| @@ -33,6 +33,8 from matplotlib.patches import Polygon | |||
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33 | 33 | from mpl_toolkits.axes_grid1 import make_axes_locatable |
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34 | 34 | from matplotlib.ticker import FuncFormatter, LinearLocator, MultipleLocator |
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35 | 35 | |
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36 | import cartopy.crs as ccrs | |
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37 | ||
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36 | 38 | from .plotting_codes import register_cmap |
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37 | 39 | |
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38 | 40 | from schainpy.model.data.jrodata import PlotterData |
| @@ -218,7 +220,8 class Plot(Operation): | |||
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218 | 220 | self.zlimits = kwargs.get('zlimits', None) |
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219 | 221 | self.xmin = kwargs.get('xmin', None) |
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220 | 222 | self.xmax = kwargs.get('xmax', None) |
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221 |
self. |
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223 | self.yrange = kwargs.get('yrange', None) | |
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224 | self.xrange = kwargs.get('xrange', None) | |
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222 | 225 | self.xscale = kwargs.get('xscale', None) |
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223 | 226 | self.ymin = kwargs.get('ymin', None) |
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224 | 227 | self.ymax = kwargs.get('ymax', None) |
| @@ -253,6 +256,9 class Plot(Operation): | |||
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253 | 256 | self.mode = kwargs.get('mode', None) |
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254 | 257 | self.mask = kwargs.get('mask', False) |
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255 | 258 | self.shapes = kwargs.get('shapes', './') |
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259 | self.map = kwargs.get('map', False) | |
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260 | self.latitude = kwargs.get('latitude', -12) | |
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261 | self.longitude = kwargs.get('longitude', -74) | |
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256 | 262 | |
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257 | 263 | if self.server: |
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258 | 264 | if not self.server.startswith('tcp://'): |
| @@ -265,6 +271,7 class Plot(Operation): | |||
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265 | 271 | if isinstance(self.attr_data, str): |
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266 | 272 | self.attr_data = [self.attr_data] |
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267 | 273 | |
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274 | ||
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268 | 275 | def __setup_plot(self): |
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269 | 276 | ''' |
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270 | 277 | Common setup for all figures, here figures and axes are created |
| @@ -298,7 +305,11 class Plot(Operation): | |||
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298 | 305 | self.figures['PPI'].append(fig_p) |
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299 | 306 | self.figures['RHI'].append(fig_r) |
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300 | 307 |
for n in range(self.nplots): |
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301 | ax_p = fig_p.add_subplot(self.nrows, self.ncols, n+1, polar=self.polar, projection=self.projection) | |
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308 | if self.map: | |
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309 | ax_p = fig_p.add_subplot(self.nrows, self.ncols, n+1, polar=self.polar, projection=ccrs.PlateCarree()) | |
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310 | else: | |
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311 | ax_p = fig_p.add_subplot(self.nrows, self.ncols, n+1, polar=self.polar) | |
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312 | print('sin projection') | |
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302 | 313 | ax_r = fig_r.add_subplot(self.nrows, self.ncols, n+1, polar=self.polar) |
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303 | 314 | ax_p.tick_params(labelsize=8) |
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304 | 315 | ax_p.firsttime = True |
| @@ -323,7 +334,12 class Plot(Operation): | |||
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323 | 334 | fig = plt.figure(figsize=(self.width, self.height), |
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324 | 335 | edgecolor='k', |
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325 | 336 | facecolor='w') |
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326 | ax_p = fig.add_subplot(1, 1, 1, polar=self.polar, projection=self.projection) | |
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337 | if self.map: | |
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338 | ax_p = fig.add_subplot(1, 1, 1, polar=self.polar, projection=ccrs.PlateCarree()) | |
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339 | else: | |
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340 | ax_p = fig.add_subplot(1, 1, 1, polar=self.polar) | |
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341 | print('sin projection') | |
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342 | ||
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327 | 343 | ax_r = fig.add_subplot(1, 1, 1, polar=self.polar) |
