Products generation (pyrad.prod
)¶
Initiate the products generation.
Auxiliary functions¶
get_dsformat_func |
Product generation¶
generate_occurrence_products (dataset, prdcfg) |
generates occurrence products. Accepted product types: |
generate_cosmo_coord_products (dataset, prdcfg) |
generates COSMO coordinates products. Accepted product types: |
generate_cosmo_to_radar_products (dataset, prdcfg) |
generates COSMO data in radar coordinates products. |
generate_sun_hits_products (dataset, prdcfg) |
generates sun hits products. Accepted product types: |
generate_intercomp_products (dataset, prdcfg) |
Generates radar intercomparison products. Accepted product types: |
generate_colocated_gates_products (dataset, …) |
Generates colocated gates products. Accepted product types: |
generate_time_avg_products (dataset, prdcfg) |
generates time average products. Accepted product types: |
generate_qvp_products (dataset, prdcfg) |
Generates quasi vertical profile-like products. |
generate_vol_products (dataset, prdcfg) |
Generates radar volume products. Accepted product types: |
generate_timeseries_products (dataset, prdcfg) |
Generates time series products. Accepted product types: |
generate_monitoring_products (dataset, prdcfg) |
generates a monitoring product. |
generate_spectra_products (dataset, prdcfg) |
generates spectra products. Accepted product types: |
generate_grid_products (dataset, prdcfg) |
generates grid products. Accepted product types: |
generate_grid_time_avg_products (dataset, prdcfg) |
generates time average products. Accepted product types: |
generate_traj_product (traj, prdcfg) |
Generates trajectory products. Accepted product types: |
generate_ml_products (dataset, prdcfg) |
Generates melting layer products. Accepted product types: |
-
pyrad.prod.
generate_colocated_gates_products
(dataset, prdcfg)[source]¶ - Generates colocated gates products. Accepted product types:
- ‘WRITE_COLOCATED_GATES’: Writes the position of the co-located gates
- in a csv file
All the products of the ‘VOL’ dataset group
Parameters: - dataset : tuple
radar objects and colocated gates dictionary
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - filename : str
the name of the file created. None otherwise
-
pyrad.prod.
generate_cosmo_coord_products
(dataset, prdcfg)[source]¶ - generates COSMO coordinates products. Accepted product types:
- ‘SAVEVOL’: Save an object containing the index of the COSMO model grid
that corresponds to each radar gate in a C/F radial file. User defined parameters:
- file_type: str
- The type of file used to save the data. Can be ‘nc’ or ‘h5’. Default ‘nc’
- physical: Bool
- If True the data will be saved in physical units (floats). Otherwise it will be quantized and saved as binary
- compression: str
- For ODIM file formats, the type of compression. Can be any of the allowed compression types for hdf5 files. Default gzip
- compression_opts: any
- The compression options allowed by the hdf5. Depends on the type of compression. Default 6 (The gzip compression level).
Parameters: - dataset : tuple
radar object containing the COSMO coordinates
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - filename : str
the name of the file created. None otherwise
-
pyrad.prod.
generate_cosmo_to_radar_products
(dataset, prdcfg)[source]¶ generates COSMO data in radar coordinates products. Accepted product types:
- ‘SAVEVOL’: Save an object containing the COSMO data in radar
- coordinatesin a C/F radial or ODIM file.
User defined parameters: file_type: str
The type of file used to save the data. Can be ‘nc’ or ‘h5’. Default ‘nc’- physical: Bool
- If True the data will be saved in physical units (floats). Otherwise it will be quantized and saved as binary
- compression: str
- For ODIM file formats, the type of compression. Can be any of the allowed compression types for hdf5 files. Default gzip
- compression_opts: any
- The compression options allowed by the hdf5. Depends on the type of compression. Default 6 (The gzip compression level).
All the products of the ‘VOL’ dataset group
Parameters: - dataset : tuple
radar object containing the COSMO coordinates
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - filename : str
the name of the file created. None otherwise
-
pyrad.prod.
generate_grid_products
(dataset, prdcfg)[source]¶ - generates grid products. Accepted product types:
- ‘CROSS_SECTION’: Plots a cross-section of gridded data
- User defined parameters:
- coord1, coord2: dict
- The two lat-lon coordinates marking the limits. They have the keywords ‘lat’ and ‘lon’ [degree]. The altitude limits are defined by the parameters in ‘rhiImageConfig’ in the ‘loc’ configuration file
- ‘HISTOGRAM’: Computes a histogram of the radar volum data
- User defined parameters:
- step: float or None
- the data quantization step. If none it will be obtained from the Py-ART configuration file
- 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
constant latitude. User defined parameters:
- lon, lat: floats
- The starting point of the cross-section. The ending point is defined by the parameters in ‘rhiImageConfig’ in the ‘loc’ configuration file
- ‘LONGITUDE_SLICE’: Plots a cross-ection of gridded data over a
constant longitude. User defined parameters:
- lon, lat: floats
- The starting point of the cross-section. The ending point is defined by the parameters in ‘rhiImageConfig’ in the ‘loc’ configuration file
- ‘SAVEALL’: Saves a gridded data object including all or a list of
user-defined fields in a netcdf file User defined parameters:
- datatypes: list of str or None
- 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. ‘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.
- 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
Parameters: - dataset : grid
grid object
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - None or name of generated files
-
pyrad.prod.
generate_grid_time_avg_products
(dataset, prdcfg)[source]¶ - generates time average products. Accepted product types:
- All the products of the ‘VOL’ dataset group
Parameters: - dataset : tuple
radar objects and colocated gates dictionary
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - filename : str
the name of the file created. None otherwise
-
pyrad.prod.
generate_intercomp_products
(dataset, prdcfg)[source]¶ - Generates radar intercomparison products. Accepted product types:
- ‘PLOT_AND_WRITE_INTERCOMP_TS’: Writes statistics of radar
intercomparison in a file and plots the time series of the statistics. User defined parameters:
- ‘add_date_in_fname’: Bool
- If true adds the year in the csv file containing the statistics. Default False
- ‘sort_by_date’: Bool
- If true sorts the statistics by date when reading the csv file containing the statistics. Default False
- ‘rewrite’: Bool
- If true rewrites the csv file containing the statistics. Default False
- ‘npoints_min’: int
- The minimum number of points to consider the statistics valid and therefore use the data point in the plotting. Default 0
- ‘corr_min’: float
- The minimum correlation to consider the statistics valid and therefore use the data point in the plotting. Default 0.
- ‘PLOT_SCATTER_INTERCOMP’: Plots a density plot with the points of
radar 1 versus the points of radar 2 User defined parameters:
- ‘step’: float
- The quantization step of the data. If none it will be computed using the Py-ART config file. Default None
- ‘scatter_type’: str
- Type of scatter plot. Can be a plot for each radar volume (‘instant’) or at the end of the processing period (‘cumulative’). Default is ‘cumulative’
- ‘WRITE_INTERCOMP’: Writes the instantaneously intercompared data
- (gate positions, values, etc.) in a csv file.
- ‘WRITE_INTERCOMP_TIME_AVG’: Writes the time-averaged intercompared
- data (gate positions, values, etc.) in a csv file.
Parameters: - dataset : tuple
values of colocated gates dictionary
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - filename : str
the name of the file created. None otherwise
-
pyrad.prod.
generate_ml_products
(dataset, prdcfg)[source]¶ - Generates melting layer products. Accepted product types:
- ‘ML_TS’: Plots and writes a time series of the melting layer, i.e.
the evolution of the average and standard deviation of the melting layer top and thickness and the the number of rays used in the retrieval. User defined parameters:
- dpi: int
- The pixel density of the plot. Default 72
- ‘SAVE_ML’: Saves an object containing the melting layer retrieval
- information in a C/F radial file
All the products of the ‘VOL’ dataset group
Parameters: - dataset : dict
dictionary containing the radar object and a keyword stating the status of the processing
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - filename : str
the name of the file created. None otherwise
-
pyrad.prod.
generate_monitoring_products
(dataset, prdcfg)[source]¶ generates a monitoring product. With the parameter ‘hist_type’ the user may define if the product is computed for each radar volume (‘instant’) or at the end of the processing period (‘cumulative’). Default is ‘cumulative’. Accepted product types:
- ‘ANGULAR_DENSITY’: For a specified elevation angle, plots a 2D
histogram with the azimuth angle in the X-axis and the data values in the Y-axis. The reference values and the user defined quantiles are also plot on the same figure User defined parameters:
- anglenr: int
- The elevation angle number to plot
- quantiles: list of floats
- The quantiles to plot. Default 25., 50., 75.
- ref_value: float
- The reference value
- vmin, vmax : floats or None
- The minimum and maximum values of the data points. If not specified they are obtained from the Py-ART config file
- ‘CUMUL_VOL_TS’: Plots time series of the average of instantaneous
quantiles stored in a csv file. User defined parameters:
- quantiles: list of 3 floats
- the quantiles to compute. Default 25., 50., 75.
- ref_value: float
- The reference value. Default 0
- sort_by_date: Bool
- If true when reading the csv file containing the statistics the data is sorted by date. Default False
- rewrite: Bool
- If true the csv file containing the statistics is rewritten
- add_data_in_fname: Bool
- If true and the data used is cumulative the year is written in the csv file name and the plot file name
- npoints_min: int
- Minimum number of points to use the data point in the plotting and to send an alarm. Default 0
- vmin, vmax: float or None
- Limits of the Y-axis (data value). If None the limits are obtained from the Py-ART config file
- alarm: Bool
- If true an alarm is sent
- tol_abs: float
- Margin of tolerance from the reference value. If the current value is above this margin an alarm is sent. If the margin is not specified it is not possible to send any alarm
- tol_trend: float
- Margin of tolerance from the reference value. If the trend of the last X events is above this margin an alarm is sent. If the margin is not specified it is not possible to send any alarm
- nevents_min: int
- Minimum number of events with sufficient points to send an alarm related to the trend. If not specified it is not possible to send any alarm
- sender: str
- The mail of the alarm sender. If not specified it is not possible to send any alarm
- receiver_list: list of str
- The list of emails of the people that will receive the alarm.. If not specified it is not possible to send any alarm
- ‘PPI_HISTOGRAM’: Plots a histogram of data at a particular
elevation angle. User defined parameters:
- anglenr: int
- The elevation angle number to plot
- ‘SAVEVOL’: Saves the monitoring data in a C/F radar file. The data
- field contains histograms of data for each pair of azimuth and elevation angles
- ‘VOL_HISTOGRAM’: Plots a histogram of data collected from all the
radar volume. User defined parameters:
- write_data: bool
- If true the resultant histogram is also saved in a csv file. Default True.
- ‘VOL_TS’: Computes statistics of the gathered data and writes them in
a csv file and plots a time series of those statistics. User defined parameters:
- quantiles: list of 3 floats
- the quantiles to compute. Default 25., 50., 75.
- ref_value: float
- The reference value. Default 0
- sort_by_date: Bool
- If true when reading the csv file containing the statistics the data is sorted by date. Default False
- rewrite: Bool
- If true the csv file containing the statistics is rewritten
- add_data_in_fname: Bool
- If true and the data used is cumulative the year is written in the csv file name and the plot file name
- npoints_min: int
- Minimum number of points to use the data point in the plotting and to send an alarm. Default 0
- vmin, vmax: float or None
- Limits of the Y-axis (data value). If None the limits are obtained from the Py-ART config file
- alarm: Bool
- If true an alarm is sent
- tol_abs: float
- Margin of tolerance from the reference value. If the current value is above this margin an alarm is sent. If the margin is not specified it is not possible to send any alarm
- tol_trend: float
- Margin of tolerance from the reference value. If the trend of the last X events is above this margin an alarm is sent. If the margin is not specified it is not possible to send any alarm
