positions))
current = self._coords_to_vector(self.mol.positions)
if self.mol.constraints:
self._constraintlist = mdt.geom.get_base_constraints(self.mol.constraints)
for i in range(self.nsteps):
grad = self.grad(current)
if np.abs(grad.max()) < self.force_tolerance: # converged
return
move = self.scale_move(grad)
armijo_goldstein_prefac = self.control * move.norm()
for icycle in range(0, 10):
g = self.gamma**icycle
newpos = self._make_move(current, g * move)
# move direction may be different than gradient direction due to constraints
move_vec = (newpos-current).normalized()
if grad.dot(move_vec) >= 0.0: # move flipped direction!
if self._constraint_convergence(newpos, current, grad):
return # flip was because we're converged
else: # flip was because move was too big
newenergy = np.inf * u.default.energy
continue
try:
newenergy = self.objective(newpos)
except mdt.QMConvergenceError:
continue
if newenergy <= lastenergy + g * armijo_goldstein_prefac * grad.dot(move_vec):
break
else:
if newenergy >= lastenergy:
raise mdt.ConvergenceFailure('Line search failed')
if self._constraint_convergence(newpos, current, grad):
return
else:
current = newpos
lastenergy = newenergy
self._sync_positions(current)
self.callback()
def scale_move(self, grad):
move = -self.scaling*grad
mmax = np.abs(move).max()
if mmax > self.max_atom_move: # rescale the move
move *= self.max_atom_move/mmax
return move
def _make_move(self, current, move):
if self.mol.constraints:
# TODO: get constraint forces from lagrange multipliers and use them to check for convergence
self._sync_positions(current)
prev = self.mol.positions.copy()
self._sync_positions(current+move)
mdt.geom.shake_positions(self.mol, prev, constraints=self._constraintlist)
return self._coords_to_vector(self.mol.positions)
else:
return current + move
def _constraint_convergence(self, pos, lastpos, energygrad):
""" Test for force-based convergence after projecting out constraint forces
Until the shake method starts explicitly storing constraint forces, we calculate this
direction as the SHAKE-adjusted displacement vector from the current descent step
"""
direction = mdt.mathutils.normalized((pos - lastpos).flatten())
proj_grad = energygrad.dot(direction)
return abs(proj_grad) < self.force_tolerance
gradient_descent = GradientDescent._as_function('gradient_descent')
exports(gradient_descent)
toplevel(gradient_descent)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/min/__init__.py | .py | 159 | 10 | def toplevel(o):
__all__.append(o.__name__)
return o
__all__ = []
from . import base
from .scipy import *
from .descent import *
from .smart import *
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/min/smart.py | .py | 4,412 | 129 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from .base import MinimizerBase
from . import toplevel, BFGS, GradientDescent, SequentialLeastSquares
from moldesign import utils
from moldesign import units as u
from moldesign.utils import exports
GDTHRESH = 1.5*u.eV/u.angstrom
@exports
class SmartMin(MinimizerBase):
""" Uses gradient descent until forces fall below a threshold,
then switches to BFGS (unconstrained) or SLSQP (constrained).
Args:
gd_threshold (u.Scalar[force]): Use gradient descent if there are any forces larger
than this; use an approximate hessian method (BFGS or SLSQP) otherwise
Note:
Not really that smart.
