Why is my model not showing predictions?

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I have the learning mode in tmRegion, and spRegion both true, but when I call run(1), tmRegion.getOutputArray(“predictiveCells”).getSDR() is always empty. Here is my code:

from htm.bindings.sdr import SDR
from htm.bindings.algorithms import SpatialPooler, TemporalMemory
from htm.bindings.encoders import ScalarEncoder
from htm.bindings.engine_internal import Network, Region
import numpy as np
from Vis import Vis

def main():
    encoders = []
    spRegion = None
    tmRegion = None

    config = """
    {network: [
        {addRegion: {name: "encoder1", type: "ScalarEncoderRegion", params: {"size": 100, "w": 2, "minValue": 0, "maxValue": 100, "periodic": false}}},
        {addRegion: {name: "encoder2", type: "ScalarEncoderRegion", params: {"size": 100, "w": 2, "minValue": 0, "maxValue": 100, "periodic": false}}},
        {addRegion: {name: "sp", type: "SPRegion", params: {columnCount: 50, learningMode: 1}}},
        {addRegion: {name: "tm", type: "TMRegion", params: {numberOfCols: 50, cellsPerColumn: 10, inputWidth: 50, learningMode: true}}},
        {addLink:   {src: "encoder1.encoded", dest: "sp.bottomUpIn"}},
        {addLink:   {src: "encoder2.encoded", dest: "sp.bottomUpIn"}},
        {addLink:   {src: "sp.bottomUpOut", dest: "tm.bottomUpIn"}}
    ]}"""

    network = Network() # Note: can't call Network().configure()
    network.configure(config)
    regions = network.getRegions()
    # Get a handle on the regions
    for name, region in regions:
        region_type = region.getType()
        if region_type == 'ScalarEncoderRegion':
            encoders.append(region)
        elif region_type == 'SPRegion':
            spRegion = region
        elif region_type == 'TMRegion':
            tmRegion = region
        print(region.getParameters())
    vis  = Vis()
    vis.run()
    value = 0
    while True:
        for enc in encoders:
            enc.setParameterReal64("sensedValue", value)
            value+=1
            if value >= 100:
                value = 0
        network.run(1)
        vis.setRegionData(encoders,spRegion, tmRegion)
            # This draws the TMRegion output as a matrix with colors representing cell state using:
            # active_cells_sdr = self.tmRegion.getOutputArray("activeCells").getSDR().dense
            # predicted_active_cells_sdr = self.tmRegion.getOutputArray("predictedActiveCells").getSDR().dense
            # predicted_cells_sdr = self.tmRegion.getOutputArray("predictiveCells").getSDR().dense
        input()
if __name__ == '__main__':
	main()
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