- nevents_min: int
- Minimum number of events with sufficient points to send an alarm related to the trend. If not specified it is not possible to send any alarm
- sender: str
- The mail of the alarm sender. If not specified it is not possible to send any alarm
- receiver_list: list of str
- The list of emails of the people that will receive the alarm.. If not specified it is not possible to send any alarm
Parameters: - dataset : dictionary
dictionary containing a histogram object and some metadata
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - filename : str
the name of the file created. None otherwise
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pyrad.prod.
generate_occurrence_products
(dataset, prdcfg)[source]¶ - generates occurrence products. Accepted product types:
- ‘WRITE_EXCESS_GATES’: Write the data that identifies radar gates
with clutter that has a frequency of occurrence above a certain threshold. User defined parameters:
- quant_min: float
- Minimum frequency of occurrence in percentage to keep the gate as valid. Default 95.
All the products of the ‘VOL’ dataset group
Parameters: - dataset : tuple
radar object and metadata dictionary
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - filename : str
the name of the file created. None otherwise
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pyrad.prod.
generate_qvp_products
(dataset, prdcfg)[source]¶ Generates quasi vertical profile-like products. Quasi vertical profiles come from azimuthal averaging of polarimetric radar data. With the variable ‘qvp_type’ the user decides if the product has to be generated at the end of the processing period (‘final’) or instantaneously (‘instant’) Accepted product types:
All the products of the ‘VOL’ dataset groupParameters: - dataset : dict
dictionary containing the radar object and a keyword stating the status of the processing
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - filename : str
the name of the file created. None otherwise
-
pyrad.prod.
generate_spectra_products
(dataset, prdcfg)[source]¶ - generates spectra products. Accepted product types:
- ‘AMPLITUDE_PHASE_ANGLE_DOPPLER’: Makes an angle Doppler plot of
complex spectra or IQ data. The plot can be along azimuth or along range. It is plotted separately the module and the phase of the signal. User defined parameters:
- along_azi : bool
- If true the plot is performed along azimuth, otherwise along elevation. Default true
- ang : float
- The fixed angle (deg). Default 0.
- rng : float
- The fixed range (m). Default 0.
- ang_tol : float
- The fixed angle tolerance (deg). Default 1.
- rng_tol : float
- The fixed range tolerance (m). Default 50.
- xaxis_info : str
- The xaxis type. Can be ‘Doppler_velocity’, ‘Doppler_frequency’ or ‘pulse_number’
- ampli_vmin, ampli_vmax, phase_vmin, phase_vmax : float or None
- Minimum and maximum of the color scale for the module and phase
- ‘AMPLITUDE_PHASE_DOPPLER’: Plots a complex Doppler spectrum or IQ data
making two separate plots for the module and phase of the signal User defined parameters:
- azi, ele, rng : float
- azimuth and elevation (deg) and range (m) of the ray to plot
- azi_to, ele_tol, rng_tol : float
- azimuth and elevation (deg) and range (m) tolerance respect to nominal position to plot. Default 1, 1, 50.
- ind_ray, ind_rng : int
- index of the ray and range to plot. Alternative to defining its antenna coordinates
- xaxis_info : str
- The xaxis type. Can be ‘Doppler_velocity’, ‘Doppler_frequency’ or ‘pulse_number’
- ampli_vmin, ampli_vmax, phase_vmin, phase_vmax : float or None
- Minimum and maximum of the color scale for the module and phase
- ‘AMPLITUDE_PHASE_RANGE_DOPPLER’: Plots a complex spectra or IQ data
range-Doppler making two separate plots for the module and phase of the signal User defined parameters:
- azi, ele : float
- azimuth and elevation (deg) of the ray to plot
- azi_to, ele_tol : float
- azimuth and elevation (deg) tolerance respect to nominal position to plot. Default 1, 1.
- ind_ray : int
- index of the ray to plot. Alternative to defining its antenna coordinates
- xaxis_info : str
- The xaxis type. Can be ‘Doppler_velocity’, ‘Doppler_frequency’ or ‘pulse_number’
- ampli_vmin, ampli_vmax, phase_vmin, phase_vmax : float or None
- Minimum and maximum of the color scale for the module and phase
- ‘AMPLITUDE_PHASE_TIME_DOPPLER’: Plots a complex spectra or IQ data
time-Doppler making two separate plots for the module and phase of the signal User defined parameters:
- xaxis_info : str
- The xaxis type. Can be ‘Doppler_velocity’ or ‘Doppler frequency’
- ampli_vmin, ampli_vmax, phase_vmin, phase_vmax : float or None
- Minimum and maximum of the color scale for the module and phase
- plot_type : str
- Can be ‘final’ or ‘temporal’. If final the data is only plotted at the end of the processing
- ‘ANGLE_DOPPLER’: Makes an angle Doppler plot. The plot can be along
azimuth or along range User defined parameters:
- along_azi : bool
- If true the plot is performed along azimuth, otherwise along elevation. Default true
- ang : float
- The fixed angle (deg). Default 0.
- rng : float
- The fixed range (m). Default 0.
- ang_tol : float
- The fixed angle tolerance (deg). Default 1.
- rng_tol : float
- The fixed range tolerance (m). Default 50.
- xaxis_info : str
- The xaxis type. Can be ‘Doppler_velocity’, ‘Doppler_frequency’ or ‘pulse_number’
- vmin, vmax : float or None
- Minimum and maximum of the color scale
- ‘COMPLEX_ANGLE_DOPPLER’: Makes an angle Doppler plot of complex
spectra or IQ data. The plot can be along azimuth or along range. The real and imaginary parts are plotted separately User defined parameters:
- along_azi : bool
- If true the plot is performed along azimuth, otherwise along elevation. Default true
- ang : float
- The fixed angle (deg). Default 0.
- rng : float
- The fixed range (m). Default 0.
- ang_tol : float
- The fixed angle tolerance (deg). Default 1.
- rng_tol : float
- The fixed range tolerance (m). Default 50.
- xaxis_info : str
- The xaxis type. Can be ‘Doppler_velocity’, ‘Doppler_frequency’ or ‘pulse_number’
- vmin, vmax : float or None
- Minimum and maximum of the color scale
- ‘COMPLEX_DOPPLER’: Plots a complex Doppler spectrum or IQ data making
two separate plots for the real and imaginary parts User defined parameters:
- azi, ele, rng : float
- azimuth and elevation (deg) and range (m) of the ray to plot
- azi_to, ele_tol, rng_tol : float
- azimuth and elevation (deg) and range (m) tolerance respect to nominal position to plot. Default 1, 1, 50.
- ind_ray, ind_rng : int
- index of the ray and range to plot. Alternative to defining its antenna coordinates
- xaxis_info : str
- The xaxis type. Can be ‘Doppler_velocity’, ‘Doppler_frequency’ or ‘pulse_number’
- vmin, vmax : float or None
- Minimum and maximum of the color scale
- ‘COMPLEX_RANGE_DOPPLER’: Plots the complex spectra or IQ data
range-Doppler making two separate plots for the real and imaginary parts User defined parameters:
- azi, ele : float
- azimuth and elevation (deg) of the ray to plot
- azi_to, ele_tol : float
- azimuth and elevation (deg) tolerance respect to nominal position to plot. Default 1, 1.
- ind_ray : int
- index of the ray to plot. Alternative to defining its antenna coordinates
- xaxis_info : str
- The xaxis type. Can be ‘Doppler_velocity’, ‘Doppler_frequency’ or ‘pulse_number’
- vmin, vmax : float or None
- Minimum and maximum of the color scale
- ‘COMPLEX_TIME_DOPPLER’: Plots the complex spectra or IQ data
time-Doppler making two separate plots for the real and imaginary parts User defined parameters:
- xaxis_info : str
- The xaxis type. Can be ‘Doppler_velocity’ or ‘Doppler frequency’
- vmin, vmax : float or None
- Minimum and maximum of the color scale
- plot_type : str
- Can be ‘final’ or ‘temporal’. If final the data is only plotted at the end of the processing
- ‘DOPPLER’: Plots a Doppler spectrum variable or IQ data variable
- User defined parameters:
- azi, ele, rng : float
- azimuth and elevation (deg) and range (m) of the ray to plot
- azi_to, ele_tol, rng_tol : float
- azimuth and elevation (deg) and range (m) tolerance respect to nominal position to plot. Default 1, 1, 50.
- ind_ray, ind_rng : int
- index of the ray and range to plot. Alternative to defining its antenna coordinates
- xaxis_info : str
- The xaxis type. Can be ‘Doppler_velocity’, ‘Doppler_frequency’ or ‘pulse_number’
- vmin, vmax : float or None
- Minimum and maximum of the color scale
- ‘RANGE_DOPPLER’: Makes a range-Doppler plot of spectral or IQ data
- User defined parameters:
- azi, ele : float
- azimuth and elevation (deg) of the ray to plot
- azi_to, ele_tol : float
- azimuth and elevation (deg) tolerance respect to nominal position to plot. Default 1, 1.
- ind_ray : int
- index of the ray to plot. Alternative to defining its antenna coordinates
- xaxis_info : str
- The xaxis type. Can be ‘Doppler_velocity’, ‘Doppler_frequency’ or ‘pulse_number’
- vmin, vmax : float or None
- Minimum and maximum of the color scale
- ‘SAVEALL’: Saves radar spectra or IQ volume data including all or a
list of userdefined fields in a netcdf file User defined parameters:
- datatypes: list of str or None
- The list of data types to save. If it is None, all fields in the radar object will be saved
- physical: Bool
- If True the data will be saved in physical units (floats). Otherwise it will be quantized and saved as binary
- ‘SAVEVOL’: Saves one field of a radar spectra or IQ volume data in a
netcdf file User defined parameters:
- physical: Bool
- If True the data will be saved in physical units (floats). Otherwise it will be quantized and saved as binary
- ‘TIME_DOPPLER’: Makes a time-Doppler plot of spectral or IQ data at a
point of interest. User defined parameters:
- xaxis_info : str
- The xaxis type. Can be ‘Doppler_velocity’, ‘Doppler_frequency’ or ‘pulse_number’
- vmin, vmax : float or None
- Minimum and maximum of the color scale
- plot_type : str
- Can be ‘final’ or ‘temporal’. If final the data is only plotted at the end of the processing
Parameters: - dataset : spectra
spectra object
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - None or name of generated files
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pyrad.prod.
generate_sun_hits_products
(dataset, prdcfg)[source]¶ - generates sun hits products. Accepted product types:
- ‘PLOT_SUN_HITS’: Plots in a sun-radar azimuth difference-sun-radar
- elevation difference grid the values of all sun hits obtained during the processing period
- ‘PLOT_SUN_RETRIEVAL’: Plots in a sun-radar azimuth difference-sun-
- radar elevation difference grid the retrieved sun pattern
- ‘PLOT_SUN_RETRIEVAL_TS’: Plots time series of the retrieved sun
pattern parameters User defined parameters:
- dpi: int
- The pixel density of the plot. Default 72
- add_date_in_fname: Bool
- If true the year is added in the plot file name
- ‘WRITE_SUN_HITS’: Writes the information concerning possible sun hits
- in a csv file
- ‘WRITE_SUN_RETRIEVAL’: Writes the retrieved sun pattern parameters in
a csv file. User defined parameters:
- add_date_in_fname: Bool
- If true the year is added in the csv file name
All the products of the ‘VOL’ dataset group
Parameters: - dataset : tuple
radar object and sun hits dictionary
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - filename : str
the name of the file created. None otherwise
-
pyrad.prod.
generate_time_avg_products
(dataset, prdcfg)[source]¶ - generates time average products. Accepted product types:
- All the products of the ‘VOL’ dataset group
Parameters: - dataset : tuple
radar objects and colocated gates dictionary
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - filename : str
the name of the file created. None otherwise
-
pyrad.prod.
generate_timeseries_products
(dataset, prdcfg)[source]¶ - Generates time series products. Accepted product types:
- ‘COMPARE_CUMULATIVE_POINT’: Plots in the same graph 2 time series of
data accumulation (tipically rainfall rate). One time series is a point measurement of radar data while the other is from a co-located instrument (rain gauge or disdrometer) User defined parameters:
- dpi: int
- The pixel density of the plot. Default 72
- vmin, vmax: float
- The limits of the Y-axis. If none they will be obtained from the Py-ART config file.
- sensor: str
- The sensor type. Can be ‘rgage’ or ‘disdro’
- sensorid: str
- The sensor ID.
- location: str
- A string identifying the location of the disdrometer
- freq: float
- The frequency used to retrieve the polarimetric variables of a disdrometer
- ele: float
- The elevation angle used to retrieve the polarimetric variables of a disdrometer
- ScanPeriod: float
- The scaning period of the radar in seconds. This parameter is defined in the ‘loc’ config file
- ‘COMPARE_POINT’: Plots in the same graph 2 time series of
data . One time series is a point measurement of radar data while the other is from a co-located instrument (rain gauge or disdrometer) User defined parameters:
- dpi: int