"""
# TODO: use non-gradient methods if forces aren't available
_strip_units = True
@utils.args_from(MinimizerBase,
inject_kwargs={'gd_threshold': GDTHRESH})
def __init__(self, *args, **kwargs):
self.gd_threshold = kwargs.pop('gd_threshold', GDTHRESH)
self.args = args
self.kwargs = kwargs
self._spmin = None
self._descent = None
self._traj = None
self._currentstep = None
self.__foundmin = None
super().__init__(*args, **kwargs)
def _run(self):
# If forces are already low, go directly to the quadratic convergence methods and return
forces = self.mol.calculate_forces()
if abs(forces).max() <= self.gd_threshold:
self._spmin = self._make_quadratic_method()
self._spmin.traj = self.traj
self._spmin._run()
return
# Otherwise, remove large forces with gradient descent; exit if we pass the cycle limit
descent_kwargs = self.kwargs.copy()
descent_kwargs['force_tolerance'] = self.gd_threshold
self._descender = GradientDescent(*self.args, **descent_kwargs)
self._descender._run()
if self._descender.current_step >= self.nsteps:
self.traj = self._descender.traj
return
# Finally, use a quadratic method to converge the optimization
kwargs = dict(_restart_from=self._descender.current_step,
_restart_energy=self._descender._initial_energy)
kwargs['frame_interval'] = self.kwargs.get('frame_interval',
self._descender.frame_interval)
self._spmin = self._make_quadratic_method(kwargs)
self._spmin.current_step = self.current_step
self._spmin._foundmin = self._foundmin
self._spmin._run()
self.traj = self._descender.traj + self._spmin.traj
self.traj.info = getattr(self._spmin, 'info', None)
@property
def _foundmin(self):
if self._descent:
return self._descent._foundmin
elif self._spmin:
return self._spmin._foundmin
else:
return self.__foundmin
@_foundmin.setter
def _foundmin(self, val):
self.__foundmin = val
@property
def currentstep(self):
if self._descent:
return self._descent.currentstep
elif self._spmin:
return self._spmin.currentstep
else:
return self._currentstep
@currentstep.setter
def currentstep(self, val):
self._currentstep = val
def _make_quadratic_method(self, kwargs=None):
if kwargs is None: kwargs = {}
kw = self.kwargs.copy()
kw.update(kwargs)
if self.mol.constraints:
spmin = SequentialLeastSquares(*self.args, **kw)
else:
spmin = BFGS(*self.args, **kw)
return spmin
minimize = SmartMin._as_function('minimize')
exports(minimize)
toplevel(minimize)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/min/base.py | .py | 8,600 | 227 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import sys
import numpy as np
import moldesign as mdt
from .. import data
from .. import units as u
class MinimizerBase(object):
_strip_units = True # callbacks expect and return dimensionless quantities scaled to default unit system
def __init__(self, mol, nsteps=20,
force_tolerance=data.DEFAULT_FORCE_TOLERANCE,
frame_interval=None,
_restart_from=0,
_restart_energy=None):
self.mol = mol
self.nsteps = nsteps - _restart_from
self.force_tolerance = force_tolerance
self.frame_interval = mdt.utils.if_not_none(frame_interval,
max(nsteps/10, 1))
self._restart_from = _restart_from
self._foundmin = None
self._calc_cache = {}
# Set up the trajectory to track the minimization
self.traj = mdt.Trajectory(mol)
self.current_step = _restart_from
if _restart_energy is None:
self.traj.new_frame(minimization_step=0,
annotation='minimization steps:%d (energy=%s)' %
(0, mol.calc_potential_energy()))
self._initial_energy = _restart_energy
self._last_energy = None
self._last_grad = None
# Figure out whether we'll use gradients
self.request_list = ['potential_energy']
if 'forces' in mol.energy_model.ALL_PROPERTIES:
self.gradtype = 'analytical'
self.request_list.append('forces')
else:
self.gradtype = 'approximate'
assert len(mol.constraints) == 0, \
'Constrained minimization only available with analytical gradients'
def _sync_positions(self, vector):
""" Set the molecule's position
"""
c = vector.reshape((self.mol.num_atoms, 3))
if self._strip_units:
self.mol.positions = c*u.default.length
else:
self.mol.positions = c
def _coords_to_vector(self, coords):
""" Convert position array to a flat vector
"""
vec = coords.reshape(self.mol.num_atoms * 3).copy()
if self._strip_units:
return vec.magnitude
else:
return vec
def objective(self, vector):
""" Callback function to calculate the objective function
"""
self._sync_positions(vector)
try:
self.mol.calculate(requests=self.request_list)
except mdt.QMConvergenceError: # returning infinity can help rescue some line searches
return np.inf
self._cachemin()
self._calc_cache[tuple(vector)] = self.mol.properties
pot = self.mol.potential_energy
if self._initial_energy is None: self._initial_energy = pot
self._last_energy = pot
if self._strip_units: return pot.defunits().magnitude
else: return pot.defunits()
def grad(self, vector):
""" Callback function to calculate the objective's gradient
"""
self._sync_positions(vector)
self.mol.calculate(requests=self.request_list)
self._cachemin()
self._calc_cache[tuple(vector)] = self.mol.properties
grad = -self.mol.forces
grad = grad.reshape(self.mol.num_atoms * 3)
self._last_grad = grad
if self._strip_units:
return grad.defunits().magnitude
else:
return grad.defunits()
def _cachemin(self):
""" Caches the minimum potential energy properties so we can return them
when the calculation is done.
