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Python MomentTensor.evaluation_status方法代码示例

本文整理汇总了Python中obspy.core.event.MomentTensor.evaluation_status方法的典型用法代码示例。如果您正苦于以下问题:Python MomentTensor.evaluation_status方法的具体用法?Python MomentTensor.evaluation_status怎么用?Python MomentTensor.evaluation_status使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在obspy.core.event.MomentTensor的用法示例。


在下文中一共展示了MomentTensor.evaluation_status方法的1个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: build

# 需要导入模块: from obspy.core.event import MomentTensor [as 别名]
# 或者: from obspy.core.event.MomentTensor import evaluation_status [as 别名]
    def build(self):
        """
        Build an obspy moment tensor focal mech event

        This makes the tensor output into an Event containing:
        1) a FocalMechanism with a MomentTensor, NodalPlanes, and PrincipalAxes
        2) a Magnitude of the Mw from the Tensor

        Which is what we want for outputting QuakeML using
        the (slightly modified) obspy code.

        Input
        -----
        filehandle => open file OR str from filehandle.read()

        Output
        ------
        event => instance of Event() class as described above
        """
        p = self.parser
        event         = Event(event_type='earthquake')
        origin        = Origin()
        focal_mech    = FocalMechanism()
        nodal_planes  = NodalPlanes()
        moment_tensor = MomentTensor()
        principal_ax  = PrincipalAxes()
        magnitude     = Magnitude()
        data_used     = DataUsed()
        creation_info = CreationInfo(agency_id='NN')
        ev_mode = 'automatic'
        ev_stat = 'preliminary'
        evid = None
        orid = None
        # Parse the entire file line by line.
        for n,l in enumerate(p.line):
            if 'REVIEWED BY NSL STAFF' in l:
                ev_mode = 'manual'
                ev_stat = 'reviewed'
            if 'Event ID' in l:
                evid = p._id(n)
            if 'Origin ID' in l:
                orid = p._id(n)
            if 'Ichinose' in l:
                moment_tensor.category = 'regional'
            if re.match(r'^\d{4}\/\d{2}\/\d{2}', l):
                ev = p._event_info(n)
            if 'Depth' in l:
                derived_depth = p._depth(n)
            if 'Mw' in l:
                magnitude.mag = p._mw(n) 
                magnitude.magnitude_type = 'Mw'
            if 'Mo' in l and 'dyne' in l:
                moment_tensor.scalar_moment = p._mo(n)
            if 'Percent Double Couple' in l:
                moment_tensor.double_couple = p._percent(n)
            if 'Percent CLVD' in l:
                moment_tensor.clvd = p._percent(n)
            if 'Epsilon' in l:
                moment_tensor.variance = p._epsilon(n)
            if 'Percent Variance Reduction' in l:
                moment_tensor.variance_reduction = p._percent(n)
            if 'Major Double Couple' in l and 'strike' in p.line[n+1]:
                np = p._double_couple(n)
                nodal_planes.nodal_plane_1 = NodalPlane(*np[0])
                nodal_planes.nodal_plane_2 = NodalPlane(*np[1])
                nodal_planes.preferred_plane = 1
            if 'Spherical Coordinates' in l:
                mt = p._mt_sphere(n)
                moment_tensor.tensor = Tensor(
                    m_rr = mt['Mrr'],
                    m_tt = mt['Mtt'],
                    m_pp = mt['Mff'],
                    m_rt = mt['Mrt'],
                    m_rp = mt['Mrf'],
                    m_tp = mt['Mtf'],
                    )
            if 'Eigenvalues and eigenvectors of the Major Double Couple' in l:
                ax = p._vectors(n)
                principal_ax.t_axis = Axis(ax['T']['trend'], ax['T']['plunge'], ax['T']['ev'])
                principal_ax.p_axis = Axis(ax['P']['trend'], ax['P']['plunge'], ax['P']['ev'])
                principal_ax.n_axis = Axis(ax['N']['trend'], ax['N']['plunge'], ax['N']['ev'])
            if 'Number of Stations' in l:
                data_used.station_count = p._number_of_stations(n)
            if 'Maximum' in l and 'Gap' in l:
                focal_mech.azimuthal_gap = p._gap(n)
            if re.match(r'^Date', l):
                creation_info.creation_time = p._creation_time(n)
        # Creation Time
        creation_info.version = orid
        # Fill in magnitude values
        magnitude.evaluation_mode = ev_mode
        magnitude.evaluation_status = ev_stat
        magnitude.creation_info = creation_info.copy()
        magnitude.resource_id = self._rid(magnitude)
        # Stub origin
        origin.time = ev.get('time')
        origin.latitude = ev.get('lat')
        origin.longitude = ev.get('lon')
        origin.depth = derived_depth * 1000.
        origin.depth_type = "from moment tensor inversion"
#.........这里部分代码省略.........
开发者ID:NVSeismoLab,项目名称:commons,代码行数:103,代码来源:ichinose.py


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