- The pixel density of the plot. Default 72
- vmin, vmax: float
- The limits of the Y-axis. If none they will be obtained from the Py-ART config file.
- sensor: str
- The sensor type. Can be ‘rgage’ or ‘disdro’
- sensorid: str
- The sensor ID.
- location: str
- A string identifying the location of the disdrometer
- freq: float
- The frequency used to retrieve the polarimetric variables of a disdrometer
- ele: float
- The elevation angle used to retrieve the polarimetric variables of a disdrometer
- ‘COMPARE_TIME_AVG’: Creates a scatter plot of average radar data
versus average sensor data. User defined parameters:
- dpi: int
- The pixel density of the plot. Default 72
- sensor: str
- The sensor type. Can be ‘rgage’ or ‘disdro’
- sensorid: str
- The sensor ID.
- location: str
- A string identifying the location of the disdrometer
- freq: float
- The frequency used to retrieve the polarimetric variables of a disdrometer
- ele: float
- The elevation angle used to retrieve the polarimetric variables of a disdrometer
- cum_time: float
- Data accumulation time [s]. Default 3600.
- base_time: float
- Starting moment of the accumulation [s from midnight]. Default 0.
- ‘PLOT_AND_WRITE’: Writes and plots a trajectory time series.
- User defined parameters:
- ymin, ymax: float
- The minimum and maximum value of the Y-axis. If none it will be obtained from the Py-ART config file.
- ‘PLOT_AND_WRITE_POINT’: Plots and writes a time series of radar data
at a particular point User defined parameters:
- dpi: int
- The pixel density of the plot. Default 72
- vmin, vmax: float
- The limits of the Y-axis. If none they will be obtained from the Py-ART config file.
- ‘PLOT_CUMULATIVE_POINT’: Plots a time series of radar data
accumulation at a particular point. User defined parameters:
- dpi: int
- The pixel density of the plot. Default 72
- vmin, vmax: float
- The limits of the Y-axis. If none they will be obtained from the Py-ART config file.
- ScanPeriod: float
- The scaning period of the radar in seconds. This parameter is defined in the ‘loc’ config file
- ‘PLOT_HIST’: plots and writes a histogram of all the data gathered
during the trajectory processing User defined parameters:
- step: float or None
- The quantization step of the data. If None it will be obtained from the Py-ART config file
- ‘TRAJ_CAPPI_IMAGE’: Creates a CAPPI image with the trajectory position
overplot on it. User defined parameters:
- color_ref: str
- The meaning of the color code with which the trajectory is plotted. Can be ‘None’, ‘altitude’ (the absolute altitude), ‘rel_altitude’ (altitude relative to the CAPPI altitude), ‘time’ (trajectory time respect of the start of the radar scan leading to the CAPPI)
- altitude: float
- The CAPPI altitude [m]
- wfunc: str
- Function used in the gridding of the radar data. The function types are defined in pyart.map.grid_from_radars. Default ‘NEAREST’
- res: float
- The CAPPI resolution [m]. Default 500.
Parameters: - dataset : dictionary
radar object
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - no return
-
pyrad.prod.
generate_traj_product
(traj, prdcfg)[source]¶ - Generates trajectory products. Accepted product types:
- ‘TRAJ_MAP’: Plots the trajectory on a lat-lon map with the altitude
- color coded
- ‘TRAJ_PLOT’: Plots time series of the trajectory respect to the radar
elevation, azimuth or range User defined parameters:
- ‘datatype’: str
- The type of parameter: ‘EL’, ‘AZ’, or ‘RANGE’
‘TRAJ_TEXT’: Writes the trajectory information in a csv file
Parameters: - traj : Trajectory object
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - None
-
pyrad.prod.
generate_vol_products
(dataset, prdcfg)[source]¶ - Generates radar volume products. Accepted product types:
- ‘CDF’: plots and writes the cumulative density function of data
- User defined parameters:
- quantiles: list of floats
- The quantiles to compute in percent. Default None
- sector: dict
dictionary defining the sector where to compute the CDF. Default is None and the CDF is computed over all the data May contain:
- rmin, rmax: float
- min and max range [m]
- azmin, azmax: float
- min and max azimuth angle [deg]
- elmin, elmax: float
- min and max elevation angle [deg]
- hmin, hmax: float
- min and max altitude [m MSL]
- vismin: float
- The minimum visibility to use the data. Default None
- absolute: Bool
- If true the absolute values of the data will be used. Default False
- use_nans: Bool
- If true NaN values will be used. Default False
- nan_value: Bool
- The value by which the NaNs are substituted if NaN values are to be used in the computation
- filterclt: Bool
- If True the gates containing clutter are filtered
- filterprec: list of ints
- The hydrometeor types that are filtered from the analysis. Default empty list.
- ‘BSCOPE_IMAGE’: Creates a B-scope image (azimuth, range)
- User defined parameters:
- anglenr : int
- The elevation angle number to use
- ray_dim : str
- the ray dimension. Can be ‘ang’ or ‘time’. Default ‘ang’
- xaxis_rng : bool
- if True the range will be in the x-axis. Otherwise it will be in the y-axis. Default True
- vmin, vmax: float or None
- The minimum and maximum values of the color scale. If None the scale is going to be set according to the Py-ART config file
- ‘CAPPI_IMAGE’: Creates a CAPPI image
- User defined parameters:
- altitude: flt
- CAPPI altitude [m MSL]
- wfunc: str
- The function used to produce the CAPPI as defined in pyart.map.grid_from_radars. Default ‘NEAREST’
- cappi_res: float
- The CAPPI resolution [m]. Default 500.
- ‘FIELD_COVERAGE’: Gets the field coverage over a certain sector
- User defined parameters:
- threshold: float or None
- Minimum value to consider the data valid. Default None
- nvalid_min: float
- Minimum number of valid gates in the ray to consider it valid. Default 5
- ele_res, azi_res: float
- Elevation and azimuth resolution of the sectors [deg]. Default 1. and 2.
- ele_min, ele_max: float
- Min and max elevation angle defining the sector [deg]. Default 0. and 30.
- ele_step: float
- Elevation step [deg]. Default 5.
- ele_sect_start, ele_sect_stop: float or None
- start and stop angles of the sector coverage. Default None
- quantiles: list of floats
- The quantiles to compute in the sector. Default 10. to 90. by steps of 10.
- AngTol: float
- The tolerance in elevation angle when putting the data in a fixed grid
- ‘FIXED_RNG_IMAGE’: Plots a fixed range image
- User defined parameters:
- AngTol : float
- The tolerance between the nominal angles and the actual radar angles. Default 1.
- ele_res, azi_res: float or None
- The resolution of the fixed grid [deg]. If None it will be obtained from the separation between angles
- vmin, vmax : float or None
- Min and Max values of the color scale. If None the values are taken from the Py-ART config file
- ‘FIXED_RNG_SPAN_IMAGE’: Plots a user-defined statistic over a fixed
range image User defined parameters:
- AngTol : float
- The tolerance between the nominal angles and the actual radar angles. Default 1.
- ele_res, azi_res: float or None
- The resolution of the fixed grid [deg]. If None it will be obtained from the separation between angles
- stat : str
- The statistic to compute. Can be ‘min’, ‘max’, ‘mean’, ‘mode’. Default ‘max’
- ‘HISTOGRAM’: Computes a histogram of the radar volum data
- User defined parameters:
- step: float or None
- the data quantization step. If none it will be obtained from the Py-ART configuration file
- write_data: Bool
- If true the histogram data is written in a csv file
- ‘PLOT_ALONG_COORD’: Plots the radar volume data along a particular
coordinate User defined parameters:
- colors: list of str or None
- The colors of each ploted line
- mode: str
- Ploting mode. Can be ‘ALONG_RNG’, ‘ALONG_AZI’ or ‘ALONG_ELE’
- value_start, value_stop: float
- The starting and ending points of the data to plot. According to the mode it may refer to the range, azimuth or elevation. If not specified the minimum and maximum possible values are used
- fix_elevations, fix_azimuths, fix_ranges: list of floats
- The elevations, azimuths or ranges to plot for each mode. ‘ALONG_RNG’ would use fix_elevations and fix_azimuths ‘ALONG_AZI’ fix_ranges and fix_elevations ‘ALONG_ELE’ fix_ranges and fix_azimuths
- AngTol: float
- The tolerance to match the radar angle to the fixed angles Default 1.
- RngTol: float
- The tolerance to match the radar range to the fixed ranges Default 50.
- ‘PPI_CONTOUR’: Plots a PPI countour plot
- User defined parameters:
- contour_values: list of floats or None
- The list of contour values to plot. If None the contour values are going to be obtained from the Py-ART config file either with the dictionary key ‘contour_values’ or from the minimum and maximum values of the field with an assumed division of 10 levels.
- anglenr: float
- The elevation angle number
- ‘PPI_CONTOUR_OVERPLOT’: Plots a PPI of a field with another field
overplotted as a contour plot. User defined parameters:
- contour_values: list of floats or None
- The list of contour values to plot. If None the contour values are going to be obtained from the Py-ART config file either with the dictionary key ‘contour_values’ or from the minimum and maximum values of the field with an assumed division of 10 levels.
- anglenr: float
- The elevation angle number
- ‘PPI_IMAGE’: Plots a PPI image. It can also plot the histogram and the
quantiles of the data in the PPI. User defined parameters:
- anglenr: float
- The elevation angle number
- plot_type: str
- The type of plot to perform. Can be ‘PPI’, ‘QUANTILES’ or ‘HISTOGRAM’
- step: float or None
- If the plot type is ‘HISTOGRAM’, the width of the histogram bin. If None it will be obtained from the Py-ART config file
- quantiles: list of float or None
- If the plot type is ‘QUANTILES’, the list of quantiles to compute. If None a default list of quantiles will be computed
- vmin, vmax: float or None
- The minimum and maximum values of the color scale. If None the scale is going to be set according to the Py-ART config file
- ‘PPI_MAP’: Plots a PPI image over a map. The map resolution and the
type of maps used are defined in the variables ‘mapres’ and ‘maps’ in ‘ppiMapImageConfig’ in the loc config file. User defined parameters:
- anglenr: float
- The elevation angle number
- ‘PPIMAP_ROI_OVERPLOT’: Over plots a polygon delimiting a region of
interest on a PPI map. The map resolution and the type of maps used are defined in the variables ‘mapres’ and ‘maps’ in ‘ppiMapImageConfig’ in the loc config file. User defined parameters:
- anglenr: float
- The elevation angle number
- ‘PROFILE_STATS’: Computes and plots a vertical profile statistics.
The statistics are saved in a csv file User defined parameters:
- heightResolution: float
- The height resolution of the profile [m]. Default 100.
- heightMin, heightMax: float or None
- The minimum and maximum altitude of the profile [m MSL]. If None the values will be obtained from the minimum and maximum gate altitude.
- quantity: str
- The type of statistics to plot. Can be ‘quantiles’, ‘mode’, ‘reqgression_mean’ or ‘mean’.
- quantiles: list of floats
- If quantity type is ‘quantiles’ the list of quantiles to compute. Default 25., 50., 75.
- nvalid_min: int
- The minimum number of valid points to consider the statistic valid. Default 4
- make_linear: Bool
- If true the data is converted from log to linear before computing the stats
- include_nans: Bool
- If true NaN values are included in the statistics
- fixed_span: Bool
- If true the profile plot has a fix X-axis
- vmin, vmax: float or None
- If fixed_span is set, the minimum and maximum values of the X-axis. If None, they are obtained from the Py-ART config file
- ‘PSEUDOPPI_CONTOUR’: Plots a pseudo-PPI countour plot
- User defined parameters:
- contour_values: list of floats or None
- The list of contour values to plot. If None the contour values are going to be obtained from the Py-ART config file either with the dictionary key ‘contour_values’ or from the minimum and maximum values of the field with an assumed division of 10 levels.
- angle: float
- The elevation angle at which compute the PPI
- EleTol: float
- The tolerance between the actual radar elevation angle and the nominal pseudo-PPI elevation angle.
- ‘PSEUDOPPI_CONTOUR_OVERPLOT’: Plots a pseudo-PPI of a field with
another field over-plotted as a contour plot User defined parameters:
- contour_values: list of floats or None
- The list of contour values to plot. If None the contour values are going to be obtained from the Py-ART config file either with the dictionary key ‘contour_values’ or from the minimum and maximum values of the field with an assumed division of 10 levels.
- angle: float
- The elevation angle at which compute the PPI
- EleTol: float
- The tolerance between the actual radar elevation angle and the nominal pseudo-PPI elevation angle.
- ‘PSEUDOPPI_IMAGE’: Plots a pseudo-PPI image. It can also plot the
histogram and the quantiles of the data in the pseudo-PPI. User defined parameters:
- angle: float
- The elevation angle of the pseudo-PPI
- EleTol: float