Underlying implementations can use this or not - it may not be valid if constraints
are present
"""
if self._foundmin is None or self.mol.potential_energy < self._foundmin.potential_energy:
self._foundmin = self.mol.properties
def __call__(self, remote=False, wait=True):
""" Run the minimization
Args:
remote (bool): launch the minimization in a remote job
wait (bool): if remote, wait until the minimization completes before returning.
(if remote=True and wait=False, will return a reference to the job)
Returns:
moldesign.Trajectory: the minimization trajectory
"""
if hasattr(self.mol.energy_model, '_PKG') and self.mol.energy_model._PKG.force_remote:
remote = True
if remote:
return self.runremotely(wait=wait)
self._run()
# Write the last step to the trajectory, if needed
if self.traj.potential_energy[-1] != self.mol.potential_energy:
assert self.traj.potential_energy[-1] > self.mol.potential_energy
self.traj.new_frame(minimization_step=self.current_step,
annotation='minimization result (%d steps) (energy=%s)'%
(self.current_step, self.mol.potential_energy))
return self.traj
def runremotely(self, wait=True):
""" Execute this minimization in a remote process
Args:
wait (bool): if True, block until the minimization is complete.
Otherwise, return a ``pyccc.PythonJob`` object
"""
return mdt.compute.runremotely(self.__call__, wait=wait,
jobname='%s: %s' % (self.__class__.__name__, self.mol.name),
when_finished=self._finishremoterun)
def _finishremoterun(self, job):
traj = job.function_result
self.mol.positions = traj.positions[-1]
self.mol.properties.update(traj.frames[-1])
return traj
def _run(self):
raise NotImplementedError('This is an abstract base class')
def callback(self, *args):
""" To be called after each minimization step
Args:
*args: ignored
"""
self.current_step += 1
if self.current_step % self.frame_interval != 0: return
self.mol.calculate(self.request_list)
self.traj.new_frame(minimization_step=self.current_step,
annotation='minimization steps:%d (energy=%s)'%
(self.current_step, self.mol.potential_energy))
if self.nsteps is None:
message = ['Minimization step %d' % self.current_step]
else:
message = ['Step %d/%d' % (self.current_step, self.nsteps + self._restart_from)]
if self._last_energy is not None:
message.append(u'\u0394E={x.magnitude:.3e} {x.units}'.format(
x=self._last_energy - self._initial_energy))
if self.gradtype == 'analytical' and self._last_grad is not None:
force = self._last_grad
message.append(u'RMS \u2207E={rmsf.magnitude:.3e}, '
u'max \u2207E={mf.magnitude:.3e} {mf.units}'.format(
rmsf=np.sqrt(force.dot(force) / self.mol.ndims),
mf=np.abs(force).max()))
if self.mol.constraints:
nsatisfied = 0
for c in self.mol.constraints:
if c.satisfied(): nsatisfied += 1
message.append('constraints:%d/%d' % (nsatisfied, len(self.mol.constraints)))
print(', '.join(message))
sys.stdout.flush()
@classmethod
def _as_function(cls, newname):
""" Create a function that runs this minimization
"""
@mdt.utils.args_from(cls, allexcept=['self'])
def asfn(*args, **kwargs):
remote = kwargs.pop('remote', False)
wait = kwargs.pop('wait', True)
obj = cls(*args, **kwargs)
return obj(remote=remote, wait=wait)
asfn.__name__ = newname
asfn.__doc__ = cls.__doc__
return asfn
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/models/amber.py | .py | 2,282 | 63 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import moldesign as mdt
from ..parameters import Parameter, WhenParam
from ..utils import exports
from . import ForceField
@exports
class GaffSmallMolecule(ForceField):
""" Model the energy using the GAFF forcefield
This is implemented as a special case of the ForceField energy model; it automates small
parameterization process
"""
# TODO: mechanism to store partial charges so they don't need to be constantly recomputed
PARAMETERS = [Parameter('partial_charges',
'Partial charge model',
type=str,
default='am1-bcc',
choices=['am1-bcc', 'gasteiger', 'esp']),
Parameter('gaff_version',
'GAFF version',
type=str,
choices='gaff gaff2'.split(),
default='gaff2')
] + ForceField.PARAMETERS
def prep(self, force=False):
self._parameterize()
return super().prep()
def calculate(self, requests=None):
if not self._prepped:
self._parameterize()
return super().calculate(requests=requests)
def _parameterize(self):
if not self.mol.ff:
params = mdt.create_ff_parameters(self.mol,
charges=self.params.partial_charges,
baseff=self.params.gaff_version)
params.assign(self.mol)
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/models/models.py | .py | 2,349 | 80 | from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# TODO: look into http://molmod.github.io/
"""
"Generic" energy models - models that can be specified directly by name, without worrying about
which specific implementation is used.
