Python SD.create方法代码示例

# 需要导入模块: from pyhdf.SD import SD [as 别名]
# 或者: from pyhdf.SD.SD import create [as 别名]
def write_interpolated(filename, f0, f1, fact, datasets):
    '''
    interpolate two hdf files f0 and f1 using factor fact, and
    write the result to filename
    '''

    hdf = SD(filename, SDC.WRITE|SDC.CREATE)
    for dataset in datasets:

        try:
            info = SD(f0).select(dataset).info()
        except:
            print >> stderr, 'Error loading %s in %s' % (dataset, f0)
            raise

        typ  = info[3]
        shp  = info[2]
        met0 = SD(f0).select(dataset).get()
        met1 = SD(f1).select(dataset).get()

        interp = (1-fact)*met0 + fact*met1

        interp = interp.astype({
                SDC.INT16: 'int16',
                SDC.FLOAT32: 'float32',
                SDC.FLOAT64: 'float64',
            }[typ])

        # write
        sds = hdf.create(dataset, typ, shp)
        sds[:] = interp[:]
        sds.endaccess()

    hdf.end()

# 需要导入模块: from pyhdf.SD import SD [as 别名]
# 或者: from pyhdf.SD.SD import create [as 别名]
    def setUp(self):
        """Create a test HDF4 file"""
        from pyhdf.SD import SD, SDC
        h = SD('test.hdf', SDC.WRITE | SDC.CREATE | SDC.TRUNC)
        data = np.arange(10. * 100, dtype=np.float32).reshape((10, 100))
        v1 = h.create('ds1_f', SDC.FLOAT32, (10, 100))
        v1[:] = data
        v2 = h.create('ds1_i', SDC.INT16, (10, 100))
        v2[:] = data.astype(np.int16)

        # Add attributes
        h.test_attr_str = 'test_string'
        h.test_attr_int = 0
        h.test_attr_float = 1.2
        # h.test_attr_str_arr = np.array(b"test_string2")
        for d in [v1, v2]:
            d.test_attr_str = 'test_string'
            d.test_attr_int = 0
            d.test_attr_float = 1.2

        h.end()

# 需要导入模块: from pyhdf.SD import SD [as 别名]
# 或者: from pyhdf.SD.SD import create [as 别名]
def write_hdf(filename, dataset, data):
    '''
    write a dataset in hdf file
    '''

    hdf = SD(filename, SDC.WRITE|SDC.CREATE)

    typ = {
            'int16'   : SDC.INT16,
            'float32' : SDC.FLOAT32,
            'float64' : SDC.FLOAT64,
            }[data.dtype.name]

    sds = hdf.create(dataset, typ, data.shape)
    sds[:] = data[:]
    sds.endaccess()

    hdf.end()

# 需要导入模块: from pyhdf.SD import SD [as 别名]
# 或者: from pyhdf.SD.SD import create [as 别名]
def write_interpolated(filename, f0, f1, fact, datasetNames):
    '''
    interpolate two hdf files f0 and f1 using factor fact, and
    write the result to filename
    '''

    hdf = SD(filename, SDC.WRITE|SDC.CREATE)
    for datasetName in datasetNames:

        try:
            info = SD(f0).select(datasetName).info()
        except:
            print >> stderr, 'Error loading %s in %s' % (datasetName, f0)
            raise

        typ  = info[3]
        shp  = info[2]
        sds_in1 = SD(f0).select(datasetName)
        met0 = sds_in1.get()
        met1 = SD(f1).select(datasetName).get()

        interp = (1-fact)*met0 + fact*met1

        interp = interp.astype({
                SDC.INT16: 'int16',
                SDC.FLOAT32: 'float32',
                SDC.FLOAT64: 'float64',
            }[typ])

        # write
        sds = hdf.create(datasetName, typ, shp)
        sds[:] = interp[:]

        # copy attributes
        attr = sds_in1.attributes()
        if len(attr) > 0:
            for name in attr.keys():
                setattr(sds, name, attr[name])
        sds.endaccess()

    hdf.end()

# 需要导入模块: from pyhdf.SD import SD [as 别名]
# 或者: from pyhdf.SD.SD import create [as 别名]
dl_data[(rad_sol <= -1)] = day1

day2 = rad_sol[(rad_sol < 1) & (rad_sol > -1)] 
day2 = 24.0 * np.arccos(day2)/np.pi
dl_data[(rad_sol < 1) & (rad_sol > -1)] = day2

day3 = rad_sol[(rad_sol >= 1)]
day3 = 0.0
dl_data[(rad_sol >= 1)] = day3

dl_data = dl_data.reshape(1080,2160)
print "day length complete"

####################################################################
#   Calculates NPP for each pixel by multiplying values for that   #
#   pixel from pbopt, zeu, tot_chl, par and dl together.           #
#   Produces output hdf file containing NPP data.                  #
####################################################################  

NPP_data = np.zeros_like(dl_data)

NPP_data = pbopt_data * zeu_data * chl_data * par_data * dl_data 

OUTPUT1 = "C:\Anaconda\envs\sat_data\NPP_3.hdf"
NPP = SD(OUTPUT1, SDC.WRITE | SDC.CREATE)
sds = NPP.create("sds1", SDC.FLOAT64,(1080,2160))
sds.setfillvalue(0)
sds[:] = NPP_data
sds.endaccess()
NPP.end()

# 需要导入模块: from pyhdf.SD import SD [as 别名]
# 或者: from pyhdf.SD.SD import create [as 别名]
def createhdf(filename, table=[]):
    hdf = SD(filename, SDC.CREATE | SDC.WRITE)
    for i in table:
        hdf.create(i, SDC.FLOAT32, 0)
    hdf.end()
    return True