- The tolerance between the actual radar elevation angle and the nominal pseudo-PPI elevation angle.
- plot_type: str
- The type of plot to perform. Can be ‘PPI’, ‘QUANTILES’ or ‘HISTOGRAM’
- step: float or None
- If the plot type is ‘HISTOGRAM’, the width of the histogram bin. If None it will be obtained from the Py-ART config file
- quantiles: list of float or None
- If the plot type is ‘QUANTILES’, the list of quantiles to compute. If None a default list of quantiles will be computed
- vmin, vmax : float or None
- Min and Max values of the color scale. If None the values are taken from the Py-ART config file
- ‘PSEUDOPPI_MAP’: Plots a pseudo-PPI image over a map. The map
resolution and the type of maps used are defined in the variables ‘mapres’ and ‘maps’ in ‘ppiMapImageConfig’ in the loc config file. User defined parameters:
- angle: float
- The elevation angle of the pseudo-PPI
- EleTol: float
- The tolerance between the actual radar elevation angle and the nominal pseudo-PPI elevation angle.
- ‘PSEUDORHI_CONTOUR’: Plots a pseudo-RHI countour plot
- User defined parameters:
- contour_values: list of floats or None
- The list of contour values to plot. If None the contour values are going to be obtained from the Py-ART config file either with the dictionary key ‘contour_values’ or from the minimum and maximum values of the field with an assumed division of 10 levels.
- angle: float
- The azimuth angle at which to compute the RPI
- AziTol: float
- The tolerance between the actual radar azimuth angle and the nominal pseudo-RHI azimuth angle.
- ‘PSEUDORHI_CONTOUR_OVERPLOT’: Plots a pseudo-RHI of a field with
another field over-plotted as a contour plot User defined parameters:
- contour_values: list of floats or None
- The list of contour values to plot. If None the contour values are going to be obtained from the Py-ART config file either with the dictionary key ‘contour_values’ or from the minimum and maximum values of the field with an assumed division of 10 levels.
- angle: float
- The azimuth angle at which to compute the RPI
- AziTol: float
- The tolerance between the actual radar azimuth angle and the nominal pseudo-RHI azimuth angle.
- ‘PSEUDORHI_IMAGE’: Plots a pseudo-RHI image. It can also plot the
histogram and the quantiles of the data in the pseudo-RHI. User defined parameters:
- angle: float
- The azimuth angle at which to compute the RPI
- AziTol: float
- The tolerance between the actual radar azimuth angle and the nominal pseudo-RHI azimuth angle.
- plot_type: str
- The type of plot to perform. Can be ‘RHI’, ‘QUANTILES’ or ‘HISTOGRAM’
- step: float or None
- If the plot type is ‘HISTOGRAM’, the width of the histogram bin. If None it will be obtained from the Py-ART config file
- quantiles: list of float or None
- If the plot type is ‘QUANTILES’, the list of quantiles to compute. If None a default list of quantiles will be computed
- vmin, vmax : float or None
- Min and Max values of the color scale. If None the values are taken from the Py-ART config file
- ‘QUANTILES’: Plots and writes the quantiles of a radar volume
- User defined parameters:
- quantiles: list of floats or None
- the list of quantiles to compute. If None a default list of quantiles will be computed.
- write_data: Bool
- If True the computed data will be also written in a csv file
- fixed_span: Bool
- If true the quantile plot has a fix Y-axis
- vmin, vmax: float or None
- If fixed_span is set, the minimum and maximum values of the Y-axis. If None, they are obtained from the Py-ART config file
- ‘RHI_CONTOUR’: Plots an RHI countour plot
- User defined parameters:
- contour_values: list of floats or None
- The list of contour values to plot. If None the contour values are going to be obtained from the Py-ART config file either with the dictionary key ‘contour_values’ or from the minimum and maximum values of the field with an assumed division of 10 levels.
- anglenr: int
- The azimuth angle number
- ‘RHI_CONTOUR_OVERPLOT’: Plots an RHI of a field with another field
over-plotted as a contour plot User defined parameters:
- contour_values: list of floats or None
- The list of contour values to plot. If None the contour values are going to be obtained from the Py-ART config file either with the dictionary key ‘contour_values’ or from the minimum and maximum values of the field with an assumed division of 10 levels.
- anglenr: int
- The azimuth angle number
- ‘RHI_IMAGE’: Plots an RHI image. It can also plot the
histogram and the quantiles of the data in the RHI. User defined parameters:
- anglenr: int
- The azimuth angle number
- plot_type: str
- The type of plot to perform. Can be ‘RHI’, ‘QUANTILES’ or ‘HISTOGRAM’
- step: float or None
- If the plot type is ‘HISTOGRAM’, the width of the histogram bin. If None it will be obtained from the Py-ART config file
- quantiles: list of float or None
- If the plot type is ‘QUANTILES’, the list of quantiles to compute. If None a default list of quantiles will be computed
- vmin, vmax: float or None
- The minimum and maximum values of the color scale. If None the scale is going to be set according to the Py-ART config file
- ‘RHI_PROFILE’: Computes and plots a vertical profile statistics out of
an RHI. The statistics are saved in a csv file User defined parameters:
- rangeStart, rangeStop: float
- The range start and stop of the data to extract from the RHI to compute the statistics [m]. Default 0., 25000.
- heightResolution: float
- The height resolution of the profile [m]. Default 100.
- heightMin, heightMax: float or None
- The minimum and maximum altitude of the profile [m MSL]. If None the values will be obtained from the minimum and maximum gate altitude.
- quantity: str
- The type of statistics to plot. Can be ‘quantiles’, ‘mode’, ‘reqgression_mean’ or ‘mean’.
- quantiles: list of floats
- If quantity type is ‘quantiles’ the list of quantiles to compute. Default 25., 50., 75.
- nvalid_min: int
- The minimum number of valid points to consider the statistic valid. Default 4
- make_linear: Bool
- If true the data is converted from log to linear before computing the stats
- include_nans: Bool
- If true NaN values are included in the statistics
- fixed_span: Bool
- If true the profile plot has a fix X-axis
- vmin, vmax: float or None
- If fixed_span is set, the minimum and maximum values of the X-axis. If None, they are obtained from the Py-ART config file
- ‘SAVEALL’: Saves radar volume data including all or a list of user-
defined fields in a C/F radial or ODIM file User defined parameters:
- file_type: str
- The type of file used to save the data. Can be ‘nc’ or ‘h5’. Default ‘nc’
- datatypes: list of str or None
- The list of data types to save. If it is None, all fields in the radar object will be saved
- physical: Bool
- If True the data will be saved in physical units (floats). Otherwise it will be quantized and saved as binary
- compression: str
- For ODIM file formats, the type of compression. Can be any of the allowed compression types for hdf5 files. Default gzip
- compression_opts: any
- The compression options allowed by the hdf5. Depends on the type of compression. Default 6 (The gzip compression level).
- ‘SAVESTATE’: Saves the last processed data in a file. Used for real-
- time data processing
- ‘SAVEVOL’: Saves one field of a radar volume data in a C/F radial or
ODIM file User defined parameters:
- file_type: str
- The type of file used to save the data. Can be ‘nc’ or ‘h5’. Default ‘nc’
- physical: Bool
- If True the data will be saved in physical units (floats). Otherwise it will be quantized and saved as binary
- compression: str
- For ODIM file formats, the type of compression. Can be any of the allowed compression types for hdf5 files. Default gzip
- compression_opts: any
- The compression options allowed by the hdf5. Depends on the type of compression. Default 6 (The gzip compression level).
- ‘SAVE_FIXED_ANGLE’: Saves the position of the first fix angle in a
- csv file
- ‘SELFCONSISTENCY’: Plots a ZDR versus KDP/ZH histogram of data.
- User defined parameters:
- retrieve_relation : bool
- If True plots also the retrieved relationship. Default True
- plot_theoretical : bool
- If True plots also the theoretical relationship. Default True
- normalize : bool
- If True the occurrence density of ZK/KDP for each ZDR bin is going to be represented. Otherwise it will show the number of gates at each bin. Default True
- ‘SELFCONSISTENCY2’: Plots a ZH measured versus ZH inferred from a self-consistency
relation histogram of data. User defined parameters:
- normalize : bool
- If True the occurrence density of ZK/KDP for each ZDR bin is going to be represented. Otherwise it will show the number of gates at each bin. Default True
- ‘TIME_RANGE’: Plots a time-range/azimuth/elevation plot
- User defined parameters:
- anglenr: float
- The number of the fixed angle to plot
- vmin, vmax: float or None
- The minimum and maximum values of the color scale. If None the scale is going to be set according to the Py-ART config file
- ‘VOL_TS’: Writes and plots a value corresponding to a time series.
Meant primarily for writing and plotting the results of the SELFCONSISTENCY2 algorithm User defined parameters:
- ref_value: float
- The reference value. Default 0
- sort_by_date: Bool
- If true when reading the csv file containing the statistics the data is sorted by date. Default False
- rewrite: Bool
- If true the csv file containing the statistics is rewritten
- add_data_in_fname: Bool
- If true and the data used is cumulative the year is written in the csv file name and the plot file name
- npoints_min: int
- Minimum number of points to use the data point in the plotting and to send an alarm. Default 0
- vmin, vmax: float or None
- Limits of the Y-axis (data value). If None the limits are obtained from the Py-ART config file
- alarm: Bool
- If true an alarm is sent
- tol_abs: float
- Margin of tolerance from the reference value. If the current value is above this margin an alarm is sent. If the margin is not specified it is not possible to send any alarm
- tol_trend: float
- Margin of tolerance from the reference value. If the trend of the last X events is above this margin an alarm is sent. If the margin is not specified it is not possible to send any alarm
- nevents_min: int
- Minimum number of events with sufficient points to send an alarm related to the trend. If not specified it is not possible to send any alarm
- sender: str
- The mail of the alarm sender. If not specified it is not possible to send any alarm
- receiver_list: list of str
- The list of emails of the people that will receive the alarm.. If not specified it is not possible to send any alarm
- ‘WIND_PROFILE’: Plots vertical profile of wind data (U, V, W
components and wind velocity and direction) out of a radar volume containing the retrieved U,V and W components of the wind, the standard deviation of the retrieval and the velocity difference between the estimated radial velocity (assuming the wind to be uniform) and the actual measured radial velocity. User defined parameters:
- heightResolution: float
- The height resolution of the profile [m]. Default 100.
- heightMin, heightMax: float or None
- The minimum and maximum altitude of the profile [m MSL]. If None the values will be obtained from the minimum and maximum gate altitude.
- min_ele: float
- The minimum elevation to be used in the computation of the vertical velocities. Default 5.
- max_ele: float
- The maximum elevation to be used in the computation of the horizontal velocities. Default 85.
- fixed_span: Bool
- If true the profile plot has a fix X-axis
- vmin, vmax: float or None
- If fixed_span is set, the minimum and maximum values of the X-axis. If None, they are obtained from the span of the U component defined in the Py-ART config file
Parameters: - dataset : dict
dictionary with key radar_out containing a radar object
- prdcfg : dictionary of dictionaries
product configuration dictionary of dictionaries
Returns: - The list of created fields or None
-
pyrad.prod.
get_prodgen_func
(dsformat, dsname, dstype)[source]¶ maps the dataset format into its processing function
Parameters: - dsformat : str
dataset group. The following is a list of dataset groups with the function that is called to generate their products. For details about what the functions do check the function documentation:
‘VOL’: generate_vol_products ‘COLOCATED_GATES’: generate_colocated_gates_products ‘COSMO_COORD’: generate_cosmo_coord_products ‘COSMO2RADAR’: generate_cosmo_to_radar_products ‘GRID’: generate_grid_products ‘SPECTRA’: generate_spectra_products ‘GRID_TIMEAVG’: generate_grid_time_avg_products ‘INTERCOMP’: generate_intercomp_products ‘ML’: generate_ml_products ‘MONITORING’: generate_monitoring_products ‘OCCURRENCE’: generate_occurrence_products ‘QVP’: generate_qvp_products ‘SPARSE_GRID’: generate_sparse_grid_products ‘SUN_HITS’: generate_sun_hits_products ‘TIMEAVG’: generate_time_avg_products ‘TIMESERIES’: generate_timeseries_products ‘TRAJ_ONLY’: generate_traj_product
Returns: - func : function
pyrad function used to generate the products