Currently, everything here is an alias. However, more complicated logic (including runtime
dispatch) may be used to determine the best implementation in a given situation
"""
from moldesign import utils
from . import PySCFPotential
from . import OpenMMPotential
##################
# ForceField
@utils.exports
class ForceField(OpenMMPotential):
pass # currently an alias
##################
# QM generics
@utils.exports
class RHF(PySCFPotential):
@utils.doc_inherit
def __init__(self, *args, **kwargs):
kwargs['theory'] = 'rhf'
super(RHF, self).__init__(*args, **kwargs)
@utils.exports
class DFT(PySCFPotential):
@utils.doc_inherit
def __init__(self, *args, **kwargs):
kwargs['theory'] = 'rks'
super(DFT, self).__init__(*args, **kwargs)
@utils.exports
class B3LYP(PySCFPotential):
@utils.doc_inherit
def __init__(self, *args, **kwargs):
kwargs['theory'] = 'rks'
kwargs['functional'] = 'b3lyp'
super(B3LYP, self).__init__(*args, **kwargs)
@utils.exports
class MP2(PySCFPotential):
@utils.doc_inherit
def __init__(self, *args, **kwargs):
kwargs['theory'] = 'mp2'
super(MP2, self).__init__(*args, **kwargs)
@utils.exports
class CASSCF(PySCFPotential):
@utils.doc_inherit
def __init__(self, *args, **kwargs):
kwargs['theory'] = 'casscf'
super(CASSCF, self).__init__(*args, **kwargs) | Python |
3D | Autodesk/molecular-design-toolkit | moldesign/models/nwchem.py | .py | 6,978 | 175 | # Copyright 2016 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import itertools
import json
import numpy as np
import pyccc
import moldesign as mdt
from moldesign.utils import exports
from moldesign import units as u
from .base import QMBase, QMMMBase
from .jsonmodel import JsonModelBase
@exports
class NWChemQM(JsonModelBase, QMBase):
""" Interface with NWChem package (QM only)
Note:
This is the first interface based on our new wrapping strategy. This is slightly hacked,
but has the potential to become very general; very few things here are NWChem-specific
"""
IMAGE = 'nwchem'
MODELNAME = 'nwchem'
DEFAULT_PROPERTIES = ['potential_energy']
ALL_PROPERTIES = DEFAULT_PROPERTIES + 'forces dipole esp'.split()
def _get_inputfiles(self):
return {'input.xyz': self.mol.write(format='xyz')}
def write_constraints(self, parameters):
parameters['constraints'] = []
for constraint in self.mol.constraints:
if not constraint.satisfied(): # TODO: factor this out into NWChem subclass
raise ValueError('Constraints must be satisfied before passing to NWChem %s'
% constraint)
cjson = {'type': constraint['desc'],
'value': constraint['value'].to_json()}
if cjson['type'] == 'position':
cjson['atomIdx'] = constraint.atom.index
elif cjson['type'] == 'distance':
cjson['atomIdx1'] = constraint.a1.index
cjson['atomIdx2'] = constraint.a2.index
@exports
class NWChemQMMM(NWChemQM):
""" Interface with NWChem package for QM/MM only. Note that this is currently only set up for
optimizations, and only of the QM geometry - the MM region cannot move.
