From e1125ec4a0f1f3cd24ccaec69566c4f8f2a42554 Mon Sep 17 00:00:00 2001 From: Daniel Wolfensberger Date: Wed, 9 Dec 2020 14:32:43 +0100 Subject: [PATCH] changed version to 0.5 --- .../source/conf.py | 4 +- .../library_reference_users/source/conf.py | 4 +- doc/pyart-mch_library_reference_dev.pdf | Bin 1120835 -> 1158097 bytes doc/pyart-mch_library_reference_users.pdf | Bin 887257 -> 891565 bytes .../source/conf.py | 4 +- .../library_reference_users/source/conf.py | 4 +- doc/pyrad_library_reference_dev.pdf | Bin 614419 -> 645770 bytes doc/pyrad_library_reference_users.pdf | Bin 459592 -> 483219 bytes doc/pyrad_user_manual.docx | Bin 248408 -> 253775 bytes doc/pyrad_user_manual.pdf | Bin 1055708 -> 1055538 bytes docs/_modules/index.html | 6 +- docs/_modules/pyrad/flow/flow_control.html | 6 +- docs/_modules/pyrad/graph/plots.html | 6 +- docs/_modules/pyrad/graph/plots_aux.html | 6 +- docs/_modules/pyrad/graph/plots_grid.html | 149 ++++--- docs/_modules/pyrad/graph/plots_spectra.html | 13 +- .../pyrad/graph/plots_timeseries.html | 6 +- docs/_modules/pyrad/graph/plots_vol.html | 6 +- docs/_modules/pyrad/io/config.html | 6 +- docs/_modules/pyrad/io/io_aux.html | 91 +++- docs/_modules/pyrad/io/read_data_cosmo.html | 12 +- docs/_modules/pyrad/io/read_data_dem.html | 6 +- docs/_modules/pyrad/io/read_data_hzt.html | 6 +- docs/_modules/pyrad/io/read_data_other.html | 6 +- docs/_modules/pyrad/io/read_data_radar.html | 148 ++++++- docs/_modules/pyrad/io/read_data_sensor.html | 24 +- docs/_modules/pyrad/io/read_data_sun.html | 6 +- docs/_modules/pyrad/io/timeseries.html | 6 +- docs/_modules/pyrad/io/trajectory.html | 6 +- docs/_modules/pyrad/io/write_data.html | 118 ++++- docs/_modules/pyrad/proc/process_Doppler.html | 135 +++++- docs/_modules/pyrad/proc/process_aux.html | 171 +++++--- docs/_modules/pyrad/proc/process_calib.html | 22 +- docs/_modules/pyrad/proc/process_cosmo.html | 44 +- docs/_modules/pyrad/proc/process_dem.html | 8 +- .../pyrad/proc/process_echoclass.html | 21 +- docs/_modules/pyrad/proc/process_grid.html | 388 +++++++++++++++- .../pyrad/proc/process_intercomp.html | 12 +- docs/_modules/pyrad/proc/process_iq.html | 6 +- .../pyrad/proc/process_monitoring.html | 6 +- docs/_modules/pyrad/proc/process_phase.html | 11 +- .../_modules/pyrad/proc/process_retrieve.html | 16 +- docs/_modules/pyrad/proc/process_spectra.html | 111 +++-- .../pyrad/proc/process_timeseries.html | 61 ++- docs/_modules/pyrad/proc/process_traj.html | 73 +++- .../pyrad/prod/process_grid_products.html | 180 +++++++- .../prod/process_intercomp_products.html | 6 +- .../prod/process_monitoring_products.html | 6 +- docs/_modules/pyrad/prod/process_product.html | 6 +- .../pyrad/prod/process_spectra_products.html | 13 +- .../prod/process_timeseries_products.html | 156 ++++--- .../pyrad/prod/process_traj_products.html | 6 +- .../pyrad/prod/process_vol_products.html | 6 +- docs/_modules/pyrad/prod/product_aux.html | 6 +- docs/_modules/pyrad/util/radar_utils.html | 42 +- docs/_modules/pyrad/util/stat_utils.html | 6 +- docs/_static/documentation_options.js | 2 +- docs/flow.html | 6 +- docs/genindex.html | 24 +- docs/graph.html | 26 +- docs/index.html | 6 +- docs/io.html | 205 +++++---- docs/objects.inv | Bin 2980 -> 3028 bytes docs/proc.html | 413 ++++++++++++++++-- docs/prod.html | 79 +++- docs/py-modindex.html | 6 +- docs/search.html | 6 +- docs/searchindex.js | 2 +- docs/util.html | 11 +- src/pyrad_proc/setup.py | 6 +- 70 files changed, 2329 insertions(+), 630 deletions(-) diff --git a/doc/pyart-mch/library_reference_developers/source/conf.py b/doc/pyart-mch/library_reference_developers/source/conf.py index 31fcaf4..dfa383f 100644 --- a/doc/pyart-mch/library_reference_developers/source/conf.py +++ b/doc/pyart-mch/library_reference_developers/source/conf.py @@ -72,9 +72,9 @@ # built documents. # # The short X.Y version. -version = '0.4' +version = '0.5' # The full version, including alpha/beta/rc tags. -release = '0.4.1' +release = '0.5.0' # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. diff --git a/doc/pyart-mch/library_reference_users/source/conf.py b/doc/pyart-mch/library_reference_users/source/conf.py index 9bdefc6..8167be9 100755 --- a/doc/pyart-mch/library_reference_users/source/conf.py +++ b/doc/pyart-mch/library_reference_users/source/conf.py @@ -72,9 +72,9 @@ # built documents. # # The short X.Y version. -version = u'0.4' +version = u'0.5' # The full version, including alpha/beta/rc tags. -release = u'0.4.1' +release = u'0.5.0' # The language for content autogenerated by Sphinx. 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  1. modules |
  2. - + diff --git a/docs/_modules/pyrad/graph/plots.html b/docs/_modules/pyrad/graph/plots.html index ae50b77..477e7eb 100644 --- a/docs/_modules/pyrad/graph/plots.html +++ b/docs/_modules/pyrad/graph/plots.html @@ -6,7 +6,7 @@ - pyrad.graph.plots — pyrad 0.4.4 documentation + pyrad.graph.plots — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

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  4. - + @@ -1575,7 +1575,7 @@

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  6. - + diff --git a/docs/_modules/pyrad/graph/plots_aux.html b/docs/_modules/pyrad/graph/plots_aux.html index b2d5346..ad766ad 100644 --- a/docs/_modules/pyrad/graph/plots_aux.html +++ b/docs/_modules/pyrad/graph/plots_aux.html @@ -6,7 +6,7 @@ - pyrad.graph.plots_aux — pyrad 0.4.4 documentation + pyrad.graph.plots_aux — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

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  8. - + @@ -378,7 +378,7 @@

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  10. - + diff --git a/docs/_modules/pyrad/graph/plots_grid.html b/docs/_modules/pyrad/graph/plots_grid.html index da521ac..3711ab4 100644 --- a/docs/_modules/pyrad/graph/plots_grid.html +++ b/docs/_modules/pyrad/graph/plots_grid.html @@ -6,7 +6,7 @@ - pyrad.graph.plots_grid — pyrad 0.4.4 documentation + pyrad.graph.plots_grid — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

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  11. modules |
  12. - + @@ -95,7 +95,8 @@

    Source code for pyrad.graph.plots_grid

     
     
     
    [docs]def plot_surface(grid, field_name, level, prdcfg, fname_list, titl=None, - save_fig=True, use_basemap=False): + alpha=None, ax=None, fig=None, display=None, save_fig=True, + use_basemap=False): """ plots a surface from gridded data @@ -113,6 +114,15 @@

    Source code for pyrad.graph.plots_grid

             list of names of the files where to store the plot
         titl : str
             Plot title
    +    alpha : float or None
    +        Set the alpha transparency of the grid plot. Useful for
    +        overplotting radar over other datasets.
    +    ax : Axis
    +        Axis to plot on. if fig is None a new axis will be created
    +    fig : Figure
    +        Figure to add the colorbar to. If none a new figure will be created
    +    display : GridMapDisplay object
    +        The display used
         save_fig : bool
             if true save the figure. If false it does not close the plot and
             returns the handle to the figure
    @@ -125,6 +135,8 @@ 

    Source code for pyrad.graph.plots_grid

     
         """
         dpi = prdcfg['gridMapImageConfig'].get('dpi', 72)
    +    vmin = prdcfg.get('vmin', None)
    +    vmax = prdcfg.get('vmax', None)
     
         norm, ticks, ticklabs = get_norm(field_name)
     
    @@ -140,50 +152,69 @@ 

    Source code for pyrad.graph.plots_grid

         lon_lines = np.arange(np.floor(min_lon), np.ceil(max_lon)+1, lonstep)
         lat_lines = np.arange(np.floor(min_lat), np.ceil(max_lat)+1, latstep)
     
    -    fig = plt.figure(figsize=[xsize, ysize], dpi=dpi)
    -    ax = fig.add_subplot(111)
    -
    -    if use_basemap:
    -        resolution = prdcfg['gridMapImageConfig'].get('mapres', 'l')
    -        if resolution not in ('c', 'l', 'i', 'h', 'f'):
    -            warn('Unknown map resolution: '+resolution)
    -            resolution = 'l'
    -
    -        if resolution == 'c':
    -            area_thresh = 10000
    -        elif resolution == 'l':
    -            area_thresh = 1000
    -        elif resolution == 'i':
    -            area_thresh = 100
    -        elif resolution == 'h':
    -            area_thresh = 10
    -        elif resolution == 'f':
    -            area_thresh = 1
    -
    -        display = pyart.graph.GridMapDisplayBasemap(grid)
    -        display.plot_basemap(
    -            lat_lines=lat_lines, lon_lines=lon_lines, resolution=resolution,
    -            area_thresh=area_thresh, auto_range=False, min_lon=min_lon,
    -            max_lon=max_lon, min_lat=min_lat, max_lat=max_lat, ax=ax)
    -        display.plot_grid(
    -            field_name, level=level, norm=norm, ticks=ticks, title=titl,
    -            ticklabs=ticklabs, ax=ax, fig=fig)
    +    if fig is None:
    +
    +
    +        fig = plt.figure(figsize=[xsize, ysize], dpi=dpi)
    +        ax = fig.add_subplot(111)
    +
    +        if use_basemap:
    +            resolution = prdcfg['gridMapImageConfig'].get('mapres', 'l')
    +            if resolution not in ('c', 'l', 'i', 'h', 'f'):
    +                warn('Unknown map resolution: '+resolution)
    +                resolution = 'l'
    +
    +            if resolution == 'c':
    +                area_thresh = 10000
    +            elif resolution == 'l':
    +                area_thresh = 1000
    +            elif resolution == 'i':
    +                area_thresh = 100
    +            elif resolution == 'h':
    +                area_thresh = 10
    +            elif resolution == 'f':
    +                area_thresh = 1
    +
    +            display = pyart.graph.GridMapDisplayBasemap(grid)
    +            display.plot_basemap(
    +                lat_lines=lat_lines, lon_lines=lon_lines,
    +                resolution=resolution, area_thresh=area_thresh,
    +                auto_range=False, min_lon=min_lon, max_lon=max_lon,
    +                min_lat=min_lat, max_lat=max_lat, ax=ax)
    +            display.plot_grid(
    +                field_name, level=level, norm=norm, ticks=ticks, title=titl,
    +                ticklabs=ticklabs, vmin=vmin, vmax=vmax, alpha=alpha, ax=ax,
    +                fig=fig)
    +        else:
    +            resolution = prdcfg['gridMapImageConfig'].get('mapres', '110m')
    +            if resolution not in ('110m', '50m', '10m'):
    +                warn('Unknown map resolution: '+resolution)
    +                resolution = '110m'
    +            background_zoom = prdcfg['gridMapImageConfig'].get(
    +                'background_zoom', 8)
    +
    +            display = pyart.graph.GridMapDisplay(grid)
    +            fig, ax = display.plot_grid(
    +                field_name, level=level, norm=norm, ticks=ticks,
    +                ticklabs=ticklabs, resolution=resolution,
    +                background_zoom=background_zoom, lat_lines=lat_lines,
    +                lon_lines=lon_lines,
    +                maps_list=prdcfg['gridMapImageConfig']['maps'],
    +                vmin=vmin, vmax=vmax, alpha=alpha, title=titl, ax=ax, fig=fig)
    +            # display.plot_crosshairs(lon=lon, lat=lat)
         else:
    -        resolution = prdcfg['gridMapImageConfig'].get('mapres', '110m')
    -        if resolution not in ('110m', '50m', '10m'):
    -            warn('Unknown map resolution: '+resolution)
    -            resolution = '110m'
    -        background_zoom = prdcfg['gridMapImageConfig'].get(
    -            'background_zoom', 8)
    -
    -        display = pyart.graph.GridMapDisplay(grid)
    -        fig, ax = display.plot_grid(
    -            field_name, level=level, norm=norm, ticks=ticks, ticklabs=ticklabs,
    -            resolution=resolution, background_zoom=background_zoom,
    -            lat_lines=lat_lines, lon_lines=lon_lines,
    -            maps_list=prdcfg['gridMapImageConfig']['maps'],
    -            title=titl, ax=ax, fig=fig)
    -        # display.plot_crosshairs(lon=lon, lat=lat)
    +        if use_basemap:
    +            display.plot_grid(
    +                field_name, level=level, norm=norm, ticks=ticks,
    +                lat_lines=lat_lines, lon_lines=lon_lines, title=titl,
    +                ticklabs=ticklabs, colorbar_flag=False, vmin=vmin, vmax=vmax,
    +                alpha=alpha, ax=ax, fig=fig)
    +        else:
    +            fig, ax = display.plot_grid(
    +                field_name, level=level, norm=norm, ticks=ticks,
    +                lat_lines=lat_lines, lon_lines=lon_lines, ticklabs=ticklabs,
    +                colorbar_flag=False, embelish=False, vmin=vmin, vmax=vmax,
    +                alpha=alpha, title=titl, ax=ax, fig=fig)
     
         if save_fig:
             for fname in fname_list:
    @@ -196,11 +227,11 @@ 

    Source code for pyrad.graph.plots_grid

     
     
     def plot_surface_contour(grid, field_name, level, prdcfg, fname_list,
    -                         contour_values=None, linewidths=1.5, ax=None,
    -                         fig=None, display=None, save_fig=True,
    +                         contour_values=None, linewidths=1.5, colors='k',
    +                         ax=None, fig=None, display=None, save_fig=True,
                              use_basemap=False):
         """
    -    plots a surface from gridded data
    +    plots a contour plot from gridded data
     
         Parameters
         ----------
    @@ -218,13 +249,19 @@ 

    Source code for pyrad.graph.plots_grid

             list of contours to plot
         linewidths : float
             width of the contour lines
    -    fig : Figure
    -        Figure to add the colorbar to. If none a new figure will be created
    +    colors : color string or sequence of colors
    +        The contour colours
         ax : Axis
             Axis to plot on. if fig is None a new axis will be created
    +    fig : Figure
    +        Figure to add the colorbar to. If none a new figure will be created
    +    display : GridMapDisplay object
    +        The display used
         save_fig : bool
             if true save the figure if false it does not close the plot and
             returns the handle to the figure
    +    use_basemap : Bool
    +        If true uses basemap, otherwise uses cartopy.
     
         Returns
         -------
    @@ -293,7 +330,7 @@ 

    Source code for pyrad.graph.plots_grid

     
                 basemap = display.get_basemap()
                 basemap.contour(
    -                lons, lats, data, contour_values, colors='k',
    +                lons, lats, data, contour_values, colors=colors,
                     linewidths=linewidths, latlon=True)
                 ax.set_title(display.generate_grid_title(field_name, level))
             else:
    @@ -308,7 +345,7 @@ 

    Source code for pyrad.graph.plots_grid

                 fig, ax = display.plot_grid_contour(
                     field_name, level=level, ax=ax, fig=fig, lat_lines=lat_lines,
                     lon_lines=lon_lines, contour_values=contour_values,
    -                linewidths=linewidths, resolution=resolution,
    +                linewidths=linewidths, colors=colors, resolution=resolution,
                     background_zoom=background_zoom,
                     maps_list=prdcfg['gridMapImageConfig']['maps'])
         else:
    @@ -318,14 +355,14 @@ 

    Source code for pyrad.graph.plots_grid

     
                 basemap = display.get_basemap()
                 basemap.contour(
    -                lons, lats, data, contour_values, colors='k',
    +                lons, lats, data, contour_values, colors=colors,
                     linewidths=linewidths, latlon=True)
             else:
                 lons, lats = grid.get_point_longitude_latitude(edges=False)
                 data = grid.fields[field_name]['data'][level, :, :]
     
                 ax.contour(
    -                lons, lats, data, contour_values, colors='k',
    +                lons, lats, data, contour_values, colors=colors,
                     linewidths=linewidths, transform=cartopy.crs.PlateCarree())
     
         if save_fig:
    @@ -503,7 +540,7 @@ 

    Navigation

  13. modules |
  14. - +
    diff --git a/docs/_modules/pyrad/graph/plots_spectra.html b/docs/_modules/pyrad/graph/plots_spectra.html index 0636203..6c5c411 100644 --- a/docs/_modules/pyrad/graph/plots_spectra.html +++ b/docs/_modules/pyrad/graph/plots_spectra.html @@ -6,7 +6,7 @@ - pyrad.graph.plots_spectra — pyrad 0.4.4 documentation + pyrad.graph.plots_spectra — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  15. modules |
  16. - +
    @@ -353,7 +353,8 @@

    Source code for pyrad.graph.plots_spectra

     
     
    [docs]def plot_time_Doppler(spectra, field_name, prdcfg, fname_list, xaxis_info='Doppler_velocity', yaxis_pos='start', - titl=None, clabel=None, vmin=None, vmax=None): + titl=None, clabel=None, vmin=None, vmax=None, xmin=None, + xmax=None, ymin=None, ymax=None): """ Makes a time-Doppler plot @@ -379,6 +380,8 @@

    Source code for pyrad.graph.plots_spectra

             The color bar label
         vmin, vmax : float or None
             The value limits
    +    xmin, xmax, ymin, ymax : float or None
    +        The axis limits
     
         Returns
         -------
    @@ -449,6 +452,8 @@ 

    Source code for pyrad.graph.plots_spectra

         ax.set_xlabel(xlabel)
         ax.set_ylabel(ylabel)
         ax.set_title(titl)
    +    ax.set_xlim(xmin, xmax)
    +    ax.set_ylim(ymin, ymax)
     
         cb = fig.colorbar(cax)
         if ticks is not None:
    @@ -1748,7 +1753,7 @@ 

    Navigation

  17. modules |
  18. - +
    diff --git a/docs/_modules/pyrad/graph/plots_timeseries.html b/docs/_modules/pyrad/graph/plots_timeseries.html index b1ef908..e2ef5f2 100644 --- a/docs/_modules/pyrad/graph/plots_timeseries.html +++ b/docs/_modules/pyrad/graph/plots_timeseries.html @@ -6,7 +6,7 @@ - pyrad.graph.plots_timeseries — pyrad 0.4.4 documentation + pyrad.graph.plots_timeseries — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  19. modules |
  20. - +
    @@ -834,7 +834,7 @@

    Navigation

  21. modules |
  22. - +
    diff --git a/docs/_modules/pyrad/graph/plots_vol.html b/docs/_modules/pyrad/graph/plots_vol.html index 6e83f26..9d379a9 100644 --- a/docs/_modules/pyrad/graph/plots_vol.html +++ b/docs/_modules/pyrad/graph/plots_vol.html @@ -6,7 +6,7 @@ - pyrad.graph.plots_vol — pyrad 0.4.4 documentation + pyrad.graph.plots_vol — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  23. modules |
  24. - +
    @@ -1781,7 +1781,7 @@

    Navigation

  25. modules |
  26. - +
    diff --git a/docs/_modules/pyrad/io/config.html b/docs/_modules/pyrad/io/config.html index 77aacd0..056faa1 100644 --- a/docs/_modules/pyrad/io/config.html +++ b/docs/_modules/pyrad/io/config.html @@ -6,7 +6,7 @@ - pyrad.io.config — pyrad 0.4.4 documentation + pyrad.io.config — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  27. modules |
  28. - +
    @@ -464,7 +464,7 @@

    Navigation

  29. modules |
  30. - +
    diff --git a/docs/_modules/pyrad/io/io_aux.html b/docs/_modules/pyrad/io/io_aux.html index d32bb22..0c02ccd 100644 --- a/docs/_modules/pyrad/io/io_aux.html +++ b/docs/_modules/pyrad/io/io_aux.html @@ -6,7 +6,7 @@ - pyrad.io.io_aux — pyrad 0.4.4 documentation + pyrad.io.io_aux — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  31. modules |
  32. - +
    @@ -1367,6 +1367,10 @@

    Source code for pyrad.io.io_aux

             field_name = 'sum_squared'
         elif datatype == 'diff':
             field_name = 'fields_difference'
    +    elif datatype == 'mask':
    +        field_name = 'field_mask'
    +    elif datatype == 'texture':
    +        field_name = 'field_texture'
     
         # spectral data
         elif datatype == 'ShhADU':
    @@ -1727,6 +1731,45 @@ 

    Source code for pyrad.io.io_aux

         elif datatype == 'CNR':
             field_name = 'cnr'
     
    +    # satellite names
    +    elif datatype == 'HRV':
    +        field_name = 'HRV'
    +    elif datatype == 'VIS006':
    +        field_name = 'VIS006'
    +    elif datatype == 'VIS008':
    +        field_name = 'VIS008'
    +    elif datatype == 'IR_016':
    +        field_name = 'IR_016'
    +
    +    elif datatype == 'IR_039':
    +        field_name = 'IR_039'
    +    elif datatype == 'WV_062':
    +        field_name = 'WV_062'
    +    elif datatype == 'WV_073':
    +        field_name = 'WV_073'
    +    elif datatype == 'IR_087':
    +        field_name = 'IR_087'
    +    elif datatype == 'IR_097':
    +        field_name = 'IR_097'
    +    elif datatype == 'IR_108':
    +        field_name = 'IR_108'
    +    elif datatype == 'IR_120':
    +        field_name = 'IR_120'
    +    elif datatype == 'IR_134':
    +        field_name = 'IR_134'
    +
    +    elif datatype == 'CTH':
    +        field_name = 'CTH'
    +
    +    elif datatype == 'HRV_norm':
    +        field_name = 'HRV_norm'
    +    elif datatype == 'VIS006_norm':
    +        field_name = 'VIS006_norm'
    +    elif datatype == 'VIS008_norm':
    +        field_name = 'VIS008_norm'
    +    elif datatype == 'IR_016_norm':
    +        field_name = 'IR_016_norm'
    +
         # cloud radar names
         elif datatype == 'SNR':
             field_name = 'SNR'
    @@ -1930,6 +1973,25 @@ 

    Source code for pyrad.io.io_aux

         elif datatype == 'quant95Vc':
             field_name = 'quant95_corrected_velocity'
     