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The roof of the hall was already burning brightly, the roaring flames painting faces bloody.From Poul Anderson's The Broken Sword.
--- layout: post title: "Page 56" date: 2008-11-27 comments: false ---
The roof of the hall was already burning brightly, the roaring flames painting faces bloody.From Poul Anderson's The Broken Sword.
I like to think of it as a Dadaist exercise, where arbitrary rules and randomness dig up things of true beauty from the Internet's subconscious.
Or, you know, maybe the monkey in us likes imitating all the other monkeys.
From 'The Paris Review Interviews Vol 1'
(Benny, this book is yours; I've been meaning to return it to you for ages!)
What's the point of the page 56 thing?
When OnChip IDE Channel10 is set to [Enabled], you can disable the primary Master and Slave UDMA or set it to [Auto].
From - XFX nForce 780i SLI 3-WAY SLI Motherboard manual.


Knock 'Em Dead: At Harvard, Crafting Comedy Is No Laughing Matter
Stand-up comics often appear to be completely at ease, dishing out joke after joke in quick succession. While impressive, this seemingly effortless delivery belies the huge amount of work that goes into crafting a stand-up routine. Writing comedy takes not only talent, but also a willingness to devote oneself to the honing of skills that take years of experience to master.


flutter_audio_capture
Capture the audio stream buffer through microphone for iOS/Android. Required OS version is iOS 13+ or Android 23+
Getting Started
Add this line to your pubspec.yaml file:
dependencies:
flutter_audio_capture: ^1.1.4
and execute
$ flutter pub get
Android
If you want to use this package on Android OS, you need to set RECORD_AUDIO
permission to AndroindManifest.xml
like below.
<manifest xmlns:android="http://schemas.android.com/apk/res/android"
package="com.ymd.flutter_audio_capture">
...
// Add this line
<uses-permission android:name="android.permission.RECORD_AUDIO"/>
</manifest>
iOS
If you want to use this package on iOS, you need to set NSMicrophoneUsageDescription
to Info.plist
like below.
<dict>
<key>NSMicrophoneUsageDescription</key>
<string>Need microphone access to capture audio</string>
...
Linux
On Linux, this package uses parec
to record audio.
While things should just work on recent Ubuntu versions,
make sure to have pulseaudio
installed on the target device.
Example
You can see full example in example/lib/main.dart
import 'package:flutter_audio_capture/flutter_audio_capture.dart';
...
// Callback function if device capture new audio stream.
// argument is audio stream buffer captured through mictophone.
// Currentry, you can only get is as Float64List.
void listener(dynamic obj) {
var buffer = Float64List.fromList(obj.cast<double>());
print(buffer);
}
// Callback function if flutter_audio_capture failure to register
// audio capture stream subscription.
void onError(Object e) {
print(e);
}
...
FlutterAudioCapture plugin = new FlutterAudioCapture();
// Start to capture audio stream buffer
// sampleRate: sample rate you want
// bufferSize: buffer size you want (iOS only)
await plugin.start(listener, onError, sampleRate: 16000, bufferSize: 3000);
// Stop to capture audio stream buffer
await plugin.stop();