"""
IMAGE = 'nwchem'
MODELNAME = 'nwchem_qmmmm'
DEFAULT_PROPERTIES = ['potential_energy', 'forces', 'esp']
ALL_PROPERTIES = DEFAULT_PROPERTIES
RUNNER = 'runqmmm.py'
PARSER = 'getresults.py'
PARAMETERS = NWChemQM.PARAMETERS + [mdt.parameters.Parameter('qm_atom_indices')]
def _get_inputfiles(self):
crdparamfile = self._makecrdparamfile()
return {'nwchem.crdparams': crdparamfile}
def _makecrdparamfile(self, include_mmterms=True):
pmdparms = self.mol.ff.parmed_obj
lines = ['qm']
qmatom_idxes = set(self.params.qm_atom_indices)
def crosses_boundary(*atoms):
total = 0
inqm = 0
for atom in atoms:
total += 1
if atom.idx in qmatom_idxes:
inqm += 1
return inqm != 0 and inqm < total
# write QM atoms
for atomidx in sorted(self.params.qm_atom_indices):
atom = self.mol.atoms[atomidx]
x, y, z = atom.position.value_in(u.angstrom)
lines.append(' %d %s %24.14f %24.14f %24.14f' %
(atom.index+1, atom.element, x, y, z))
qmatom_idxes.add(atom.index)
# write MM atoms
lines.append('end\n\nmm')
for atom, patm in zip(self.mol.atoms, pmdparms.atoms):
assert atom.index == patm.idx
assert atom.atnum == patm.element
x, y, z = atom.position.value_in(u.angstrom)
if atom.index not in qmatom_idxes:
lines.append(' %d %s %24.14f %24.14f %24.14f %24.14f'
%(atom.index+1, atom.element, x, y, z, patm.charge))
lines.append('end\n\nbond\n# i j k_ij r0')
if include_mmterms:
for term in pmdparms.bonds:
if crosses_boundary(term.atom1, term.atom2):
lines.append(' %d %d %20.10f %20.10f' %
(term.atom1.idx+1, term.atom2.idx+1, term.type.k, term.type.req))
lines.append('end\n\nangle\n# i j k k_ijk theta0')
if include_mmterms:
for term in pmdparms.angles:
if crosses_boundary(term.atom1, term.atom2, term.atom3):
lines.append(' %d %d %d %20.10f %20.10f' %
(term.atom1.idx+1, term.atom2.idx+1, term.atom3.idx+1,
term.type.k, term.type.theteq))
lines.append('end\n\ndihedral\n'
'# i j k l k_ijkl periodicity phase')
if include_mmterms:
for term in pmdparms.dihedrals:
if crosses_boundary(term.atom1, term.atom2, term.atom3, term.atom4):
lines.append(' %d %d %d %d %20.10f %d %20.10f' %
(term.atom1.idx+1, term.atom2.idx+1, term.atom3.idx+1, term.atom4.idx+1,
term.type.phi_k, term.type.per, term.type.phase))
lines.append('end\n\nvdw\n'
'# i j A_coeff B_coeff')
if include_mmterms:
for atom1idx, atom2 in itertools.product(qmatom_idxes, pmdparms.atoms):
if atom2.idx in qmatom_idxes: continue
atom1 = pmdparms.atoms[atom1idx]
epsilon = np.sqrt(atom1.epsilon * atom2.epsilon)
if epsilon == 0: continue
sigma = (atom1.sigma + atom2.sigma) / 2.0
lj_a = 4.0 * epsilon * sigma**12
lj_b = 4.0 * epsilon * sigma**6
lines.append(' %d %d %20.10e %20.10e' %
(atom1.idx+1, atom2.idx+1, lj_a, lj_b))
lines.append('end\n\nscaled_vdw\n'
'# i j A_coeff B_coeff one_scnb')
# TODO: this part
lines.append('end')
return pyccc.files.StringContainer('\n'.join(lines))
def finish_min(self, job):
traj = mdt.Trajectory(self.mol)
traj.new_frame()
results = json.loads(job.get_output('results.json').read())
new_state = self._json_to_quantities(results['states'][0])
for iatom in sorted(self.params.qm_indices):
for position in new_state['positions']:
self.mol.atoms[iatom].position = position
properties = self._process_results(results)
properties.positions = self.mol.positions
self.mol.properties = properties
traj.new_frame()
return traj
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/models/jsonmodel.py | .py | 6,004 | 167 | # Copyright 2016 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import json
import pyccc
import moldesign as mdt
from .. import units as u
from .base import EnergyModelBase
class JsonModelBase(EnergyModelBase):
""" Abstract energy model interface using JSON inputs and outputs
"""
IMAGE = None # base name of the docker image
MODELNAME = 'abstract model'
RUNNER = 'run.py'
PARSER = 'getresults.py'
def prep(self):
parameters = self.params.copy()
parameters['constraints'] = []
for constraint in self.mol.constraints:
self._handle_constraint(constraint)
parameters['charge'] = self.mol.charge.value_in(u.q_e)