    +    elif datatype == 'avgdealV':
    +        field_name = 'avg_dealiased_velocity'
    +    elif datatype == 'NdealV':
    +        field_name = 'npoints_dealiased_velocity'
    +    elif datatype == 'quant05dealV':
    +        field_name = 'quant05_dealiased_velocity'
    +    elif datatype == 'quant10dealV':
    +        field_name = 'quant10_dealiased_velocity'
    +    elif datatype == 'quant20dealV':
    +        field_name = 'quant20_dealiased_velocity'
    +    elif datatype == 'quant50dealV':
    +        field_name = 'quant50_dealiased_velocity'
    +    elif datatype == 'quant80dealV':
    +        field_name = 'quant80_dealiased_velocity'
    +    elif datatype == 'quant90dealV':
    +        field_name = 'quant90_dealiased_velocity'
    +    elif datatype == 'quant95dealV':
    +        field_name = 'quant95_dealiased_velocity'
    +
         else:
             raise ValueError('ERROR: Unknown data type '+datatype)
     
    @@ -2036,7 +2098,7 @@ 

    Source code for pyrad.io.io_aux

                     dayfilelist = glob.glob(datapath+basename+'*.'+scan+'*')
                     for filename in dayfilelist:
                         t_filelist.append(filename)
    -            elif datagroup in('RAD4ALPGRID', 'RAD4ALPGIF', 'RAD4ALPBIN'):
    +            elif datagroup in ('RAD4ALPGRID', 'RAD4ALPGIF', 'RAD4ALPBIN'):
                     acronym, termination = get_rad4alp_prod_fname(datatype)
                     dir_day = starttime+datetime.timedelta(days=i)
                     dayinfo = dir_day.strftime('%y%j')
    @@ -2053,6 +2115,20 @@ 

    Source code for pyrad.io.io_aux

                     dayfilelist = glob.glob(datapath+basename+'*'+termination)
                     for filename in dayfilelist:
                         t_filelist.append(filename)
    +            elif datagroup == 'SATGRID':
    +                daydir = (
    +                    starttime +
    +                    datetime.timedelta(days=i)).strftime('%Y/%m/%d/')
    +                dayinfo = (starttime+datetime.timedelta(days=i)).strftime(
    +                    '%Y%m%d')
    +                datapath = cfg['satpath'][ind_rad] + daydir
    +                if not os.path.isdir(datapath):
    +                    # warn("WARNING: Unknown datapath '%s'" % datapath)
    +                    continue
    +                dayfilelist = glob.glob(
    +                    datapath+'MSG?_ccs4_'+dayinfo+'*_rad_PLAX.nc')
    +                for filename in dayfilelist:
    +                    t_filelist.append(filename)
     
                 elif datagroup in ('ODIM', 'CFRADIAL2', 'CF1', 'NEXRADII'):
                     if scan is None:
    @@ -2735,7 +2811,7 @@ 

    Source code for pyrad.io.io_aux

     
             daydir = runtime.strftime('%Y-%m-%d')
             datapath = cfg['cosmopath'][ind_rad]+datatype+'/raw/'+daydir+'/'
    -        for model in ('cosmo-1', 'cosmo-2', 'cosmo-7'):
    +        for model in ('cosmo-1e', 'cosmo-1', 'cosmo-2', 'cosmo-7'):
                 if datatype == 'TEMP':
                     search_name = (datapath+model+'_MDR_3D_'+runtimestr+'.nc')
                 elif datatype == 'WIND':
    @@ -2762,7 +2838,7 @@ 

    Source code for pyrad.io.io_aux

     
             daydir = runtime.strftime('%Y-%m-%d')
             datapath = cfg['cosmopath'][ind_rad]+datatype+'/raw1/'+daydir+'/'
    -        for model in ('cosmo-1', 'cosmo-2', 'cosmo-7'):
    +        for model in ('cosmo-1e', 'cosmo-1', 'cosmo-2', 'cosmo-7'):
                 if datatype == 'TEMP':
                     search_name = (datapath+model+'_MDR_3D_'+runtimestr+'.nc')
                 elif datatype == 'WIND':
    @@ -2944,6 +3020,9 @@ 

    Source code for pyrad.io.io_aux

         elif datagroup == 'COSMORAW':
             datetimestr = bfile[-13:-3]
             fdatetime = datetime.datetime.strptime(datetimestr, '%Y%m%d%H')
    +    elif datagroup == 'SATGRID':
    +        datetimestr = bfile[10:22]
    +        fdatetime = datetime.datetime.strptime(datetimestr, '%Y%m%d%H%M')
         else:
             warn('unknown data group')
             return None
    @@ -3005,7 +3084,7 @@ 

    Navigation

  33. modules |
  34. - +
    diff --git a/docs/_modules/pyrad/io/read_data_cosmo.html b/docs/_modules/pyrad/io/read_data_cosmo.html index cec8126..5767525 100644 --- a/docs/_modules/pyrad/io/read_data_cosmo.html +++ b/docs/_modules/pyrad/io/read_data_cosmo.html @@ -6,7 +6,7 @@ - pyrad.io.read_data_cosmo — pyrad 0.4.4 documentation + pyrad.io.read_data_cosmo — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  35. modules |
  36. - +
    @@ -287,6 +287,7 @@

    Source code for pyrad.io.read_data_cosmo

     
         return cosmo_fields
    + # @profile
    [docs]def read_cosmo_data(fname, field_names=['temperature'], celsius=True): """ @@ -324,6 +325,11 @@

    Source code for pyrad.io.read_data_cosmo

                 warn(field+' data not present in COSMO file '+fname)
             else:
                 var_data = _ncvar_to_dict(ncvars[cosmo_name], dtype='float16')
    +
    +            # remove dimension ensemble member of cosmo-1e
    +            if var_data['data'].ndim == 5:
    +                var_data['data'] = np.squeeze(var_data['data'], axis=1)
    +
                 if field == 'temperature' and celsius:
                     var_data['data'] -= 273.15
                     var_data['units'] = 'degrees Celsius'
    @@ -586,7 +592,7 @@ 

    Navigation

  37. modules |
  38. - +
    diff --git a/docs/_modules/pyrad/io/read_data_dem.html b/docs/_modules/pyrad/io/read_data_dem.html index 32fb3f0..317f78f 100644 --- a/docs/_modules/pyrad/io/read_data_dem.html +++ b/docs/_modules/pyrad/io/read_data_dem.html @@ -6,7 +6,7 @@ - pyrad.io.read_data_dem — pyrad 0.4.4 documentation + pyrad.io.read_data_dem — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  39. modules |
  40. - +
    @@ -344,7 +344,7 @@

    Navigation

  41. modules |
  42. - +
    diff --git a/docs/_modules/pyrad/io/read_data_hzt.html b/docs/_modules/pyrad/io/read_data_hzt.html index 0fb1ebf..a7ae3fc 100644 --- a/docs/_modules/pyrad/io/read_data_hzt.html +++ b/docs/_modules/pyrad/io/read_data_hzt.html @@ -6,7 +6,7 @@ - pyrad.io.read_data_hzt — pyrad 0.4.4 documentation + pyrad.io.read_data_hzt — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  43. modules |
  44. - +
    @@ -394,7 +394,7 @@

    Navigation

  45. modules |
  46. - +
    diff --git a/docs/_modules/pyrad/io/read_data_other.html b/docs/_modules/pyrad/io/read_data_other.html index a64b4ba..e280b83 100644 --- a/docs/_modules/pyrad/io/read_data_other.html +++ b/docs/_modules/pyrad/io/read_data_other.html @@ -6,7 +6,7 @@ - pyrad.io.read_data_other — pyrad 0.4.4 documentation + pyrad.io.read_data_other — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  47. modules |
  48. - +
    @@ -1618,7 +1618,7 @@

    Navigation

  49. modules |
  50. - +
    diff --git a/docs/_modules/pyrad/io/read_data_radar.html b/docs/_modules/pyrad/io/read_data_radar.html index 71a4ff1..ec84b6e 100644 --- a/docs/_modules/pyrad/io/read_data_radar.html +++ b/docs/_modules/pyrad/io/read_data_radar.html @@ -6,7 +6,7 @@ - pyrad.io.read_data_radar — pyrad 0.4.4 documentation + pyrad.io.read_data_radar — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  51. modules |
  52. - +
    @@ -82,6 +82,7 @@

    Source code for pyrad.io.read_data_radar

         merge_fields_psr
         merge_fields_psr_spectra
         merge_fields_rad4alp_grid
    +    merge_fields_sat_grid
         merge_fields_pyrad
         merge_fields_pyradcosmo
         merge_fields_pyradgrid
    @@ -203,7 +204,7 @@ 

    Source code for pyrad.io.read_data_radar

                     product is stored.
                     Example: CFRADIAL:dBZc,Att_ZPhi,SAVEVOL_dBZc
                 'CFRADIALCOSMO': COSMO data in radar coordinates in a CFRadial
    -            file format.
    +                file format.
                 'ODIMPYRAD': ODIM file format with the naming convention and
                     directory structure in which Pyrad saves the data.  For such
                     datatypes 'dataset' specifies the directory where the dataset
    @@ -220,6 +221,8 @@ 

    Source code for pyrad.io.read_data_radar

                     is stored and 'product' specifies the directroy where the
                     product is stored.
                     Example: ODIMPYRAD:RR,RZC,SAVEVOL
    +            'SATGRID': CF Netcdf from used for the MeteoSat satellite data
    +                in the CCS4 (Radar composite) grid.
     
                 'PSRSPECTRA': Format used to store Rainbow power spectra
                     recordings.
    @@ -272,6 +275,7 @@ 

    Source code for pyrad.io.read_data_radar

         datatype_rad4alpgrid = list()
         datatype_rad4alpgif = list()
         datatype_rad4alpbin = list()
    +    datatype_satgrid = list()
         datatype_rad4alpIQ = list()
         datatype_mxpol = list()
         datatype_pyradgrid = list()
    @@ -339,6 +343,8 @@ 

    Source code for pyrad.io.read_data_radar

                 datatype_pyradgrid.append(datatype)
                 dataset_pyradgrid.append(dataset)
                 product_pyradgrid.append(product)
    +        elif datagroup == 'SATGRID':
    +            datatype_satgrid.append(datatype)
             elif datagroup == 'PSR':
                 datatype_psr.append(datatype)
             elif datagroup == 'PSRSPECTRA':
    @@ -369,6 +375,7 @@ 

    Source code for pyrad.io.read_data_radar

         ndatatypes_rad4alpgrid = len(datatype_rad4alpgrid)
         ndatatypes_rad4alpgif = len(datatype_rad4alpgif)
         ndatatypes_rad4alpbin = len(datatype_rad4alpbin)
    +    ndatatypes_satgrid = len(datatype_satgrid)
         ndatatypes_rad4alpIQ = len(datatype_rad4alpIQ)
         ndatatypes_pyradgrid = len(datatype_pyradgrid)
         ndatatypes_psr = len(datatype_psr)
    @@ -504,18 +511,46 @@ 

    Source code for pyrad.io.read_data_radar

     
         # add other grid object files
         if ndatatypes_rad4alpgif > 0:
    -        radar = merge_fields_rad4alp_grid(
    +        radar_aux = merge_fields_rad4alp_grid(
                 voltime, datatype_rad4alpgif, cfg, ind_rad=ind_rad, ftype='gif')
    +        if radar_aux is not None:
    +            if radar is not None:
    +                radar = merge_grids(radar, radar_aux)
    +            else:
    +                radar = radar_aux
     
         if ndatatypes_rad4alpbin > 0:
    -        radar = merge_fields_rad4alp_grid(
    +        radar_aux = merge_fields_rad4alp_grid(
                 voltime, datatype_rad4alpbin, cfg, ind_rad=ind_rad, ftype='bin')
    +        if radar_aux is not None:
    +            if radar is not None:
    +                radar = merge_grids(radar, radar_aux)
    +            else:
    +                radar = radar_aux
     
         if ndatatypes_pyradgrid > 0:
             radar_aux = merge_fields_pyradgrid(
                 cfg['loadbasepath'][ind_rad], cfg['loadname'][ind_rad], voltime,
                 datatype_pyradgrid, dataset_pyradgrid, product_pyradgrid, cfg)
    -        radar = add_field(radar, radar_aux)
    +        if radar_aux is not None:
    +            if radar is not None:
    +                radar = merge_grids(radar, radar_aux)
    +            else:
    +                radar = radar_aux
    +
    +    if ndatatypes_satgrid > 0:
    +        radar_aux = merge_fields_sat_grid(
    +            voltime, datatype_satgrid, cfg, ind_rad=ind_rad)
    +        if radar_aux is not None:
    +            if radar is not None:
    +                radar = merge_grids(radar, radar_aux)
    +            else:
    +                radar = radar_aux
    +
    +        # for field in radar.fields:
    +        #     print(
    +        #         'Field size (z, y, x): ', radar.fields[field]['data'].shape)
    +        #     break
     
         # add COSMO files to the radar field
         if ndatatypes_cosmo > 0 and _WRADLIB_AVAILABLE:
    @@ -2542,10 +2577,78 @@ 

    Source code for pyrad.io.read_data_radar

         lon_max = cfg.get('lonmax', None)
         alt_min = cfg.get('altmin', None)
         alt_max = cfg.get('altmax', None)
    +    nx = cfg.get('nx', None)
    +    ny = cfg.get('ny', None)
    +    nz = cfg.get('nz', None)
    +
    +    return crop_grid(
    +        grid, lat_min=lat_min, lat_max=lat_max, lon_min=lon_min,
    +        lon_max=lon_max, alt_min=alt_min, alt_max=alt_max, nx=nx, ny=ny,
    +        nz=nz)
    +
    +
    +def merge_fields_sat_grid(voltime, datatype_list, cfg, ind_rad=0,
    +                          ftype='METRANET'):
    +    """
    +    merge rad4alp Cartesian products
    +
    +    Parameters
    +    ----------
    +    voltime: datetime object
    +        reference time of the scan
    +    datatype : str
    +        name of the data type to read
    +    cfg : dict
    +        configuration dictionary
    +    ind_rad : int
    +        radar index
    +    ftype : str
    +        File type. Can be 'METRANET', 'gif' or 'bin'
    +
    +    Returns
    +    -------
    +    radar : Radar
    +        radar object
    +
    +    """
    +    grid = None
    +    daydir = voltime.strftime('%Y/%m/%d/')
    +    dayinfo = voltime.strftime('%Y%m%d%H%M')
    +    datapath = cfg['satpath'][ind_rad] + daydir
    +    if not os.path.isdir(datapath):
    +        # warn("WARNING: Unknown datapath '%s'" % datapath)
    +        return grid
    +
    +    filename = glob.glob(datapath+'MSG?_ccs4_'+dayinfo+'*_rad_PLAX.nc')
    +    if not filename:
    +        warn(
    +            'No file found in '+datapath+'MSG?_ccs4_'+dayinfo+'*_rad_PLAX.nc')
    +        return grid
    +
    +    field_names = []
    +    for datatype in datatype_list:
    +        field_names.append(get_fieldname_pyart(datatype))
    +
    +    grid = pyart.aux_io.read_cf1_cartesian(filename[0], field_names)
    +
    +    if grid is None:
    +        return grid
    +
    +    # Crop the data
    +    lat_min = cfg.get('latmin', None)
    +    lat_max = cfg.get('latmax', None)
    +    lon_min = cfg.get('lonmin', None)
    +    lon_max = cfg.get('lonmax', None)
    +    alt_min = cfg.get('altmin', None)
    +    alt_max = cfg.get('altmax', None)
    +    nx = cfg.get('nx', None)
    +    ny = cfg.get('ny', None)
    +    nz = cfg.get('nz', None)
     
         return crop_grid(
             grid, lat_min=lat_min, lat_max=lat_max, lon_min=lon_min,
    -        lon_max=lon_max, alt_min=alt_min, alt_max=alt_max)
    +        lon_max=lon_max, alt_min=alt_min, alt_max=alt_max, nx=nx, ny=ny,
    +        nz=nz)
     
     
     def merge_fields_pyrad(basepath, loadname, voltime, datatype_list,
    @@ -2864,10 +2967,14 @@ 

    Source code for pyrad.io.read_data_radar

         lon_max = cfg.get('lonmax', None)
         alt_min = cfg.get('altmin', None)
         alt_max = cfg.get('altmax', None)
    +    nx = cfg.get('nx', None)
    +    ny = cfg.get('ny', None)
    +    nz = cfg.get('nz', None)
     
         return crop_grid(
             grid, lat_min=lat_min, lat_max=lat_max, lon_min=lon_min,
    -        lon_max=lon_max, alt_min=alt_min, alt_max=alt_max)
    +        lon_max=lon_max, alt_min=alt_min, alt_max=alt_max, nx=nx, ny=ny,
    +        nz=nz)
     
     
     def merge_fields_dem(basepath, scan_name, datatype_list):
    @@ -3414,9 +3521,11 @@ 

    Source code for pyrad.io.read_data_radar

     
     
     def crop_grid(grid, lat_min=None, lat_max=None, lon_min=None, lon_max=None,
    -              alt_min=None, alt_max=None):
    +              alt_min=None, alt_max=None, nx=None, ny=None, nz=None):
         """
    -    crops a grid object
    +    crops a grid object. The cropping can be done either specifying min and
    +    max lat, lon and altitude or by specifying the min lat, lon and altitude
    +    and the length in pixels of each side
     
         Parameters
         ----------
    @@ -3426,6 +3535,8 @@ 

    Source code for pyrad.io.read_data_radar

             the lat/lon limits of the object (deg)
         alt_min, alt_max : float
             the altitude limits of the object (m MSL)
    +    nx, ny ,nz : int
    +        The number of pixels in each direction
     
         Returns
         -------
    @@ -3435,7 +3546,8 @@ 

    Source code for pyrad.io.read_data_radar

         """
         grid_crop = deepcopy(grid)
         if (lat_min is None and lat_max is None and lon_min is None
    -            and lon_max is None and alt_min is None and alt_max is None):
    +            and lon_max is None and alt_min is None and alt_max is None
    +            and nx is None and ny is None and nz is None):
             return grid_crop
     
         if lat_min is not None:
    @@ -3449,7 +3561,9 @@ 

    Source code for pyrad.io.read_data_radar

         else:
             iy_min = 0
     
    -    if lat_max is not None:
    +    if ny is not None:
    +        iy_max = iy_min+ny
    +    elif lat_max is not None:
             iz, iy, ix = np.where(grid.point_latitude['data'] <= lat_max)
             if iy.size == 0:
                 warn('Max latitude '+str(lat_max)+' outside of grid. ' +
    @@ -3471,7 +3585,9 @@ 

    Source code for pyrad.io.read_data_radar

         else:
             ix_min = 0
     
    -    if lon_max is not None:
    +    if nx is not None:
    +        ix_max = ix_min+nx
    +    elif lon_max is not None:
             iz, iy, ix = np.where(grid.point_longitude['data'] <= lon_max)
             if ix.size == 0:
                 warn('Max longitude '+str(lon_max)+' outside of grid. ' +
    @@ -3493,7 +3609,9 @@ 

    Source code for pyrad.io.read_data_radar

         else:
             iz_min = 0
     
    -    if alt_max is not None:
    +    if nz is not None:
    +        iz_max = iz_min+nz
    +    elif alt_max is not None:
             iz, iy, ix = np.where(grid.point_altitude['data'] <= alt_max)
             if iz.size == 0:
                 warn('Max longitude '+str(lon_max)+' outside of grid. ' +
    @@ -3682,7 +3800,7 @@ 

    Navigation

  53. modules |
  54. - +
    diff --git a/docs/_modules/pyrad/io/read_data_sensor.html b/docs/_modules/pyrad/io/read_data_sensor.html index 70e033e..b14ec05 100644 --- a/docs/_modules/pyrad/io/read_data_sensor.html +++ b/docs/_modules/pyrad/io/read_data_sensor.html @@ -6,7 +6,7 @@ - pyrad.io.read_data_sensor — pyrad 0.4.4 documentation + pyrad.io.read_data_sensor — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  55. modules |
  56. - +
    @@ -255,12 +255,17 @@

    Source code for pyrad.io.read_data_sensor

                     delimiter=';')
     
                 for i, row in enumerate(reader):
    -                dt_remote[i] = datetime.datetime.strptime(
    -                    row['Datum(Remote)']+' '+row['Uhrzeit(Remote)'],
    -                    '%d.%m.%Y %H:%M:%S')
    -                dt_server[i] = datetime.datetime.strptime(
    -                    row['Datum(Server)']+' '+row['Uhrzeit(Server)'],
    -                    '%d.%m.%Y %H:%M:%S')
    +                if 'Datum(Remote)' in row and 'Uhrzeit(Remote)' in row:
    +                    dt_remote[i] = datetime.datetime.strptime(
    +                        row['Datum(Remote)']+' '+row['Uhrzeit(Remote)'],
    +                        '%d.%m.%Y %H:%M:%S')
    +                    dt_server[i] = datetime.datetime.strptime(
    +                        row['Datum(Server)']+' '+row['Uhrzeit(Server)'],
    +                        '%d.%m.%Y %H:%M:%S')
    +                else:
    +                    dt_remote[i] = datetime.datetime.strptime(
    +                        row['Datum (Anlage)']+' '+row['Zeit (Anlage)'],
    +                        '%d.%m.%Y %H:%M:%S')
                     rotor_speed_avg[i] = float(
                         row['Rotordrehzahl'].replace(',', '.'))
                     rotor_speed_min[i] = float(
    @@ -607,7 +612,6 @@ 

    Source code for pyrad.io.read_data_sensor

                 lon = np.ma.array([])
                 scan_time = np.ma.array([], dtype=datetime.datetime)
     
    -            nscans_aux = -1
                 while 0 == 0:
                     line = txtfile.readline()
                     if not line:
    @@ -2074,7 +2078,7 @@ 

    Navigation

  57. modules |
  58. - +
    diff --git a/docs/_modules/pyrad/io/read_data_sun.html b/docs/_modules/pyrad/io/read_data_sun.html index 64fcb3c..d0d87f5 100644 --- a/docs/_modules/pyrad/io/read_data_sun.html +++ b/docs/_modules/pyrad/io/read_data_sun.html @@ -6,7 +6,7 @@ - pyrad.io.read_data_sun — pyrad 0.4.4 documentation + pyrad.io.read_data_sun — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  59. modules |
  60. - +
    @@ -481,7 +481,7 @@

    Navigation

  61. modules |
  62. - +
    diff --git a/docs/_modules/pyrad/io/timeseries.html b/docs/_modules/pyrad/io/timeseries.html index de350d0..f8c2a54 100644 --- a/docs/_modules/pyrad/io/timeseries.html +++ b/docs/_modules/pyrad/io/timeseries.html @@ -6,7 +6,7 @@ - pyrad.io.timeseries — pyrad 0.4.4 documentation + pyrad.io.timeseries — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  63. modules |
  64. - +
    @@ -311,7 +311,7 @@

    Navigation

  65. modules |
  66. - +
    diff --git a/docs/_modules/pyrad/io/trajectory.html b/docs/_modules/pyrad/io/trajectory.html index e3ec6ef..2aeb46c 100644 --- a/docs/_modules/pyrad/io/trajectory.html +++ b/docs/_modules/pyrad/io/trajectory.html @@ -6,7 +6,7 @@ - pyrad.io.trajectory — pyrad 0.4.4 documentation + pyrad.io.trajectory — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  67. modules |
  68. - +
    @@ -773,7 +773,7 @@