Mix Of The Day: Moodymann Plays Motown
Kenny Dixon Jr. celebrates 60 years of the Detroit label with an all-Motown set.
by Resident AdvisorMoodymann has put together an all-Motown set for Carhartt WIP Radio.
Read Matt McDermott's interview with Moodymann about roller skating.


{% extends "main.html" %} {% block content %}
This application has a list of missiles owned by different countries. If you know any more, please add.


Views are used render the user interface, views can be parallel as well as nested in each other and an application can define as many views as needed.
A single property, template
that automatically detects if it's a url,
function or a simple html string.
Alternatively a template object can be provided that defines either url
,
fn
or html
to explicitly define sort of template it is.
Defined on each view if needed, controllers will be bound to the view element.
Just like with the ngRoute
module, controllers are used to provide the data to the view.
Views can be managed through the $view
service, the same service as the state
engine uses.
Views can be created, refreshed, updated and removed.
A transactional concept is supported for grouping multiple changes into a single commit.
demo.js
This example shows how multiple views can be used and a number of different options to populate them through states.
We have two views at root level and three that is embeded in each their parent view template.
We have chosen to name embeded views with a prefix of their parent main.aboutContent
, this
is just a convention chosen here to indicate their relation ship, but they are completely unaware of each other.
template
The sample demonstrates three ways of declaring templates:
Templates can also be defined by passing an object with either a url
, fn
or html
property, this is useful when 'templates/home.html' was actually meant to be treated
as a html string rather than a URL.
controller
sticky


Hello! I'm Pavan Boro. This page consists of my personal interests. Read more on this page to know more about me.
C, Java, JavaScript


Vegas airport marks busiest month ever by passenger count
LAS VEGAS (AP) - October turned out to be the busiest month ever by passenger count at the main airport in Las Vegas.
The Clark County Department of Aviation reported Monday that McCarran International Airport handled more than 4.6 million arriving and departing travelers last month, up 4.2% compared with the same month a year ago.
Passenger traffic is a measurement of tourism in Las Vegas, where the airport has handled more than 43 million passengers in 2019 and could soar past 50 million for the first time.
McCarran is one of the 10 busiest airports in the U.S. based on number of passengers served.
Southwest Airlines remains the busiest commercial carrier at McCarran, followed by Spirit, Delta, American and United.
The Department of Aviation also operates Henderson and North Las Vegas airports.
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Copyright © 2019 The Washington Times, LLC.
Please read our comment policy before commenting.


钩子¶
钩子是可插入的中间件函数,可以在 before, after 或者在a 服务 的 __error__s 之前注册. 您可以注册单个钩子函数或创建它们的链,以创建复杂的工作流程. 大多数情况下,多个挂钩都被注册,因此示例显示了“挂钩链”数组样式注册.
钩子是 独立传输,这意味着它是否通过HTTP(S)(REST),Socket.io,Primus或任何其他传输Feathers可能在将来支持无关紧要.它们也是服务不可知的,这意味着它们可以与任何服务一起使用,无论它们是否具有模型.
钩子通常用于处理诸如验证,记录,填充相关实体,发送通知等内容.此模式使您的应用程序逻辑保持灵活,可组合,并且更容易跟踪和调试.有关钩子背后的设计模式的更多信息,请参阅 此博客文章.
快速示例¶
下面的示例在将数据保存到数据库之前添加了 createdAt
和 updatedAt
属性,并记录了服务上的任何错误:
const feathers = require('@feathersjs/feathers');
const app = feathers();
app.service('messages').hooks({
before: {
create(context) {
context.data.createdAt = new Date();
},
update(context) {
context.data.updatedAt = new Date();
},
patch(context) {
context.data.updatedAt = new Date();
}
},
error(context) {
console.error(`Error in ${context.path} calling ${context.method} method`, context.error);
}
});
钩子功能¶
钩子函数可以是普通的或 async
函数或箭头函数,它以 hook context 作为参数,可以
return a
context
objectreturn nothing (
undefined
)返回
feathers.SKIP
以跳过所有进一步的钩子throw
错误对于异步操作,返回一个 Promise
用
context
对象解析用
undefined
解决拒绝错误
有关更多信息,请参阅 hook flow 和 asynchronous hooks section.
// normal hook function
function(context) {
return context;
}
// asynchronous hook function with promise
function(context) {
return Promise.resolve(context);
}
// async hook function
async function(context) {
return context;
}
// normal arrow function
context => {
return context;
}
// asynchronous arrow function with promise
context => {
return Promise.resolve(context);
}
// async arrow function
async context => {
return context;
}
// skip further hooks
const feathers = require('@feathersjs/feathers');
async context => {
return feathers.SKIP;
}
钩子上下文¶
钩子 context
被传递给一个钩子函数,并包含有关服务方法调用的信息.它具有 只读 属性,不应被修改, 可写 属性,可以为后续挂钩更改.
小技巧
在整个服务方法调用中,``context`` 对象是相同的,因此可以添加属性并在以后的其他钩子中使用它们.
context.service¶
context.service
是一个 read only 属性,包含当前运行此钩子的服务.
context.path¶
context.path
是一个 read only 属性,包含没有前导或尾部斜杠的服务名称(或路径).
context.type¶
context.type
是一个 read only 属性,带有钩子类型(before
, after
或 error
之一).
context.params¶
context.params
is a writeable property that contains the
服务 parameters (including params.query
).
For more information see the params.
context.id¶
context.id
is a writeable property and the id
for a get
,
remove
, update
and patch
service method call. For
remove
, update
and patch
context.id
can also be null
when modifying multiple entries. In all other cases it will be
undefined
.
注解
context.id
is only available for method types get
,
remove
, update
and patch
.
context.data¶
context.data
is a writeable property containing the data of a
create
, update
and patch
service method call.
注解
context.data``只适用于方法类型``create
,``update``和``patch``.
context.error¶
context.error
is a writeable property with the error object that
was thrown in a failed method call. It is only available in error
hooks.
注解
context.error
will only be available if
context.type
is error
.
context.result¶
context.result
is a writeable property containing the result of
the successful service method call. It is only available in after
hooks. context.result
can also be set in
A
before
hook to skip the actual service method (database) callAn
error
hook to swallow the error and return a result instead
注解
context.result
will only be available if
context.type
is after
or if context.result
has been set.
context.dispatch¶
context.dispatch
is a writeable, optional property and contains
a “safe” version of the data that should be sent to any client. If
context.dispatch
has not been set context.result
will be sent to
the client instead.
context.statusCode¶
context.statusCode
is a writeable, optional property that allows
to override the standard HTTP status
code that
should be returned.
钩子流¶
In general, hooks are executed in the order they are registered with the
original service method being called after all before
hooks. This
flow can be affected as follows.
抛出一个错误¶
When an error is thrown (or the promise is rejected), all subsequent hooks - and the service method call if it didn’t run already - will be skipped and only the error hooks will run.
The following example throws an error when the text for creating a new message is empty. You can also create very similar hooks to use your Node validation library of choice.
app.service('messages').hooks({
before: {
create: [
function(context) {
if(context.data.text.trim() === '') {
throw new Error('Message text can not be empty');
}
}
]
}
});
Setting context.result
¶
When context.result
is set in a before
hook, the original
服务 call will be skipped. All other hooks
will still execute in their normal order. The following example always
returns the currently authenticated
user instead of the actual user for all
get
method calls:
app.service('users').hooks({
before: {
get: [
function(context) {
// Never call the actual users service
// just use the authenticated user
context.result = context.params.user;
}
]
}
});
Returning feathers.SKIP
¶
require('@feathersjs/feathers').SKIP
can be returned from a hook to
indicate that all following hooks should be skipped. If returned by a
before hook, the remaining before hooks are skipped; any
after hooks will still be run. If it hasn’t run yet, the service
method will still be called unless context.result
is set already.
异步钩子¶
When the hook function is async
or a Promise is returned it will
wait until all asynchronous operations resolve or reject before
continuing to the next hook.
重要
As stated in the hook functions
section the promise has to either resolve with the context
object
(usually done with .then(() => context)
at the end of the promise
chain) or with undefined
.
async/await¶
When using Node v8.0.0 or later the use of
async/await
is highly recommended. This will avoid many common issues when using
Promises and asynchronous hook flows. Any hook function can be async
in which case it will wait until all await
operations are completed.
Just like a normal hook it should return the context
object or
undefined
.
The following example shows an async/await hook that uses another
service to retrieve and populate the messages user
when getting a
single message:
app.service('messages').hooks({
after: {
get: [
async function(context) {
const userId = context.result.userId;
// Since context.app.service('users').get returns a promise we can `await` it
const user = await context.app.service('users').get(userId);
// Update the result (the message)
context.result.user = user;
// Returning will resolve the promise with the `context` object
return context;
}
]
}
});
回报承诺¶
The following example shows an asynchronous hook that uses another
service to retrieve and populate the messages user
when getting a
single message.
app.service('messages').hooks({
after: {
get: [
function(context) {
const userId = context.result.userId;
// context.app.service('users').get returns a Promise already
return context.app.service('users').get(userId).then(user => {
// Update the result (the message)
context.result.user = user;
// Returning will resolve the promise with the `context` object
return context;
});
}
]
}
});
注解
A common issue when hooks are not running in the expected
order is a missing return
statement of a promise at the top level
of the hook function.
重要
Most Feathers service calls and newer Node packages
already return Promises. They can be returned and chained directly.
There is no need to instantiate your own new
Promise instance in
those cases.
转换回调¶
When the asynchronous operation is using a callback instead of
returning a promise you have to create and return a new Promise
(new Promise((resolve, reject) => {})
) or use
util.promisify.
The following example reads a JSON file converting
fs.readFile
with util.promisify
:
const fs = require('fs');
const util = require('util');
const readFile = util.promisify(fs.readFile);
app.service('messages').hooks({
after: {
get: [
function(context) {
return readFile('./myfile.json').then(data => {
context.result.myFile = data.toString();
return context;
});
}
]
}
});
小技巧
Other tools like Bluebird also help converting between callbacks and promises.
注册钩子¶
Hook函数通过``app.service(<servicename>).hooks(hooks)``方法在服务上注册.什么可以作为``hooks``传递:
// The standard all at once way (also used by the generator)
// an array of functions per service method name (and for `all` methods)
app.service('servicename').hooks({
before: {
all: [
// Use normal functions
function(context) { console.log('before all hook ran'); }
],
find: [
// Use ES6 arrow functions
context => console.log('before find hook 1 ran'),
context => console.log('before find hook 2 ran')
],
get: [ /* other hook functions here */ ],
create: [],
update: [],
patch: [],
remove: []
},
after: {
all: [],
find: [],
get: [],
create: [],
update: [],
patch: [],
remove: []
},
error: {
all: [],
find: [],
get: [],
create: [],
update: [],
patch: [],
remove: []
}
});
// Register a single hook before, after and on error for all methods
app.service('servicename').hooks({
before(context) {
console.log('before all hook ran');
},
after(context) {
console.log('after all hook ran');
},
error(context) {
console.log('error all hook ran');
}
});
小技巧
当使用完整对象时, all
是一个特殊的关键字, 这意味着这个钩子将为所有方法运行. all
钩子将在其他特定于方法的钩子之前注册.
小技巧
app.service(<servicename>).hooks(hooks)
can be
called multiple times and the hooks will be registered in that order.
Normally all hooks should be registered at once however to see at a
glance what the service is going to do.
应用程序挂钩¶
To add hooks to every service app.hooks(hooks)
can be used.
Application hooks are registered in the same format as service
hooks and also work exactly the same.
注解
when application hooks will be executed however:
before
应用程序挂钩总是在*所有服务before
挂钩之前运行*after
应用程序挂钩总是在 all service ``after`` 挂钩后运行error
应用程序挂钩总是在 all service ``error`` 挂钩后运行
下面是一个非常有用的应用程序挂钩的示例, 它使用服务和方法名称以及错误堆栈记录每个服务方法错误.
app.hooks({
error(context) {
console.error(`Error in '${context.path}' service method '${context.method}'`, context.error.stack);
}
});