self._jobparams = parameters
self._prepped = True
def calculate(self, requests=None):
if requests is None:
requests = self.DEFAULT_PROPERTIES
job = self._make_calculation_job(requests)
return mdt.compute.run_job(job, _return_result=True)
def _handle_constraint(self, constraint):
raise NotImplementedError()
def _make_calculation_job(self, requests=None):
params, inputfiles = self._prep_calculation(requests)
inputfiles['params.json'] = mdt.utils.json_dumps(dict(params))
job = pyccc.Job(image=mdt.compute.get_image_path(self.IMAGE),
command='%s && %s' % (self.RUNNER, self.PARSER),
inputs=inputfiles,
when_finished=self.finish,
name='%s/%s' % (self.MODELNAME, self.mol.name))
return job
def _prep_calculation(self, requests):
self.prep()
parameters = self._jobparams.copy()
parameters['runType'] = 'singlePoint'
parameters['properties'] = list(requests)
if self.mol.constraints:
self.write_constraints(parameters)
inputfiles = self._get_inputfiles()
return parameters, inputfiles
def finish(self, job):
results = json.loads(job.get_output('results.json').read())
return self._process_results(results)
def _process_results(self, results):
assert len(results['states']) == 1
jsonprops = results['states'][0]['calculated']
if 'orbitals' in jsonprops:
wfn = self._make_wfn(results['states'][0])
else:
wfn = None
result = mdt.MolecularProperties(self.mol,
**self._json_to_quantities(jsonprops))
if wfn:
result['wfn'] = wfn
return result
def _make_wfn(self, state):
from moldesign import orbitals
try:
basis_fns = state['calculated']['method']['aobasis']
except KeyError:
basis_set = None
else:
bfs = [orbitals.AtomicBasisFunction(**bdata) for bdata in basis_fns]
basis_set = orbitals.BasisSet(self.mol,
orbitals=bfs,
name=self.params.basis)
wfn = orbitals.ElectronicWfn(self.mol,
self.mol.num_electrons,
aobasis=basis_set)
for setname, orbdata in state['calculated']['orbitals'].items():
orbs = []
for iorb in range(len(orbdata['coefficients'])):
orbs.append(orbitals.Orbital(orbdata['coefficients'][iorb]))
if 'occupations' in orbs:
orbs[-1].occupation = orbdata['occupations'][iorb]
wfn.add_orbitals(orbs, orbtype=setname)
return wfn
@staticmethod
def _json_to_quantities(jsonprops): # TODO: handle this within JSON decoder
props = {}
for name, property in jsonprops.items():
if isinstance(property, dict) and len(property) == 2 and \
'units' in property and 'value' in property:
props[name] = property['value'] * u.ureg(property['units'])
else:
props[name] = property
return props
def _get_inputfiles(self):
""" Override this method to pass additional input files to the program
"""
return {}
def minimize(self, nsteps=None):
job = self._make_minimization_job(nsteps)
return mdt.compute.run_job(job, _return_result=True)
def _make_minimization_job(self, nsteps):
params, inputfiles = self._prep_calculation([self.DEFAULT_PROPERTIES])
params['runType'] = 'minimization'
if nsteps is not None:
params['minimization_steps'] = 100
inputfiles['params.json'] = mdt.utils.json_dumps(dict(params))
job = pyccc.Job(image=mdt.compute.get_image_path(self.IMAGE),
command='%s && %s' % (self.RUNNER, self.PARSER),
inputs=inputfiles,
when_finished=self.finish_min,
name='%s/%s' % (self.MODELNAME, self.mol.name))
return job
def finish_min(self, job):
# TODO: parse more data than just the final minimization state
traj = mdt.Trajectory(self.mol)
traj.new_frame()
results = json.loads(job.get_output('results.json').read())
new_state = self._json_to_quantities(results['states'][0])
self.mol.positions = new_state['positions']
self.mol.properties = self._process_results(results)
traj.new_frame()
return traj
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/models/qmmm.py | .py | 8,032 | 208 | # Copyright 2016 Autodesk Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import moldesign as mdt
from ..molecules import MolecularProperties
from ..utils import exports
from .base import QMMMBase
class QMMMEmbeddingBase(QMMMBase):
""" Abstract class for standard QM/MM embedding models.