    Navigation

  69. modules |
  70. - +
    diff --git a/docs/_modules/pyrad/io/write_data.html b/docs/_modules/pyrad/io/write_data.html index d9aa934..ac6be85 100644 --- a/docs/_modules/pyrad/io/write_data.html +++ b/docs/_modules/pyrad/io/write_data.html @@ -6,7 +6,7 @@ - pyrad.io.write_data — pyrad 0.4.4 documentation + pyrad.io.write_data — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  71. modules |
  72. - +
    @@ -84,6 +84,7 @@

    Source code for pyrad.io.write_data

         write_ts_polar_data
         write_ts_grid_data
         write_ts_ml
    +    write_ts_stats
         write_ts_cum
         write_monitoring_ts
         write_excess_gates
    @@ -113,7 +114,6 @@ 

    Source code for pyrad.io.write_data

     from .io_aux import generate_field_name_str
     
     
    -
     
    [docs]def write_proc_periods(start_times, end_times, fname): """ writes an output file containing start and stop times of periods to @@ -1207,8 +1207,13 @@

    Source code for pyrad.io.write_data

     
         """
         filelist = glob.glob(fname)
    +    nsamples = len(dataset['used_antenna_coordinates_az_el_r'][0])
         if not filelist:
             with open(fname, 'w', newline='') as csvfile:
    +            if nsamples > 1:
    +                start_time = dataset['time'][0]
    +            else:
    +                start_time = dataset['time']
                 csvfile.write('# Weather radar timeseries data file\n')
                 csvfile.write('# Comment lines are preceded by "#"\n')
                 csvfile.write('# Description: \n')
    @@ -1225,29 +1230,54 @@ 

    Source code for pyrad.io.write_data

                 csvfile.write('# Fill Value: '+str(get_fillvalue())+'\n')
                 csvfile.write(
                     '# Start: ' +
    -                dataset['time'].strftime('%Y-%m-%d %H:%M:%S UTC')+'\n')
    +                start_time.strftime('%Y-%m-%d %H:%M:%S UTC')+'\n')
                 csvfile.write('#\n')
     
                 fieldnames = ['date', 'az', 'el', 'r', 'value']
                 writer = csv.DictWriter(csvfile, fieldnames)
                 writer.writeheader()
    -            writer.writerow(
    -                {'date': dataset['time'],
    -                 'az': dataset['used_antenna_coordinates_az_el_r'][0],
    -                 'el': dataset['used_antenna_coordinates_az_el_r'][1],
    -                 'r': dataset['used_antenna_coordinates_az_el_r'][2],
    -                 'value': dataset['value']})
    +
    +            if nsamples == 1:
    +                writer.writerow({
    +                    'date': dataset['time'],
    +                    'az': dataset['used_antenna_coordinates_az_el_r'][0][0],
    +                    'el': dataset['used_antenna_coordinates_az_el_r'][1][0],
    +                    'r': dataset['used_antenna_coordinates_az_el_r'][2][0],
    +                    'value': dataset['value']})
    +            else:
    +                for i in range(nsamples):
    +                    writer.writerow({
    +                        'date': dataset['time'][i],
    +                        'az':
    +                            dataset['used_antenna_coordinates_az_el_r'][0][i],
    +                        'el':
    +                            dataset['used_antenna_coordinates_az_el_r'][1][i],
    +                        'r':
    +                            dataset['used_antenna_coordinates_az_el_r'][2][i],
    +                        'value': dataset['value'][i]})
                 csvfile.close()
         else:
             with open(fname, 'a', newline='') as csvfile:
                 fieldnames = ['date', 'az', 'el', 'r', 'value']
                 writer = csv.DictWriter(csvfile, fieldnames)
    -            writer.writerow(
    -                {'date': dataset['time'],
    -                 'az': dataset['used_antenna_coordinates_az_el_r'][0],
    -                 'el': dataset['used_antenna_coordinates_az_el_r'][1],
    -                 'r': dataset['used_antenna_coordinates_az_el_r'][2],
    -                 'value': dataset['value']})
    +            if nsamples == 1:
    +                writer.writerow({
    +                    'date': dataset['time'],
    +                    'az': dataset['used_antenna_coordinates_az_el_r'][0][0],
    +                    'el': dataset['used_antenna_coordinates_az_el_r'][1][0],
    +                    'r': dataset['used_antenna_coordinates_az_el_r'][2][0],
    +                    'value': dataset['value']})
    +            else:
    +                for i in range(nsamples):
    +                    writer.writerow({
    +                        'date': dataset['time'][i],
    +                        'az':
    +                            dataset['used_antenna_coordinates_az_el_r'][0][i],
    +                        'el':
    +                            dataset['used_antenna_coordinates_az_el_r'][1][i],
    +                        'r':
    +                            dataset['used_antenna_coordinates_az_el_r'][2][i],
    +                        'value': dataset['value'][i]})
                 csvfile.close()
     
         return fname
    @@ -1398,6 +1428,60 @@

    Source code for pyrad.io.write_data

         return fname
     
     
    +
    [docs]def write_ts_stats(dt, value, fname, stat='mean'): + """ + writes time series of statistics + + Parameters + ---------- + dt : date time array + array of time steps + value: float arrays + the average and the standard deviation of the melting layer top height + fname : str + file name where to store the data + stat : str + Statistic that is written + + Returns + ------- + fname : str + the name of the file where data has written + + """ + filelist = glob.glob(fname) + if not filelist: + with open(fname, 'w', newline='') as csvfile: + csvfile.write( + '# Statistics\n' + + '# Comment lines are preceded by "#"\n' + + '# Description: \n' + + '# Time series of '+stat+'.\n' + + '# Fill Value: '+str(get_fillvalue())+'\n' + + '# Start: '+dt.strftime('%Y-%m-%d %H:%M:%S UTC')+'\n' + + '#\n') + + fieldnames = ['date-time [UTC]', 'value'] + writer = csv.DictWriter(csvfile, fieldnames) + writer.writeheader() + writer.writerow( + {'date-time [UTC]': dt.strftime('%Y-%m-%d %H:%M:%S'), + 'value': value.filled( + fill_value=get_fillvalue())[0]}) + csvfile.close() + else: + with open(fname, 'a', newline='') as csvfile: + fieldnames = ['date-time [UTC]', 'value'] + writer = csv.DictWriter(csvfile, fieldnames) + writer.writerow( + {'date-time [UTC]': dt.strftime('%Y-%m-%d %H:%M:%S'), + 'value': value.filled( + fill_value=get_fillvalue())[0]}) + csvfile.close() + + return fname
    + +
    [docs]def write_ts_cum(dataset, fname): """ writes time series accumulation of data @@ -2251,7 +2335,7 @@

    Navigation

  73. modules |
  74. - +
    diff --git a/docs/_modules/pyrad/proc/process_Doppler.html b/docs/_modules/pyrad/proc/process_Doppler.html index d25d21c..7698f58 100644 --- a/docs/_modules/pyrad/proc/process_Doppler.html +++ b/docs/_modules/pyrad/proc/process_Doppler.html @@ -6,7 +6,7 @@ - pyrad.proc.process_Doppler — pyrad 0.4.4 documentation + pyrad.proc.process_Doppler — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  75. modules |
  76. - +
    @@ -67,6 +67,7 @@

    Source code for pyrad.proc.process_Doppler

         process_dealias_fourdd
         process_dealias_region_based
         process_dealias_unwrap_phase
    +    process_radial_velocity
         process_wind_vel
         process_windshear
         process_vad
    @@ -487,6 +488,134 @@ 

    Source code for pyrad.proc.process_Doppler

         return new_dataset, ind_rad
    +
    [docs]def process_radial_velocity(procstatus, dscfg, radar_list=None): + """ + Estimates the radial velocity respect to the radar from the wind velocity + + Parameters + ---------- + procstatus : int + Processing status: 0 initializing, 1 processing volume, + 2 post-processing + dscfg : dictionary of dictionaries + data set configuration. Accepted Configuration Keywords:: + + datatype : string. Dataset keyword + The input data type + latitude, longitude : float + arbitrary coordinates [deg] from where to compute the radial + velocity. If any of them is None it will be the radar position + altitude : float + arbitrary altitude [m MSL] from where to compute the radial + velocity. If None it will be the radar altitude + radar_list : list of Radar objects + Optional. list of radar objects + + Returns + ------- + new_dataset : dict + dictionary containing the output + ind_rad : int + radar index + + """ + if procstatus != 1: + return None, None + + v_speed_field = None + h_speed_field = None + h_dir_field = None + for datatypedescr in dscfg['datatype']: + radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr) + if datatype == 'wind_vel_v': + v_speed_field = get_fieldname_pyart(datatype) + if datatype == 'WIND_SPEED': + h_speed_field = get_fieldname_pyart(datatype) + if datatype == 'WIND_DIRECTION': + h_dir_field = get_fieldname_pyart(datatype) + + if h_speed_field is None or h_dir_field is None: + warn('Horizontal wind speed and direction fields required' + ' to estimate radial velocity') + return None, None + + ind_rad = int(radarnr[5:8])-1 + if radar_list[ind_rad] is None: + warn('No valid radar') + return None, None + radar = radar_list[ind_rad] + + if h_speed_field not in radar.fields or h_dir_field not in radar.fields: + warn('Unable to estimate radial velocity. ' + 'Missing horizontal wind') + return None, None + + h_speed = radar.fields[h_speed_field]['data'] + h_dir = radar.fields[h_dir_field]['data'] + + if v_speed_field is None or v_speed_field not in radar.fields: + warn('Unknown vertical wind speed. Assumed 0') + + if v_speed_field is None: + v_speed_field == 'vertical_wind_component' + + v_speed = np.ma.zeros((radar.nrays, radar.ngates)) + else: + v_speed = radar.fields[v_speed_field]['data'] + + # user defined parameters + lat = dscfg.get('latitude', None) + lon = dscfg.get('longitude', None) + alt = dscfg.get('altitude', None) + + # get u and v wind components + h_dir_rad = np.deg2rad(h_dir) + speed_h_u = h_speed*np.sin(h_dir_rad) # eastward component + speed_h_v = h_speed*np.cos(h_dir_rad) # northward component + + if lat is not None or lon is not None or alt is not None: + # get antenna coordinates respect to new radar location + if lat is None: + lat = radar.latitude['data'][0] + if lon is None: + lon = radar.longitude['data'][0] + if alt is None: + alt = radar.altitude['data'][0] + + x, y = pyart.core.geographic_to_cartesian_aeqd( + radar.gate_longitude['data'], radar.gate_latitude['data'], lon, + lat) + z = radar.gate_altitude['data'] - alt + _, azimuths, elevations = pyart.core.cartesian_to_antenna( + x, y, z) + azi_2D_rad = np.deg2rad(azimuths) + ele_2D_rad = np.deg2rad(elevations) + else: + azi_2D_rad = np.broadcast_to( + np.deg2rad(radar.azimuth['data'])[:, np.newaxis], + (radar.nrays, radar.ngates)) + ele_2D_rad = np.broadcast_to( + np.deg2rad(radar.elevation['data'])[:, np.newaxis], + (radar.nrays, radar.ngates)) + + r_speed = pyart.config.get_metadata('velocity') + + # assuming no vertical velocity + # r_speed['data'] = h_speed*np.cos(h_dir_rad-azi_2D_rad)*np.cos(ele_2D_rad) + + # with vertical velocity included + r_speed['data'] = ( + (speed_h_u*np.sin(azi_2D_rad)+speed_h_v*np.cos(azi_2D_rad)) * + np.cos(ele_2D_rad)+np.sin(ele_2D_rad)*v_speed) + + # prepare for exit + new_dataset = {'radar_out': deepcopy(radar)} + new_dataset['radar_out'].fields = dict() + new_dataset['radar_out'].add_field('velocity', r_speed) + + return new_dataset, ind_rad
    + +
    [docs]def process_wind_vel(procstatus, dscfg, radar_list=None): """ Estimates the horizontal or vertical component of the wind from the @@ -694,7 +823,7 @@

    Navigation

  77. modules |
  78. - +
    diff --git a/docs/_modules/pyrad/proc/process_aux.html b/docs/_modules/pyrad/proc/process_aux.html index 6cebf8d..9e4f9e1 100644 --- a/docs/_modules/pyrad/proc/process_aux.html +++ b/docs/_modules/pyrad/proc/process_aux.html @@ -6,7 +6,7 @@ - pyrad.proc.process_aux — pyrad 0.4.4 documentation + pyrad.proc.process_aux — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  79. modules |
  80. - +
    @@ -78,6 +78,8 @@

    Source code for pyrad.proc.process_aux

     
     """
     
    +from time import time
    +
     from copy import deepcopy
     from warnings import warn
     import numpy as np
    @@ -159,6 +161,7 @@ 

    Source code for pyrad.proc.process_aux

                     'RADAR_RESAMPLING': process_radar_resampling
                     'RADIAL_NOISE_HS': process_radial_noise_hs
                     'RADIAL_NOISE_IVIC': process_radial_noise_ivic
    +                'RADIAL_VELOCITY': process_radial_velocity
                     'RAINRATE': process_rainrate
                     'RAW': process_raw
                     'REFLECTIVITY': process_reflectivity
    @@ -220,6 +223,11 @@ 

    Source code for pyrad.proc.process_aux

                 'GRID' format output:
                     'RAW_GRID': process_raw_grid
                     'GRID': process_grid
    +                'GRID_FIELDS_DIFF': process_grid_fields_diff
    +                'GRID_MASK': process_grid_mask
    +                'GRID_TEXTURE': process_grid_texture
    +                'NORMALIZE_LUMINOSITY': process_normalize_luminosity
    +                'PIXEL_FILTER': process_pixel_filter
                 'GRID_TIMEAVG' format output:
                     'GRID_TIME_STATS': process_grid_time_stats
                     'GRID_TIME_STATS2': process_grid_time_stats2
    @@ -289,6 +297,21 @@ 

    Source code for pyrad.proc.process_aux

         elif dataset_type == 'RAW_GRID':
             func_name = 'process_raw_grid'
             dsformat = 'GRID'
    +    elif dataset_type == 'GRID_FIELDS_DIFF':
    +        func_name = 'process_grid_fields_diff'
    +        dsformat = 'GRID'
    +    elif dataset_type == 'GRID_MASK':
    +        func_name = 'process_grid_mask'
    +        dsformat = 'GRID'
    +    elif dataset_type == 'GRID_TEXTURE':
    +        func_name = 'process_grid_texture'
    +        dsformat = 'GRID'
    +    elif dataset_type == 'NORMALIZE_LUMINOSITY':
    +        func_name = 'process_normalize_luminosity'
    +        dsformat = 'GRID'
    +    elif dataset_type == 'PIXEL_FILTER':
    +        func_name = 'process_pixel_filter'
    +        dsformat = 'GRID'
         elif dataset_type == 'RAW_SPECTRA':
             func_name = 'process_raw_spectra'
             dsformat = 'SPECTRA'
    @@ -437,6 +460,8 @@ 

    Source code for pyrad.proc.process_aux

             func_name = 'process_dealias_region_based'
         elif dataset_type == 'DEALIAS_UNWRAP':
             func_name = 'process_dealias_unwrap_phase'
    +    elif dataset_type == 'RADIAL_VELOCITY':
    +        func_name = 'process_radial_velocity'
         elif dataset_type == 'WIND_VEL':
             func_name = 'process_wind_vel'
         elif dataset_type == 'VAD':
    @@ -1017,14 +1042,16 @@ 

    Source code for pyrad.proc.process_aux

             datatype : string. Dataset keyword
                 The data type where we want to extract the point measurement
             angle : float or None. Dataset keyword
    -            The
    +            The center angle to average. If not set or set to -1 all
    +            available azimuth angles will be used
             delta_azi : float. Dataset keyword
    -
    +            The angle span to average. If not set or set to -1 all the
    +            available azimuth angles will be used
             avg_type : str. Dataset keyword
    -
    +            Average type. Can be mean or median
             nvalid_min : int. Dataset keyword
    -             the (minimum) radius of the region of interest in m. Default half
    -             the largest resolution
    +            the (minimum) radius of the region of interest in m. Default half
    +            the largest resolution
     
         radar_list : list of Radar objects
             Optional. list of radar objects
    @@ -1172,7 +1199,7 @@ 

    Source code for pyrad.proc.process_aux

             antennaType : str. Dataset keyword
                 Type of antenna of the radar we want to get the view from. Can
                 be AZIMUTH, ELEVATION, LOWBEAM, HIGHBEAM
    -        par_azimuth_antenna : dict. Global ekyword
    +        par_azimuth_antenna : dict. Global keyword
                 Dictionary containing the parameters of the PAR azimuth antenna,
                 i.e. name of the file with the antenna elevation pattern and fixed
                 antenna angle
    @@ -1194,7 +1221,7 @@ 

    Source code for pyrad.proc.process_aux

                 assume the radar is collocated
             change_antenna_pattern : Bool. Dataset keyword
                 If true the target radar has a different antenna pattern than the
    -            observations radar
    +            observations radar. Default True
             rhi_resolution : Bool. Dataset keyword
                 Resolution of the synthetic RHI used to compute the data as viewed
                 from the synthetic radar [deg]. Default 0.5
    @@ -1205,9 +1232,19 @@ 

    Source code for pyrad.proc.process_aux

                 The tolerance in latitude and longitude to determine which
                 synthetic radar gates are co-located with real radar gates [deg].
                 Default 0.04
    -        alt_tol : float. Datset keyword
    +        alt_tol : float. Dataset keyword
                 The tolerance in altitude to determine which synthetic
                 radar gates are co-located with real radar gates [m]. Default 1000.
    +        distance_upper_bound : float. Dataset keyword
    +            The maximum distance where to look for a neighbour when
    +            determining which synthetic radar gates are co-located with real
    +            radar gates [m]. Default 1000.
    +        use_cKDTree : Bool. Dataset keyword
    +            Which function to use to find co-located real radar gates with the
    +            synthetic radar. If True a function using cKDTree from
    +            scipy.spatial is used. This function uses parameter
    +            distance_upper_bound. If False a native implementation is used
    +            that takes as parameters latlon_tol and alt_tol. Default True.
             pattern_thres : float. Dataset keyword
                 The minimum of the sum of the weights given to each value in order
                 to consider the weighted quantile valid. It is related to the
    @@ -1216,17 +1253,27 @@ 

    Source code for pyrad.proc.process_aux

                 Dictionary specifying for each field if it is in log (True) or
                 linear units (False). Default False
             use_nans : dict. Dataset keyword
    -            Dictionary specyfing whether the nans have to be used in the
    +            Dictionary specifying whether the nans have to be used in the
                 computation of the statistics for each field. Default False
             nan_value : dict. Dataset keyword
                 Dictionary with the value to use to substitute the NaN values when
                 computing the statistics of each field. Default 0
    +        moving_angle_min, moving_angle_max: float. Dataset keyword
    +            The minimum and maximum azimuth angle (deg) of the target radar.
    +            Default 0, 360.
    +        ray_res: float
    +            Ray resolution (deg). Default 1 deg.
    +        rng_min, rng_max:
    +            The minimum and maximum range of the target radar (m).
    +            Default 0, 100000
    +        rng_res : float
    +            The target radar range resolution (m). Default 100.
         radar_list : list of Radar objects
             Optional. list of radar objects
     
         Returns
         -------
    -    new_dataset : Trajectory object
    +    new_dataset : dict
             dictionary containing the new radar
         ind_rad : int
             radar index
    @@ -1236,11 +1283,11 @@ 

    Source code for pyrad.proc.process_aux

             return None, None
     
         # Process
    -    field_names = []
    +    field_names_aux = []
         datatypes = []
         for datatypedescr in dscfg['datatype']:
             radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr)
    -        field_names.append(get_fieldname_pyart(datatype))
    +        field_names_aux.append(get_fieldname_pyart(datatype))
             datatypes.append(datatype)
     
         ind_rad = int(radarnr[5:8])-1
    @@ -1249,6 +1296,13 @@ 

    Source code for pyrad.proc.process_aux

             return None, None
         radar = deepcopy(radar_list[ind_rad])
     
    +    field_names = []
    +    for field_name in field_names_aux:
    +        if field_name not in radar.fields:
    +            warn('Field '+field_name+' not in observations radar object')
    +            continue
    +        field_names.append(field_name)
    +
         if not dscfg['initialized']:
             if 'antennaType' not in dscfg:
                 raise Exception("ERROR: Undefined 'antennaType' for dataset '%s'"
    @@ -1326,6 +1380,8 @@ 

    Source code for pyrad.proc.process_aux

             max_altitude = dscfg.get('max_altitude', 12000.)  # [m]
             latlon_tol = dscfg.get('latlon_tol', 0.04)  # [deg]
             alt_tol = dscfg.get('alt_tol', 1000.)  # [m]
    +        distance_upper_bound = dscfg.get('distance_upper_bound', 1000.)
    +        use_cKDTree = dscfg.get('use_cKDTree', True)
             quants = np.array(dscfg.get(
                 'quants', [0.05, 0.1, 0.2, 0.5, 0.8, 0.9, 0.95]))
     
    @@ -1345,7 +1401,8 @@ 

    Source code for pyrad.proc.process_aux

                 else:
                     antpattern = read_antenna_pattern(patternfile, linear=True,
                                                       twoway=True)
    -        except:
    +        except Exception as ee:
    +            warn(str(ee))
                 raise
     
             pattern_angles = antpattern['angle'] + fixed_angle_val[0]
    @@ -1413,6 +1470,8 @@ 

    Source code for pyrad.proc.process_aux

                 'max_altitude': max_altitude,
                 'latlon_tol': latlon_tol,
                 'alt_tol': alt_tol,
    +            'distance_upper_bound': distance_upper_bound,
    +            'use_cKDTree': use_cKDTree,
                 'data_is_log': data_is_log,
                 'change_antenna_pattern': change_antenna_pattern})
     
    @@ -1482,6 +1541,8 @@ 

    Source code for pyrad.proc.process_aux

         max_altitude = tadict['max_altitude']
         latlon_tol = tadict['latlon_tol']
         alt_tol = tadict['alt_tol']
    +    distance_upper_bound = tadict['distance_upper_bound']
    +    use_cKDTree = tadict['use_cKDTree']
         data_is_log = tadict['data_is_log']
         change_antenna_pattern = tadict['change_antenna_pattern']
     
    @@ -1496,6 +1557,9 @@ 

    Source code for pyrad.proc.process_aux

         _, ind_vec = tree.query(np.transpose(
             (x_target.flatten(), y_target.flatten(), z_target.flatten())), k=1)
     
    +    # temporary solution to get right time:
    +    target_radar.time['data'][:] = radar.time['data'][0]
    +
         if not change_antenna_pattern:
             for field_name in field_names:
                 if field_name not in radar.fields:
    @@ -1510,11 +1574,17 @@ 

