def compute_col_pos(xz,xy,col_pos_end, col_pos_interval, col_pos_number):

    ##DESCRIPTION:
    ##returns rounded values of cumulative displacements

    ##INPUT:
    ##xz; dataframe; horizontal linear displacements along the planes defined by xa-za
    ##xy; dataframe; horizontal linear displacements along the planes defined by xa-ya
    ##col_pos_end; string; right bound for generating dates
    ##col_pos_interval; string ; interval between two adjacent column position dates
    ##col_pos_number; integer; number of column position dates to plot

    ##OUTPUT:
    ##np.round(cs_x,4), np.round(cs_xz,4), np.round(cs_xy,4)    
    
    #computing x from xz and xy
    x=pd.DataFrame(data=None,index=xz.index)
    num_nodes=len(xz.columns.tolist())
    for n in np.arange(1,1+num_nodes):
        x[n]=gf.x_from_xzxy(seg_len, xz.loc[:,n].values, xy.loc[:,n].values)

    #getting dates for column positions
    colposdates=pd.date_range(end=col_pos_end, freq=col_pos_interval,periods=col_pos_number, name='ts',closed=None)

    #reversing column order
    revcols=xz.columns.tolist()[::-1]
    xz=xz[revcols]
    xy=xy[revcols]
    x=x[revcols]

    #getting cumulative displacements
    cs_x=pd.DataFrame()
    cs_xz=pd.DataFrame()
    cs_xy=pd.DataFrame()
    for i in colposdates:
        cs_x=cs_x.append(x[(x.index==i)].cumsum(axis=1),ignore_index=True)
        cs_xz=cs_xz.append(xz[(xz.index==i)].cumsum(axis=1),ignore_index=True)
        cs_xy=cs_xy.append(xy[(xy.index==i)].cumsum(axis=1),ignore_index=True)
    cs_x=cs_x.set_index(colposdates)
    cs_xz=cs_xz.set_index(colposdates)
    cs_xy=cs_xy.set_index(colposdates)

    
    #returning to original column order
    cols=cs_x.columns.tolist()[::-1]
    cs_xz=cs_xz[cols]
    cs_xy=cs_xy[cols]
    cs_x=cs_x[cols]

    #appending 0 values to bottom of column (last node)
    cs_x[num_nodes+1]=0  
    cs_xz[num_nodes+1]=0
    cs_xy[num_nodes+1]=0

    
    return np.round(cs_x,4), np.round(cs_xz,4), np.round(cs_xy,4)
Exemple #2
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def compute_col_pos(xz,xy,col_pos_end, col_pos_interval, col_pos_number):

    ##DESCRIPTION:
    ##returns rounded values of cumulative displacements

    ##INPUT:
    ##xz; dataframe; horizontal linear displacements along the planes defined by xa-za
    ##xy; dataframe; horizontal linear displacements along the planes defined by xa-ya
    ##col_pos_end; string; right bound for generating dates
    ##col_pos_interval; string ; interval between two adjacent column position dates
    ##col_pos_number; integer; number of column position dates to plot

    ##OUTPUT:
    ##np.round(cs_x,4), np.round(cs_xz,4), np.round(cs_xy,4)    
    
    #computing x from xz and xy
    x=pd.DataFrame(data=None,index=xz.index)
    num_nodes=len(xz.columns.tolist())
    for n in np.arange(1,1+num_nodes):
        x[n]=gf.x_from_xzxy(seg_len, xz.loc[:,n].values, xy.loc[:,n].values)

    #getting dates for column positions
    colposdates=pd.date_range(end=col_pos_end, freq=col_pos_interval,periods=col_pos_number, name='ts',closed=None)

    #reversing column order
    revcols=xz.columns.tolist()[::-1]
    xz=xz[revcols]
    xy=xy[revcols]
    x=x[revcols]

    #getting cumulative displacements
    cs_x=pd.DataFrame()
    cs_xz=pd.DataFrame()
    cs_xy=pd.DataFrame()
    for i in colposdates:
        cs_x=cs_x.append(x[(x.index==i)].cumsum(axis=1),ignore_index=True)
        cs_xz=cs_xz.append(xz[(xz.index==i)].cumsum(axis=1),ignore_index=True)
        cs_xy=cs_xy.append(xy[(xy.index==i)].cumsum(axis=1),ignore_index=True)
    cs_x=cs_x.set_index(colposdates)
    cs_xz=cs_xz.set_index(colposdates)
    cs_xy=cs_xy.set_index(colposdates)

    
    #returning to original column order
    cols=cs_x.columns.tolist()[::-1]
    cs_xz=cs_xz[cols]
    cs_xy=cs_xy[cols]
    cs_x=cs_x[cols]

    #appending 0 values to bottom of column (last node)
    cs_x[num_nodes+1]=0  
    cs_xz[num_nodes+1]=0
    cs_xy[num_nodes+1]=0

    
    return np.round(cs_x,4), np.round(cs_xz,4), np.round(cs_xy,4)
def compute_col_pos(xz, xy, col_pos_end, col_pos_interval, col_pos_number,
                    seg_len):

    #computing x from xz and xy
    x = pd.DataFrame(data=None, index=xz.index)
    num_nodes = len(xz.columns.tolist())
    for n in np.arange(1, 1 + num_nodes):
        x[n] = gf.x_from_xzxy(seg_len, xz.loc[:, n].values, xy.loc[:,
                                                                   n].values)

    #getting dates for column positions
    colposdates = pd.date_range(end=col_pos_end,
                                freq=col_pos_interval,
                                periods=col_pos_number,
                                name='ts',
                                closed=None)

    #reversing column order
    revcols = xz.columns.tolist()[::-1]
    xz = xz[revcols]
    xy = xy[revcols]
    x = x[revcols]

    #getting cumulative displacements
    cs_x = pd.DataFrame()
    cs_xz = pd.DataFrame()
    cs_xy = pd.DataFrame()
    for i in colposdates:
        cs_x = cs_x.append(x[(x.index == i)].cumsum(axis=1), ignore_index=True)
        cs_xz = cs_xz.append(xz[(xz.index == i)].cumsum(axis=1),
                             ignore_index=True)
        cs_xy = cs_xy.append(xy[(xy.index == i)].cumsum(axis=1),
                             ignore_index=True)
    cs_x = cs_x.set_index(colposdates)
    cs_xz = cs_xz.set_index(colposdates)
    cs_xy = cs_xy.set_index(colposdates)

    #returning to original column order
    cols = cs_x.columns.tolist()[::-1]
    cs_xz = cs_xz[cols]
    cs_xy = cs_xy[cols]
    cs_x = cs_x[cols]

    #appending 0 values to bottom of column (last node)
    cs_x[num_nodes + 1] = 0
    cs_xz[num_nodes + 1] = 0
    cs_xy[num_nodes + 1] = 0

    return np.round(cs_x, 4), np.round(cs_xz, 4), np.round(cs_xy, 4)