Corinto, on Nicaragua's Pacific coast, is the country's largest port and offers an authentic experience of the country. Latitude: 12° 28.56 N Longitude: 87° 10.49 W. Corinto is approximately 14 miles south of Aserradores.
Few boats are stopping into Corinto now that Marina Puesta Del Sol is open for business. The same Port Captain and Immigration Officers process papers at Corinto and at Puesta Del Sol. Therefore if coming from Puesta del Sol checking into Corinto is not needed.
If Corinto is your first port of entry, the port captain’s office will send for officials to give you clearance. It is recommended that you take the initiative to check in with the port captain’s office located near the shipyard’s front gate. Immigration office is in the same building. Clearance is normally quick, effective and reasonable. The total cost of clearing in is around US$25.
Port control keep a 24 hour watch on VHF Channel 16 and should be contacted for instructions concerning clearance. Use the "official" anchorage a few hundred meters east of the shipyard, near the shrimp boats. Stay clear of the power plant as they have underwater exhaust and intake pipes.
It is recommended that you radio the Port Captain as you approach for information regarding shipping traffic. The harbor entrance is wide and well marked with navigational buoys. You must approach via the main channel as any short cuts are shallow. The main channel is 40 feet deep all the way to the last buoy, then 12 to 20 feet deep all the way to the bridge, at low tide. The harbor is protected by a large peninsula that has a lighthouse at the entrance.
Anchorages
The inner harbour is well protected. There is a good anchorage off the beach, opposite the distinctive silver fuel tank, in about 10 metres. The holding is good in mud and sand, although this anchorage is sometimes subject to swell at low water.
An alternative, smoother anchorage, is well into the inner harbour at the industrial zone of Estero Grande, near a fleet of ageing fishing boats. Unfortunately, the nearby generating plant rather disturbs the peace and boats her are rather vunerable to theft nor is there any safe place to leave a dinghy while ashore.
Corinto marina, up the river next to the Pasocaballo bridge that connects Corinto to the mainland, used to offer a secure anchorage, dinghy dock and clearance assistance to visiting cruisers. However the marina does not offer these services anymore. It is still possible to anchor here, however you cannot get ashore other than at the town "beach" end.
Ten miles north of Corinto (via sea - about 40 km by land) is Marina Puesta Del Sol, inside the protected estuary and lagoon of Aserradores.
Last updated March 2012.


_______ __ __ _____ | __| |_.--.--| |-----.| \-----.----.----.-----. |__ | _| | | | -__|| -- | _ | __| __| _ | |_______|____|___ |__|_____||_____/_____|____|____|_____| |_____|
StyleDocco generates documentation and style guide documents from your stylesheets.
Stylesheet comments will be parsed through Markdown and displayed in a generated HTML document. You can write code examples inside GitHub Markdown code fences (```
) or prefixed with 4 spacesin your comments, and StyleDocco both renders the HTML and shows the code example.
The document automatically starts a new section when it encounters a level 1 or 2 heading. Read more about the syntax in the Markdown guide. Only comments at the beginning of new lines are included, so to exclude something from the style guide, put some whitespace before the comment.
If your project includes a README
file, it will be used as the base for an index.html
. StyleDocco will also add some default styles to your documentation, but they are easy to modify to make it fit with your project.
StyleDocco will automatically compile any SASS, SCSS, Less or Stylus code before it is applied to the page.
StyleDocco requires Node.js.
npm install -g styledocco
or check out this repository.
StyleDocco is free software, released under the MIT license.
styledocco [options] [INPUT]
--name
, -n
Name of the project (required)--out
, -o
Output directory (default: "docs")--tmpl
Directory for custom index.jade
and docs.jade
templates (optional)--overwrite
Overwrite existing files (docs.css
) in target directory.
<button class="btn primary">Primary</button>
/
.btn.primary {
background: blue;
color: white;
}/* Provides extra visual weight and identifies the primary action in a set of buttons
```
<button class="btn primary">Primary</button>
``` */
.btn.primary {
background: blue;
color: white;
}
Would display the description, a button as well as the example HTML code. The CSS will be included in the style
element of the document.
See the examples
folder for more in-depth examples.
A lot of the heavy lifting in StyleDocco is done by the excellent Marked module by Christopher Jeffrey. The original Docco by Jeremy Ashkenas and Docco Husky by Mike Brevoort were also of great help to this project.


We are ‘determined’ to return to winning ways, says striker Afif
Qatar aim to put behind them their disappointing opening match loss against Iraq and come back strongly against Yemen, said striker Akram Afif (pictured).
Afif said his team-mates are fully aware of the task which lies ahead of them and the responsibilities which come along with it.
“The outcome of the Iraq match was disappointing and this is something we must forget. We are determined to return back to winning ways. We know the difficult task which lies ahead for us and also we are aware of the size of the responsibility.”
Afif said they were targeting full points and it does not matter how the goals came.
“We will play according to the plan and it does not matter how we score. We are thinking of winning and achieving the three points.”
Afif shot down the suggestion that his team-mates were tense during the opening match against Iraq.
“No, that is not true. We did not appear tense. We played the game calmly and what happened was that we did not take advantage of the opportunities,” he added.
Read also
Read More
Iraq to host next Gulf Cup
Read More
UAE target full points against Iraq
Both the teams began their campaign on a winning note in the eight-nation regional championship, with UAE trouncing Yemen 3-0 while Iraq squeezed past hosts Qatar 2-1.


Scan the following QR code using the Google Authenticator (or other TOTP compatible) app.
Alternatively, you can manually enter the following secret:
{{ secret }}
Once you have set up the new account on your app, enter a code to ensure everything is working OK:
{{ enable_error }}


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Everton finalising new deal for Richarlison
The 22-year-old joined the Toffees from Watford.
Everton are putting the finishing touches on a new contract extension for Brazil international Richarlison, director of football Marcel Brands has revealed.
The 22-year-old joined the Toffees from Watford during July 2018 in a deal understood to be worth around £40million.
Richarlison has scored five goals for Everton this season, as the Goodison Park club fight to climb the Premier League table, with the position of manager Marco Silva under scrutiny.
Brands said on Everton TV: “We have to look positive ahead, and I try to do that always.
“One of the positive things during a week like this which happened is we are now busy with the last details of extending the contract with one of our key players Richarlison until 2024.
“That is something positive, especially for the long-term of course.”
A 2-0 home defeat by struggling Norwich put further pressure on Silva, with some fans calling for him to be dismissed.
“As a board, we have got to support that. Of course, we know in sport, as always, you have to perform – that’s me, the manager, the players, for everyone,” he said.
“It’s also important, especially in this club, after a couple of years of instability, to stick together in this situation.
“I think it is important that everyone has the feeling that we can turn this around to better results.
“Of course, everyone was disappointed last Saturday, but you saw also really in the eyes of the players the fire that they want to resolve this, to turn this around – together with the whole staff.
“That’s important coming up towards the next couple of games. They will be tough games, but games where we can improve.”


§412:10-803 Organization. The application, approval and formation process for the corporate credit union shall be the same as for any other credit union, except that ten or more credit unions shall be required to file an application for a charter. [L 1993, c 350, pt of §1]


GoGreen is Pleased to Announce its Nomination for a UNEF Sustainable Business Award
New York-Nairobi. GoGreen is among 10 global businesses recognized by the United Nations Environmental Fund with a nomination for the prestigious Sustainable Business Award. According to the Sustainable Business Awards announcement, GoGreen has been nominated for its “outstanding contributions to fighting climate change with its global corporate social responsibility strategy.”
“We’re thrilled to be nominated for Sustainable Business Award” notes GoGreen’s CEO Robert Greene, “we thoroughly respect the work of the UNEF and are proud to be listed among such visionary companies.” Winners of the Sustainable Business Award will be announced at a ceremony in Nairobi this December.


Date: Tue Jun 10 2014 02:00:00 GMT+0200 (CEST)
It's still june, and this is another post.
Date: Sun Jun 01 2014 02:00:00 GMT+0200 (CEST)
This is the first post. I just want to say hello world!


How will you be purchasing?
Online Purchases can be mailed or you can print the tickets yourself
A delivery fee of $5.95 will be added for mailing tickets


Using cryptography to keep exchanges secure, blockchain provides a decentralized database, or “digital ledger”, of transactions that everyone on the network can see. This network is essentially a chain of computers that must all approve an exchange before it can be verified and recorded.
Link to BlockchainImmersive learning is the process of learning with the usage of a simulated or artificial environment. The environment enables the learners to completely get immersed in the learning and in a way that feels like experiencing an actual learning environment.
Link to Immersive Experiencean emerging term for the technological developments that are expected to bring computers into the physical environment as autonomous entities without human direction, freely moving and interacting with humans and other objects.
Link to Autonomous Things


| project | technical | examples | links | # | |
|
project - summary - tutorial (2) (3) (4) (5) (6) (7) (8) (9) - usage (2) technical - reasoning - two passes - still tiny - sitemaps - variables - accessibility WAI SubSects examples - horizontal - vertical - tabbed (2) - multi section - printer style links - some hints - faq&issues - all features # - about me - our sitemap - download
(C) 2004 |


Nets’ Irving to miss 3rd straight game with shoulder injury
by Associated PressBrooklyn guard Kyrie Irving will miss a third straight game with a right shoulder injury.
The Nets said Tuesday that the All-Star guard wouldn’t play Wednesday when they host Charlotte.
Brooklyn beat Chicago on Saturday in its first game without Irving, but lost Monday to Indiana in its return home after a five-game road trip.
The Nets are also without their other starting guard, as Caris LeVert had surgery on his right thumb.


| GEOS SDK TechDocs
|
| 2.2 Strategy and Internals
| 3 Geode Parameters File
You might have noticed some of the names of variables, messages, and routines and seen a pattern of naming. Geoworks has developed a few naming conventions for various different items in the system. You don't have to follow these conventions, of course; it may help, however, if you keep to our conventions until you're familiar with most of the system. Some of the items that have special naming conventions are
-
Variables
-
Typically, variables begin with a lower case letter and have each subword in the name capitalized. The variable
helloTextColor
is a good example. Variables with just one word in the name are all lower case.
-
Classes
-
Class names should always have the suffix
Class
. Typically, the first portion of a class' name will describe the particular application, library, or module it is associated with. The second portion of the name should reflect the class' superclass. Each portion of the class name should be capitalized. Thus,
HelloProcessClass
conforms because it begins with the application's name (Hello), then has the superclass' name (Process), and finally has the suffix Class.
-
Constants
-
Constants are typically all upper case with underscores to delineate the portions of the name. C_BLUE is a good example; it is a set value that does not change. The structure of the name should reflect the use of the constant. (In this case, the enumerated type
Color
is reflected in the C_ portion of the constant's name.)
-
Routines
-
Kernel and UI routines, as well as method names, should have each portion capitalized. They should begin with some abbreviation relating to the module they belong to. For example,
GrCreateState()
is a graphics system routine, as is
GrInvalRect()
.
-
Messages
-
Message names should be all uppercase and begin with MSG_. Each portion of the name should be separated with underscores, and the first portion after
MSG_
should reflect the class in which the message is defined. For example,
MSG_HELLO_CHANGE_TO_BLUE
follows all these conventions.
-
Objects
-
Object names are typically capitalized in the same manner as routines and classes. The object's name should reflect both the object's module and its class (or its function if not its class). HelloView is a good example.
-
Instance Data
-
Instance data fields typically have as their first portion an all-caps acronym for the class name with an I tacked on for "instance." The second portion is like a variable name, and the two portions are separated by an underscore. For example,
GI_visMoniker
is a field of
GenClass
(hence the
GI_
), and
visMoniker
is the variable name of the field.
| GEOS SDK TechDocs
|
| 2.2 Strategy and Internals
| 3 Geode Parameters File


Everything that's new
$250.00$199.00
$340.00$299.00
$100.00$99.00
$350.00$225.00
$100.00$99.00
$100.00$99.00
$55.00$35.00
$250.00$150.00
Everything that's new
$100.00$99.00
$100.00$99.00
$55.00$35.00
$250.00$150.00
Everything that's new
$250.00$150.00
$250.00$150.00
$250.00$150.00
$250.00$150.00


Pig fatback filet mignon chuck pastrami. T-bone beef tenderloin, boudin bresaola meatball jowl beef ribs ribeye corned beef filet mignon salami. Cow filet mignon venison sausage. Pork chop frankfurter rump tongue bacon salami short loin sausage.  Tail kielbasa ground round, frankfurter pastrami pork chop salami strip steak meatball jerky ham hock shankle.