To use any of this classes' subclasses, the MM models must support the ability to
calculate the internal energies and interaction energies between subsystems,
using the ``calculation_groups`` parameter.
"""
def __init__(self, *args, **kwargs):
super(QMMMEmbeddingBase, self).__init__(*args, **kwargs)
self.qmmol = None
self.mmmol = None
self.qm_atoms = None
self.qm_link_atoms = None
self._qm_index_set = None
# TODO: add `qm_atom_indices` to QMMMBase parameters
def calculate(self, requests):
self.prep()
self.mmmol.positions = self.mol.positions
self._set_qm_positions()
qmprops = self.qmmol.calculate(requests)
mmprops = self.mmmol.calculate(requests)
potential_energy = mmprops.potential_energy+qmprops.potential_energy
forces = mmprops.forces.copy()
for iatom, realatom in enumerate(self.qm_atoms):
forces[realatom.index] = qmprops.forces[iatom]
for atom in self.qm_link_atoms:
self._distribute_linkatom_forces(forces, atom)
properties = MolecularProperties(self.mol,
mmprops=mmprops,
qmprops=qmprops,
potential_energy=potential_energy,
forces=forces)
if 'wfn' in qmprops:
properties.wfn = qmprops.wfn
return properties
def prep(self):
if self._prepped:
return None
self.params.qm_atom_indices.sort()
self.qm_atoms = [self.mol.atoms[idx] for idx in self.params.qm_atom_indices]
self._qm_index_set = set(self.params.qm_atom_indices)
self.qmmol = self._setup_qm_subsystem()
self.mmmol = mdt.Molecule(self.mol,
name='%s MM subsystem' % self.mol.name)
self.mol.ff.copy_to(self.mmmol)
self._turn_off_qm_forcefield(self.mmmol.ff)
self.mmmol.set_energy_model(self.params.mm_model)
self._prepped = True
return True
def _setup_qm_subsystem(self):
raise NotImplemented("%s is an abstract class, use one of its subclasses"
% self.__class__.__name__)
def _turn_off_qm_forcefield(self, ff):
self._remove_internal_qm_bonds(ff.parmed_obj)
self._exclude_internal_qm_ljterms(ff.parmed_obj)
def _exclude_internal_qm_ljterms(self, pmdobj):
# Turn off QM/QM LJ interactions (must be done AFTER _remove_internal_qm_bonds)
numqm = len(self.params.qm_atom_indices)
for i in range(numqm):
for j in range(i+1, numqm):
pmdobj.atoms[i].exclude(pmdobj.atoms[j])
def _remove_internal_qm_bonds(self, pmdobj):
for i, iatom in enumerate(self.params.qm_atom_indices):
pmdatom = pmdobj.atoms[iatom]
allterms = ((pmdatom.bonds, 2), (pmdatom.angles, 3),
(pmdatom.dihedrals, 4), (pmdatom.impropers, 4))
for termlist, numatoms in allterms:
for term in termlist[:]: # make a copy so it doesn't change during iteration
if self._term_in_qm_system(term, numatoms):
term.delete()
@staticmethod
def _distribute_linkatom_forces(fullforces, linkatom):
""" Distribute forces according to the apparently indescribable and unciteable "lever rule"
"""
