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How to use get_dtypes method in pandera
Best Python code snippet using pandera_python
simfile.py
Source:simfile.py 
...33 # Return output34 return out35####################################################################################################################################36# METHOD TO RETURN DATA TYPES37def get_dtypes():38 """39 Returns a dictionary of data types used40 """41 dtypes={'long' :np.int32,42 'float':np.float32,43 'char' :np.int8}#np.dtype((str,1))}44 return dtypes45####################################################################################################################################46# METHOD TO READ/WRITE FOFCAT FILE47def readgrpcat(fname,grptyp=None,**exkw):48 """49 Reads data from group catelogue files files50 """51 out={} ; dts=get_dtypes()52 grptyp=mmlpars.mml_pars(grptyp,list=['fof','sub'],default='fof')53 varlist=[dict(name='len' ,dim=1,dtype=dts['long']),54 dict(name='offset',dim=1,dtype=dts['long'])]55 if grptyp=='fof': varlist+=[dict(name='subs' ,dim=1,dtype=dts['long'])]56 elif grptyp=='sub': varlist+=[dict(name='parent',dim=1,dtype=dts['long'])]57 with open(fname,mode='rb') as file: 58 out['Ngrp']=np.fromfile(file,dtype=dts['long'],count=1)[0]59 if out['Ngrp']==0:60 for ivar in varlist: out[ivar['name']]=np.zeros((out['Ngrp']*ivar['dim']),dtype=ivar['dtype'])61 else:62 for ivar in varlist: out[ivar['name']]=np.fromfile(file,dtype=ivar['dtype'],count=out['Ngrp']*ivar['dim'])63 for ivar in varlist: 64 if ivar['dim']>1: out[ivar['name']]=out[ivar['name']].reshape((-1,ivar['dim']))65 return out66####################################################################################################################################67# METHOD TO READ GROUP PROPERTY FILES68def readgrpprop(fname,grptyp=None,**exkw):69 """70 Reads data from group property files71 """72 out={} ; dts=get_dtypes()73 grptyp=mmlpars.mml_pars(grptyp,list=['fof','sub'],default='fof')74 varlist=[dict(name='cm' ,dim=3,dtype=dts['float']),75 dict(name='cmv' ,dim=3,dtype=dts['float']),76 dict(name='mtot',dim=1,dtype=dts['float']),77 dict(name='mgas',dim=1,dtype=dts['float'])]78 with open(fname,mode='rb') as file: 79 out['Ngrp']=np.fromfile(file,dtype=dts['long'],count=1)[0]80 if out['Ngrp']==0:81 for ivar in varlist: out[ivar['name']]=np.zeros((out['Ngrp']*ivar['dim']),dtype=ivar['dtype'])82 else:83 for ivar in varlist: out[ivar['name']]=np.fromfile(file,dtype=ivar['dtype'],count=out['Ngrp']*ivar['dim'])84 for ivar in varlist: 85 if ivar['dim']>1: out[ivar['name']]=out[ivar['name']].reshape((-1,ivar['dim']))86 return out87####################################################################################################################################88# METHOD TO READ GROUP TYPE FILES89def readgrptype(fname,grptyp=None,**exkw):90 """91 Reads data from group type files92 """93 out={} ; dts=get_dtypes()94 grptyp=mmlpars.mml_pars(grptyp,list=['fof','sub'],default='fof')95 varlist=[dict(name='type',dim=1,dtype=dts['char'])]96 with open(fname,mode='rb') as file: 97 out['Npart']=np.fromfile(file,dtype=dts['long'],count=1)[0]98 if out['Npart']==0:99 for ivar in varlist: out[ivar['name']]=np.zeros((out['Npart']*ivar['dim']),dtype=ivar['dtype'])100 else:101 for ivar in varlist: out[ivar['name']]=np.fromfile(file,dtype=ivar['dtype'],count=out['Npart']*ivar['dim'])102 for ivar in varlist: 103 if ivar['dim']>1: out[ivar['name']]=out[ivar['name']].reshape((-1,ivar['dim']))104 return out105####################################################################################################################################106# METHOD TO READ GROUP PARTICLE ID FILES107def readgrpids(fname,grptyp=None,**exkw):108 """109 Reads data from group particle ID files110 """111 out={} ; dts=get_dtypes()112 grptyp=mmlpars.mml_pars(grptyp,list=['fof','sub'],default='fof')113 varlist=[dict(name='ids',dim=1,dtype=dts['long'])]114 with open(fname,mode='rb') as file: 115 out['Npart']=np.fromfile(file,dtype=dts['long'],count=1)[0]116 if out['Npart']==0:117 for ivar in varlist: out[ivar['name']]=np.zeros((out['Npart']*ivar['dim']),dtype=ivar['dtype'])118 else:119 for ivar in varlist: out[ivar['name']]=np.fromfile(file,dtype=ivar['dtype'],count=out['Npart']*ivar['dim'])120 for ivar in varlist: 121 if ivar['dim']>1: out[ivar['name']]=out[ivar['name']].reshape((-1,ivar['dim']))122 return out123####################################################################################################################################124# METHOD TO READ GROUP PARTICLE POSITION FILES125def readgrppos(fname,grptyp=None,**exkw):126 """127 Reads data from group particle position files128 """129 out={} ; dts=get_dtypes()130 grptyp=mmlpars.mml_pars(grptyp,list=['fof','sub'],default='fof')131 varlist=[dict(name='pos',dim=3,dtype=dts['float'])]132 with open(fname,mode='rb') as file: 133 out['Npart']=np.fromfile(file,dtype=dts['long'],count=1)[0]134 if out['Npart']==0:135 for ivar in varlist: out[ivar['name']]=np.zeros((out['Npart']*ivar['dim']),dtype=ivar['dtype'])136 else:137 for ivar in varlist: out[ivar['name']]=np.fromfile(file,dtype=ivar['dtype'],count=out['Npart']*ivar['dim'])138 for ivar in varlist: 139 if ivar['dim']>1: out[ivar['name']]=out[ivar['name']].reshape((-1,ivar['dim']))140 return out141####################################################################################################################################142# METHOD TO READ GROUP PARTICLE VELOCITY FILES143def readgrpvel(fname,grptyp=None,**exkw):144 """145 Reads data from group particle velocity files146 """147 out={} ; dts=get_dtypes()148 grptyp=mmlpars.mml_pars(grptyp,list=['fof','sub'],default='fof')149 varlist=[dict(name='vel',dim=3,dtype=dts['float'])]150 with open(fname,mode='rb') as file: 151 out['Npart']=np.fromfile(file,dtype=dts['long'],count=1)[0]152 if out['Npart']==0:153 for ivar in varlist: out[ivar['name']]=np.zeros((out['Npart']*ivar['dim']),dtype=ivar['dtype'])154 else:155 for ivar in varlist: out[ivar['name']]=np.fromfile(file,dtype=ivar['dtype'],count=out['Npart']*ivar['dim'])156 for ivar in varlist: 157 if ivar['dim']>1: out[ivar['name']]=out[ivar['name']].reshape((-1,ivar['dim']))158 return out159####################################################################################################################################160# METHOD TO READ/WRITE MTREE TABLES161def rwtable(rwid,fname,method=None,**exkw):...
app.py
Source:app.py
...110 # Segment.generate_manip_options()111 112 form = ManipulateForm()113 114 fields = Segments[session['id']].get_dtypes()115 if 'btn_manip_normalize' in request.form.keys():116 col = request.form['select-variable']117 Segments[session['id']].manip_num_normalize(col)118 fields = Segments[session['id']].get_dtypes()119 return render_template(120 'manipulate.html',121 variables=fields,122 manipulations=Segments[session['id']]._manipulations,123 html_table=create_html_output(Segments[session['id']].df, DIV_SIZE),124 dfshape=Segments[session['id']].df.shape,125 form=form126 )127 if 'btn_manip_trim' in request.form.keys():128 col = request.form['select-variable']129 lower = int(request.form['manip_trim_lower'])130 upper = int(request.form['manip_trim_upper'])131 Segments[session['id']].manip_num_trim(col, upper, lower)132 fields = Segments[session['id']].get_dtypes()133 return render_template(134 'manipulate.html',135 variables=fields,136 manipulations=Segments[session['id']]._manipulations,137 html_table=create_html_output(Segments[session['id']].df, DIV_SIZE),138 dfshape=Segments[session['id']].df.shape,139 form=form140 )141 if 'btn_manip_bin' in request.form.keys():142 d = request.form.to_dict()143 d = {144 re.sub('manip_bin_','',k): v 145 for k,v in d.items() if k.startswith('manip_bin')146 }147 Segments[session['id']].manip_cat_bins(request.form.get('select-variable'), d)148 fields = Segments[session['id']].get_dtypes()149 Segments[session['id']].generate_manip_options() # Regenerate the manip options as cats will have changed150 return render_template(151 'manipulate.html',152 variables=fields,153 manipulations=Segments[session['id']]._manipulations,154 html_table=create_html_output(Segments[session['id']].df, DIV_SIZE),155 dfshape=Segments[session['id']].df.shape,156 form=form157 )158 159 if 'btn_manip_datediff' in request.form.keys():160 col = request.form['select-variable']161 datediff = request.form['manip_datediff']162 Segments[session['id']].manip_dt_datediff(col, datediff)163 fields = Segments[session['id']].get_dtypes()164 return render_template(165 'manipulate.html',166 variables=fields,167 manipulations=Segments[session['id']]._manipulations,168 html_table=create_html_output(Segments[session['id']].df, DIV_SIZE),169 