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328 | 344 | ax_p.tick_params(labelsize=8) |
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329 | 345 | ax_p.firsttime = True |
| @@ -442,9 +458,10 class Plot(Operation): | |||
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442 | 458 | ax.cbar.set_label(self.cb_labels[n], size=8) |
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443 | 459 | else: |
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444 | 460 | ax.cbar = None |
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445 | if self.mode == 'RHI': | |
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461 | #if self.mode == 'RHI': | |
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446 | 462 |
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447 | 463 |
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464 | ||
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448 | 465 | ax.firsttime = False |
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449 | 466 | if self.grid: |
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450 | 467 | ax.grid(True) |
| @@ -463,7 +480,6 class Plot(Operation): | |||
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463 | 480 | '%Y-%m-%d %H:%M:%S'), |
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464 | 481 | self.time_label), |
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465 | 482 | size=8) |
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466 | ax.set_ylim(0, self.ymax) | |
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467 | 483 | if self.mode == 'PPI': |
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468 | 484 | ax.set_yticks(ax.get_yticks(), labels=ax.get_yticks(), color='white') |
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469 | 485 | ax.yaxis.labelpad = 28 |
| @@ -4,11 +4,10 import warnings | |||
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4 | 4 | import numpy |
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5 | 5 | from mpl_toolkits.axisartist.grid_finder import FixedLocator, DictFormatter |
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6 | 6 | from matplotlib.patches import Circle |
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7 | import cartopy.crs as ccrs | |
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8 | 7 | from cartopy.feature import ShapelyFeature |
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9 | 8 | import cartopy.io.shapereader as shpreader |
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10 | 9 | |
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11 | from schainpy.model.graphics.jroplot_base import Plot, plt | |
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10 | from schainpy.model.graphics.jroplot_base import Plot, plt, ccrs | |
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12 | 11 | from schainpy.model.graphics.jroplot_spectra import SpectraPlot, RTIPlot, CoherencePlot, SpectraCutPlot |
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13 | 12 | from schainpy.utils import log |
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14 | 13 | from schainpy.model.graphics.plotting_codes import cb_tables |
| @@ -515,19 +514,15 class PolarMapPlot(Plot): | |||
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515 | 514 | self.data.parameters[x], title) for x in self.channels] |
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516 | 515 | |
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517 | 516 | class WeatherParamsPlot(Plot): |
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518 | #CODE = 'RHI' | |
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519 | #plot_name = 'RHI' | |
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517 | ||
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520 | 518 | plot_type = 'scattermap' |
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521 | 519 | buffering = False |
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522 | projection = ccrs.PlateCarree() | |
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523 | 520 | |
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524 | 521 | def setup(self): |
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525 | 522 | |
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526 | 523 | self.ncols = 1 |
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527 | 524 | self.nrows = 1 |
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528 | 525 | self.nplots= 1 |
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529 | self.ylabel= 'Height [km]' | |
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530 | self.xlabel= 'Distance from radar [km]' | |
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531 | 526 | |
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532 | 527 | if self.channels is not None: |
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533 | 528 | self.nplots = len(self.channels) |
| @@ -630,8 +625,6 class WeatherParamsPlot(Plot): | |||
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630 | 625 | r = data['r'] |
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631 | 626 | self.titles = [] |
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632 | 627 | |
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633 | self.ymax = self.ymax if self.ymax else numpy.nanmax(r) | |
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634 | self.ymin = self.ymin if self.ymin else numpy.nanmin(r) | |
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635 | 628 | self.zmax = self.zmax if self.zmax else numpy.nanmax(z) |
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636 | 629 | self.zmin = self.zmin if self.zmin is not None else numpy.nanmin(z) |
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637 | 630 | |
| @@ -643,14 +636,43 class WeatherParamsPlot(Plot): | |||