    Source code for pyrad.proc.process_aux

             return target_radar
     
         # Find closest azimuth and elevation ray to target radar
    -    ind_rngs = (ind_vec/radar.ngates).astype(int)
    -    ind_rays = (ind_vec % radar.ngates).astype(int)
    +    rad_ind_rays, rad_ind_rngs = np.unravel_index(
    +        ind_vec, (radar.nrays, radar.ngates))
    +    for sample, (rad_ind_ray, rad_ind_rng) in enumerate(
    +            zip(rad_ind_rays, rad_ind_rngs)):
    +
    +        # measure time
    +        tstart = time()
    +
    +        trad_ind_ray, trad_ind_rng = np.unravel_index(
    +            sample, (target_radar.nrays, target_radar.ngates))
     
    -    nsamples = target_radar.nrays*target_radar.ngates
    -    for sample, (ind_ray, ind_rng) in enumerate(zip(ind_rngs, ind_rays)):
             if radar_antenna_atsameplace:
                 # ==============================================================
                 # Radar and scanning antenna are at the SAME place
    @@ -1525,11 +1595,11 @@ 

    Source code for pyrad.proc.process_aux

                 if is_azimuth_antenna:
                     angles = radar.azimuth['data']
                     angles_scan = radar.elevation['data']
    -                ray_angle = radar.azimuth['data'][ind_ray]
    +                ray_angle = radar.azimuth['data'][rad_ind_ray]
                 else:
                     angles = radar.elevation['data']
                     angles_scan = radar.azimuth['data']
    -                ray_angle = radar.elevation['data'][ind_ray]
    +                ray_angle = radar.elevation['data'][rad_ind_ray]
     
                 d_angle = np.abs(angles - ray_angle)
                 ray_inds = np.where(d_angle < 0.09)[0]
    @@ -1550,7 +1620,8 @@ 

    Source code for pyrad.proc.process_aux

                         warn("Datatype '%s' not available in radar data" %
                              field_name)
                         continue
    -                values = radar.fields[field_name]['data'][ray_inds, ind_rng]
    +                values = radar.fields[field_name]['data'][
    +                    ray_inds, rad_ind_rng]
                     if use_nans[field_name]:
                         values_ma = np.ma.getmaskarray(values)
                         values[values_ma] = nan_value[field_name]
    @@ -1571,15 +1642,11 @@ 

    Source code for pyrad.proc.process_aux

     
                     # average field
                     target_radar.fields['avg_'+field_name]['data'][
    -                    np.unravel_index(
    -                        sample, (target_radar.nrays, target_radar.ngates))] = (
    -                            avg)
    +                    trad_ind_ray, trad_ind_rng] = avg
     
                     # npoints field
                     target_radar.fields['npoints_'+field_name]['data'][
    -                    np.unravel_index(
    -                        sample, (target_radar.nrays, target_radar.ngates))] = (
    -                            nvals_valid)
    +                    trad_ind_ray, trad_ind_rng] = nvals_valid
     
                     # quantile fields
                     for quant, val in zip(tadict['quantiles'], qvals):
    @@ -1589,18 +1656,20 @@ 

    Source code for pyrad.proc.process_aux

                             'quant'+'{:02d}'.format(int(100*quant))+'_' +
                             field_name)
                         target_radar.fields[quant_field]['data'][
    -                        np.unravel_index(
    -                            sample,
    -                            (target_radar.nrays, target_radar.ngates))] = val
    +                        trad_ind_ray, trad_ind_rng] = val
             else:
                 # ================================================================
                 # Radar and scanning antenna are NOT at the same place
                 # ================================================================
                 ray_inds, rng_inds, w_inds = _get_gates_antenna_pattern(
    -                radar, target_radar, radar.azimuth['data'][ind_ray],
    -                radar.range['data'][ind_rng],
    -                radar.time['data'][ind_ray], scan_angles, alt_tol=alt_tol,
    -                latlon_tol=latlon_tol, max_altitude=max_altitude)
    +                radar, target_radar,
    +                target_radar.azimuth['data'][trad_ind_ray],
    +                target_radar.range['data'][trad_ind_rng],
    +                target_radar.time['data'][trad_ind_ray], scan_angles,
    +                alt_tol=alt_tol, latlon_tol=latlon_tol,
    +                max_altitude=max_altitude,
    +                distance_upper_bound=distance_upper_bound,
    +                use_cKDTree=use_cKDTree)
     
                 w_vec = tadict['weightvec'][w_inds]
                 for field_name in field_names:
    @@ -1629,16 +1698,11 @@ 

    Source code for pyrad.proc.process_aux

     
                     # average field
                     target_radar.fields['avg_'+field_name]['data'][
    -                    np.unravel_index(
    -                        sample, (target_radar.nrays, target_radar.ngates))] = (
    -                            avg)
    +                    trad_ind_ray, trad_ind_rng] = avg
     
                     # npoints field
                     target_radar.fields['npoints_'+field_name]['data'][
    -                    np.unravel_index(
    -                        sample,
    -                        (target_radar.nrays, target_radar.ngates))] = (
    -                            nvals_valid)
    +                    trad_ind_ray, trad_ind_rng] = nvals_valid
     
                     # quantile fields
                     for quant, val in zip(tadict['quantiles'], qvals):
    @@ -1648,9 +1712,18 @@ 

    Source code for pyrad.proc.process_aux

                             'quant'+'{:02d}'.format(int(100*quant))+'_' +
                             field_name)
                         target_radar.fields[quant_field]['data'][
    -                        np.unravel_index(
    -                            sample,
    -                            (target_radar.nrays, target_radar.ngates))] = val
    +                        trad_ind_ray, trad_ind_rng] = val
    +
    +            tend = time()
    +
    +            print(
    +                'original radar indices (azi, rng): '+str(rad_ind_ray)+', ' +
    +                str(rad_ind_rng) +
    +                ' target radar indices (azi, rng): '+str(trad_ind_ray)+', ' +
    +                str(trad_ind_rng) +
    +                ' Samples done: '+str(sample)+'/'+str(rad_ind_rngs.size) +
    +                ' Time used: '+str(tend-tstart),
    +                end="\r", flush=True)
     
         return target_radar
     
    @@ -1705,9 +1778,9 @@ 

    Source code for pyrad.proc.process_aux

         elevation = get_metadata('elevation')
         metadata = dict()
     
    -    latitude = radar.latitude
    -    longitude = radar.longitude
    -    altitude = radar.altitude
    +    latitude = deepcopy(radar.latitude)
    +    longitude = deepcopy(radar.longitude)
    +    altitude = deepcopy(radar.altitude)
         if 'target_radar_pos' in dscfg:
             latitude['data'] = np.array(
                 [dscfg['target_radar_pos']['latitude']], dtype=np.float)
    @@ -1807,7 +1880,7 @@ 

    Navigation

  81. modules |
  82. - +
    diff --git a/docs/_modules/pyrad/proc/process_calib.html b/docs/_modules/pyrad/proc/process_calib.html index faeda3f..ef2cb58 100644 --- a/docs/_modules/pyrad/proc/process_calib.html +++ b/docs/_modules/pyrad/proc/process_calib.html @@ -6,7 +6,7 @@ - pyrad.proc.process_calib — pyrad 0.4.4 documentation + pyrad.proc.process_calib — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  83. modules |
  84. - +
    @@ -1102,9 +1102,6 @@

    Source code for pyrad.proc.process_calib

                 Default number of pulses used in the computation of the ray. If the
                 number of pulses is not in radar.instrument_parameters this will be
                 used instead. Used in Ivic method. Default 30
    -        flat_reg_wlen : int
    -            Length of the flat region window [m]. Used in Ivic method. Default
    -            8000.
             iterations: int
                 number of iterations in step 7 of Ivic method. Default 10.
             max_std_pwr : float. Dataset keyword
    @@ -1299,20 +1296,15 @@ 

    Source code for pyrad.proc.process_calib

                     pwrv_field=pwrv_field, zdr_field=zdr_field)
             else:
                 npulses_ray = dscfg.get('npulses_ray', 30)
    -            flat_reg_wlen_rng = dscfg.get('flat_reg_wlen', 8000.)
                 nbins_min = dscfg.get('nbins_min', 800)
                 iterations = dscfg.get('iterations', 10)
     
    -            r_res = radar.range['data'][1]-radar.range['data'][0]
    -            flat_reg_wlen = int(flat_reg_wlen_rng/r_res)
    -
                 sun_hits, new_radar = pyart.correct.get_sun_hits_ivic(
                     radar, delev_max=delev_max, dazim_max=dazim_max, elmin=elmin,
    -                npulses_ray=npulses_ray, flat_reg_wlen=flat_reg_wlen,
    -                nbins_min=nbins_min, iterations=iterations, attg=attg,
    -                max_std_zdr=max_std_zdr, sun_position=sun_position,
    -                pwrh_field=pwrh_field, pwrv_field=pwrv_field,
    -                zdr_field=zdr_field)
    +                npulses_ray=npulses_ray, nbins_min=nbins_min,
    +                iterations=iterations, attg=attg, max_std_zdr=max_std_zdr,
    +                sun_position=sun_position, pwrh_field=pwrh_field,
    +                pwrv_field=pwrv_field, zdr_field=zdr_field)
     
             if sun_hits is None:
                 return None, None
    @@ -1571,7 +1563,7 @@ 

    Navigation

  85. modules |
  86. - +
    diff --git a/docs/_modules/pyrad/proc/process_cosmo.html b/docs/_modules/pyrad/proc/process_cosmo.html index eb0a12c..f3c213d 100644 --- a/docs/_modules/pyrad/proc/process_cosmo.html +++ b/docs/_modules/pyrad/proc/process_cosmo.html @@ -6,7 +6,7 @@ - pyrad.proc.process_cosmo — pyrad 0.4.4 documentation + pyrad.proc.process_cosmo — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  87. modules |
  88. - +
    @@ -180,6 +180,12 @@

    Source code for pyrad.proc.process_cosmo

             warn('Unknown NWP model '+model)
             return None, None
     
    +    # check if model is cosmo-1 or cosmo-1e
    +    if model == 'cosmo-1':
    +        model_aux = os.path.basename(fname)[0:8]
    +        if model_aux == 'cosmo-1e':
    +            model = model_aux
    +
         if keep_in_memory:
             if dscfg['initialized'] == 0:
                 cosmo_coord = read_cosmo_coord(
    @@ -399,6 +405,7 @@ 

    Source code for pyrad.proc.process_cosmo

     
         return new_dataset, ind_rad
    + # @profile
    [docs]def process_cosmo_lookup_table(procstatus, dscfg, radar_list=None): """ @@ -483,10 +490,16 @@

    Source code for pyrad.proc.process_cosmo

             return None, None
     
         model = os.path.basename(fname)[0:7]
    -    if model not in ('cosmo-1', 'cosmo-2', 'cosmo-7'):
    +    if model not in ('cosmo-1', 'cosmo-1e', 'cosmo-2', 'cosmo-7'):
             warn('Unknown NWP model '+model)
             return None, None
     
    +    # check if model is cosmo-1 or cosmo-1e
    +    if model == 'cosmo-1':
    +        model_aux = os.path.basename(fname)[0:8]
    +        if model_aux == 'cosmo-1e':
    +            model = model_aux
    +
         if dscfg['initialized'] == 0:
             if lookup_table:
                 savedir = dscfg['cosmopath'][ind_rad]+'rad2cosmo/'
    @@ -817,10 +830,16 @@ 

    Source code for pyrad.proc.process_cosmo

             return None, None
     
         model = os.path.basename(fname)[0:7]
    -    if model not in ('cosmo-1', 'cosmo-2', 'cosmo-7'):
    +    if model not in ('cosmo-1', 'cosmo-1e', 'cosmo-2', 'cosmo-7'):
             warn('Unknown NWP model '+model)
             return None, None
     
    +    # check if model is cosmo-1 or cosmo-1e
    +    if model == 'cosmo-1':
    +        model_aux = os.path.basename(fname)[0:8]
    +        if model_aux == 'cosmo-1e':
    +            model = model_aux
    +
         if dscfg['initialized'] == 0:
             savedir = dscfg['cosmopath'][ind_rad]+'rad2cosmo/'
             fname_ind = 'rad2cosmo_cosmo_index_'+dscfg['procname']+'.nc'
    @@ -871,7 +890,8 @@ 

    Source code for pyrad.proc.process_cosmo

     
             radar_out = deepcopy(dscfg['global_data']['cosmo_radar'])
             radar_out.fields = dict()
    -        radar_out.time['units'] = dtc.strftime('seconds since %Y-%m-%dT%H:%M:%SZ')
    +        radar_out.time['units'] = dtc.strftime(
    +            'seconds since %Y-%m-%dT%H:%M:%SZ')
     
             for field in cosmo_fields:
                 for field_name in field:
    @@ -902,7 +922,7 @@ 

    Source code for pyrad.proc.process_cosmo

             cosmopath : string. General keyword
                 path where to store the look up table
             model : string. Dataset keyword
    -            The COSMO model to use. Can be cosmo-1, cosmo-2, cosmo-7
    +            The COSMO model to use. Can be cosmo-1, cosmo-1e, cosmo-2, cosmo-7
         radar_list : list of Radar objects
             Optional. list of radar objects
     
    @@ -930,11 +950,17 @@ 

    Source code for pyrad.proc.process_cosmo

             return None, None
         radar = radar_list[ind_rad]
     
    -    model = dscfg.get('model', 'cosmo-1')
    -    if model not in ('cosmo-1', 'cosmo-2', 'cosmo-7'):
    +    model = dscfg.get('model', 'cosmo-1e')
    +    if model not in ('cosmo-1', 'cosmo-1e', 'cosmo-2', 'cosmo-7'):
             warn('Unknown NWP model '+model)
             return None, None
     
    +    # check if model is cosmo-1 or cosmo-1e
    +    if model == 'cosmo-1':
    +        model_aux = os.path.basename(fname)[0:8]
    +        if model_aux == 'cosmo-1e':
    +            model = model_aux
    +
         cosmo_coord = read_cosmo_coord(
             dscfg['cosmopath'][ind_rad]+'rad2cosmo/'+model+'_MDR_3D_const.nc',
             zmin=None)
    @@ -1046,7 +1072,7 @@ 

    Navigation

  89. modules |
  90. - +
    diff --git a/docs/_modules/pyrad/proc/process_dem.html b/docs/_modules/pyrad/proc/process_dem.html index 31efd28..ba1e9b2 100644 --- a/docs/_modules/pyrad/proc/process_dem.html +++ b/docs/_modules/pyrad/proc/process_dem.html @@ -6,7 +6,7 @@ - pyrad.proc.process_dem — pyrad 0.4.4 documentation + pyrad.proc.process_dem — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  91. modules |
  92. - +
    @@ -83,7 +83,7 @@

    Source code for pyrad.proc.process_dem

     
     
    [docs]def process_dem(procstatus, dscfg, radar_list=None): """ - Gets COSMO data and put it in radar coordinates + Gets DEM data and put it in radar coordinates Parameters ---------- @@ -261,7 +261,7 @@

    Navigation

  93. modules |
  94. - +
    diff --git a/docs/_modules/pyrad/proc/process_echoclass.html b/docs/_modules/pyrad/proc/process_echoclass.html index 8baecfa..ed04c54 100644 --- a/docs/_modules/pyrad/proc/process_echoclass.html +++ b/docs/_modules/pyrad/proc/process_echoclass.html @@ -6,7 +6,7 @@ - pyrad.proc.process_echoclass — pyrad 0.4.4 documentation + pyrad.proc.process_echoclass — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  95. modules |
  96. - +
    @@ -360,11 +360,15 @@

    Source code for pyrad.proc.process_echoclass

    if procstatus != 1:
             return None, None
     
    +    echoid_field = None
         for datatypedescr in dscfg['datatype']:
             radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr)
             if datatype == 'echoID':
                 echoid_field = get_fieldname_pyart(datatype)
                 break
    +    if echoid_field is None:
    +        warn('echoID field required to filter data')
    +        return None, None
     
         ind_rad = int(radarnr[5:8])-1
         if radar_list[ind_rad] is None:
    @@ -572,7 +576,6 @@ 

    Source code for pyrad.proc.process_echoclass

    new_field_name = 'corrected_'+field_name
             new_dataset['radar_out'].add_field(new_field_name, radar_field)
     
    -
         if not new_dataset['radar_out'].fields:
             return None, None
     
    @@ -1491,7 +1494,8 @@ 

    Source code for pyrad.proc.process_echoclass

    zdr_dict['data'], wind_len=smooth_window_len, min_valid=1,
                 wind_type='mean')
     
    -    zdr_dict['data'][radar.fields[rhv_field]['data'] < rhohv_min] = np.ma.masked
    +    zdr_dict['data'][
    +        radar.fields[rhv_field]['data'] < rhohv_min] = np.ma.masked
         zdr_dict['data'][zdr_dict['data'] < zdr_min] = np.ma.masked
         zdr_dict['data'][radar.fields[temp_field]['data'] > 0.] = np.ma.masked
         zdr_valid = np.logical_not(np.ma.getmaskarray(zdr_dict['data']))
    @@ -1561,12 +1565,13 @@ 

    Source code for pyrad.proc.process_echoclass

    # put data in output array
                 lat_cols = np.append(
    -                lat_cols, radar.gate_latitude['data'][ind_ray_col, ind_rng_col])
    +                lat_cols,
    +                radar.gate_latitude['data'][ind_ray_col, ind_rng_col])
                 lon_cols = np.append(
    -                lon_cols, radar.gate_longitude['data'][ind_ray_col, ind_rng_col])
    +                lon_cols,
    +                radar.gate_longitude['data'][ind_ray_col, ind_rng_col])
                 zdr_cols = np.append(zdr_cols, zdr_col)
     
    -
         zdr_col_dict = pyart.config.get_metadata(
             'differential_reflectivity_column_height')
         zdr_col_dict['data'] = zdr_cols/1000.
    @@ -1597,7 +1602,7 @@ 

    Navigation

  97. modules |
  98. - +
    diff --git a/docs/_modules/pyrad/proc/process_grid.html b/docs/_modules/pyrad/proc/process_grid.html index d76ee6d..7d5c376 100644 --- a/docs/_modules/pyrad/proc/process_grid.html +++ b/docs/_modules/pyrad/proc/process_grid.html @@ -6,7 +6,7 @@ - pyrad.proc.process_grid — pyrad 0.4.4 documentation + pyrad.proc.process_grid — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  99. modules |
  100. - +
    @@ -68,6 +68,11 @@

    Source code for pyrad.proc.process_grid

         process_grid_point
         process_grid_time_stats
         process_grid_time_stats2
    +    process_grid_fields_diff
    +    process_grid_texture
    +    process_grid_mask
    +    process_normalize_luminosity
    +    process_pixel_filter
     
     """
     
    @@ -349,6 +354,7 @@ 

    Source code for pyrad.proc.process_grid

             # prepare for exit
             new_dataset = {
                 'time': dscfg['global_data']['time'],
    +            'ref_time': dscfg['global_data']['ref_time'],
                 'datatype': datatype,
                 'point_coordinates_WGS84_lon_lat_alt': (
                     dscfg['global_data']['point_coordinates_WGS84_lon_lat_alt']),
    @@ -422,15 +428,19 @@ 

    Source code for pyrad.proc.process_grid

             poi = {
                 'point_coordinates_WGS84_lon_lat_alt': [lon, lat, alt],
                 'grid_points_iz_iy_ix': [iz, iy, ix],
    -            'time': time}
    +            'time': time,
    +            'ref_time': dscfg['timeinfo']}
             dscfg['global_data'] = poi
             dscfg['initialized'] = 1
     
    +    dscfg['global_data']['ref_time'] = dscfg['timeinfo']
    +
         # prepare for exit
         new_dataset = dict()
         new_dataset.update({'value': val})
         new_dataset.update({'datatype': datatype})
         new_dataset.update({'time': time})
    +    new_dataset.update({'ref_time': dscfg['timeinfo']})
         new_dataset.update(
             {'point_coordinates_WGS84_lon_lat_alt': [lon, lat, alt]})
         new_dataset.update({'grid_points_iz_iy_ix': [iz, iy, ix]})
    @@ -752,7 +762,7 @@ 

    Source code for pyrad.proc.process_grid

     
     
    [docs]def process_grid_time_stats2(procstatus, dscfg, radar_list=None): """ - computes the temporal mean of a field + computes temporal statistics of a field Parameters ---------- @@ -816,7 +826,8 @@

    Source code for pyrad.proc.process_grid

             # prepare auxiliary radar
             field_dict = deepcopy(grid.fields[field_name])
             if use_nan:
    -            field_dict['data'] = np.ma.asarray(field_dict['data'].filled(nan_value))
    +            field_dict['data'] = np.ma.asarray(
    +                field_dict['data'].filled(nan_value))
             npoints_dict = pyart.config.get_metadata('number_of_samples')
             npoints_dict['data'] = np.ma.asarray(
                 np.logical_not(np.ma.getmaskarray(field_dict['data'])), dtype=int)
    @@ -961,6 +972,371 @@ 