# TODO: CHECK THIS!!!!
mmatom = linkatom.metadata.mmatom
qmatom = linkatom.metadata.mmpartner
dfull = mmatom.distance(qmatom)
d_mm = linkatom.distance(mmatom)
p = (dfull - d_mm)/dfull
fullforces[qmatom.index] += p*linkatom.force
fullforces[mmatom.index] += (1.0-p) * linkatom.force
def _set_qm_positions(self):
for qmatom, realatom in zip(self.qmmol.atoms, self.qm_atoms):
qmatom.position = realatom.position
mdt.helpers.qmmm.set_link_atom_positions(self.qm_link_atoms)
def _term_in_qm_system(self, t, numatoms):
""" Check if an FF term is entirely within the QM subsystem """
for iatom in range(numatoms):
attrname = 'atom%i' % (iatom + 1)
if not getattr(t, attrname).idx in self._qm_index_set:
return True
else:
return False
@exports
class MechanicalEmbeddingQMMM(QMMMEmbeddingBase):
"""
Handles _non-covalent_ QM/MM with mechanical embedding.
No electrostatic interactions will be calculated between the QM and MM subsystems.
No covalent bonds are are allowed between the two susbystems.
"""
def prep(self):
if not super(MechanicalEmbeddingQMMM, self).prep():
return # was already prepped
# Set QM partial charges to 0
self.mmmol.energy_model._prepped = False
pmdobj = self.mmmol.ff.parmed_obj
for i, iatom in enumerate(self.params.qm_atom_indices):
pmdatom = pmdobj.atoms[iatom]
pmdatom.charge = 0.0
def _setup_qm_subsystem(self):
""" QM subsystem for mechanical embedding is the QM atoms + any link atoms
"""
qm_atoms = [self.mol.atoms[iatom] for iatom in self.params.qm_atom_indices]
self.qm_link_atoms = mdt.helpers.qmmm.create_link_atoms(self.mol, qm_atoms)
qmmol = mdt.Molecule(qm_atoms + self.qm_link_atoms,
name='%s QM subsystem' % self.mol.name)
for real_atom, qm_atom in zip(self.qm_atoms, qmmol.atoms):
qm_atom.metadata.real_atom = real_atom
qmmol.set_energy_model(self.params.qm_model)
return qmmol
@exports
class ElectrostaticEmbeddingQMMM(QMMMEmbeddingBase):
""" Handles _non-covalent_ QM/MM with electrostaic embedding.
No bonds allowed across the QM/MM boundaries.
To support this calculation type, the QM model must support the ability to denote
a subset of atoms as the "QM" atoms, using the ``qm_atom_indices`` parameter.
To support this calculation type, the QM model must support the ability to denote
a subset of atoms as the "QM" atoms, using the ``qm_atom_indices`` parameter.
The MM models must support the ability to turn of _internal_ interactions for
a certain subset of the system, using the ``no_internal_calculations`` parameter.
"""
def prep(self):
if not super(ElectrostaticEmbeddingQMMM, self).prep():
return # was already prepped
if not self.params.qm_model.supports_parameter('qm_atom_indices'):
raise TypeError('Supplied QM model ("%s") does not support QM/MM'
% self.params.qm_model.__name__)
def _setup_qm_subsystem(self):
qmmol = mdt.Molecule(self.mol)
self.mol.ff.copy_to(qmmol)
self.qm_link_atoms = mdt.helpers.qmmm.create_link_atoms(self.mol, self.qm_atoms)
if self.qm_link_atoms:
raise ValueError('The %s model does not support link atoms' % self.__class__.__name__)
qmmol.set_energy_model(self.params.qm_model)
qmmol.energy_model.params.qm_atom_indices = self.params.qm_atom_indices
return qmmol
| Python |
3D | Autodesk/molecular-design-toolkit | moldesign/models/__init__.py | .py | 172 | 8 | from .openmm import *
from .pyscf import *
from .models import *
from .toys import *
from .amber import *
from .openbabel import *
from .nwchem import *
from .qmmm import * | Python |
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