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643 | 636 | len_aux = int(data['azi'].shape[0]/4) |
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644 | 637 | mean = numpy.mean(data['azi'][len_aux:-len_aux]) |
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645 | 638 | x, y = r*numpy.cos(theta), r*numpy.sin(theta) |
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639 | if self.yrange: | |
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640 | self.ylabel= 'Height [km]' | |
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641 | self.xlabel= 'Distance from radar [km]' | |
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642 | self.ymax = self.yrange | |
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643 | self.ymin = 0 | |
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644 | self.xmax = self.xrange if self.xrange else numpy.nanmax(r) | |
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645 | self.xmin = -self.xrange if self.xrange else -numpy.nanmax(r) | |
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646 | self.setrhilimits = False | |
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647 | else: | |
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648 | self.ymin = 0 | |
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649 | self.ymax = numpy.nanmax(r) | |
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650 | self.xmin = -numpy.nanmax(r) | |
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651 | self.xmax = numpy.nanmax(r) | |
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652 | ||
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646 | 653 | elif data['mode_op'] == 'PPI': |
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647 | 654 | r, theta = numpy.meshgrid(r, -numpy.radians(data['azi'])+numpy.pi/2) |
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648 | 655 | len_aux = int(data['ele'].shape[0]/4) |
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649 | 656 | mean = numpy.mean(data['ele'][len_aux:-len_aux]) |
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650 | 657 | x, y = r*numpy.cos(theta)*numpy.cos(numpy.radians(mean)), r*numpy.sin( |
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651 | 658 | theta)*numpy.cos(numpy.radians(mean)) |
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652 |
x = km2deg(x) + |
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653 |
y = km2deg(y) + |
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659 | x = km2deg(x) + self.longitude | |
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660 | y = km2deg(y) + self.latitude | |
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661 | if self.xrange: | |
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662 | self.ylabel= 'Latitude' | |
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663 | self.xlabel= 'Longitude' | |
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664 | ||
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665 | self.xmin = km2deg(-self.xrange) + self.longitude | |
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666 | self.xmax = km2deg(self.xrange) + self.longitude | |
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667 | ||
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668 | self.ymin = km2deg(-self.xrange) + self.latitude | |
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669 | self.ymax = km2deg(self.xrange) + self.latitude | |
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670 | else: | |
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671 | self.xmin = km2deg(-numpy.nanmax(r)) + self.longitude | |
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672 | self.xmax = km2deg(numpy.nanmax(r)) + self.longitude | |
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673 | ||
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674 | self.ymin = km2deg(-numpy.nanmax(r)) + self.latitude | |
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675 | self.ymax = km2deg(numpy.nanmax(r)) + self.latitude | |
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654 | 676 | |
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655 | 677 | self.clear_figures() |
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656 | 678 | |
| @@ -665,8 +687,6 class WeatherParamsPlot(Plot): | |||
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665 | 687 | norm = None |
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666 | 688 | |
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667 | 689 | for i, ax in enumerate(axes): |
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668 | if data['mode_op'] == 'PPI': | |
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669 | ax.set_extent([-75.745893, -74.845893, -12.490436, -11.590436]) | |
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670 | 690 | |
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671 | 691 | if norm is None: |
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672 | 692 | ax.plt = ax.pcolormesh(x, y, z[i], cmap=self.colormap, vmin=self.zmin, vmax=self.zmax) |
| @@ -690,14 +710,13 class WeatherParamsPlot(Plot): | |||
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690 | 710 | self.mode_value = round(mean,1) |
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691 | 711 | |
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692 | 712 | if data['mode_op'] == 'PPI': |
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713 | if self.map: | |
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693 | 714 | gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=True, |
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694 | 715 | linewidth=1, color='gray', alpha=0.5, linestyle='--') |
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695 | 716 | gl.xlabel_style = {'size': 8} |