    Source code for pyrad.proc.process_grid

                 'timeinfo': dscfg['global_data']['endtime']}
     
             return new_dataset, ind_rad
    + + +
    [docs]def process_grid_fields_diff(procstatus, dscfg, radar_list=None): + """ + Computes grid field differences + + Parameters + ---------- + procstatus : int + Processing status: 0 initializing, 1 processing volume, + 2 post-processing + dscfg : dictionary of dictionaries + data set configuration. Accepted Configuration Keywords:: + + datatype : list of string. Dataset keyword + The input data types + radar_list : list of Radar objects + Optional. list of radar objects + + Returns + ------- + new_dataset : dict + dictionary containing a radar object containing the field differences + ind_rad : int + radar index + + """ + if procstatus != 1: + return None, None + + # create the list of data types for each radar + if len(dscfg['datatype']) != 2: + warn( + 'Two and only two fields are required to compute the field' + ' differences') + return None, None + + radarnr, _, datatype, _, _ = get_datatype_fields(dscfg['datatype'][0]) + field_name_1 = get_fieldname_pyart(datatype) + + radarnr, _, datatype, _, _ = get_datatype_fields(dscfg['datatype'][1]) + field_name_2 = get_fieldname_pyart(datatype) + + ind_rad = int(radarnr[5:8])-1 + if radar_list[ind_rad] is None: + warn('No valid radar') + return None, None + + grid = radar_list[ind_rad] + if ((field_name_1 not in grid.fields) or + (field_name_2 not in grid.fields)): + warn('Unable to compare fields '+field_name_1+'and '+field_name_2 + + '. Fields missings') + return None, None + + field_diff = pyart.config.get_metadata('fields_difference') + field_diff['data'] = ( + grid.fields[field_name_1]['data'] - + grid.fields[field_name_2]['data']) + field_diff['long_name'] = field_name_1+' - '+field_name_2 + + grid_diff = deepcopy(grid) + grid_diff.fields = dict() + grid_diff.add_field('fields_difference', field_diff) + + new_dataset = {'radar_out': grid_diff} + + return new_dataset, ind_rad
    + + +
    [docs]def process_grid_texture(procstatus, dscfg, radar_list=None): + """ + Computes the 2D texture of a gridded field + + Parameters + ---------- + procstatus : int + Processing status: 0 initializing, 1 processing volume, + 2 post-processing + dscfg : dictionary of dictionaries + data set configuration. Accepted Configuration Keywords:: + + datatype : list of string. Dataset keyword + The input data types + xwind, ywind : int + The size of the local window in the x and y axis. Default 7 + fill_value : float + The value with which to fill masked data. Default np.NaN + radar_list : list of Radar objects + Optional. list of radar objects + + Returns + ------- + new_dataset : dict + dictionary containing a radar object containing the field differences + ind_rad : int + radar index + + """ + if procstatus != 1: + return None, None + + # create the list of data types for each radar + if len(dscfg['datatype']) != 1: + warn('Texture can only be computed on one field') + return None, None + + radarnr, _, datatype, _, _ = get_datatype_fields(dscfg['datatype'][0]) + field_name = get_fieldname_pyart(datatype) + + ind_rad = int(radarnr[5:8])-1 + if radar_list[ind_rad] is None: + warn('No valid radar') + return None, None + + grid = radar_list[ind_rad] + if field_name not in grid.fields: + warn('Unable to compute field '+field_name+' texture. Field missing') + return None, None + + xwind = dscfg.get('xwind', 7) + ywind = dscfg.get('ywind', 7) + fill_value = dscfg.get('fill_value', np.NaN) + + field_text = pyart.config.get_metadata('field_texture') + field_text['data'] = np.ma.masked_all( + (grid.nz, grid.ny, grid.nx), + dtype=grid.fields[field_name]['data'].dtype) + + for level in range(grid.nz): + field_array = deepcopy(grid.fields[field_name]['data'][level, :, :]) + field_array = field_array.filled(fill_value=fill_value) + field_text['data'][level, :, :] = pyart.util.grid_texture_2d( + field_array, xwind=xwind, ywind=ywind) + + grid_text = deepcopy(grid) + grid_text.fields = dict() + grid_text.add_field('field_texture', field_text) + + new_dataset = {'radar_out': grid_text} + + return new_dataset, ind_rad
    + + +
    [docs]def process_grid_mask(procstatus, dscfg, radar_list=None): + """ + Mask data. Puts True if data is above a certain threshold and false + otherwise. + + Parameters + ---------- + procstatus : int + Processing status: 0 initializing, 1 processing volume, + 2 post-processing + dscfg : dictionary of dictionaries + data set configuration + radar_list : list of Radar objects + Optional. list of radar objects + threshold : float + Threshold used for the mask. Values below threshold are set to False. + Above threshold are set to True. Default 0. + x_dir_ext, y_dir_ext : int + Number of pixels by which to extend the mask on each side of the + west-east direction and south-north direction + + Returns + ------- + new_dataset : dict + dictionary containing the output + ind_rad : int + radar index + + """ + + if procstatus != 1: + return None, None + + radarnr, _, datatype, _, _ = get_datatype_fields(dscfg['datatype'][0]) + field_name = get_fieldname_pyart(datatype) + + ind_rad = int(radarnr[5:8])-1 + if (radar_list is None) or (radar_list[ind_rad] is None): + warn('ERROR: No valid radar') + return None, None + + grid = radar_list[ind_rad] + + if field_name not in grid.fields: + warn('Unable to mask field '+field_name+' Field missing in grid') + return None, None + + threshold = dscfg.get('threshold', 0.) + x_dir_ext = dscfg.get('x_dir_ext', 0) + y_dir_ext = dscfg.get('y_dir_ext', 0) + + field_mask = pyart.config.get_metadata('field_mask') + field_mask['data'] = np.ma.masked_all( + (grid.nz, grid.ny, grid.nx), dtype=np.int8) + field_mask['data'][:] = 0 + valid = np.logical_not(np.ma.getmaskarray(grid.fields[field_name]['data'])) + field_mask['data'][valid] = 1 + field_mask['data'][grid.fields[field_name]['data'] >= threshold] = 2 + field_mask['long_name'] = field_name+' threshold '+str(threshold) + + if x_dir_ext > 0 or y_dir_ext > 0: + ind_z, ind_y, ind_x = np.where(field_mask['data'] == 2) + + if ind_z.size > 0: + for z, y, x in zip(ind_z, ind_y, ind_x): + field_mask['data'][ + 0, y-y_dir_ext:y+y_dir_ext+1, + x-x_dir_ext:x+x_dir_ext+1] = 2 + + grid_mask = deepcopy(grid) + grid_mask.fields = dict() + grid_mask.add_field('field_mask', field_mask) + + new_dataset = {'radar_out': grid_mask} + + return new_dataset, ind_rad
    + + +
    [docs]def process_normalize_luminosity(procstatus, dscfg, radar_list=None): + """ + Normalize the data by the sinus of the sun elevation. The sun elevation is + computed at the central pixel. + + Parameters + ---------- + procstatus : int + Processing status: 0 initializing, 1 processing volume, + 2 post-processing + dscfg : dictionary of dictionaries + data set configuration + radar_list : list of Radar objects + Optional. list of radar objects + + Returns + ------- + new_dataset : dict + dictionary containing the output + ind_rad : int + radar index + + """ + + if procstatus != 1: + return None, None + + radarnr, _, _, _, _ = get_datatype_fields(dscfg['datatype'][0]) + ind_rad = int(radarnr[5:8])-1 + if (radar_list is None) or (radar_list[ind_rad] is None): + warn('ERROR: No valid radar') + return None, None + + grid = radar_list[ind_rad] + + # get normalization factor + lat_point = grid.point_latitude['data'][0, int(grid.ny/2), int(grid.nx/2)] + lon_point = grid.point_longitude['data'][ + 0, int(grid.ny/2), int(grid.nx/2)] + + el_sun, _ = pyart.correct.sun_position_pysolar( + dscfg['timeinfo'], lat_point, lon_point) + norm = np.sin(np.deg2rad(el_sun)) + + grid_norm = deepcopy(grid) + grid_norm.fields = dict() + + for datatypedescr in dscfg['datatype']: + radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr) + field_name = get_fieldname_pyart(datatype) + + if field_name not in grid.fields: + warn('Unable to normalize field '+field_name + + '. Field missing in grid') + continue + + norm_field = pyart.config.get_metadata(field_name+'_norm') + norm_field['data'] = grid.fields[field_name]['data']/norm + + grid_norm.add_field(field_name+'_norm', norm_field) + + new_dataset = {'radar_out': grid_norm} + + return new_dataset, ind_rad
    + + +
    [docs]def process_pixel_filter(procstatus, dscfg, radar_list=None): + """ + Masks all pixels that are not of the class specified in keyword pixel_type + + Parameters + ---------- + procstatus : int + Processing status: 0 initializing, 1 processing volume, + 2 post-processing + dscfg : dictionary of dictionaries + data set configuration. Accepted Configuration Keywords:: + + pixel_type : int or list of ints + The type of pixels to keep: 0 No data, 1 Below threshold, 2 Above + threshold. Default 2 + radar_list : list of Radar objects + Optional. list of radar objects + + Returns + ------- + new_dataset : dict + dictionary containing the output + ind_rad : int + radar index + + """ + + if procstatus != 1: + return None, None + + mask_field = None + for datatypedescr in dscfg['datatype']: + radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr) + if datatype == 'mask': + mask_field = get_fieldname_pyart(datatype) + break + if mask_field is None: + warn('mask field required to filter data') + return None, None + + ind_rad = int(radarnr[5:8])-1 + if (radar_list is None) or (radar_list[ind_rad] is None): + warn('ERROR: No valid radar') + return None, None + + grid = radar_list[ind_rad] + + if mask_field not in grid.fields: + warn('Unable to filter data. Missing mask field') + return None, None + + pixel_type = dscfg.get('pixel_type', 2) + mask = np.ma.isin( + grid.fields[mask_field]['data'], pixel_type, invert=True) + + grid_mask = deepcopy(grid) + grid_mask.fields = dict() + + for datatypedescr in dscfg['datatype']: + radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr) + if datatype == 'mask': + continue + + field_name = get_fieldname_pyart(datatype) + if field_name not in grid.fields: + warn('Unable to normalize field '+field_name + + '. Field missing in grid') + continue + + field = deepcopy(grid.fields[field_name]) + field['data'] = np.ma.masked_where(mask, field['data']) + + grid_mask.add_field(field_name, field) + + new_dataset = {'radar_out': grid_mask} + + return new_dataset, ind_rad
    @@ -977,7 +1353,7 @@

    Navigation

  101. modules |
  102. - +
    diff --git a/docs/_modules/pyrad/proc/process_intercomp.html b/docs/_modules/pyrad/proc/process_intercomp.html index f171b0b..6f32445 100644 --- a/docs/_modules/pyrad/proc/process_intercomp.html +++ b/docs/_modules/pyrad/proc/process_intercomp.html @@ -6,7 +6,7 @@ - pyrad.proc.process_intercomp — pyrad 0.4.4 documentation + pyrad.proc.process_intercomp — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  103. modules |
  104. - +
    @@ -2205,12 +2205,14 @@

    Source code for pyrad.proc.process_intercomp

    '. Field missing in one of the radars')
             return None, None
     
    -    rad_diff = deepcopy(radar1)
    -    rad_diff.fields = dict()
         field_diff = pyart.config.get_metadata('fields_difference')
         field_diff['data'] = (
             radar1.fields[field_name_1]['data'] -
             radar2.fields[field_name_2]['data'])
    +    field_diff['long_name'] = field_name_1+' - '+field_name_2
    +
    +    rad_diff = deepcopy(radar1)
    +    rad_diff.fields = dict()
         rad_diff.add_field('fields_difference', field_diff)
     
         new_dataset = {'radar_out': rad_diff}
    @@ -2316,7 +2318,7 @@ 

    Navigation

  105. modules |
  106. - +
    diff --git a/docs/_modules/pyrad/proc/process_iq.html b/docs/_modules/pyrad/proc/process_iq.html index c56c295..10cac23 100644 --- a/docs/_modules/pyrad/proc/process_iq.html +++ b/docs/_modules/pyrad/proc/process_iq.html @@ -6,7 +6,7 @@ - pyrad.proc.process_iq — pyrad 0.4.4 documentation + pyrad.proc.process_iq — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  107. modules |
  108. - +
    @@ -954,7 +954,7 @@

    Navigation

  109. modules |
  110. - +
    diff --git a/docs/_modules/pyrad/proc/process_monitoring.html b/docs/_modules/pyrad/proc/process_monitoring.html index 629b887..27642b5 100644 --- a/docs/_modules/pyrad/proc/process_monitoring.html +++ b/docs/_modules/pyrad/proc/process_monitoring.html @@ -6,7 +6,7 @@ - pyrad.proc.process_monitoring — pyrad 0.4.4 documentation + pyrad.proc.process_monitoring — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  111. modules |
  112. - +
    @@ -1671,7 +1671,7 @@

    Navigation

  113. modules |
  114. - +
    diff --git a/docs/_modules/pyrad/proc/process_phase.html b/docs/_modules/pyrad/proc/process_phase.html index 36f32cc..191bd76 100644 --- a/docs/_modules/pyrad/proc/process_phase.html +++ b/docs/_modules/pyrad/proc/process_phase.html @@ -6,7 +6,7 @@ - pyrad.proc.process_phase — pyrad 0.4.4 documentation + pyrad.proc.process_phase — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  115. modules |
  116. - +
    @@ -1136,6 +1136,7 @@

    Source code for pyrad.proc.process_phase

     
         temp = None
         iso0 = None
    +    zdr = None
         for datatypedescr in dscfg['datatype']:
             radarnr, _, datatype, _, _ = get_datatype_fields(datatypedescr)
             if datatype == 'dBZc':
    @@ -1161,9 +1162,7 @@ 

    Source code for pyrad.proc.process_phase

             return None, None
         radar = radar_list[ind_rad]
     
    -    if ((phidp not in radar.fields) or
    -            (refl not in radar.fields) or
    -            (zdr not in radar.fields)):
    +    if phidp not in radar.fields or refl not in radar.fields:
             warn('Unable to compute attenuation. Missing data')
             return None, None
     
    @@ -1257,7 +1256,7 @@ 

    Navigation

  117. modules |
  118. - +
    diff --git a/docs/_modules/pyrad/proc/process_retrieve.html b/docs/_modules/pyrad/proc/process_retrieve.html index bf0d78f..840b60f 100644 --- a/docs/_modules/pyrad/proc/process_retrieve.html +++ b/docs/_modules/pyrad/proc/process_retrieve.html @@ -6,7 +6,7 @@ - pyrad.proc.process_retrieve — pyrad 0.4.4 documentation + pyrad.proc.process_retrieve — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  119. modules |
  120. - +
    @@ -748,8 +748,6 @@

    Source code for pyrad.proc.process_retrieve

                 Default number of pulses used in the computation of the ray. If
                 the number of pulses is not in radar.instrument_parameters this
                 will be used instead. Default 30
    -        flat_reg_wlen : int
    -            range of window considered to find flat regions [m]. Default 8000.
             ngates_min: int
                 minimum number of gates with noise to consider the retrieval
                 valid. Default 800
    @@ -788,14 +786,10 @@ 

    Source code for pyrad.proc.process_retrieve

     
         # user values
         npulses_ray = dscfg.get('npulses_ray', 30)
    -    flat_reg_wlen_rng = dscfg.get('flat_reg_wlen', 8000.)
         ngates_min = dscfg.get('ngates_min', 800)
         iterations = dscfg.get('iterations', 10)
         get_noise_pos = dscfg.get('get_noise_pos', False)
     
    -    r_res = radar.range['data'][1]-radar.range['data'][0]
    -    flat_reg_wlen = int(flat_reg_wlen_rng/r_res)
    -
         if 'hh' in pwr_field:
             noise_field = 'noisedBm_hh'
             noise_pos_field = 'noise_pos_h'
    @@ -804,8 +798,8 @@ 

    Source code for pyrad.proc.process_retrieve

             noise_pos_field = 'noise_pos_v'
     
         noise, noise_pos = pyart.retrieve.compute_radial_noise_ivic(
    -        radar, npulses_ray=npulses_ray, flat_reg_wlen=flat_reg_wlen,
    -        ngates_min=ngates_min, iterations=iterations, noise_field=noise_field,
    +        radar, npulses_ray=npulses_ray, ngates_min=ngates_min,
    +        iterations=iterations, pwr_field=pwr_field, noise_field=noise_field,
             get_noise_pos=get_noise_pos)
     
         # prepare for exit
    @@ -1478,7 +1472,7 @@ 

    Navigation

  121. modules |
  122. - +
    diff --git a/docs/_modules/pyrad/proc/process_spectra.html b/docs/_modules/pyrad/proc/process_spectra.html index 106c992..ea751cb 100644 --- a/docs/_modules/pyrad/proc/process_spectra.html +++ b/docs/_modules/pyrad/proc/process_spectra.html @@ -6,7 +6,7 @@ - pyrad.proc.process_spectra — pyrad 0.4.4 documentation + pyrad.proc.process_spectra — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  123. modules |
  124. - +
    @@ -233,6 +233,11 @@

    Source code for pyrad.proc.process_spectra

     
             datatype : string. Dataset keyword
                 The data type where we want to extract the point measurement
    +        single_point : boolean. Dataset keyword
    +            if True only one gate per radar volume is going to be kept.
    +            Otherwise all gates within the azimuth and elevation tolerance
    +            are going to be kept. This is useful to extract all data from
    +            fixed pointing scans. Default True
             latlon : boolean. Dataset keyword
                 if True position is obtained from latitude, longitude information,
                 otherwise position is obtained from antenna coordinates
    @@ -314,6 +319,7 @@ 

    Source code for pyrad.proc.process_spectra

         truealt = dscfg.get('truealt', True)
         latlon = dscfg.get('latlon', False)
     
    +    single_point = dscfg.get('single_point', True)
         if latlon:
             lon = dscfg['lon']
             lat = dscfg['lat']
    @@ -355,36 +361,46 @@ 

    Source code for pyrad.proc.process_spectra

             lon = lon[0]
             lat = lat[0]
     
    -    d_az = np.min(np.abs(psr.azimuth['data'] - az))
    -    if d_az > azi_tol:
    +    d_az = np.abs(psr.azimuth['data'] - az)
    +    if np.min(d_az) > azi_tol:
             warn(' No psr bin found for point (az, el, r):(' +
                  str(az)+', '+str(el)+', '+str(r) +
                  '). Minimum distance to psr azimuth '+str(d_az) +
                  ' larger than tolerance')
             return None, None
     
    -    d_el = np.min(np.abs(psr.elevation['data'] - el))
    -    if d_el > ele_tol:
    +    d_el = np.abs(psr.elevation['data'] - el)
    +    if np.min(d_el) > ele_tol:
             warn(' No psr bin found for point (az, el, r):(' +
                  str(az)+', '+str(el)+', '+str(r) +
                  '). Minimum distance to psr elevation '+str(d_el) +
                  ' larger than tolerance')
             return None, None
     
    -    d_r = np.min(np.abs(psr.range['data'] - r))
    -    if d_r > rng_tol:
    +    d_r = np.abs(psr.range['data'] - r)
    +    if np.min(d_r) > rng_tol:
             warn(' No psr bin found for point (az, el, r):(' +
                  str(az)+', '+str(el)+', '+str(r) +
                  '). Minimum distance to psr range bin '+str(d_r) +
                  ' larger than tolerance')
             return None, None
     
    -    ind_ray = np.argmin(np.abs(psr.azimuth['data'] - az) +
    -                        np.abs(psr.elevation['data'] - el))
    +    if single_point:
    +        ind_ray = np.argmin(np.abs(psr.azimuth['data'] - az) +
    +                            np.abs(psr.elevation['data'] - el))
    +    else:
    +        ind_ray = np.where(np.logical_and(
    +            d_az <= azi_tol, d_el <= ele_tol))[0]
         ind_rng = np.argmin(np.abs(psr.range['data'] - r))
    +    nrays = ind_ray.size
     
         time_poi = num2date(psr.time['data'][ind_ray], psr.time['units'],
                             psr.time['calendar'])
    +    if nrays > 1:
    +        time_ref = time_poi[0]
    +    else:
    +        time_ref = time_poi
    +        time_poi = np.array([time_poi])
     
         # initialize dataset
         if not dscfg['initialized']:
    @@ -393,6 +409,9 @@ 

    Source code for pyrad.proc.process_spectra

             # prepare space for field
             psr_poi.fields = dict()
             for field_name in field_names:
    +            if field_name not in psr.fields:
    +                warn('Field '+field_name+' not in psr object')
    +                return None, None
                 psr_poi.add_field(field_name, deepcopy(psr.fields[field_name]))
                 psr_poi.fields[field_name]['data'] = np.array([])
     
    @@ -400,7 +419,7 @@ 

    Source code for pyrad.proc.process_spectra

             psr_poi.range['data'] = np.array([r])
             psr_poi.ngates = 1
     
    -        psr_poi.time['units'] = pyart.io.make_time_unit_str(time_poi)
    +        psr_poi.time['units'] = pyart.io.make_time_unit_str(time_ref)
             psr_poi.time['data'] = np.array([])
             psr_poi.scan_type = 'poi_time_series'
             psr_poi.sweep_number['data'] = np.array([], dtype=np.int32)
    @@ -431,15 +450,18 @@ 

    Source code for pyrad.proc.process_spectra

             dscfg['initialized'] = 1
     
         psr_poi = dscfg['global_data']['psr_poi']
    +    psr_poi.sweep_end_ray_index['data'][0] += nrays
    +    psr_poi.rays_per_sweep['data'][0] += nrays
    +    psr_poi.nrays += nrays
    +    psr_poi.azimuth['data'] = np.append(
    +        psr_poi.azimuth['data'], np.zeros(nrays)+az)
    +    psr_poi.elevation['data'] = np.append(
    +        psr_poi.elevation['data'], np.zeros(nrays)+el)
         start_time = num2date(
             0, psr_poi.time['units'], psr_poi.time['calendar'])
    -    psr_poi.time['data'] = np.append(
    -        psr_poi.time['data'], (time_poi - start_time).total_seconds())
    -    psr_poi.sweep_end_ray_index['data'][0] += 1
    -    psr_poi.rays_per_sweep['data'][0] += 1
    -    psr_poi.nrays += 1
    -    psr_poi.azimuth['data'] = np.append(psr_poi.azimuth['data'], az)
    -    psr_poi.elevation['data'] = np.append(psr_poi.elevation['data'], el)
    +    for i in range(nrays):
    +        psr_poi.time['data'] = np.append(
    +            psr_poi.time['data'], (time_poi[i] - start_time).total_seconds())
     
         psr_poi.gate_longitude['data'] = (
             np.ones((psr_poi.nrays, psr_poi.ngates), dtype='float64')*lon)
    @@ -449,34 +471,37 @@ 

    Source code for pyrad.proc.process_spectra

             alt, (psr_poi.nrays, psr_poi.ngates))
     
         for field_name in field_names:
    -        dtype = psr.fields[field_name]['data'].dtype
    +        dtype = psr_poi.fields[field_name]['data'].dtype
             if field_name not in psr.fields:
                 warn('Field '+field_name+' not in psr object')
    -            poi_data = np.ma.masked_all((1, 1, psr.npulses_max), dtype=dtype)
    +            poi_data = np.ma.masked_all(
    +                (nrays, 1, psr.npulses_max), dtype=dtype)
             else:
                 poi_data = psr.fields[field_name]['data'][ind_ray, ind_rng, :]
    -            poi_data = poi_data.reshape(1, 1, psr.npulses_max)
    +            poi_data = poi_data.reshape(nrays, 1, psr.npulses_max)
     
             # Put data in radar object
             if np.size(psr_poi.fields[field_name]['data']) == 0:
                 psr_poi.fields[field_name]['data'] = poi_data.reshape(
    -                1, 1, psr_poi.npulses_max)
    +                nrays, 1, psr_poi.npulses_max)
             else:
                 if psr_poi.npulses_max == psr.npulses_max:
                     psr_poi.fields[field_name]['data'] = np.ma.append(
                         psr_poi.fields[field_name]['data'], poi_data, axis=0)
                 elif psr.npulses_max < psr_poi.npulses_max:
                     poi_data_aux = np.ma.masked_all(
    -                    (1, 1, psr_poi.npulses_max), dtype=dtype)
    -                poi_data_aux[0, 0, 0:psr.npulses_max] = poi_data
    +                    (nrays, 1, psr_poi.npulses_max), dtype=dtype)
    +                for i in range(nrays):
    +                    poi_data_aux[i, 0, 0:psr.npulses_max] = poi_data[i, 0, :]
                     psr_poi.fields[field_name]['data'] = np.ma.append(
                         psr_poi.fields[field_name]['data'], poi_data_aux, axis=0)
                 else:
                     poi_data_aux = np.ma.masked_all(
                         (psr_poi.nrays, 1, psr.npulses_max), dtype=dtype)
    -                poi_data_aux[0:psr_poi.nrays-1, :, 0:psr_poi.npulses_max] = (
    -                    psr_poi.fields[field_name]['data'])
    -                poi_data_aux[psr_poi.nrays-1, :, :] = poi_data
    +                poi_data_aux[
    +                    :psr_poi.nrays-nrays, :, 0:psr_poi.npulses_max] = (
    +                        psr_poi.fields[field_name]['data'])
    +                poi_data_aux[psr_poi.nrays-nrays:, :, :] = poi_data
                     psr_poi.fields[field_name]['data'] = poi_data_aux
     
         psr_poi.npulses['data'] = np.append(
    @@ -485,52 +510,54 @@ 

    Source code for pyrad.proc.process_spectra

             if np.size(psr_poi.Doppler_velocity['data']) == 0:
                 psr_poi.Doppler_velocity['data'] = (
                     psr.Doppler_velocity['data'][ind_ray, :].reshape(
    -                    1, psr_poi.npulses_max))
    +                    nrays, psr_poi.npulses_max))
             else:
                 Doppler_data = psr.Doppler_velocity['data'][ind_ray, :]
    -            Doppler_data = Doppler_data.reshape(1, psr.npulses_max)
    +            Doppler_data = Doppler_data.reshape(nrays, psr.npulses_max)
     
                 if psr_poi.npulses_max == psr.npulses_max:
                     psr_poi.Doppler_velocity['data'] = np.ma.append(
                         psr_poi.Doppler_velocity['data'],
                         Doppler_data, axis=0)
                 elif psr.npulses_max < psr_poi.npulses_max:
    -                Doppler_aux = np.ma.masked_all((1, psr_poi.npulses_max))
    -                Doppler_aux[0, 0:psr.npulses_max] = Doppler_data
    +                Doppler_aux = np.ma.masked_all((nrays, psr_poi.npulses_max))
    +                for i in range(nrays):
    +                    Doppler_aux[i, 0:psr.npulses_max] = Doppler_data[i, :]
                     psr_poi.Doppler_velocity['data'] = np.ma.append(
                         psr_poi.Doppler_velocity['data'], Doppler_aux, axis=0)
                 else:
                     Doppler_aux = np.ma.masked_all(
                         (psr_poi.nrays, psr.npulses_max))
    -                Doppler_aux[0:psr_poi.nrays-1, 0:psr_poi.npulses_max] = (
    +                Doppler_aux[:psr_poi.nrays-nrays, 0:psr_poi.npulses_max] = (
                         psr_poi.Doppler_velocity['data'])
    -                Doppler_aux[psr_poi.nrays-1, :] = Doppler_data
    +                Doppler_aux[psr_poi.nrays-nrays:, :] = Doppler_data
                     psr_poi.Doppler_velocity['data'] = Doppler_aux
     
         if psr_poi.Doppler_frequency is not None:
             if np.size(psr_poi.Doppler_frequency['data']) == 0:
                 psr_poi.Doppler_frequency['data'] = (
                     psr.Doppler_frequency['data'][ind_ray, :].reshape(
    -                    1, psr_poi.npulses_max))
    +                    nrays, psr_poi.npulses_max))
             else:
                 Doppler_data = psr.Doppler_frequency['data'][ind_ray, :]
    -            Doppler_data = Doppler_data.reshape(1, psr.npulses_max)
    +            Doppler_data = Doppler_data.reshape(nrays, psr.npulses_max)
     
                 if psr_poi.npulses_max == psr.npulses_max:
                     psr_poi.Doppler_frequency['data'] = np.ma.append(
                         psr_poi.Doppler_frequency['data'],
                         Doppler_data, axis=0)
                 elif psr.npulses_max < psr_poi.npulses_max:
    -                Doppler_aux = np.ma.masked_all((1, psr_poi.npulses_max))
    -                Doppler_aux[0, 0:psr.npulses_max] = Doppler_data
    +                Doppler_aux = np.ma.masked_all((nrays, psr_poi.npulses_max))
    +                for i in range(nrays):
    +                    Doppler_aux[i, 0:psr.npulses_max] = Doppler_data[i, :]
                     psr_poi.Doppler_frequency['data'] = np.ma.append(
                         psr_poi.Doppler_frequency['data'], Doppler_aux, axis=0)
                 else:
                     Doppler_aux = np.ma.masked_all(
                         (psr_poi.nrays, psr.npulses_max))
    -                Doppler_aux[0:psr_poi.nrays-1, 0:psr_poi.npulses_max] = (
    +                Doppler_aux[0:psr_poi.nrays-nrays, 0:psr_poi.npulses_max] = (
                         psr_poi.Doppler_frequency['data'])
    -                Doppler_aux[psr_poi.nrays-1, :] = Doppler_data
    +                Doppler_aux[psr_poi.nrays-nrays:, :] = Doppler_data
                     psr_poi.Doppler_frequency['data'] = Doppler_aux
     
         psr_poi.npulses_max = max(psr_poi.npulses_max, psr.npulses_max)
    @@ -1436,10 +1463,10 @@ 

    Source code for pyrad.proc.process_spectra

             datatype : list of string. Dataset keyword
                 The input data types
             subtract_noise : Bool
    -            If True noise will be subtracted from the signal
    +            If True noise will be subtracted from the signal. Default False
             smooth_window : int or None
                 Size of the moving Gaussian smoothing window. If none no smoothing
    -            will be applied
    +            will be applied. Default None
             variables : list of str
                 list of variables to compute. Default dBZ
         radar_list : list of spectra objects
    @@ -2012,7 +2039,7 @@ 

    Navigation

  125. modules |
  126. - +
    diff --git a/docs/_modules/pyrad/proc/process_timeseries.html b/docs/_modules/pyrad/proc/process_timeseries.html index aa6595e..a958722 100644 --- a/docs/_modules/pyrad/proc/process_timeseries.html +++ b/docs/_modules/pyrad/proc/process_timeseries.html @@ -6,7 +6,7 @@ - pyrad.proc.process_timeseries — pyrad 0.4.4 documentation + pyrad.proc.process_timeseries — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  127. modules |
  128. - +
    @@ -96,6 +96,11 @@

    Source code for pyrad.proc.process_timeseries

    datatype : string. Dataset keyword The data type where we want to extract the point measurement + single_point : boolean. Dataset keyword + if True only one gate per radar volume is going to be kept. + Otherwise all gates within the azimuth and elevation tolerance + are going to be kept. This is useful to extract all data from + fixed pointing scans. Default True latlon : boolean. Dataset keyword if True position is obtained from latitude, longitude information, otherwise position is obtained from antenna coordinates @@ -152,6 +157,7 @@

    Source code for pyrad.proc.process_timeseries

    # prepare for exit new_dataset = { 'time': dscfg['global_data']['time'], + 'ref_time': dscfg['global_data']['ref_time'], 'datatype': datatype, 'point_coordinates_WGS84_lon_lat_alt': ( dscfg['global_data']['point_coordinates_WGS84_lon_lat_alt']), @@ -176,6 +182,7 @@

    Source code for pyrad.proc.process_timeseries

    projparams.update({'lon_0': radar.longitude['data']}) projparams.update({'lat_0': radar.latitude['data']}) + single_point = dscfg.get('single_point', True) if dscfg['latlon']: lon = dscfg['lon'] lat = dscfg['lat'] @@ -211,34 +218,43 @@

    Source code for pyrad.proc.process_timeseries

    lon = lon[0] lat = lat[0] - d_az = np.min(np.abs(radar.azimuth['data'] - az)) - if d_az > dscfg['AziTol']: + d_az = np.abs(radar.azimuth['data'] - az) + if np.min(d_az) > dscfg['AziTol']: warn(' No radar bin found for point (az, el, r):(' + str(az)+', '+str(el)+', '+str(r) + '). Minimum distance to radar azimuth '+str(d_az) + ' larger than tolerance') return None, None - d_el = np.min(np.abs(radar.elevation['data'] - el)) - if d_el > dscfg['EleTol']: + d_el = np.abs(radar.elevation['data'] - el) + if np.min(d_el) > dscfg['EleTol']: warn(' No radar bin found for point (az, el, r):(' + str(az)+', '+str(el)+', '+str(r) + '). Minimum distance to radar elevation '+str(d_el) + ' larger than tolerance') return None, None - d_r = np.min(np.abs(radar.range['data'] - r)) - if d_r > dscfg['RngTol']: + d_r = np.abs(radar.range['data'] - r) + if np.min(d_r) > dscfg['RngTol']: warn(' No radar bin found for point (az, el, r):(' + str(az)+', '+str(el)+', '+str(r) + '). Minimum distance to radar range bin '+str(d_r) + ' larger than tolerance') return None, None - ind_ray = np.argmin(np.abs(radar.azimuth['data'] - az) + - np.abs(radar.elevation['data'] - el)) + if single_point: + ind_ray = np.argmin(np.abs(radar.azimuth['data'] - az) + + np.abs(radar.elevation['data'] - el)) + else: + ind_ray = np.where(np.logical_and( + d_az <= dscfg['AziTol'], d_el <= dscfg['EleTol']))[0] ind_r = np.argmin(np.abs(radar.range['data'] - r)) + ant_coord = np.empty((3, ind_ray.size), np.float32) + ant_coord[0, :] = radar.azimuth['data'][ind_ray] + ant_coord[1, :] = radar.elevation['data'][ind_ray] + ant_coord[2, :] = np.zeros(ind_ray.size)+radar.range['data'][ind_r] + val = radar.fields[field_name]['data'].data[ind_ray, ind_r] time = num2date(radar.time['data'][ind_ray], radar.time['units'], radar.time['calendar']) @@ -248,23 +264,23 @@

    Source code for pyrad.proc.process_timeseries

    poi = { 'point_coordinates_WGS84_lon_lat_alt': [lon, lat, alt], 'antenna_coordinates_az_el_r': [az, el, r], - 'time': time} + 'time': time, + 'ref_time': dscfg['timeinfo']} dscfg['global_data'] = poi dscfg['initialized'] = 1 + dscfg['global_data']['ref_time'] = dscfg['timeinfo'] + # prepare for exit new_dataset = dict() new_dataset.update({'value': val}) new_dataset.update({'datatype': datatype}) new_dataset.update({'time': time}) + new_dataset.update({'ref_time': dscfg['timeinfo']}) new_dataset.update( {'point_coordinates_WGS84_lon_lat_alt': [lon, lat, alt]}) new_dataset.update({'antenna_coordinates_az_el_r': [az, el, r]}) - new_dataset.update( - {'used_antenna_coordinates_az_el_r': [ - radar.azimuth['data'][ind_ray], - radar.elevation['data'][ind_ray], - radar.range['data'][ind_r]]}) + new_dataset.update({'used_antenna_coordinates_az_el_r': ant_coord}) new_dataset.update({'final': False}) return new_dataset, ind_rad
    @@ -429,9 +445,6 @@

    Source code for pyrad.proc.process_timeseries

    datatype : string. Dataset keyword The data type where we want to extract the point measurement - anglenr : int - The sweep number to use. It assumes the radar volume consists on - PPI scans hmax : float The maximum height to plot [m]. Default 10000. hres : float @@ -619,8 +632,8 @@

    Source code for pyrad.proc.process_timeseries

    Reference --------- Kaltenboeck R., Ryzhkov A. 2016: A freezing rain storm explored with a - C-band polarimetric weather radar using the QVP methodology. Meteorologische - Zeitschrift vol. 26 pp 207-222 + C-band polarimetric weather radar using the QVP methodology. + Meteorologische Zeitschrift vol. 26 pp 207-222 """ if procstatus == 0: @@ -1018,8 +1031,8 @@

    Source code for pyrad.proc.process_timeseries

    ALONG_RNG fixed_range, fixed_azimuth, fixed_elevation : float The fixed range [m], azimuth [deg] or elevation [deg] to extract. - In each mode two of these parameters have to be defined. If they are - not defined they default to 0. + In each mode two of these parameters have to be defined. If they + are not defined they default to 0. ang_tol, rng_tol : float The angle tolerance [deg] and range tolerance [m] around the fixed range or azimuth/elevation @@ -1160,7 +1173,7 @@

    Navigation

  129. modules |
  130. - +
    diff --git a/docs/_modules/pyrad/proc/process_traj.html b/docs/_modules/pyrad/proc/process_traj.html index ed2f9c2..5b5c728 100644 --- a/docs/_modules/pyrad/proc/process_traj.html +++ b/docs/_modules/pyrad/proc/process_traj.html @@ -6,7 +6,7 @@ - pyrad.proc.process_traj — pyrad 0.4.4 documentation + pyrad.proc.process_traj — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  131. modules |
  132. - +
    @@ -293,7 +293,8 @@

    Source code for pyrad.proc.process_traj

             field_dict = deepcopy(radar.fields[field_name])
             field_dict['data'] = np.ma.empty(
                 (radar_roi.nrays, radar_roi.ngates), dtype=float)
    -        field_dict['data'][0, :] = radar.fields[field_name]['data'][inds_ray, inds_rng]
    +        field_dict['data'][0, :] = radar.fields[field_name]['data'][
    +            inds_ray, inds_rng]
             radar_roi.add_field(field_name, field_dict)
     
         new_dataset = {'radar_out': radar_roi}
    @@ -301,7 +302,8 @@ 

    Source code for pyrad.proc.process_traj

         return new_dataset, ind_rad
    -
    [docs]def process_traj_trt_contour(procstatus, dscfg, radar_list=None, trajectory=None): +
    [docs]def process_traj_trt_contour(procstatus, dscfg, radar_list=None, + trajectory=None): """ Gets the TRT cell contour corresponding to each radar volume @@ -904,15 +906,26 @@

    Source code for pyrad.proc.process_traj

                 Max altitude of the data to use when computing the view from the
                 synthetic radar [m MSL]. Default 12000.
             latlon_tol : float. Dataset keyword
    -            The tolerance in latitude and longitude to determine which synthetic
    -            radar gates are co-located with real radar gates [deg]. Default 0.04
    +            The tolerance in latitude and longitude to determine which
    +            synthetic radar gates are co-located with real radar gates [deg].
    +            Default 0.04
             alt_tol : float. Datset keyword
                 The tolerance in altitude to determine which synthetic
                 radar gates are co-located with real radar gates [m]. Default 1000.
    +        distance_upper_bound : float. Dataset keyword
    +            The maximum distance where to look for a neighbour when
    +            determining which synthetic radar gates are co-located with real
    +            radar gates [m]. Default 1000.
    +        use_cKDTree : Bool. Dataset keyword
    +            Which function to use to find co-located real radar gates with the
    +            synthetic radar. If True a function using cKDTree from
    +            scipy.spatial is used. This function uses parameter
    +            distance_upper_bound. If False a native implementation is used
    +            that takes as parameters latlon_tol and alt_tol. Default True.
             pattern_thres : float. Dataset keyword
                 The minimum of the sum of the weights given to each value in order
    -            to consider the weighted quantile valid. It is related to the number
    -            of valid data points
    +            to consider the weighted quantile valid. It is related to the
    +            number of valid data points
             data_is_log : dict. Dataset keyword
                 Dictionary specifying for each field if it is in log (True) or
                 linear units (False). Default False
    @@ -951,7 +964,6 @@ 

    Source code for pyrad.proc.process_traj

             }
             return dataset, tadict['ind_rad']
     
    -
         # Process
         field_names = []
         datatypes = []
    @@ -1123,9 +1135,11 @@ 

    Source code for pyrad.proc.process_traj

             # Config parameters for processing when the weather radar and the
             # antenna are not at the same place:
             rhi_resolution = dscfg.get('rhi_resolution', 0.5)  # [deg]
    -        max_altitude = dscfg.get('max_altitude', 12000.) # [m]
    +        max_altitude = dscfg.get('max_altitude', 12000.)  # [m]
             latlon_tol = dscfg.get('latlon_tol', 0.04)  # [deg]
             alt_tol = dscfg.get('alt_tol', 1000.)  # [m]
    +        distance_upper_bound = dscfg.get('distance_upper_bound', 1000.)
    +        use_cKDTree = dscfg.get('use_cKDTree', True)
     
             # Get antenna pattern and make weight vector
             try:
    @@ -1138,7 +1152,8 @@ 

    Source code for pyrad.proc.process_traj

                 else:
                     antpattern = read_antenna_pattern(patternfile, linear=True,
                                                       twoway=True)
    -        except:
    +        except Exception as ee:
    +            warn(str(ee))
                 raise
     
             pattern_angles = antpattern['angle'] + fixed_angle
    @@ -1242,6 +1257,8 @@ 

    Source code for pyrad.proc.process_traj

                 'max_altitude': max_altitude,
                 'latlon_tol': latlon_tol,
                 'alt_tol': alt_tol,
    +            'distance_upper_bound': distance_upper_bound,
    +            'use_cKDTree': use_cKDTree,
                 'data_is_log': data_is_log,
                 'ts_dict': ts_dict})
             traj_ind = trajectory.get_samples_in_period(end=dt_task_start)
    @@ -1308,6 +1325,8 @@ 

    Source code for pyrad.proc.process_traj

         max_altitude = tadict['max_altitude']
         latlon_tol = tadict['latlon_tol']
         alt_tol = tadict['alt_tol']
    +    distance_upper_bound = tadict['distance_upper_bound']
    +    use_cKDTree = tadict['use_cKDTree']
         data_is_log = tadict['data_is_log']
     
         traj_time_vec = date2num(trajectory.time_vector, radar.time['units'],
    @@ -1407,7 +1426,9 @@ 

    Source code for pyrad.proc.process_traj

                 ray_inds, rng_inds, w_inds = _get_gates_antenna_pattern(
                     radar_sel, target_radar, az, rr, tt, scan_angles,
                     alt_tol=alt_tol, latlon_tol=latlon_tol,
    -                max_altitude=max_altitude)
    +                max_altitude=max_altitude,
    +                distance_upper_bound=distance_upper_bound,
    +                use_cKDTree=use_cKDTree)
     
                 w_vec = tadict['weightvec'][w_inds]
     
    @@ -1703,7 +1724,8 @@ 

    Source code for pyrad.proc.process_traj

     
     def _get_gates_antenna_pattern(radar_sel, target_radar, az, rr, tt,
                                    scan_angles, alt_tol=1000., latlon_tol=0.04,
    -                               max_altitude=12000.):
    +                               max_altitude=12000.,
    +                               distance_upper_bound=1000., use_cKDTree=True):
         """
         Find the gates of the radar object that have to be used to compute the
         data of a trajectory as seen by another radar system
    @@ -1725,7 +1747,13 @@ 

    Source code for pyrad.proc.process_traj

         latlon_tol : float
             The tolerance in latitude and longitude [deg]
         max_altitude : float
    -        The maximum altitude where to look for radar data
    +        The maximum altitude where to look for radar data [m MSL]
    +    distance_upper_bound : float
    +        The maximum distance where to look for neighbors [m]
    +    use_cKDTree : Bool
    +        If True the nearest neighbour to the synthetic radar is found using
    +        the cKDTree function of scipy.spatial. Otherwise it is found by Pyrad
    +        implementation
     
         Returns
         -------
    @@ -1738,12 +1766,12 @@ 

    Source code for pyrad.proc.process_traj

         # Create dummy Radar object with fix az and r, and all elevations
         n_rays = scan_angles.size
     
    -    r_time = {'data': [tt * n_rays]}
    -    r_range = {'data': [rr]}
    +    r_time = {'data': np.array([tt * n_rays])}
    +    r_range = {'data': np.array([rr])}
         r_azimuth = get_metadata('azimuth')
         r_azimuth['data'] = np.ones(n_rays) * az
         r_elevation = {'data': scan_angles}
    -    r_sweep_number = {'data': [0]}
    +    r_sweep_number = {'data': np.array([0])}
         r_fields = {'colocated_gates': get_metadata('colocated_gates')}
         r_fields['colocated_gates']['data'] = 2*np.ma.ones((n_rays, 1), dtype=int)
     
    @@ -1767,8 +1795,13 @@ 

    Source code for pyrad.proc.process_traj

         radar_sel.add_field(
             'colocated_gates', gate_coloc_radar_sel, replace_existing=True)
     
    -    (colgates, r_radar_colg) = pyart.util.colocated_gates(
    -        r_radar, radar_sel, h_tol=alt_tol, latlon_tol=latlon_tol)
    +    if use_cKDTree:
    +        colgates, r_radar_colg = pyart.util.colocated_gates2(
    +            r_radar, radar_sel, distance_upper_bound=distance_upper_bound)
    +    else:
    +        colgates, r_radar_colg = pyart.util.colocated_gates(
    +            r_radar, radar_sel, h_tol=alt_tol, latlon_tol=latlon_tol)
    +
         w_ind = np.where(r_radar_colg['data'] > 1)[0]
     
         return colgates['rad2_ray_ind'], colgates['rad2_rng_ind'], w_ind
    @@ -1923,7 +1956,7 @@ 

    Navigation

  133. modules |
  134. - +
    diff --git a/docs/_modules/pyrad/prod/process_grid_products.html b/docs/_modules/pyrad/prod/process_grid_products.html index 5e4b49c..f168d5f 100644 --- a/docs/_modules/pyrad/prod/process_grid_products.html +++ b/docs/_modules/pyrad/prod/process_grid_products.html @@ -6,7 +6,7 @@ - pyrad.prod.process_grid_products — pyrad 0.4.4 documentation + pyrad.prod.process_grid_products — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  135. modules |
  136. - +
    @@ -78,7 +78,7 @@

    Source code for pyrad.prod.process_grid_products

    from ..io.io_aux import get_fieldname_pyart from ..io.io_aux import get_save_dir, make_filename -from ..io.write_data import write_histogram +from ..io.write_data import write_histogram, write_ts_stats from ..graph.plots_grid import plot_surface, plot_surface_contour from ..graph.plots_grid import plot_longitude_slice, plot_latitude_slice @@ -203,6 +203,11 @@

    Source code for pyrad.prod.process_grid_products

    step: float or None the data quantization step. If none it will be obtained from the Py-ART configuration file + vmin, vmax: float or None + The minimum and maximum values. If None they will be + obtained from the Py-ART configuration file + mask_val: float or None + A value to mask. write_data: Bool If true the histogram data is written in a csv file 'LATITUDE_SLICE': Plots a cross-section of gridded data over a @@ -226,18 +231,63 @@

    Source code for pyrad.prod.process_grid_products

    The list of data types to save. If it is None, all fields in the radar object will be saved 'SAVEVOL': Saves on field of a gridded data object in a netcdf file. + 'STATS': Computes statistics over the whole images and stores them in + a file. + User defined parameters: + stat: str + The statistic used. Can be mean, median, min, max 'SURFACE_IMAGE': Plots a surface image of gridded data. User defined parameters: level: int The altitude level to plot. The rest of the parameters are defined by the parameters in 'ppiImageConfig' and 'ppiMapImageConfig' in the 'loc' configuration file - 'SURFACE_CONTOUR': Plots a surface image of gridded data. + 'SURFACE_CONTOUR': Plots a surface image of contour gridded data. + User defined parameters: + level: int + The altitude level to plot. The rest of the parameters are + defined by the parameters in 'ppiImageConfig' and + 'ppiMapImageConfig' in the 'loc' configuration file + contour_values : float array or None + The contour values. If None the values are taken from the + 'boundaries' keyword in the field description in the + Py-ART config file. If 'boundaries' is not set the + countours are 10 values linearly distributed from vmin to + vmax + linewidths : float + width of the contour lines + colors : color string or sequence of colors + The contour colours + SURFACE_CONTOUR_OVERPLOT: + Plots a surface image of gridded data with a contour overplotted. + User defined parameters: + level: int + The altitude level to plot. The rest of the parameters are + defined by the parameters in 'ppiImageConfig' and + 'ppiMapImageConfig' in the 'loc' configuration file + contour_values : float array or None + The contour values. If None the values are taken from the + 'boundaries' keyword in the field description in the + Py-ART config file. If 'boundaries' is not set the + countours are 10 values linearly distributed from vmin to + vmax + linewidths : float + width of the contour lines + colors : color string or sequence of colors + The contour colours + SURFACE_OVERPLOT: + Plots on the same surface two images, one on top of the other. User defined parameters: level: int The altitude level to plot. The rest of the parameters are defined by the parameters in 'ppiImageConfig' and 'ppiMapImageConfig' in the 'loc' configuration file + contour_values : float array or None + The contour values. If None the values are taken from the + 'boundaries' keyword in the field description in the + Py-ART config file. If 'boundaries' is not set the + countours are 10 values linearly distributed from vmin to + vmax Parameters ---------- @@ -257,6 +307,55 @@

    Source code for pyrad.prod.process_grid_products

    if 'dssavename' in prdcfg: dssavedir = prdcfg['dssavename'] + if prdcfg['type'] == 'STATS': + field_name = get_fieldname_pyart(prdcfg['voltype']) + if field_name not in dataset['radar_out'].fields: + warn( + ' Field type ' + field_name + + ' not available in data set. Skipping product ' + + prdcfg['type']) + return None + + # user defined values + stat = prdcfg.get('stat', 'mean') + + savedir = get_save_dir( + prdcfg['basepath'], prdcfg['procname'], dssavedir, + prdcfg['prdname'], timeinfo=None) + + fname = make_filename( + 'stats', prdcfg['dstype'], prdcfg['voltype'], + ['csv'], prdcfginfo=stat, + timeinfo=None, runinfo=prdcfg['runinfo'])[0] + + fname = savedir+fname + + if stat == 'mean': + value = np.ma.masked_all(1) + value[0] = np.ma.mean( + dataset['radar_out'].fields[field_name]['data']) + elif stat == 'median': + value = np.ma.masked_all(1) + value[0] = np.ma.median( + dataset['radar_out'].fields[field_name]['data']) + elif stat == 'min': + value = np.ma.masked_all(1) + value[0] = np.ma.min( + dataset['radar_out'].fields[field_name]['data']) + elif stat == 'max': + value = np.ma.masked_all(1) + value[0] = np.ma.max( + dataset['radar_out'].fields[field_name]['data']) + else: + warn('Unsupported statistic '+stat) + return None + + write_ts_stats(prdcfg['timeinfo'], value, fname, stat=stat) + + print('----- save to '+fname) + + return fname + if prdcfg['type'] == 'SURFACE_IMAGE': field_name = get_fieldname_pyart(prdcfg['voltype']) if field_name not in dataset['radar_out'].fields: @@ -299,6 +398,8 @@

    Source code for pyrad.prod.process_grid_products

    # user defined values contour_values = prdcfg.get('contour_values', None) + linewidths = prdcfg.get('linewidths', 1.5) + colors = prdcfg.get('colors', 'k') level = prdcfg.get('level', 0) savedir = get_save_dir( @@ -315,7 +416,8 @@

    Source code for pyrad.prod.process_grid_products

    plot_surface_contour( dataset['radar_out'], field_name, level, prdcfg, fname_list, - contour_values=contour_values) + contour_values=contour_values, linewidths=linewidths, + colors=colors) print('----- save to '+' '.join(fname_list)) @@ -339,6 +441,8 @@

    Source code for pyrad.prod.process_grid_products

    return None contour_values = prdcfg.get('contour_values', None) + linewidths = prdcfg.get('linewidths', 1.5) + colors = prdcfg.get('colors', 'k') level = prdcfg.get('level', 0) contour_level = prdcfg.get('contour_level', level) @@ -347,7 +451,8 @@

    Source code for pyrad.prod.process_grid_products

    prdcfg['prdname'], timeinfo=prdcfg['timeinfo']) fname_list = make_filename( - 'surface', prdcfg['dstype'], prdcfg['voltype'], + 'surface-contour', prdcfg['dstype'], + prdcfg['voltype']+'-'+prdcfg['contourtype'], prdcfg['imgformat'], prdcfginfo='l'+str(level), timeinfo=prdcfg['timeinfo'], runinfo=prdcfg['runinfo']) @@ -367,7 +472,61 @@

    Source code for pyrad.prod.process_grid_products

    fname_list = plot_surface_contour( dataset['radar_out'], contour_name, contour_level, prdcfg, - fname_list, contour_values=contour_values, ax=ax, fig=fig, + fname_list, contour_values=contour_values, linewidths=linewidths, + colors=colors, ax=ax, fig=fig, display=display, save_fig=True) + + print('----- save to '+' '.join(fname_list)) + + return fname_list + + if prdcfg['type'] == 'SURFACE_OVERPLOT': + field_name_btm = get_fieldname_pyart(prdcfg['voltype_btm']) + if field_name_btm not in dataset['radar_out'].fields: + warn( + ' Field type ' + field_name_btm + + ' not available in data set. Skipping product ' + + prdcfg['type']) + return None + + field_name_top = get_fieldname_pyart(prdcfg['voltype_top']) + if field_name_top not in dataset['radar_out'].fields: + warn( + 'Contour type ' + field_name_top + + ' not available in data set. Skipping product ' + + prdcfg['type']) + return None + + level_btm = prdcfg.get('level_btm', 0) + level_top = prdcfg.get('level_top', 0) + alpha = prdcfg.get('alpha', None) + + savedir = get_save_dir( + prdcfg['basepath'], prdcfg['procname'], dssavedir, + prdcfg['prdname'], timeinfo=prdcfg['timeinfo']) + + fname_list = make_filename( + 'surface_overplot', prdcfg['dstype'], + prdcfg['voltype_btm']+'-'+prdcfg['voltype_top'], + prdcfg['imgformat'], prdcfginfo='l'+str(level_btm), + timeinfo=prdcfg['timeinfo'], runinfo=prdcfg['runinfo']) + + for i, fname in enumerate(fname_list): + fname_list[i] = savedir+fname + + titl = ( + pyart.graph.common.generate_grid_title( + dataset['radar_out'], field_name_btm, level_btm) + + ' - ' + + pyart.graph.common.generate_field_name( + dataset['radar_out'], field_name_top)) + + fig, ax, display = plot_surface( + dataset['radar_out'], field_name_btm, level_btm, prdcfg, + fname_list, titl=titl, save_fig=False) + + fname_list = plot_surface( + dataset['radar_out'], field_name_top, level_top, prdcfg, + fname_list, titl=titl, alpha=alpha, ax=ax, fig=fig, display=display, save_fig=True) print('----- save to '+' '.join(fname_list)) @@ -504,6 +663,8 @@

    Source code for pyrad.prod.process_grid_products

    return None step = prdcfg.get('step', None) + vmin = prdcfg.get('vmin', None) + vmax = prdcfg.get('vmax', None) mask_val = prdcfg.get('mask_val', None) write_data = prdcfg.get('write_data', 0) @@ -522,7 +683,8 @@

    Source code for pyrad.prod.process_grid_products

    values = dataset['radar_out'].fields[field_name]['data'] if mask_val is not None: values = np.ma.masked_values(values, mask_val) - bin_edges, values = compute_histogram(values, field_name, step=step) + bin_edges, values = compute_histogram( + values, field_name, step=step, vmin=vmin, vmax=vmax) titl = ( pyart.graph.common.generate_grid_time_begin( @@ -638,7 +800,7 @@

    Navigation

  137. modules |
  138. - +
    diff --git a/docs/_modules/pyrad/prod/process_intercomp_products.html b/docs/_modules/pyrad/prod/process_intercomp_products.html index 71175b5..2ef2c59 100644 --- a/docs/_modules/pyrad/prod/process_intercomp_products.html +++ b/docs/_modules/pyrad/prod/process_intercomp_products.html @@ -6,7 +6,7 @@ - pyrad.prod.process_intercomp_products — pyrad 0.4.4 documentation + pyrad.prod.process_intercomp_products — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  139. modules |
  140. - +
    @@ -447,7 +447,7 @@

    Navigation

  141. modules |
  142. - +
    diff --git a/docs/_modules/pyrad/prod/process_monitoring_products.html b/docs/_modules/pyrad/prod/process_monitoring_products.html index 4403efa..7e80ad1 100644 --- a/docs/_modules/pyrad/prod/process_monitoring_products.html +++ b/docs/_modules/pyrad/prod/process_monitoring_products.html @@ -6,7 +6,7 @@ - pyrad.prod.process_monitoring_products — pyrad 0.4.4 documentation + pyrad.prod.process_monitoring_products — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  143. modules |
  144. - +
    @@ -862,7 +862,7 @@

    Navigation

  145. modules |
  146. - +
    diff --git a/docs/_modules/pyrad/prod/process_product.html b/docs/_modules/pyrad/prod/process_product.html index e5e4a94..2bf52ca 100644 --- a/docs/_modules/pyrad/prod/process_product.html +++ b/docs/_modules/pyrad/prod/process_product.html @@ -6,7 +6,7 @@ - pyrad.prod.process_product — pyrad 0.4.4 documentation + pyrad.prod.process_product — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  147. modules |
  148. - +
    @@ -785,7 +785,7 @@

    Navigation

  149. modules |
  150. - +
    diff --git a/docs/_modules/pyrad/prod/process_spectra_products.html b/docs/_modules/pyrad/prod/process_spectra_products.html index bf791c1..1e508ec 100644 --- a/docs/_modules/pyrad/prod/process_spectra_products.html +++ b/docs/_modules/pyrad/prod/process_spectra_products.html @@ -6,7 +6,7 @@ - pyrad.prod.process_spectra_products — pyrad 0.4.4 documentation + pyrad.prod.process_spectra_products — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  151. modules |
  152. - +
    @@ -477,6 +477,10 @@

    Source code for pyrad.prod.process_spectra_products

    xaxis_info = prdcfg.get('xaxis_info', 'Doppler_velocity') vmin = prdcfg.get('vmin', None) vmax = prdcfg.get('vmax', None) + xmin = prdcfg.get('xmin', None) + xmax = prdcfg.get('xmax', None) + ymin = prdcfg.get('ymin', None) + ymax = prdcfg.get('ymax', None) plot_type = prdcfg.get('plot_type', 'final') if plot_type == 'final' and not dataset['final']: @@ -517,7 +521,8 @@

    Source code for pyrad.prod.process_spectra_products

    else: plot_time_Doppler( dataset['radar_out'], field_name, prdcfg, fname_list, - xaxis_info=xaxis_info, vmin=vmin, vmax=vmax) + xaxis_info=xaxis_info, vmin=vmin, vmax=vmax, xmin=xmin, + xmax=xmax, ymin=ymin, ymax=ymax) print('----- save to '+' '.join(fname_list)) @@ -1225,7 +1230,7 @@

    Navigation

  153. modules |
  154. - +
    diff --git a/docs/_modules/pyrad/prod/process_timeseries_products.html b/docs/_modules/pyrad/prod/process_timeseries_products.html index b318f64..69ffcbf 100644 --- a/docs/_modules/pyrad/prod/process_timeseries_products.html +++ b/docs/_modules/pyrad/prod/process_timeseries_products.html @@ -6,7 +6,7 @@ - pyrad.prod.process_timeseries_products — pyrad 0.4.4 documentation + pyrad.prod.process_timeseries_products — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  155. modules |
  156. - +
    @@ -231,15 +231,12 @@

    Source code for pyrad.prod.process_timeseries_products

    prdsavedir = prdcfg['prdsavedir'] if prdcfg['type'] == 'PLOT_AND_WRITE_POINT': - if dataset['final']: - return None - - dpi = prdcfg.get('dpi', 72) - set_time_info = prdcfg.get('set_time_info', 1) - + set_time_info = prdcfg.get('set_time_info', True) if 'antenna_coordinates_az_el_r' in dataset: - az = '{:.1f}'.format(dataset['antenna_coordinates_az_el_r'][0]) - el = '{:.1f}'.format(dataset['antenna_coordinates_az_el_r'][1]) + az = '{:.1f}'.format( + dataset['antenna_coordinates_az_el_r'][0]) + el = '{:.1f}'.format( + dataset['antenna_coordinates_az_el_r'][1]) r = '{:.1f}'.format(dataset['antenna_coordinates_az_el_r'][2]) gateinfo = ('az'+az+'r'+r+'el'+el) else: @@ -251,15 +248,15 @@

    Source code for pyrad.prod.process_timeseries_products

    dataset['point_coordinates_WGS84_lon_lat_alt'][2]) gateinfo = ('lon'+lon+'lat'+lat+'alt'+alt) - timeinfo = None timeformat = None + timeinfo = None if set_time_info: - timeinfo = prdcfg['timeinfo'] timeformat = '%Y%m%d' + timeinfo = dataset['ref_time'] savedir = get_save_dir( - prdcfg['basepath'], prdcfg['procname'], dssavedir, - prdsavedir, timeinfo=timeinfo) + prdcfg['basepath'], prdcfg['procname'], dssavedir, prdsavedir, + timeinfo=timeinfo) csvfname = make_filename( 'ts', prdcfg['dstype'], dataset['datatype'], ['csv'], @@ -268,22 +265,29 @@

    Source code for pyrad.prod.process_timeseries_products

    csvfname = savedir+csvfname - if 'antenna_coordinates_az_el_r' in dataset: - write_ts_polar_data(dataset, csvfname) - else: - write_ts_grid_data(dataset, csvfname) - print('saved CSV file: '+csvfname) + if not dataset['final']: + if 'antenna_coordinates_az_el_r' in dataset: + write_ts_polar_data(dataset, csvfname) + else: + write_ts_grid_data(dataset, csvfname) + print('saved CSV file: '+csvfname) - date, value = read_timeseries(csvfname) + dpi = prdcfg.get('dpi', 72) + vmin = prdcfg.get('vmin', None) + vmax = prdcfg.get('vmax', None) + plot_only_final = prdcfg.get('plot_only_final', False) + + if plot_only_final and not dataset['final']: + return None + if not plot_only_final and dataset['final']: + return None + date, value = read_timeseries(csvfname) if date is None: warn( 'Unable to plot time series. No valid data') return None - vmin = prdcfg.get('vmin', None) - vmax = prdcfg.get('vmax', None) - timeinfo_fig = None if set_time_info: timeinfo_fig = date[0] @@ -313,12 +317,16 @@

    Source code for pyrad.prod.process_timeseries_products

    return figfname_list if prdcfg['type'] == 'PLOT_CUMULATIVE_POINT': - if dataset['final']: - return None - dpi = prdcfg.get('dpi', 72) vmin = prdcfg.get('vmin', None) vmax = prdcfg.get('vmax', None) + plot_only_final = prdcfg.get('plot_only_final', False) + set_time_info = prdcfg.get('set_time_info', True) + + if plot_only_final and not dataset['final']: + return None + if not plot_only_final and dataset['final']: + return None if 'antenna_coordinates_az_el_r' in dataset: az = '{:.1f}'.format(dataset['antenna_coordinates_az_el_r'][0]) @@ -334,14 +342,20 @@

    Source code for pyrad.prod.process_timeseries_products

    dataset['point_coordinates_WGS84_lon_lat_alt'][2]) gateinfo = ('lon'+lon+'lat'+lat+'alt'+alt) + timeformat = None + timeinfo = None + if set_time_info: + timeformat = '%Y%m%d' + timeinfo = dataset['ref_time'] + savedir = get_save_dir( prdcfg['basepath'], prdcfg['procname'], dssavedir, - prdcfg['prdid'], timeinfo=prdcfg['timeinfo']) + prdcfg['prdid'], timeinfo=timeinfo) csvfname = make_filename( 'ts', prdcfg['dstype'], dataset['datatype'], ['csv'], - prdcfginfo=gateinfo, timeinfo=prdcfg['timeinfo'], - timeformat='%Y%m%d')[0] + prdcfginfo=gateinfo, timeinfo=timeinfo, + timeformat=timeformat)[0] csvfname = savedir+csvfname @@ -352,10 +366,14 @@

    Source code for pyrad.prod.process_timeseries_products

    'Unable to plot accumulation time series. No valid data') return None + timeinfo_fig = None + if set_time_info: + timeinfo_fig = date[0] + figfname_list = make_filename( 'ts_cum', prdcfg['dstype'], dataset['datatype'], prdcfg['imgformat'], prdcfginfo=gateinfo, - timeinfo=date[0], timeformat='%Y%m%d') + timeinfo=timeinfo_fig, timeformat=timeformat) for i, figfname in enumerate(figfname_list): figfname_list[i] = savedir+figfname @@ -378,10 +396,16 @@

    Source code for pyrad.prod.process_timeseries_products

    return figfname_list if prdcfg['type'] == 'COMPARE_POINT': - if dataset['final']: - return None - dpi = prdcfg.get('dpi', 72) + vmin = prdcfg.get('vmin', None) + vmax = prdcfg.get('vmax', None) + plot_only_final = prdcfg.get('plot_only_final', False) + set_time_info = prdcfg.get('set_time_info', True) + + if plot_only_final and not dataset['final']: + return None + if not plot_only_final and dataset['final']: + return None if 'antenna_coordinates_az_el_r' in dataset: az = '{:.1f}'.format(dataset['antenna_coordinates_az_el_r'][0]) @@ -397,14 +421,20 @@

    Source code for pyrad.prod.process_timeseries_products

    dataset['point_coordinates_WGS84_lon_lat_alt'][2]) gateinfo = ('lon'+lon+'lat'+lat+'alt'+alt) + timeformat = None + timeinfo = None + if set_time_info: + timeformat = '%Y%m%d' + timeinfo = dataset['ref_time'] + savedir_ts = get_save_dir( prdcfg['basepath'], prdcfg['procname'], dssavedir, - prdcfg['prdid'], timeinfo=prdcfg['timeinfo']) + prdcfg['prdid'], timeinfo=timeinfo) csvfname = make_filename( 'ts', prdcfg['dstype'], dataset['datatype'], ['csv'], - prdcfginfo=gateinfo, timeinfo=prdcfg['timeinfo'], - timeformat='%Y%m%d')[0] + prdcfginfo=gateinfo, timeinfo=timeinfo, + timeformat=timeformat)[0] csvfname = savedir_ts+csvfname @@ -423,17 +453,18 @@

    Source code for pyrad.prod.process_timeseries_products

    'No valid sensor data') return None - vmin = prdcfg.get('vmin', None) - vmax = prdcfg.get('vmax', None) + timeinfo_fig = None + if set_time_info: + timeinfo_fig = radardate[0] savedir = get_save_dir( prdcfg['basepath'], prdcfg['procname'], dssavedir, - prdsavedir, timeinfo=radardate[0]) + prdsavedir, timeinfo=timeinfo_fig) figfname_list = make_filename( 'ts_comp', prdcfg['dstype'], dataset['datatype'], prdcfg['imgformat'], prdcfginfo=gateinfo, - timeinfo=radardate[0], timeformat='%Y%m%d') + timeinfo=timeinfo_fig, timeformat=timeformat) for i, figfname in enumerate(figfname_list): figfname_list[i] = savedir+figfname @@ -455,10 +486,16 @@

    Source code for pyrad.prod.process_timeseries_products

    return figfname_list if prdcfg['type'] == 'COMPARE_CUMULATIVE_POINT': - if dataset['final']: - return None - dpi = prdcfg.get('dpi', 72) + vmin = prdcfg.get('vmin', None) + vmax = prdcfg.get('vmax', None) + plot_only_final = prdcfg.get('plot_only_final', False) + set_time_info = prdcfg.get('set_time_info', True) + + if plot_only_final and not dataset['final']: + return None + if not plot_only_final and dataset['final']: + return None if 'antenna_coordinates_az_el_r' in dataset: az = '{:.1f}'.format(dataset['antenna_coordinates_az_el_r'][0]) @@ -474,14 +511,20 @@

    Source code for pyrad.prod.process_timeseries_products

    dataset['point_coordinates_WGS84_lon_lat_alt'][2]) gateinfo = ('lon'+lon+'lat'+lat+'alt'+alt) + timeformat = None + timeinfo = None + if set_time_info: + timeformat = '%Y%m%d' + timeinfo = dataset['ref_time'] + savedir_ts = get_save_dir( prdcfg['basepath'], prdcfg['procname'], dssavedir, - prdcfg['prdid'], timeinfo=prdcfg['timeinfo']) + prdcfg['prdid'], timeinfo=timeinfo) csvfname = make_filename( 'ts', prdcfg['dstype'], dataset['datatype'], ['csv'], - prdcfginfo=gateinfo, timeinfo=prdcfg['timeinfo'], - timeformat='%Y%m%d')[0] + prdcfginfo=gateinfo, timeinfo=timeinfo, + timeformat=timeformat)[0] csvfname = savedir_ts+csvfname @@ -500,17 +543,18 @@

    Source code for pyrad.prod.process_timeseries_products

    'No valid sensor data') return None - vmin = prdcfg.get('vmin', None) - vmax = prdcfg.get('vmax', None) + timeinfo_fig = None + if set_time_info: + timeinfo_fig = radardate[0] savedir = get_save_dir( prdcfg['basepath'], prdcfg['procname'], dssavedir, - prdsavedir, timeinfo=radardate[0]) + prdsavedir, timeinfo=timeinfo_fig) figfname_list = make_filename( 'ts_cumcomp', prdcfg['dstype'], dataset['datatype'], prdcfg['imgformat'], prdcfginfo=gateinfo, - timeinfo=radardate[0], timeformat='%Y%m%d') + timeinfo=timeinfo_fig, timeformat=timeformat) for i, figfname in enumerate(figfname_list): figfname_list[i] = savedir+figfname @@ -535,10 +579,13 @@

    Source code for pyrad.prod.process_timeseries_products

    return figfname_list if prdcfg['type'] == 'COMPARE_TIME_AVG': - if not dataset['final']: - return None - dpi = prdcfg.get('dpi', 72) + plot_only_final = prdcfg.get('plot_only_final', False) + + if plot_only_final and not dataset['final']: + return None + if not plot_only_final and dataset['final']: + return None az = '{:.1f}'.format(dataset['antenna_coordinates_az_el_r'][0]) el = '{:.1f}'.format(dataset['antenna_coordinates_az_el_r'][1]) @@ -673,7 +720,6 @@

    Source code for pyrad.prod.process_timeseries_products

    timeformat='%Y%m%d%H%M%S', runinfo=prdcfg['runinfo']) - ymin = prdcfg.get('ymin', None) ymax = prdcfg.get('ymax', None) @@ -787,7 +833,7 @@