dfshape=Segments[session['id']].df.shape,170 form=form171 )172 173 if 'btn_manip_emb' in request.form.keys():174 col = request.form['select-variable']175 Segments[session['id']].manip_str_embeddings(col)176 fields = Segments[session['id']].get_dtypes()177 return render_template(178 'manipulate.html',179 variables=fields,180 manipulations=Segments[session['id']]._manipulations,181 html_table=create_html_output(Segments[session['id']].df, DIV_SIZE),182 dfshape=Segments[session['id']].df.shape,183 form=form184 )185 if 'btn_manipulate_to_visualise' in request.form.keys():186 return redirect('/visualise')187 return render_template(188 'manipulate.html',189 variables=fields,190 manipulations=Segments[session['id']]._manipulations,191 html_table=create_html_output(Segments[session['id']].df, DIV_SIZE),192 dfshape=Segments[session['id']].df.shape,193 form=form194 )195@app.route("/visualise", methods=["GET","POST"])196def visualise():197 form = ManipulateForm()198 if 'btn_viz_to_cluster' in request.form.keys():199 return redirect('/cluster')200 graphJSON = generate_graph(request.args, Segments[session['id']].df)201 return render_template(202 'visualise.html',203 graphJSON=graphJSON,204 dtypes=Segments[session['id']].get_dtypes(),205 dfshape=Segments[session['id']].df.shape,206 form=form207 )208@app.route("/callback", methods=["GET","POST"])209def cb():210 return generate_graph(request.args, Segments[session['id']].df)211@app.route("/cluster", methods=["GET","POST"])212def cluster():213 # Segment.df = pd.read_csv('/home/george/Development/Personal/Python/Segment/data/processed.csv')214 # Segment.edit_to_cat('Cat')215 # Segment.edit_to_datetime('FirstOrder')216 # Segment.edit_to_str('CustomerID')217 218 # Segment.manip_cat_bins('Cat',{'A':'A','B':'B','C':'C','D':'E'})219 # Segment.manip_dt_datediff('FirstOrder','2010-12-01')220 # Segment.manip_num_normalize('Num_Orders')221 # Segment.manip_num_trim('Num_Orders',15,0)222 # Segment.manip_str_embeddings('Description')223 # Segment.generate_manip_options()224 form = ClusterForm()225 if form.validate_on_submit():226 if 'btn_cluster_to_clusterviz' in request.form.keys():227 return redirect('/clusterviz')228 return render_template(229 'cluster.html',230 dtypes=Segments[session['id']].get_dtypes(),231 clustered=Segments[session['id']]._is_clustered,232 dfshape=Segments[session['id']].df.shape,233 html_table=create_html_output(Segments[session['id']].df, DIV_SIZE),234 form=form235 )236@app.route("/cluster-data", methods=["GET","POST","PUT"])237def cluster_data():238 data = request.get_json()239 tsne_comps = 3 if data['tsne'] else None240 Segments[session['id']]._cluster_fields = data['fields']241 Segments[session['id']].cluster(Segments[session['id']]._cluster_fields, n_components=tsne_comps)242 return "ok!"243@app.route("/clusterviz", methods=["GET","POST"])244def clusterviz():245 246 form = ManipulateForm()247 graphJSON = generate_graph(request.args, Segments[session['id']].df)248 return render_template(249 'cluster_viz.html',250 graphJSON=graphJSON,251 dtypes=Segments[session['id']].get_dtypes(),252 clustered=Segments[session['id']]._is_clustered,253 dfshape=Segments[session['id']].df.shape,254 form=form255 )256if __name__ == '__main__':...
load_data.py
Source:load_data.py
1import scipy.io2import numpy as np3def load_data(filename):4 arr = scipy.io.loadmat(filename)['data']5 dtypes = get_dtypes(arr)6 output = np.zeros([], dtype=dtypes)7 copy_values(arr, output)8 return output.view(np.recarray)9def get_dtypes(arr):10 names = arr.dtype.names11 dtypes = []12 shapes = []13 for name in names:14 sub_names = arr[name][0][0].dtype.names15 if sub_names:16 dtypes.append(get_dtypes(arr[name][0][0]))17 else:18 dtypes.append(arr[name][0][0].dtype)19 shapes.append(arr[name][0][0].squeeze().shape)20 return {'names': names, 'formats': zip(dtypes, shapes)}21def copy_values(copy_from, copy_to):22 names = copy_to.dtype.names23 for name in names:24 if isinstance(copy_to[name], (np.ndarray, np.record)) and copy_to[name].dtype.names:25 copy_values(copy_from[name][0][0], copy_to[name])26 else:27 copy_to[name] = copy_from[name][0][0].squeeze()28def test_load_data():29 data = load_data('/Volumes/rhino/data/eeg/scalp/ltp/ltpFR/behavioral/data/stat_data_LTP063.mat')30 from spc.view_recarray import pprint_rec as ppr...
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