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696 | 717 | gl.ylabel_style = {'size': 8} |
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697 | 718 | gl.xlabels_top = False |
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698 | 719 | gl.ylabels_right = False |
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699 | #self.shapes="/home/soporte/workspace/sirm/volumes/schain/shapes/" | |
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700 | #print("self.shapes",self.shapes) | |
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701 | 720 | shape_p = os.path.join(self.shapes,'PER_ADM2/PER_ADM2.shp') |
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702 | 721 | shape_d = os.path.join(self.shapes,'PER_ADM1/PER_ADM1.shp') |
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703 | 722 | capitales = os.path.join(self.shapes,'CAPITALES/cap_provincia.shp') |
| @@ -706,10 +725,10 class WeatherParamsPlot(Plot): | |||
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706 | 725 | reader_p = shpreader.BasicReader(shape_d, encoding='latin1') |
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707 | 726 | reader_c = shpreader.BasicReader(capitales, encoding='latin1') |
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708 | 727 | reader_v = shpreader.BasicReader(vias, encoding='latin1') |
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709 |
caps = [x for x in reader_c.records() |
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710 |
districts = [x for x in reader_d.records() |
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711 |
provs = [x for x in reader_p.records() |
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712 |
vias = [x for x in reader_v.records() |
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728 | caps = [x for x in reader_c.records() ]#if x.attributes["Departa"] in ("JUNIN", "LIMA", "ICA", "PIURA")] | |
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729 | districts = [x for x in reader_d.records() ]# if x.attributes["Name"] in ("JUNÍN", "CHANCHAMAYO", "CHUPACA", "CONCEPCIÓN", "HUANCAYO", "JAUJA", "SATIPO", "TARMA", "YAUYOS", "HUAROCHIRÍ", "CANTA", "HUANTA", "TAYACAJA")] | |
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730 | provs = [x for x in reader_p.records()]# if x.attributes["NAME"] in ("Junín", "Lima")] | |
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731 | vias = [x for x in reader_v.records()]# if x.attributes["DEP"] in ("JUNIN", "LIMA")] | |
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713 | 732 | |
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714 | 733 | # Display limits and streets |
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715 | 734 | shape_feature = ShapelyFeature([x.geometry for x in districts], ccrs.PlateCarree(), facecolor="none", edgecolor='grey', lw=0.5) |
| @@ -720,17 +739,19 class WeatherParamsPlot(Plot): | |||
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720 | 739 | ax.add_feature(shape_feature) |
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721 | 740 | |
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722 | 741 | for cap in caps: |
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723 | if cap.attributes['Nombre'] in ("LA OROYA", "CONCEPCIÓN", "HUANCAYO", "JAUJA", "CHUPACA", "YAUYOS", "HUANTA", "PAMPAS"): | |
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742 | #if cap.attributes['Nombre'] in ("LA OROYA", "CONCEPCIÓN", "HUANCAYO", "JAUJA", "CHUPACA", "YAUYOS", "HUANTA", "PAMPAS"): | |
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724 | 743 | ax.text(cap.attributes['X'], cap.attributes['Y'], cap.attributes['Nombre'].title(), size=7, color='white') |
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725 | ax.text(-75.052003, -11.915552, 'Huaytapallana', size=7, color='cyan') | |
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726 | ax.plot(-75.052003, -11.915552, '*') | |
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727 | ||
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744 | #ax.text(-75.052003, -11.915552, 'Huaytapallana', size=7, color='cyan') | |
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745 | #ax.plot(-75.052003, -11.915552, '*') | |
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746 | else: | |
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747 | ax.grid(color='grey', alpha=0.5, linestyle='--', linewidth=1) | |
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728 | 748 | for R in (10, 20, 30 , 40, 50): |
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729 | circle = Circle((-75.295893, -12.040436), km2deg(R), facecolor='none', | |
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749 | if R <= self.xrange: | |
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750 | circle = Circle((self.longitude, self.latitude), km2deg(R), facecolor='none', | |
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730 | 751 | edgecolor='skyblue', linewidth=1, alpha=0.5) |
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731 | 752 | ax.add_patch(circle) |
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732 |
ax.text(km2deg(R)*numpy.cos(numpy.radians(45)) |
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733 |
km2deg(R)*numpy.sin(numpy.radians(45)) |
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753 | ax.text(km2deg(R)*numpy.cos(numpy.radians(45))+self.longitude, | |
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754 | km2deg(R)*numpy.sin(numpy.radians(45))+self.latitude, | |
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734 | 755 | '{}km'.format(R), color='skyblue', size=7) |
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735 | 756 | elif data['mode_op'] == 'RHI': |
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736 | 757 | ax.grid(color='grey', alpha=0.5, linestyle='--', linewidth=1) |
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