    Navigation

  157. modules |
  158. - +
    diff --git a/docs/_modules/pyrad/prod/process_traj_products.html b/docs/_modules/pyrad/prod/process_traj_products.html index ee1310d..8b440db 100644 --- a/docs/_modules/pyrad/prod/process_traj_products.html +++ b/docs/_modules/pyrad/prod/process_traj_products.html @@ -6,7 +6,7 @@ - pyrad.prod.process_traj_products — pyrad 0.4.4 documentation + pyrad.prod.process_traj_products — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

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    @@ -236,7 +236,7 @@

    Navigation

  161. modules |
  162. - +
    diff --git a/docs/_modules/pyrad/prod/process_vol_products.html b/docs/_modules/pyrad/prod/process_vol_products.html index 4a947d1..8c81e64 100644 --- a/docs/_modules/pyrad/prod/process_vol_products.html +++ b/docs/_modules/pyrad/prod/process_vol_products.html @@ -6,7 +6,7 @@ - pyrad.prod.process_vol_products — pyrad 0.4.4 documentation + pyrad.prod.process_vol_products — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

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    @@ -3202,7 +3202,7 @@

    Navigation

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    diff --git a/docs/_modules/pyrad/prod/product_aux.html b/docs/_modules/pyrad/prod/product_aux.html index 5685816..0172ccc 100644 --- a/docs/_modules/pyrad/prod/product_aux.html +++ b/docs/_modules/pyrad/prod/product_aux.html @@ -6,7 +6,7 @@ - pyrad.prod.product_aux — pyrad 0.4.4 documentation + pyrad.prod.product_aux — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

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    @@ -176,7 +176,7 @@

    Navigation

  169. modules |
  170. - +
    diff --git a/docs/_modules/pyrad/util/radar_utils.html b/docs/_modules/pyrad/util/radar_utils.html index 087dbf6..ce370fd 100644 --- a/docs/_modules/pyrad/util/radar_utils.html +++ b/docs/_modules/pyrad/util/radar_utils.html @@ -6,7 +6,7 @@ - pyrad.util.radar_utils — pyrad 0.4.4 documentation + pyrad.util.radar_utils — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

  171. modules |
  172. - +
    @@ -1487,7 +1487,8 @@

    Source code for pyrad.util.radar_utils

         """
         if bin_edges is None:
             if field_name is not None:
    -            bin_edges = get_histogram_bins(field_name, step=step)
    +            bin_edges = get_histogram_bins(
    +                field_name, step=step, vmin=vmin, vmax=vmax)
             else:
                 if vmin is None:
                     vmin = np.ma.min(field)
    @@ -1506,7 +1507,8 @@ 

    Source code for pyrad.util.radar_utils

         return bin_edges, values
    -
    [docs]def compute_histogram_sweep(field, ray_start, ray_end, field_name, step=None): +
    [docs]def compute_histogram_sweep(field, ray_start, ray_end, field_name, step=None, + vmin=None, vmax=None): """ computes histogram of the data in a particular sweep @@ -1520,6 +1522,8 @@

    Source code for pyrad.util.radar_utils

             name of the field
         step : float
             size of bin
    +    vmin, vmax : float
    +        minimum and maximum values
     
         Returns
         -------
    @@ -1529,7 +1533,8 @@ 

    Source code for pyrad.util.radar_utils

             values at each bin
     
         """
    -    bin_edges = get_histogram_bins(field_name, step=step)
    +    bin_edges = get_histogram_bins(
    +        field_name, step=step, vmin=vmin, vmax=vmax)
         step_aux = bin_edges[1]-bin_edges[0]
         bin_centers = bin_edges[:-1]+step_aux/2.
         values = field[ray_start:ray_end+1, :].compressed()
    @@ -1539,10 +1544,10 @@ 

    Source code for pyrad.util.radar_utils

         return bin_edges, values
    -def get_histogram_bins(field_name, step=None): +def get_histogram_bins(field_name, step=None, vmin=None, vmax=None): """ - gets the histogram bins using the range limits of the field as defined - in the Py-ART config file. + gets the histogram bins. If vmin or vmax are not define the range limits + of the field as defined in the Py-ART config file are going to be used. Parameters ---------- @@ -1550,6 +1555,8 @@

    Source code for pyrad.util.radar_utils

             name of the field
         step : float
             size of bin
    +    vmin, vmax : float
    +        The minimum and maximum value of the histogram
     
         Returns
         -------
    @@ -1561,7 +1568,12 @@ 

    Source code for pyrad.util.radar_utils

         if 'boundaries' in field_dict:
             return np.array(field_dict['boundaries'])
     
    -    vmin, vmax = pyart.config.get_field_limits(field_name)
    +    vmin_aux, vmax_aux = pyart.config.get_field_limits(field_name)
    +    if vmin is None:
    +        vmin = vmin_aux
    +    if vmax is None:
    +        vmax = vmax_aux
    +
         if step is None:
             step = (vmax-vmin)/50.
             warn('No step has been defined. Default '+str(step)+' will be used')
    @@ -1732,7 +1744,7 @@ 

    Source code for pyrad.util.radar_utils

             field2.filled(fill_value=fill_value), bins=[bin_edges1, bin_edges2])
    -def quantize_field(field, field_name, step): +def quantize_field(field, field_name, step, vmin=None, vmax=None): """ quantizes data @@ -1744,6 +1756,8 @@

    Source code for pyrad.util.radar_utils

             name of the field
         step : float
             size of bin
    +    vmin, vmax : float
    +        min and max values
     
         Returns
         -------
    @@ -1753,7 +1767,11 @@ 

    Source code for pyrad.util.radar_utils

             values at each bin
     
         """
    -    vmin, vmax = pyart.config.get_field_limits(field_name)
    +    vmin_aux, vmax_aux = pyart.config.get_field_limits(field_name)
    +    if vmin is None:
    +        vmin = vmin_aux
    +    if vmax is None:
    +        vmax = vmax_aux
         field[field < vmin] = vmin
         field[field > vmax] = vmax
         fieldq = ((field+vmin)/step+1).astype(int)
    @@ -2011,7 +2029,7 @@ 

    Navigation

  173. modules |
  174. - +
    diff --git a/docs/_modules/pyrad/util/stat_utils.html b/docs/_modules/pyrad/util/stat_utils.html index 2b1aaf9..60c4ad7 100644 --- a/docs/_modules/pyrad/util/stat_utils.html +++ b/docs/_modules/pyrad/util/stat_utils.html @@ -6,7 +6,7 @@ - pyrad.util.stat_utils — pyrad 0.4.4 documentation + pyrad.util.stat_utils — pyrad 0.5.0 documentation @@ -27,7 +27,7 @@

    Navigation

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    @@ -226,7 +226,7 @@

    Navigation

  177. modules |
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    diff --git a/docs/_static/documentation_options.js b/docs/_static/documentation_options.js index 4477b69..2ddefb1 100644 --- a/docs/_static/documentation_options.js +++ b/docs/_static/documentation_options.js @@ -1,6 +1,6 @@ var DOCUMENTATION_OPTIONS = { URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'), - VERSION: '0.4.4', + VERSION: '0.5.0', LANGUAGE: 'None', COLLAPSE_INDEX: false, FILE_SUFFIX: '.html', diff --git a/docs/flow.html b/docs/flow.html index 8d3a907..b3fee7a 100644 --- a/docs/flow.html +++ b/docs/flow.html @@ -6,7 +6,7 @@ - processing flow control (pyrad.flow) — pyrad 0.4.4 documentation + processing flow control (pyrad.flow) — pyrad 0.5.0 documentation @@ -31,7 +31,7 @@

    Navigation

  179. previous |
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    @@ -4914,7 +4953,7 @@

    Navigation

  181. modules |
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    ‘GRID_TIMEAVG’ format output:

    ‘GRID_TIME_STATS’: process_grid_time_stats @@ -1084,17 +1108,21 @@

    DEM data: dictionary of dictionaries

    data set configuration. Accepted Configuration Keywords:

    -
    +
    datatype : string. Dataset keyword

    The data type where we want to extract the point measurement

    angle : float or None. Dataset keyword
    -

    The

    +

    The center angle to average. If not set or set to -1 all +available azimuth angles will be used

    +
    +
    delta_azi : float. Dataset keyword
    +

    The angle span to average. If not set or set to -1 all the +available azimuth angles will be used

    +
    +
    avg_type : str. Dataset keyword
    +

    Average type. Can be mean or median

    -
    -

    delta_azi : float. Dataset keyword

    -

    avg_type : str. Dataset keyword

    -
    nvalid_min : int. Dataset keyword

    the (minimum) radius of the region of interest in m. Default half the largest resolution

    @@ -1679,7 +1707,7 @@

    DEM datapath where to store the look up table

    model : string. Dataset keyword
    -

    The COSMO model to use. Can be cosmo-1, cosmo-2, cosmo-7

    +

    The COSMO model to use. Can be cosmo-1, cosmo-1e, cosmo-2, cosmo-7

    @@ -1982,7 +2010,7 @@

    DEM data
    pyrad.proc.process_dem(procstatus, dscfg, radar_list=None)[source]
    -

    Gets COSMO data and put it in radar coordinates

    +

    Gets DEM data and put it in radar coordinates

    @@ -3040,6 +3068,92 @@

    DEM data +
    +pyrad.proc.process_grid_fields_diff(procstatus, dscfg, radar_list=None)[source]
    +

    Computes grid field differences

    +

    +++ + + + + + +
    Parameters:
    +
    procstatus : int
    +

    Processing status: 0 initializing, 1 processing volume, +2 post-processing

    +
    +
    dscfg : dictionary of dictionaries
    +

    data set configuration. Accepted Configuration Keywords:

    +
    +
    datatype : list of string. Dataset keyword
    +

    The input data types

    +
    +
    +
    +
    radar_list : list of Radar objects
    +

    Optional. list of radar objects

    +
    +
    +
    Returns:
    +
    new_dataset : dict
    +

    dictionary containing a radar object containing the field differences

    +
    +
    ind_rad : int
    +

    radar index

    +
    +
    +
    +

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+ +
+
+pyrad.proc.process_grid_mask(procstatus, dscfg, radar_list=None)[source]
+

Mask data. Puts True if data is above a certain threshold and false +otherwise.

+ +++ + + + + + +
Parameters:
+
procstatus : int
+

Processing status: 0 initializing, 1 processing volume, +2 post-processing

+
+
dscfg : dictionary of dictionaries
+

data set configuration

+
+
radar_list : list of Radar objects
+

Optional. list of radar objects

+
+
threshold : float
+

Threshold used for the mask. Values below threshold are set to False. +Above threshold are set to True. Default 0.

+
+
x_dir_ext, y_dir_ext : int
+

Number of pixels by which to extend the mask on each side of the +west-east direction and south-north direction

+
+
+
Returns:
+
new_dataset : dict
+

dictionary containing the output

+
+
ind_rad : int
+

radar index

+
+
+
+
+
pyrad.proc.process_grid_point(procstatus, dscfg, radar_list=None)[source]
@@ -3104,6 +3218,53 @@

DEM data +
+pyrad.proc.process_grid_texture(procstatus, dscfg, radar_list=None)[source]
+

Computes the 2D texture of a gridded field

+ +++ + + + + + +
Parameters:
+
procstatus : int
+

Processing status: 0 initializing, 1 processing volume, +2 post-processing

+
+
dscfg : dictionary of dictionaries
+

data set configuration. Accepted Configuration Keywords:

+
+
datatype : list of string. Dataset keyword
+

The input data types

+
+
xwind, ywind : int
+

The size of the local window in the x and y axis. Default 7

+
+
fill_value : float
+

The value with which to fill masked data. Default np.NaN

+
+
+
+
radar_list : list of Radar objects
+

Optional. list of radar objects

+
+
+
Returns:
+
new_dataset : dict
+

dictionary containing a radar object containing the field differences

+
+
ind_rad : int
+

radar index

+
+
+
+

+
pyrad.proc.process_grid_time_stats(procstatus, dscfg, radar_list=None)[source]
@@ -3168,7 +3329,7 @@

DEM data
pyrad.proc.process_grid_time_stats2(procstatus, dscfg, radar_list=None)[source]
-

computes the temporal mean of a field

+

computes temporal statistics of a field

@@ -3988,6 +4149,43 @@

DEM data +
+pyrad.proc.process_normalize_luminosity(procstatus, dscfg, radar_list=None)[source]
+

Normalize the data by the sinus of the sun elevation. The sun elevation is +computed at the central pixel.

+

+++ + + + + + +
Parameters:
+
procstatus : int
+

Processing status: 0 initializing, 1 processing volume, +2 post-processing

+
+
dscfg : dictionary of dictionaries
+

data set configuration

+
+
radar_list : list of Radar objects
+

Optional. list of radar objects

+
+
+
Returns:
+
new_dataset : dict
+

dictionary containing the output

+
+
ind_rad : int
+

radar index

+
+
+
+

+
pyrad.proc.process_occurrence(procstatus, dscfg, radar_list=None)[source]
@@ -4401,6 +4599,48 @@

DEM data +
+pyrad.proc.process_pixel_filter(procstatus, dscfg, radar_list=None)[source]
+

Masks all pixels that are not of the class specified in keyword pixel_type

+ +++ + + + + + +
Parameters:
+
procstatus : int
+

Processing status: 0 initializing, 1 processing volume, +2 post-processing

+
+
dscfg : dictionary of dictionaries
+

data set configuration. Accepted Configuration Keywords:

+
+
pixel_type : int or list of ints
+

The type of pixels to keep: 0 No data, 1 Below threshold, 2 Above +threshold. Default 2

+
+
+
+
radar_list : list of Radar objects
+

Optional. list of radar objects

+
+
+
Returns:
+
new_dataset : dict
+

dictionary containing the output

+
+
ind_rad : int
+

radar index

+
+
+
+

+
pyrad.proc.process_point_measurement(procstatus, dscfg, radar_list=None)[source]
@@ -4420,6 +4660,12 @@

DEM data: string. Dataset keyword

The data type where we want to extract the point measurement

+
single_point : boolean. Dataset keyword
+

if True only one gate per radar volume is going to be kept. +Otherwise all gates within the azimuth and elevation tolerance +are going to be kept. This is useful to extract all data from +fixed pointing scans. Default True

+
latlon : boolean. Dataset keyword

if True position is obtained from latitude, longitude information, otherwise position is obtained from antenna coordinates @@ -4501,11 +4747,11 @@

DEM dataThe input data types

subtract_noise : Bool
-

If True noise will be subtracted from the signal

+

If True noise will be subtracted from the signal. Default False

smooth_window : int or None

Size of the moving Gaussian smoothing window. If none no smoothing -will be applied

+will be applied. Default None

variables : list of str

list of variables to compute. Default dBZ

@@ -4688,7 +4934,7 @@

DEM dataType of antenna of the radar we want to get the view from. Can be AZIMUTH, ELEVATION, LOWBEAM, HIGHBEAM

-
par_azimuth_antenna : dict. Global ekyword
+
par_azimuth_antenna : dict. Global keyword

Dictionary containing the parameters of the PAR azimuth antenna, i.e. name of the file with the antenna elevation pattern and fixed antenna angle

@@ -4715,7 +4961,7 @@

DEM data: Bool. Dataset keyword

If true the target radar has a different antenna pattern than the -observations radar

+observations radar. Default True

rhi_resolution : Bool. Dataset keyword

Resolution of the synthetic RHI used to compute the data as viewed @@ -4730,10 +4976,22 @@

DEM data: float. Datset keyword +
alt_tol : float. Dataset keyword

The tolerance in altitude to determine which synthetic radar gates are co-located with real radar gates [m]. Default 1000.

+
distance_upper_bound : float. Dataset keyword
+

The maximum distance where to look for a neighbour when +determining which synthetic radar gates are co-located with real +radar gates [m]. Default 1000.

+
+
use_cKDTree : Bool. Dataset keyword
+

Which function to use to find co-located real radar gates with the +synthetic radar. If True a function using cKDTree from +scipy.spatial is used. This function uses parameter +distance_upper_bound. If False a native implementation is used +that takes as parameters latlon_tol and alt_tol. Default True.

+
pattern_thres : float. Dataset keyword

The minimum of the sum of the weights given to each value in order to consider the weighted quantile valid. It is related to the @@ -4744,13 +5002,27 @@

DEM data: dict. Dataset keyword -

Dictionary specyfing whether the nans have to be used in the +

Dictionary specifying whether the nans have to be used in the computation of the statistics for each field. Default False

nan_value : dict. Dataset keyword

Dictionary with the value to use to substitute the NaN values when computing the statistics of each field. Default 0

+
moving_angle_min, moving_angle_max: float. Dataset keyword
+

The minimum and maximum azimuth angle (deg) of the target radar. +Default 0, 360.

+
+
ray_res: float
+

Ray resolution (deg). Default 1 deg.

+
+
rng_min, rng_max:
+

The minimum and maximum range of the target radar (m). +Default 0, 100000

+
+
rng_res : float
+

The target radar range resolution (m). Default 100.

+

radar_list : list of Radar objects
@@ -4760,7 +5032,7 @@

DEM dataReturns:
-
new_dataset : Trajectory object
+
new_dataset : dict

dictionary containing the new radar

ind_rad : int
@@ -4854,9 +5126,6 @@

DEM data: int -

range of window considered to find flat regions [m]. Default 8000.

-
ngates_min: int

minimum number of gates with noise to consider the retrieval valid. Default 800

@@ -4890,6 +5159,55 @@

DEM data +
+pyrad.proc.process_radial_velocity(procstatus, dscfg, radar_list=None)[source]
+

Estimates the radial velocity respect to the radar from the wind velocity

+ +++ + + + + + +
Parameters:
+
procstatus : int
+

Processing status: 0 initializing, 1 processing volume, +2 post-processing

+
+
dscfg : dictionary of dictionaries
+

data set configuration. Accepted Configuration Keywords:

+
+
datatype : string. Dataset keyword
+

The input data type

+
+
latitude, longitude : float
+

arbitrary coordinates [deg] from where to compute the radial +velocity. If any of them is None it will be the radar position

+
+
altitude : float
+

arbitrary altitude [m MSL] from where to compute the radial +velocity. If None it will be the radar altitude

+
+
+
+
radar_list : list of Radar objects
+

Optional. list of radar objects

+
+
+
Returns:
+
new_dataset : dict
+

dictionary containing the output

+
+
ind_rad : int
+

radar index

+
+
+
+

+
pyrad.proc.process_rainfall_accumulation(procstatus, dscfg, radar_list=None)[source]
@@ -5615,10 +5933,6 @@

DEM data: string. Dataset keyword

The data type where we want to extract the point measurement

-
anglenr : int
-

The sweep number to use. It assumes the radar volume consists on -PPI scans

-
hmax : float

The maximum height to plot [m]. Default 10000.

@@ -6304,6 +6618,12 @@

DEM data: string. Dataset keyword

The data type where we want to extract the point measurement

+
single_point : boolean. Dataset keyword
+

if True only one gate per radar volume is going to be kept. +Otherwise all gates within the azimuth and elevation tolerance +are going to be kept. This is useful to extract all data from +fixed pointing scans. Default True

+
latlon : boolean. Dataset keyword

if True position is obtained from latitude, longitude information, otherwise position is obtained from antenna coordinates @@ -6842,10 +7162,6 @@

DEM data: int -

Length of the flat region window [m]. Used in Ivic method. Default -8000.

-
iterations: int

number of iterations in step 7 of Ivic method. Default 10.

@@ -7447,17 +7763,30 @@

DEM data: float. Dataset keyword -

The tolerance in latitude and longitude to determine which synthetic -radar gates are co-located with real radar gates [deg]. Default 0.04

+

The tolerance in latitude and longitude to determine which +synthetic radar gates are co-located with real radar gates [deg]. +Default 0.04

alt_tol : float. Datset keyword

The tolerance in altitude to determine which synthetic radar gates are co-located with real radar gates [m]. Default 1000.

+
distance_upper_bound : float. Dataset keyword
+

The maximum distance where to look for a neighbour when +determining which synthetic radar gates are co-located with real +radar gates [m]. Default 1000.

+
+
use_cKDTree : Bool. Dataset keyword
+

Which function to use to find co-located real radar gates with the +synthetic radar. If True a function using cKDTree from +scipy.spatial is used. This function uses parameter +distance_upper_bound. If False a native implementation is used +that takes as parameters latlon_tol and alt_tol. Default True.

+
pattern_thres : float. Dataset keyword

The minimum of the sum of the weights given to each value in order -to consider the weighted quantile valid. It is related to the number -of valid data points

+to consider the weighted quantile valid. It is related to the +number of valid data points

data_is_log : dict. Dataset keyword

Dictionary specifying for each field if it is in log (True) or @@ -7780,8 +8109,8 @@

DEM data: float

The fixed range [m], azimuth [deg] or elevation [deg] to extract. -In each mode two of these parameters have to be defined. If they are -not defined they default to 0.

+In each mode two of these parameters have to be defined. If they +are not defined they default to 0.

ang_tol, rng_tol : float

The angle tolerance [deg] and range tolerance [m] around the fixed @@ -8429,7 +8758,7 @@

Navigation

  • modules |
  • - +

    + + +
    +
    ‘SURFACE_IMAGE’: Plots a surface image of gridded data.
    +
    User defined parameters:
    level: int
    @@ -377,9 +393,8 @@

    Product generation -
    ‘SURFACE_CONTOUR’: Plots a surface image of gridded data.
    +

    +
    ‘SURFACE_CONTOUR’: Plots a surface image of contour gridded data.
    User defined parameters:
    @@ -387,10 +402,60 @@

    Product generation: float array or None +
    The contour values. If None the values are taken from the +‘boundaries’ keyword in the field description in the +Py-ART config file. If ‘boundaries’ is not set the +countours are 10 values linearly distributed from vmin to +vmax
    +
    linewidths : float
    +
    width of the contour lines
    +
    colors : color string or sequence of colors
    +
    The contour colours

    +
    SURFACE_CONTOUR_OVERPLOT:
    +

    Plots a surface image of gridded data with a contour overplotted. +User defined parameters:

    +
    +
    +
    level: int
    +
    The altitude level to plot. The rest of the parameters are +defined by the parameters in ‘ppiImageConfig’ and +‘ppiMapImageConfig’ in the ‘loc’ configuration file
    +
    contour_values : float array or None
    +
    The contour values. If None the values are taken from the +‘boundaries’ keyword in the field description in the +Py-ART config file. If ‘boundaries’ is not set the +countours are 10 values linearly distributed from vmin to +vmax
    +
    linewidths : float
    +
    width of the contour lines
    +
    colors : color string or sequence of colors
    +
    The contour colours
    +
    +
    +
    +
    SURFACE_OVERPLOT:
    +

    Plots on the same surface two images, one on top of the other. +User defined parameters:

    +
    +
    +
    level: int
    +
    The altitude level to plot. The rest of the parameters are +defined by the parameters in ‘ppiImageConfig’ and +‘ppiMapImageConfig’ in the ‘loc’ configuration file
    +
    contour_values : float array or None
    +
    The contour values. If None the values are taken from the +‘boundaries’ keyword in the field description in the +Py-ART config file. If ‘boundaries’ is not set the +countours are 10 values linearly distributed from vmin to +vmax
    +
    +
    +
    @@ -2317,7 +2382,7 @@

    Navigation

  • modules |
  • - +

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