Greetings! My name is Cody Fritz, welcome to my Portfolio! I am a junior developer in training. Here you will find a list of my projects, my interests, and skills!
I have a delightful variety of interests, in no particular order:
I have many skills and I intend to continue learning new skills as I improve my existing ones!
I am interested and would like to or intend to learn the following:
My cat chester is clearly the best boy, he knows it and demands the attention that title
deserves. Whether he demands it by serenading you with hours of music at 6am or by laying on your face while
you sleep, depends on the day.
This was a project I started to document the rather grand DND-Esque adventure/rpg
my roommate and I had been enjoying for several months when I began to learn HTML, I did this project during my
first week with Epicodus.
Born in Florida, my family moved around alot while I was growing up, I moved from Crystal
River, FL to Orlando, FL when I was 6, then we moved to Hemingway, SC when I was 9. We stayed in SC until I was
16, where we moved to Boise, ID.
I graduated Timberline High School in 2013, briefly entered the U.S Air Force
in 2014 where I discovered I had an unfortunate physical disability in my legs known as chronic-compartment
syndrome. After 2 months of heartbreak I was sent home from the military, several years of therapy and surgery
later, I reapplied to all branches of the military in 2016 and was denied entry.
Since then I have
pursued increasingly technical careers through assorted call centers, moved out, and in 2018 I moved from Boise,
ID to Portland, OR where I got a last job in a call center that got briefly technical enough to sate my thirst
for an interesting job. Now I am persuing a more technical career in programming and development in hopes of a
career with excellent remote potential and interesting daily activities
Cody Fritz
Email:
<EMAIL_ADDRESS>Born in 1995


Open Web Privacy Measurements is a platform for blackbox testing online technologies.
Think of what we do as an analog of the CDC for web privacy — we identify new online privacy threats, quantify and characterize existing ones, and inform the public on these issues.
https://citp.princeton.edu/webtransparency/
(and some early ideas for solutions)
How do we let researchers distribute their experiments so that others can run them to verify results?
How do you ship
simple_crawl.py
and writing separate analysis scripts Best Case
import Pyro4
...
def main()
parent_con, child_con = Pipe()
p = Process(target=childproc,
args=(child_con,))
p.start();
url = parent_con.recv();
print "Pyro4 url: {0}".format(url)
#now get the object
webdriver = Pyro4.Proxy(url)
webdriver.get("http://www.python.org")
print "Title: {0}".format(webdriver.title)
#subprocess code for creating a browser
def childproc(pipe):
display = Display(visible=0)
display.start()
firefox = webdriver.Firefox()
#above should look familiar
daemon=Pyro4.Daemon()
url=daemon.register(firefox)
pipe.send(url)
daemon.requestLoop()
$ pip install OpenWPM
(Really Big Data)
| Date | Milestone |
|---|---|
| September 30th |
|
| October 10th | Integration of RPC code into codebase with submitted pull request |
| October 17th | ORM layer added into branch and submitted for code review & spec finalization |
| October 31 |
|
| November 14th | Delta Encoding shimmed into ORM layer w/ proof of consistency |
| November 28th | ORM layer w/o delta encoding pull request submitted |
| December 5th | Delta Encding benchmarks completed & Delta encoding submitted for pull request |
| Jan 12th | Updated Documentation & Test cases completed and submitted in pull request |
| After that... | Write-up of results |
| 2nd semster | Tackle other big problem: Intelligent and automated crawling |
/


LOOP is a set of modules with functions that help doing object-oriented programming (OOP) in <%=link("Lua")%>. Much like the <%=link("LuaManual.TableLib")%> module from the <%=link("LuaManual.StdLibs")%> provides functions to manipulate sequences (e.g. insert or remove elements), LOOP modules provide functions to manipulate objects (e.g. get its class) and classes (e.g. define its superclass). LOOP is based on common solutions adopted by programmers doing OOP in Lua with focus in simplicity and efficiency.
LOOP modules are intended to aid the programmer to perform common tasks using well known solutions for OOP in Lua. Objects and classes created with LOOP usually interoperate well with other objects and libraries due to this adoption of well known solutions.
Note: Are you new to Lua? Then read <%=link("Intro","this")%>.


BrowserStack
Native
BrowserStack Details
Credentials
Capabilities
Record and Playback
Overview
Run Test on BrowserStack
BrowserStack Local
Start/Stop Local Connection
Manage Mobile Apps
Manual
Automation
Logs(Automate/App-Automate)
Console Logs
Network Logs


Should extract the binary files using the json file
LOAD JSON URL
Load Binary URL sub folder
Strange, the only way I can get this running is when tf.io.loadWeights() is by using a sub folder called strange
instead of the URL https://hpssjellis.github.io/beginner-tensorflowjs-examples-in-javascript/saved-models/batches-20000-done.weights.bin"


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New
York
Botanical
Garden
copyright
reserved
FLORA
NEOTROPICA
Manilkara
New
York
Botanical
Garden
Arthur
Cronquist,
1945
^Aurica.
&A>oesc_e^s
§^tll
Mus.
Botan.
Stockholm.
Plantū
Indias
Occidentalis
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Jir,
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YORK
BOTANICAL
GARDEN
01442876
01442876
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


Cockeysville, Maryland
System Source Computer Museum
Its diverse collection of computers and technology spans the ages.
Housed in the System Source office, this museum contains a vast collection of computing equipment from the ancient and modern world. They are all organized through an array of thoughtful exhibits that also include interactive examples.
Visitors to the museum learn about the early days of computing and automation. Exhibits include a replica of an Apple I, information on how heavy the aluminum cover of a Cray supercomputer is, and several computing instruments from the past such as Napier’s Bones and an Antikythera mechanism. The displays are crafted so that all visitors can garner a better understanding of the advancements of computing technology.
If you’re a tech enthusiast that wants to learn more about the history of computing, or have a strong desire to stroll down memory lane, this is the place for you.
Know Before You Go
The museum is located in a business park. Parking is abundant. The museum is open between 8:30 a.m. to 5:00 p.m. Guided tours are available by calling in advance. All tours are free.
Atlas Obscura Experiences
The Raptors of the Nation's Capital
Laurel, Maryland
$40 per person
Community Discussion
-
No Comments Yet
Start the discussion.
forum Visit our forums.


Conference Schedule
Saturday, April 4, 2009
1:00pm-3:45pm Afternoon Talk Session
4:00pm-5:30pm Keynote Address - Prof.
Douglas Hofstadter
6:00pm-7:00pm Poster Session
Sunday, April 5, 2009
9:00am-12 noon Cognitive Science Open House
1:00pm-3:20pm Afternoon Talk Session
3:30pm-5:00pm Graduate School Panel Discussion


For a new entry you will need:
- url to listen for as trigger
- url to ping when the first url is found in a tab of your chrome window
- repeating interval in minutes
| URL (Trigger) | Url (Ping) | Repeating interval (minutes) |
|---|


Model: {{ car.model }}
Brand: {{ car.brand }}
Description: {{ car.description }}
Registration number: {{ car.number }}
Fuel Type: {{ car.fuelType }}
Transmission: {{ car.transmission }}
Are you sure you want to delete this car?


After interviewing New.edu's newly hired instructors, we created a persona "Jennifer". We used Jennifer to identify common goals, needs, and scenarios, which guided our design.
This design addressed the need for course instructors to manage multiple courses at once.
This design was validated by instructors. We also defined an "at-risk" algorithm to flag students.
This page was designed to help faculty to track student progress and communications.
After launch, we added a tab to show students who were pre-term (starting soon)
This was the version we deployed (though activity is sparse in this screenshot).
We needed a state dependant screen that could offer students a breakdown of their score, while offering supportive feedback to passing and not-passing students.
In this case they are a breakdown of their score, and information about re-taking the the exam.
At the bottom of the page, they are given an easy-click button to request a retake from their instructor, and encouragement to reach out for support.
After a second failure, students may not re-take the exam. At the bottom of the page, students are advised about how they may re-take the course in the next term, and are encouraged to reach out with their student advisor for study support.
We offer congratulations, and a breakdown of their score. Students are informed that they have earned credit for the course.
At the bottom of the page, students are encouraged to share their results with their instructor.
Students can upload multiple files into a submission. They are reminded to double-check that their submission is complete.
Graders accept project one at a time, and students are anonymous (they are labeled with in ID number). After they go into grade a project, graders use a clickable rubric. They are required to offer written feedback before a grade can be submitted.
One of my favorite things about working in boot-strapping start-ups is getting to work on all kinds of projects outside of my job description. Here are a few examples from University Now.


--- layout: post status: publish published: true title:
Andy, Corey and Kurt gather (sans mustaches) to talk about this week's events in the world of the Chicago Cubs.
The Cubs have acquired back-up catcher George Kottaras from the Kansas City Royals. We talk about why Kottaras should be a good back-up for Welington Castillo. We also talk about why the Cubs will not try to re-sign Dioner Navarro.
We talk a little about the hot commodity (once he becomes a free-agent) from Japan, Masahiro Tanaka. Who is he and why do the big spenders in baseball want him? And are the Cubs really in the list of organization willing to spend the big money to get the right-handed pitcher?
Corey gives the Samardzija trade rumors update. We answer listener questions, which include questions about the Ivy Envy bus trip to a Cubs game and a Doctor Who based question involving the Cubs.
We read some Internet Muscle Flexes and pick this winner for the photo caption contest: